--- tags: - mteb model-index: - name: mlm results: - task: type: Classification dataset: type: mteb/amazon_counterfactual name: MTEB AmazonCounterfactualClassification (en) config: en split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics: - type: accuracy value: 82.97014925373135 - type: ap value: 49.6288385893607 - type: f1 value: 77.58957447993662 - task: type: Classification dataset: type: mteb/amazon_polarity name: MTEB AmazonPolarityClassification config: default split: test revision: e2d317d38cd51312af73b3d32a06d1a08b442046 metrics: - type: accuracy value: 90.975425 - type: ap value: 87.57349835900825 - type: f1 value: 90.96732416386632 - task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (en) config: en split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics: - type: accuracy value: 48.708 - type: f1 value: 47.736228936979586 - task: type: Retrieval dataset: type: arguana name: MTEB ArguAna config: default split: test revision: None metrics: - type: map_at_1 value: 32.006 - type: map_at_10 value: 49.268 - type: map_at_100 value: 49.903999999999996 - type: map_at_1000 value: 49.909 - type: map_at_3 value: 44.334 - type: map_at_5 value: 47.374 - type: mrr_at_1 value: 32.788000000000004 - type: mrr_at_10 value: 49.707 - type: mrr_at_100 value: 50.346999999999994 - type: mrr_at_1000 value: 50.352 - type: mrr_at_3 value: 44.95 - type: mrr_at_5 value: 47.766999999999996 - type: ndcg_at_1 value: 32.006 - type: ndcg_at_10 value: 58.523 - type: ndcg_at_100 value: 61.095 - type: ndcg_at_1000 value: 61.190999999999995 - type: ndcg_at_3 value: 48.431000000000004 - type: ndcg_at_5 value: 53.94 - type: precision_at_1 value: 32.006 - type: precision_at_10 value: 8.791 - type: precision_at_100 value: 0.989 - type: precision_at_1000 value: 0.1 - type: precision_at_3 value: 20.104 - type: precision_at_5 value: 14.751 - type: recall_at_1 value: 32.006 - type: recall_at_10 value: 87.909 - type: recall_at_100 value: 98.86200000000001 - type: recall_at_1000 value: 99.57300000000001 - type: recall_at_3 value: 60.313 - type: recall_at_5 value: 73.75500000000001 - task: type: Clustering dataset: type: mteb/arxiv-clustering-p2p name: MTEB ArxivClusteringP2P config: default split: test revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d metrics: - type: v_measure value: 47.01500173547629 - task: type: Clustering dataset: type: mteb/arxiv-clustering-s2s name: MTEB ArxivClusteringS2S config: default split: test revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 metrics: - type: v_measure value: 43.52209238193538 - task: type: Reranking dataset: type: mteb/askubuntudupquestions-reranking name: MTEB AskUbuntuDupQuestions config: default split: test revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 metrics: - type: map value: 64.1348784470504 - type: mrr value: 76.93762916062083 - task: type: STS dataset: type: mteb/biosses-sts name: MTEB BIOSSES config: default split: test revision: d3fb88f8f02e40887cd149695127462bbcf29b4a metrics: - type: cos_sim_pearson value: 87.8322696692348 - type: cos_sim_spearman value: 86.53751398463592 - type: euclidean_pearson value: 86.1435544054336 - type: euclidean_spearman value: 86.70799979698164 - type: manhattan_pearson value: 86.1206703865016 - type: manhattan_spearman value: 86.47004256773585 - task: type: Classification dataset: type: mteb/banking77 name: MTEB Banking77Classification config: default split: test revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 metrics: - type: accuracy value: 88.1461038961039 - type: f1 value: 88.09877611214092 - task: type: Clustering dataset: type: mteb/biorxiv-clustering-p2p name: MTEB BiorxivClusteringP2P config: default split: test revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 metrics: - type: v_measure value: 35.53021718892608 - task: type: Clustering dataset: type: mteb/biorxiv-clustering-s2s name: MTEB BiorxivClusteringS2S config: default split: test revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 metrics: - type: v_measure value: 35.34236915611622 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackAndroidRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 36.435 - type: map_at_10 value: 49.437999999999995 - type: map_at_100 value: 51.105999999999995 - type: map_at_1000 value: 51.217999999999996 - type: map_at_3 value: 44.856 - type: map_at_5 value: 47.195 - type: mrr_at_1 value: 45.78 - type: mrr_at_10 value: 56.302 - type: mrr_at_100 value: 56.974000000000004 - type: mrr_at_1000 value: 57.001999999999995 - type: mrr_at_3 value: 53.6 - type: mrr_at_5 value: 55.059999999999995 - type: ndcg_at_1 value: 44.921 - type: ndcg_at_10 value: 56.842000000000006 - type: ndcg_at_100 value: 61.586 - type: ndcg_at_1000 value: 63.039 - type: ndcg_at_3 value: 50.612 - type: ndcg_at_5 value: 53.181 - type: precision_at_1 value: 44.921 - type: precision_at_10 value: 11.245 - type: precision_at_100 value: 1.7069999999999999 - type: precision_at_1000 value: 0.216 - type: precision_at_3 value: 24.224999999999998 - type: precision_at_5 value: 17.511 - type: recall_at_1 value: 36.435 - type: recall_at_10 value: 70.998 - type: recall_at_100 value: 89.64 - type: recall_at_1000 value: 98.654 - type: recall_at_3 value: 53.034000000000006 - type: recall_at_5 value: 60.41 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackEnglishRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 33.371 - type: map_at_10 value: 45.301 - type: map_at_100 value: 46.663 - type: map_at_1000 value: 46.791 - type: map_at_3 value: 41.79 - type: map_at_5 value: 43.836999999999996 - type: mrr_at_1 value: 42.611 - type: mrr_at_10 value: 51.70400000000001 - type: mrr_at_100 value: 52.342 - type: mrr_at_1000 value: 52.38 - type: mrr_at_3 value: 49.374 - type: mrr_at_5 value: 50.82 - type: ndcg_at_1 value: 42.166 - type: ndcg_at_10 value: 51.49 - type: ndcg_at_100 value: 56.005 - type: ndcg_at_1000 value: 57.748 - type: ndcg_at_3 value: 46.769 - type: ndcg_at_5 value: 49.155 - type: precision_at_1 value: 42.166 - type: precision_at_10 value: 9.841 - type: precision_at_100 value: 1.569 - type: precision_at_1000 value: 0.202 - type: precision_at_3 value: 22.803 - type: precision_at_5 value: 16.229 - type: recall_at_1 value: 33.371 - type: recall_at_10 value: 62.52799999999999 - type: recall_at_100 value: 81.269 - type: recall_at_1000 value: 91.824 - type: recall_at_3 value: 48.759 - type: recall_at_5 value: 55.519 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGamingRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 41.421 - type: map_at_10 value: 55.985 - type: map_at_100 value: 56.989999999999995 - type: map_at_1000 value: 57.028 - type: map_at_3 value: 52.271 - type: map_at_5 value: 54.517 - type: mrr_at_1 value: 47.272999999999996 - type: mrr_at_10 value: 59.266 - type: mrr_at_100 value: 59.821999999999996 - type: mrr_at_1000 value: 59.839 - type: mrr_at_3 value: 56.677 - type: mrr_at_5 value: 58.309999999999995 - type: ndcg_at_1 value: 47.147 - type: ndcg_at_10 value: 62.596 - type: ndcg_at_100 value: 66.219 - type: ndcg_at_1000 value: 66.886 - type: ndcg_at_3 value: 56.558 - type: ndcg_at_5 value: 59.805 - type: precision_at_1 value: 47.147 - type: precision_at_10 value: 10.245 - type: precision_at_100 value: 1.302 - type: precision_at_1000 value: 0.13899999999999998 - type: precision_at_3 value: 25.663999999999998 - type: precision_at_5 value: 17.793 - type: recall_at_1 value: 41.421 - type: recall_at_10 value: 78.77499999999999 - type: recall_at_100 value: 93.996 - type: recall_at_1000 value: 98.60600000000001 - type: recall_at_3 value: 62.891 - type: recall_at_5 value: 70.819 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGisRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 27.517999999999997 - type: map_at_10 value: 37.468 - type: map_at_100 value: 38.667 - type: map_at_1000 value: 38.743 - type: map_at_3 value: 34.524 - type: map_at_5 value: 36.175000000000004 - type: mrr_at_1 value: 29.378999999999998 - type: mrr_at_10 value: 39.54 - type: mrr_at_100 value: 40.469 - type: mrr_at_1000 value: 40.522000000000006 - type: mrr_at_3 value: 36.685 - type: mrr_at_5 value: 38.324000000000005 - type: ndcg_at_1 value: 29.718 - type: ndcg_at_10 value: 43.091 - type: ndcg_at_100 value: 48.44 - type: ndcg_at_1000 value: 50.181 - type: ndcg_at_3 value: 37.34 - type: ndcg_at_5 value: 40.177 - type: precision_at_1 value: 29.718 - type: precision_at_10 value: 6.723 - type: precision_at_100 value: 0.992 - type: precision_at_1000 value: 0.117 - type: precision_at_3 value: 16.083 - type: precision_at_5 value: 11.322000000000001 - type: recall_at_1 value: 27.517999999999997 - type: recall_at_10 value: 58.196999999999996 - type: recall_at_100 value: 82.07799999999999 - type: recall_at_1000 value: 94.935 - type: recall_at_3 value: 42.842 - type: recall_at_5 value: 49.58 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackMathematicaRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 19.621 - type: map_at_10 value: 30.175 - type: map_at_100 value: 31.496000000000002 - type: map_at_1000 value: 31.602000000000004 - type: map_at_3 value: 26.753 - type: map_at_5 value: 28.857 - type: mrr_at_1 value: 25.497999999999998 - type: mrr_at_10 value: 35.44 - type: mrr_at_100 value: 36.353 - type: mrr_at_1000 value: 36.412 - type: mrr_at_3 value: 32.275999999999996 - type: mrr_at_5 value: 34.434 - type: ndcg_at_1 value: 24.502 - type: ndcg_at_10 value: 36.423 - type: ndcg_at_100 value: 42.289 - type: ndcg_at_1000 value: 44.59 - type: ndcg_at_3 value: 30.477999999999998 - type: ndcg_at_5 value: 33.787 - type: precision_at_1 value: 24.502 - type: precision_at_10 value: 6.978 - type: precision_at_100 value: 1.139 - type: precision_at_1000 value: 0.145 - type: precision_at_3 value: 15.008 - type: precision_at_5 value: 11.468 - type: recall_at_1 value: 19.621 - type: recall_at_10 value: 50.516000000000005 - type: recall_at_100 value: 75.721 - type: recall_at_1000 value: 91.77199999999999 - type: recall_at_3 value: 34.695 - type: recall_at_5 value: 42.849 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackPhysicsRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 33.525 - type: map_at_10 value: 46.153 - type: map_at_100 value: 47.61 - type: map_at_1000 value: 47.715 - type: map_at_3 value: 42.397 - type: map_at_5 value: 44.487 - type: mrr_at_1 value: 42.445 - type: mrr_at_10 value: 52.174 - type: mrr_at_100 value: 52.986999999999995 - type: mrr_at_1000 value: 53.016 - type: mrr_at_3 value: 49.647000000000006 - type: mrr_at_5 value: 51.215999999999994 - type: ndcg_at_1 value: 42.156 - type: ndcg_at_10 value: 52.698 - type: ndcg_at_100 value: 58.167 - type: ndcg_at_1000 value: 59.71300000000001 - type: ndcg_at_3 value: 47.191 - type: ndcg_at_5 value: 49.745 - type: precision_at_1 value: 42.156 - type: precision_at_10 value: 9.682 - type: precision_at_100 value: 1.469 - type: precision_at_1000 value: 0.17700000000000002 - type: precision_at_3 value: 22.682 - type: precision_at_5 value: 16.035 - type: recall_at_1 value: 33.525 - type: recall_at_10 value: 66.142 - type: recall_at_100 value: 88.248 - type: recall_at_1000 value: 97.806 - type: recall_at_3 value: 50.541000000000004 - type: recall_at_5 value: 57.275 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackProgrammersRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 28.249000000000002 - type: map_at_10 value: 41.659 - type: map_at_100 value: 43.001 - type: map_at_1000 value: 43.094 - type: map_at_3 value: 37.607 - type: map_at_5 value: 39.662 - type: mrr_at_1 value: 36.301 - type: mrr_at_10 value: 47.482 - type: mrr_at_100 value: 48.251 - type: mrr_at_1000 value: 48.288 - type: mrr_at_3 value: 44.444 - type: mrr_at_5 value: 46.013999999999996 - type: ndcg_at_1 value: 35.616 - type: ndcg_at_10 value: 49.021 - type: ndcg_at_100 value: 54.362 - type: ndcg_at_1000 value: 55.864999999999995 - type: ndcg_at_3 value: 42.515 - type: ndcg_at_5 value: 45.053 - type: precision_at_1 value: 35.616 - type: precision_at_10 value: 9.372 - type: precision_at_100 value: 1.4120000000000001 - type: precision_at_1000 value: 0.172 - type: precision_at_3 value: 21.043 - type: precision_at_5 value: 14.84 - type: recall_at_1 value: 28.249000000000002 - type: recall_at_10 value: 65.514 - type: recall_at_100 value: 87.613 - type: recall_at_1000 value: 97.03 - type: recall_at_3 value: 47.21 - type: recall_at_5 value: 54.077 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 29.164583333333333 - type: map_at_10 value: 40.632000000000005 - type: map_at_100 value: 41.96875 - type: map_at_1000 value: 42.07508333333333 - type: map_at_3 value: 37.18458333333333 - type: map_at_5 value: 39.13700000000001 - type: mrr_at_1 value: 35.2035 - type: mrr_at_10 value: 45.28816666666666 - type: mrr_at_100 value: 46.11466666666667 - type: mrr_at_1000 value: 46.15741666666667 - type: mrr_at_3 value: 42.62925 - type: mrr_at_5 value: 44.18141666666667 - type: ndcg_at_1 value: 34.88958333333333 - type: ndcg_at_10 value: 46.90650000000001 - type: ndcg_at_100 value: 52.135333333333335 - type: ndcg_at_1000 value: 53.89766666666668 - type: ndcg_at_3 value: 41.32075 - type: ndcg_at_5 value: 44.02083333333333 - type: precision_at_1 value: 34.88958333333333 - type: precision_at_10 value: 8.392833333333332 - type: precision_at_100 value: 1.3085833333333334 - type: precision_at_1000 value: 0.16458333333333333 - type: precision_at_3 value: 19.361166666666666 - type: precision_at_5 value: 13.808416666666668 - type: recall_at_1 value: 29.164583333333333 - type: recall_at_10 value: 60.874666666666656 - type: recall_at_100 value: 83.21008333333334 - type: recall_at_1000 value: 95.09275000000001 - type: recall_at_3 value: 45.37591666666667 - type: recall_at_5 value: 52.367666666666665 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackStatsRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 28.682000000000002 - type: map_at_10 value: 37.913000000000004 - type: map_at_100 value: 39.037 - type: map_at_1000 value: 39.123999999999995 - type: map_at_3 value: 35.398 - type: map_at_5 value: 36.906 - type: mrr_at_1 value: 32.362 - type: mrr_at_10 value: 40.92 - type: mrr_at_100 value: 41.748000000000005 - type: mrr_at_1000 value: 41.81 - type: mrr_at_3 value: 38.701 - type: mrr_at_5 value: 39.936 - type: ndcg_at_1 value: 32.208999999999996 - type: ndcg_at_10 value: 42.84 - type: ndcg_at_100 value: 47.927 - type: ndcg_at_1000 value: 50.048 - type: ndcg_at_3 value: 38.376 - type: ndcg_at_5 value: 40.661 - type: precision_at_1 value: 32.208999999999996 - type: precision_at_10 value: 6.718 - type: precision_at_100 value: 1.012 - type: precision_at_1000 value: 0.127 - type: precision_at_3 value: 16.667 - type: precision_at_5 value: 11.503 - type: recall_at_1 value: 28.682000000000002 - type: recall_at_10 value: 54.872 - type: recall_at_100 value: 77.42999999999999 - type: recall_at_1000 value: 93.054 - type: recall_at_3 value: 42.577999999999996 - type: recall_at_5 value: 48.363 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackTexRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 19.698 - type: map_at_10 value: 28.777 - type: map_at_100 value: 30.091 - type: map_at_1000 value: 30.209999999999997 - type: map_at_3 value: 25.874000000000002 - type: map_at_5 value: 27.438000000000002 - type: mrr_at_1 value: 24.295 - type: mrr_at_10 value: 33.077 - type: mrr_at_100 value: 34.036 - type: mrr_at_1000 value: 34.1 - type: mrr_at_3 value: 30.523 - type: mrr_at_5 value: 31.891000000000002 - type: ndcg_at_1 value: 24.535 - type: ndcg_at_10 value: 34.393 - type: ndcg_at_100 value: 40.213 - type: ndcg_at_1000 value: 42.748000000000005 - type: ndcg_at_3 value: 29.316 - type: ndcg_at_5 value: 31.588 - type: precision_at_1 value: 24.535 - type: precision_at_10 value: 6.483 - type: precision_at_100 value: 1.102 - type: precision_at_1000 value: 0.151 - type: precision_at_3 value: 14.201 - type: precision_at_5 value: 10.344000000000001 - type: recall_at_1 value: 19.698 - type: recall_at_10 value: 46.903 - type: recall_at_100 value: 72.624 - type: recall_at_1000 value: 90.339 - type: recall_at_3 value: 32.482 - type: recall_at_5 value: 38.452 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackUnixRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 30.56 - type: map_at_10 value: 41.993 - type: map_at_100 value: 43.317 - type: map_at_1000 value: 43.399 - type: map_at_3 value: 38.415 - type: map_at_5 value: 40.472 - type: mrr_at_1 value: 36.474000000000004 - type: mrr_at_10 value: 46.562 - type: mrr_at_100 value: 47.497 - type: mrr_at_1000 value: 47.532999999999994 - type: mrr_at_3 value: 43.905 - type: mrr_at_5 value: 45.379000000000005 - type: ndcg_at_1 value: 36.287000000000006 - type: ndcg_at_10 value: 48.262 - type: ndcg_at_100 value: 53.789 - type: ndcg_at_1000 value: 55.44 - type: ndcg_at_3 value: 42.358000000000004 - type: ndcg_at_5 value: 45.221000000000004 - type: precision_at_1 value: 36.287000000000006 - type: precision_at_10 value: 8.265 - type: precision_at_100 value: 1.24 - type: precision_at_1000 value: 0.148 - type: precision_at_3 value: 19.558 - type: precision_at_5 value: 13.880999999999998 - type: recall_at_1 value: 30.56 - type: recall_at_10 value: 62.891 - type: recall_at_100 value: 85.964 - type: recall_at_1000 value: 97.087 - type: recall_at_3 value: 46.755 - type: recall_at_5 value: 53.986000000000004 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWebmastersRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 29.432000000000002 - type: map_at_10 value: 40.898 - type: map_at_100 value: 42.794 - type: map_at_1000 value: 43.029 - type: map_at_3 value: 37.658 - type: map_at_5 value: 39.519 - type: mrr_at_1 value: 36.364000000000004 - type: mrr_at_10 value: 46.9 - type: mrr_at_100 value: 47.819 - type: mrr_at_1000 value: 47.848 - type: mrr_at_3 value: 44.202999999999996 - type: mrr_at_5 value: 45.715 - type: ndcg_at_1 value: 35.573 - type: ndcg_at_10 value: 47.628 - type: ndcg_at_100 value: 53.88699999999999 - type: ndcg_at_1000 value: 55.584 - type: ndcg_at_3 value: 42.669000000000004 - type: ndcg_at_5 value: 45.036 - type: precision_at_1 value: 35.573 - type: precision_at_10 value: 8.933 - type: precision_at_100 value: 1.8159999999999998 - type: precision_at_1000 value: 0.256 - type: precision_at_3 value: 20.29 - type: precision_at_5 value: 14.387 - type: recall_at_1 value: 29.432000000000002 - type: recall_at_10 value: 60.388 - type: recall_at_100 value: 87.144 - type: recall_at_1000 value: 97.154 - type: recall_at_3 value: 45.675 - type: recall_at_5 value: 52.35300000000001 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWordpressRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 21.462999999999997 - type: map_at_10 value: 31.824 - type: map_at_100 value: 32.853 - type: map_at_1000 value: 32.948 - type: map_at_3 value: 28.671999999999997 - type: map_at_5 value: 30.579 - type: mrr_at_1 value: 23.66 - type: mrr_at_10 value: 34.091 - type: mrr_at_100 value: 35.077999999999996 - type: mrr_at_1000 value: 35.138999999999996 - type: mrr_at_3 value: 31.516 - type: mrr_at_5 value: 33.078 - type: ndcg_at_1 value: 23.845 - type: ndcg_at_10 value: 37.594 - type: ndcg_at_100 value: 42.74 - type: ndcg_at_1000 value: 44.93 - type: ndcg_at_3 value: 31.667 - type: ndcg_at_5 value: 34.841 - type: precision_at_1 value: 23.845 - type: precision_at_10 value: 6.229 - type: precision_at_100 value: 0.943 - type: precision_at_1000 value: 0.125 - type: precision_at_3 value: 14.11 - type: precision_at_5 value: 10.388 - type: recall_at_1 value: 21.462999999999997 - type: recall_at_10 value: 52.772 - type: recall_at_100 value: 76.794 - type: recall_at_1000 value: 92.852 - type: recall_at_3 value: 37.049 - type: recall_at_5 value: 44.729 - task: type: Retrieval dataset: type: climate-fever name: MTEB ClimateFEVER config: default split: test revision: None metrics: - type: map_at_1 value: 15.466 - type: map_at_10 value: 25.275 - type: map_at_100 value: 27.176000000000002 - type: map_at_1000 value: 27.374 - type: map_at_3 value: 21.438 - type: map_at_5 value: 23.366 - type: mrr_at_1 value: 35.699999999999996 - type: mrr_at_10 value: 47.238 - type: mrr_at_100 value: 47.99 - type: mrr_at_1000 value: 48.021 - type: mrr_at_3 value: 44.463 - type: mrr_at_5 value: 46.039 - type: ndcg_at_1 value: 35.244 - type: ndcg_at_10 value: 34.559 - type: ndcg_at_100 value: 41.74 - type: ndcg_at_1000 value: 45.105000000000004 - type: ndcg_at_3 value: 29.284 - type: ndcg_at_5 value: 30.903999999999996 - type: precision_at_1 value: 35.244 - type: precision_at_10 value: 10.463000000000001 - type: precision_at_100 value: 1.8259999999999998 - type: precision_at_1000 value: 0.246 - type: precision_at_3 value: 21.65 - type: precision_at_5 value: 16.078 - type: recall_at_1 value: 15.466 - type: recall_at_10 value: 39.782000000000004 - type: recall_at_100 value: 64.622 - type: recall_at_1000 value: 83.233 - type: recall_at_3 value: 26.398 - type: recall_at_5 value: 31.676 - task: type: Retrieval dataset: type: dbpedia-entity name: MTEB DBPedia config: default split: test revision: None metrics: - type: map_at_1 value: 9.414 - type: map_at_10 value: 22.435 - type: map_at_100 value: 32.393 - type: map_at_1000 value: 34.454 - type: map_at_3 value: 15.346000000000002 - type: map_at_5 value: 18.282999999999998 - type: mrr_at_1 value: 71.5 - type: mrr_at_10 value: 78.795 - type: mrr_at_100 value: 79.046 - type: mrr_at_1000 value: 79.054 - type: mrr_at_3 value: 77.333 - type: mrr_at_5 value: 78.146 - type: ndcg_at_1 value: 60.75000000000001 - type: ndcg_at_10 value: 46.829 - type: ndcg_at_100 value: 52.370000000000005 - type: ndcg_at_1000 value: 59.943999999999996 - type: ndcg_at_3 value: 51.33 - type: ndcg_at_5 value: 48.814 - type: precision_at_1 value: 71.75 - type: precision_at_10 value: 37.525 - type: precision_at_100 value: 12.075 - type: precision_at_1000 value: 2.464 - type: precision_at_3 value: 54.75 - type: precision_at_5 value: 47.55 - type: recall_at_1 value: 9.414 - type: recall_at_10 value: 28.67 - type: recall_at_100 value: 59.924 - type: recall_at_1000 value: 83.921 - type: recall_at_3 value: 16.985 - type: recall_at_5 value: 21.372 - task: type: Classification dataset: type: mteb/emotion name: MTEB EmotionClassification config: default split: test revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 metrics: - type: accuracy value: 52.18000000000001 - type: f1 value: 47.04613218997081 - task: type: Retrieval dataset: type: fever name: MTEB FEVER config: default split: test revision: None metrics: - type: map_at_1 value: 82.57900000000001 - type: map_at_10 value: 88.465 - type: map_at_100 value: 88.649 - type: map_at_1000 value: 88.661 - type: map_at_3 value: 87.709 - type: map_at_5 value: 88.191 - type: mrr_at_1 value: 88.899 - type: mrr_at_10 value: 93.35900000000001 - type: mrr_at_100 value: 93.38499999999999 - type: mrr_at_1000 value: 93.38499999999999 - type: mrr_at_3 value: 93.012 - type: mrr_at_5 value: 93.282 - type: ndcg_at_1 value: 88.98899999999999 - type: ndcg_at_10 value: 91.22 - type: ndcg_at_100 value: 91.806 - type: ndcg_at_1000 value: 92.013 - type: ndcg_at_3 value: 90.236 - type: ndcg_at_5 value: 90.798 - type: precision_at_1 value: 88.98899999999999 - type: precision_at_10 value: 10.537 - type: precision_at_100 value: 1.106 - type: precision_at_1000 value: 0.11399999999999999 - type: precision_at_3 value: 33.598 - type: precision_at_5 value: 20.618 - type: recall_at_1 value: 82.57900000000001 - type: recall_at_10 value: 94.95400000000001 - type: recall_at_100 value: 97.14 - type: recall_at_1000 value: 98.407 - type: recall_at_3 value: 92.203 - type: recall_at_5 value: 93.747 - task: type: Retrieval dataset: type: fiqa name: MTEB FiQA2018 config: default split: test revision: None metrics: - type: map_at_1 value: 27.871000000000002 - type: map_at_10 value: 46.131 - type: map_at_100 value: 48.245 - type: map_at_1000 value: 48.361 - type: map_at_3 value: 40.03 - type: map_at_5 value: 43.634 - type: mrr_at_1 value: 52.932 - type: mrr_at_10 value: 61.61299999999999 - type: mrr_at_100 value: 62.205 - type: mrr_at_1000 value: 62.224999999999994 - type: mrr_at_3 value: 59.388 - type: mrr_at_5 value: 60.760999999999996 - type: ndcg_at_1 value: 53.395 - type: ndcg_at_10 value: 54.506 - type: ndcg_at_100 value: 61.151999999999994 - type: ndcg_at_1000 value: 62.882000000000005 - type: ndcg_at_3 value: 49.903999999999996 - type: ndcg_at_5 value: 51.599 - type: precision_at_1 value: 53.395 - type: precision_at_10 value: 15.247 - type: precision_at_100 value: 2.221 - type: precision_at_1000 value: 0.255 - type: precision_at_3 value: 33.539 - type: precision_at_5 value: 24.722 - type: recall_at_1 value: 27.871000000000002 - type: recall_at_10 value: 62.074 - type: recall_at_100 value: 86.531 - type: recall_at_1000 value: 96.574 - type: recall_at_3 value: 45.003 - type: recall_at_5 value: 53.00899999999999 - task: type: Retrieval dataset: type: hotpotqa name: MTEB HotpotQA config: default split: test revision: None metrics: - type: map_at_1 value: 40.513 - type: map_at_10 value: 69.066 - type: map_at_100 value: 69.903 - type: map_at_1000 value: 69.949 - type: map_at_3 value: 65.44200000000001 - type: map_at_5 value: 67.784 - type: mrr_at_1 value: 80.891 - type: mrr_at_10 value: 86.42699999999999 - type: mrr_at_100 value: 86.577 - type: mrr_at_1000 value: 86.58200000000001 - type: mrr_at_3 value: 85.6 - type: mrr_at_5 value: 86.114 - type: ndcg_at_1 value: 81.026 - type: ndcg_at_10 value: 76.412 - type: ndcg_at_100 value: 79.16 - type: ndcg_at_1000 value: 79.989 - type: ndcg_at_3 value: 71.45 - type: ndcg_at_5 value: 74.286 - type: precision_at_1 value: 81.026 - type: precision_at_10 value: 16.198999999999998 - type: precision_at_100 value: 1.831 - type: precision_at_1000 value: 0.194 - type: precision_at_3 value: 46.721000000000004 - type: precision_at_5 value: 30.266 - type: recall_at_1 value: 40.513 - type: recall_at_10 value: 80.99300000000001 - type: recall_at_100 value: 91.526 - type: recall_at_1000 value: 96.935 - type: recall_at_3 value: 70.081 - type: recall_at_5 value: 75.665 - task: type: Classification dataset: type: mteb/imdb name: MTEB ImdbClassification config: default split: test revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 metrics: - type: accuracy value: 87.42320000000001 - type: ap value: 83.59975323233843 - type: f1 value: 87.38669942597816 - task: type: Retrieval dataset: type: msmarco name: MTEB MSMARCO config: default split: dev revision: None metrics: - type: map_at_1 value: 22.676 - type: map_at_10 value: 35.865 - type: map_at_100 value: 37.019000000000005 - type: map_at_1000 value: 37.062 - type: map_at_3 value: 31.629 - type: map_at_5 value: 34.050999999999995 - type: mrr_at_1 value: 23.023 - type: mrr_at_10 value: 36.138999999999996 - type: mrr_at_100 value: 37.242 - type: mrr_at_1000 value: 37.28 - type: mrr_at_3 value: 32.053 - type: mrr_at_5 value: 34.383 - type: ndcg_at_1 value: 23.308999999999997 - type: ndcg_at_10 value: 43.254 - type: ndcg_at_100 value: 48.763 - type: ndcg_at_1000 value: 49.788 - type: ndcg_at_3 value: 34.688 - type: ndcg_at_5 value: 38.973 - type: precision_at_1 value: 23.308999999999997 - type: precision_at_10 value: 6.909999999999999 - type: precision_at_100 value: 0.967 - type: precision_at_1000 value: 0.106 - type: precision_at_3 value: 14.818999999999999 - type: precision_at_5 value: 11.072 - type: recall_at_1 value: 22.676 - type: recall_at_10 value: 66.077 - type: recall_at_100 value: 91.4 - type: recall_at_1000 value: 99.143 - type: recall_at_3 value: 42.845 - type: recall_at_5 value: 53.08500000000001 - task: type: Classification dataset: type: mteb/mtop_domain name: MTEB MTOPDomainClassification (en) config: en split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics: - type: accuracy value: 96.16279069767444 - type: f1 value: 96.02183835878418 - task: type: Classification dataset: type: mteb/mtop_intent name: MTEB MTOPIntentClassification (en) config: en split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics: - type: accuracy value: 85.74783401732788 - type: f1 value: 70.59661579230463 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (en) config: en split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 79.67047747141895 - type: f1 value: 77.06311183471965 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (en) config: en split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 82.82447881640887 - type: f1 value: 82.37598020010746 - task: type: Clustering dataset: type: mteb/medrxiv-clustering-p2p name: MTEB MedrxivClusteringP2P config: default split: test revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 metrics: - type: v_measure value: 30.266131881264467 - task: type: Clustering dataset: type: mteb/medrxiv-clustering-s2s name: MTEB MedrxivClusteringS2S config: default split: test revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 metrics: - type: v_measure value: 29.673653452453998 - task: type: Reranking dataset: type: mteb/mind_small name: MTEB MindSmallReranking config: default split: test revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 metrics: - type: map value: 32.91846122902102 - type: mrr value: 34.2557300204471 - task: type: Retrieval dataset: type: nfcorpus name: MTEB NFCorpus config: default split: test revision: None metrics: - type: map_at_1 value: 6.762 - type: map_at_10 value: 15.134 - type: map_at_100 value: 19.341 - type: map_at_1000 value: 20.961 - type: map_at_3 value: 10.735999999999999 - type: map_at_5 value: 12.751999999999999 - type: mrr_at_1 value: 52.941 - type: mrr_at_10 value: 60.766 - type: mrr_at_100 value: 61.196 - type: mrr_at_1000 value: 61.227 - type: mrr_at_3 value: 58.720000000000006 - type: mrr_at_5 value: 59.866 - type: ndcg_at_1 value: 50.929 - type: ndcg_at_10 value: 39.554 - type: ndcg_at_100 value: 36.307 - type: ndcg_at_1000 value: 44.743 - type: ndcg_at_3 value: 44.157000000000004 - type: ndcg_at_5 value: 42.142 - type: precision_at_1 value: 52.322 - type: precision_at_10 value: 29.412 - type: precision_at_100 value: 9.365 - type: precision_at_1000 value: 2.2159999999999997 - type: precision_at_3 value: 40.557 - type: precision_at_5 value: 35.913000000000004 - type: recall_at_1 value: 6.762 - type: recall_at_10 value: 19.689999999999998 - type: recall_at_100 value: 36.687 - type: recall_at_1000 value: 67.23 - type: recall_at_3 value: 11.773 - type: recall_at_5 value: 15.18 - task: type: Retrieval dataset: type: nq name: MTEB NQ config: default split: test revision: None metrics: - type: map_at_1 value: 36.612 - type: map_at_10 value: 54.208 - type: map_at_100 value: 55.056000000000004 - type: map_at_1000 value: 55.069 - type: map_at_3 value: 49.45 - type: map_at_5 value: 52.556000000000004 - type: mrr_at_1 value: 41.976 - type: mrr_at_10 value: 56.972 - type: mrr_at_100 value: 57.534 - type: mrr_at_1000 value: 57.542 - type: mrr_at_3 value: 53.312000000000005 - type: mrr_at_5 value: 55.672999999999995 - type: ndcg_at_1 value: 41.338 - type: ndcg_at_10 value: 62.309000000000005 - type: ndcg_at_100 value: 65.557 - type: ndcg_at_1000 value: 65.809 - type: ndcg_at_3 value: 53.74100000000001 - type: ndcg_at_5 value: 58.772999999999996 - type: precision_at_1 value: 41.338 - type: precision_at_10 value: 10.107 - type: precision_at_100 value: 1.1900000000000002 - type: precision_at_1000 value: 0.121 - type: precision_at_3 value: 24.488 - type: precision_at_5 value: 17.596 - type: recall_at_1 value: 36.612 - type: recall_at_10 value: 84.408 - type: recall_at_100 value: 97.929 - type: recall_at_1000 value: 99.725 - type: recall_at_3 value: 62.676 - type: recall_at_5 value: 74.24199999999999 - task: type: Retrieval dataset: type: quora name: MTEB QuoraRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 71.573 - type: map_at_10 value: 85.81 - type: map_at_100 value: 86.434 - type: map_at_1000 value: 86.446 - type: map_at_3 value: 82.884 - type: map_at_5 value: 84.772 - type: mrr_at_1 value: 82.53 - type: mrr_at_10 value: 88.51299999999999 - type: mrr_at_100 value: 88.59700000000001 - type: mrr_at_1000 value: 88.598 - type: mrr_at_3 value: 87.595 - type: mrr_at_5 value: 88.266 - type: ndcg_at_1 value: 82.39999999999999 - type: ndcg_at_10 value: 89.337 - type: ndcg_at_100 value: 90.436 - type: ndcg_at_1000 value: 90.498 - type: ndcg_at_3 value: 86.676 - type: ndcg_at_5 value: 88.241 - type: precision_at_1 value: 82.39999999999999 - type: precision_at_10 value: 13.58 - type: precision_at_100 value: 1.543 - type: precision_at_1000 value: 0.157 - type: precision_at_3 value: 38.04 - type: precision_at_5 value: 25.044 - type: recall_at_1 value: 71.573 - type: recall_at_10 value: 96.066 - type: recall_at_100 value: 99.73100000000001 - type: recall_at_1000 value: 99.991 - type: recall_at_3 value: 88.34 - type: recall_at_5 value: 92.79899999999999 - task: type: Clustering dataset: type: mteb/reddit-clustering name: MTEB RedditClustering config: default split: test revision: 24640382cdbf8abc73003fb0fa6d111a705499eb metrics: - type: v_measure value: 61.767168063971724 - task: type: Clustering dataset: type: mteb/reddit-clustering-p2p name: MTEB RedditClusteringP2P config: default split: test revision: 282350215ef01743dc01b456c7f5241fa8937f16 metrics: - type: v_measure value: 66.00502775826037 - task: type: Retrieval dataset: type: scidocs name: MTEB SCIDOCS config: default split: test revision: None metrics: - type: map_at_1 value: 4.718 - type: map_at_10 value: 12.13 - type: map_at_100 value: 14.269000000000002 - type: map_at_1000 value: 14.578 - type: map_at_3 value: 8.605 - type: map_at_5 value: 10.483 - type: mrr_at_1 value: 23.7 - type: mrr_at_10 value: 34.354 - type: mrr_at_100 value: 35.522 - type: mrr_at_1000 value: 35.571999999999996 - type: mrr_at_3 value: 31.15 - type: mrr_at_5 value: 32.98 - type: ndcg_at_1 value: 23.3 - type: ndcg_at_10 value: 20.171 - type: ndcg_at_100 value: 28.456 - type: ndcg_at_1000 value: 33.826 - type: ndcg_at_3 value: 19.104 - type: ndcg_at_5 value: 16.977999999999998 - type: precision_at_1 value: 23.3 - type: precision_at_10 value: 10.45 - type: precision_at_100 value: 2.239 - type: precision_at_1000 value: 0.35300000000000004 - type: precision_at_3 value: 17.933 - type: precision_at_5 value: 15.1 - type: recall_at_1 value: 4.718 - type: recall_at_10 value: 21.221999999999998 - type: recall_at_100 value: 45.42 - type: recall_at_1000 value: 71.642 - type: recall_at_3 value: 10.922 - type: recall_at_5 value: 15.322 - task: type: STS dataset: type: mteb/sickr-sts name: MTEB SICK-R config: default split: test revision: a6ea5a8cab320b040a23452cc28066d9beae2cee metrics: - type: cos_sim_pearson value: 85.2065344862739 - type: cos_sim_spearman value: 83.2276569587515 - type: euclidean_pearson value: 83.42726762105312 - type: euclidean_spearman value: 83.31396596997742 - type: manhattan_pearson value: 83.41123401762816 - type: manhattan_spearman value: 83.34393052682026 - task: type: STS dataset: type: mteb/sts12-sts name: MTEB STS12 config: default split: test revision: a0d554a64d88156834ff5ae9920b964011b16384 metrics: - type: cos_sim_pearson value: 81.28253173719754 - type: cos_sim_spearman value: 76.12995701324436 - type: euclidean_pearson value: 75.30693691794121 - type: euclidean_spearman value: 75.12472789129536 - type: manhattan_pearson value: 75.35860808729171 - type: manhattan_spearman value: 75.30445827952794 - task: type: STS dataset: type: mteb/sts13-sts name: MTEB STS13 config: default split: test revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca metrics: - type: cos_sim_pearson value: 82.09358031005694 - type: cos_sim_spearman value: 83.18811147636619 - type: euclidean_pearson value: 82.65513459991631 - type: euclidean_spearman value: 82.71085530442987 - type: manhattan_pearson value: 82.67700926821576 - type: manhattan_spearman value: 82.73815539380426 - task: type: STS dataset: type: mteb/sts14-sts name: MTEB STS14 config: default split: test revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 metrics: - type: cos_sim_pearson value: 81.51365440223137 - type: cos_sim_spearman value: 80.59933905019179 - type: euclidean_pearson value: 80.56660025433806 - type: euclidean_spearman value: 80.27926539084027 - type: manhattan_pearson value: 80.64632724055481 - type: manhattan_spearman value: 80.43616365139444 - task: type: STS dataset: type: mteb/sts15-sts name: MTEB STS15 config: default split: test revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 metrics: - type: cos_sim_pearson value: 86.8590461417506 - type: cos_sim_spearman value: 87.16337291721602 - type: euclidean_pearson value: 85.8847725068404 - type: euclidean_spearman value: 86.12602873624066 - type: manhattan_pearson value: 86.04095861363909 - type: manhattan_spearman value: 86.35535645007629 - task: type: STS dataset: type: mteb/sts16-sts name: MTEB STS16 config: default split: test revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 metrics: - type: cos_sim_pearson value: 83.61371557181502 - type: cos_sim_spearman value: 85.16330754442785 - type: euclidean_pearson value: 84.20831431260608 - type: euclidean_spearman value: 84.33191523212125 - type: manhattan_pearson value: 84.34911007642411 - type: manhattan_spearman value: 84.49670164290394 - 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: 90.54452933158781 - type: cos_sim_spearman value: 90.88214621695892 - type: euclidean_pearson value: 91.38488015281216 - type: euclidean_spearman value: 91.01822259603908 - type: manhattan_pearson value: 91.36449776198687 - type: manhattan_spearman value: 90.90478717381717 - 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: 68.00941643037453 - type: cos_sim_spearman value: 67.03588472081898 - type: euclidean_pearson value: 67.35224911601603 - type: euclidean_spearman value: 66.35544831459266 - type: manhattan_pearson value: 67.35080066508304 - type: manhattan_spearman value: 66.07893473733782 - task: type: STS dataset: type: mteb/stsbenchmark-sts name: MTEB STSBenchmark config: default split: test revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 metrics: - type: cos_sim_pearson value: 85.18291011086279 - type: cos_sim_spearman value: 85.66913777481429 - type: euclidean_pearson value: 84.81115930027242 - type: euclidean_spearman value: 85.07133983924173 - type: manhattan_pearson value: 84.88932120524983 - type: manhattan_spearman value: 85.176903109055 - task: type: Reranking dataset: type: mteb/scidocs-reranking name: MTEB SciDocsRR config: default split: test revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab metrics: - type: map value: 83.67543572266588 - type: mrr value: 95.9468146232852 - task: type: Retrieval dataset: type: scifact name: MTEB SciFact config: default split: test revision: None metrics: - type: map_at_1 value: 59.633 - type: map_at_10 value: 69.801 - type: map_at_100 value: 70.504 - type: map_at_1000 value: 70.519 - type: map_at_3 value: 67.72500000000001 - type: map_at_5 value: 68.812 - type: mrr_at_1 value: 62.333000000000006 - type: mrr_at_10 value: 70.956 - type: mrr_at_100 value: 71.489 - type: mrr_at_1000 value: 71.504 - type: mrr_at_3 value: 69.44399999999999 - type: mrr_at_5 value: 70.244 - type: ndcg_at_1 value: 62.0 - type: ndcg_at_10 value: 73.98599999999999 - type: ndcg_at_100 value: 76.629 - type: ndcg_at_1000 value: 77.054 - type: ndcg_at_3 value: 70.513 - type: ndcg_at_5 value: 71.978 - type: precision_at_1 value: 62.0 - type: precision_at_10 value: 9.633 - type: precision_at_100 value: 1.097 - type: precision_at_1000 value: 0.11299999999999999 - type: precision_at_3 value: 27.556000000000004 - type: precision_at_5 value: 17.666999999999998 - type: recall_at_1 value: 59.633 - type: recall_at_10 value: 85.52199999999999 - type: recall_at_100 value: 96.667 - type: recall_at_1000 value: 100.0 - type: recall_at_3 value: 75.767 - type: recall_at_5 value: 79.76100000000001 - task: type: PairClassification dataset: type: mteb/sprintduplicatequestions-pairclassification name: MTEB SprintDuplicateQuestions config: default split: test revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 metrics: - type: cos_sim_accuracy value: 99.77821782178218 - type: cos_sim_ap value: 94.58684455008866 - type: cos_sim_f1 value: 88.51282051282053 - type: cos_sim_precision value: 90.84210526315789 - type: cos_sim_recall value: 86.3 - type: dot_accuracy value: 99.77623762376237 - type: dot_ap value: 94.86277541733045 - type: dot_f1 value: 88.66897575457693 - type: dot_precision value: 87.75710088148874 - type: dot_recall value: 89.60000000000001 - type: euclidean_accuracy value: 99.76732673267327 - type: euclidean_ap value: 94.12114402691984 - type: euclidean_f1 value: 87.96804792810784 - type: euclidean_precision value: 87.83649052841476 - type: euclidean_recall value: 88.1 - type: manhattan_accuracy value: 99.77227722772277 - type: manhattan_ap value: 94.33665105240306 - type: manhattan_f1 value: 88.25587206396803 - type: manhattan_precision value: 88.21178821178822 - type: manhattan_recall value: 88.3 - type: max_accuracy value: 99.77821782178218 - type: max_ap value: 94.86277541733045 - type: max_f1 value: 88.66897575457693 - task: type: Clustering dataset: type: mteb/stackexchange-clustering name: MTEB StackExchangeClustering config: default split: test revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 metrics: - type: v_measure value: 72.03943478268592 - task: type: Clustering dataset: type: mteb/stackexchange-clustering-p2p name: MTEB StackExchangeClusteringP2P config: default split: test revision: 815ca46b2622cec33ccafc3735d572c266efdb44 metrics: - type: v_measure value: 35.285037897356496 - task: type: Reranking dataset: type: mteb/stackoverflowdupquestions-reranking name: MTEB StackOverflowDupQuestions config: default split: test revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 metrics: - type: map value: 51.83578447913503 - type: mrr value: 52.69070696460402 - task: type: Summarization dataset: type: mteb/summeval name: MTEB SummEval config: default split: test revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c metrics: - type: cos_sim_pearson value: 30.89437612567638 - type: cos_sim_spearman value: 30.7277819987126 - type: dot_pearson value: 30.999783674122526 - type: dot_spearman value: 30.992168551124905 - task: type: Retrieval dataset: type: trec-covid name: MTEB TRECCOVID config: default split: test revision: None metrics: - type: map_at_1 value: 0.22699999999999998 - type: map_at_10 value: 1.8950000000000002 - type: map_at_100 value: 11.712 - type: map_at_1000 value: 28.713 - type: map_at_3 value: 0.65 - type: map_at_5 value: 1.011 - type: mrr_at_1 value: 92.0 - type: mrr_at_10 value: 95.39999999999999 - type: mrr_at_100 value: 95.39999999999999 - type: mrr_at_1000 value: 95.39999999999999 - type: mrr_at_3 value: 95.0 - type: mrr_at_5 value: 95.39999999999999 - type: ndcg_at_1 value: 83.0 - type: ndcg_at_10 value: 76.658 - type: ndcg_at_100 value: 60.755 - type: ndcg_at_1000 value: 55.05 - type: ndcg_at_3 value: 82.961 - type: ndcg_at_5 value: 80.008 - type: precision_at_1 value: 90.0 - type: precision_at_10 value: 79.80000000000001 - type: precision_at_100 value: 62.019999999999996 - type: precision_at_1000 value: 24.157999999999998 - type: precision_at_3 value: 88.0 - type: precision_at_5 value: 83.6 - type: recall_at_1 value: 0.22699999999999998 - type: recall_at_10 value: 2.086 - type: recall_at_100 value: 15.262 - type: recall_at_1000 value: 51.800000000000004 - type: recall_at_3 value: 0.679 - type: recall_at_5 value: 1.0739999999999998 - task: type: Retrieval dataset: type: webis-touche2020 name: MTEB Touche2020 config: default split: test revision: None metrics: - type: map_at_1 value: 1.521 - type: map_at_10 value: 7.281 - type: map_at_100 value: 12.717 - type: map_at_1000 value: 14.266000000000002 - type: map_at_3 value: 3.62 - type: map_at_5 value: 4.7010000000000005 - type: mrr_at_1 value: 18.367 - type: mrr_at_10 value: 34.906 - type: mrr_at_100 value: 36.333 - type: mrr_at_1000 value: 36.348 - type: mrr_at_3 value: 29.592000000000002 - type: mrr_at_5 value: 33.367000000000004 - type: ndcg_at_1 value: 19.387999999999998 - type: ndcg_at_10 value: 18.523 - type: ndcg_at_100 value: 30.932 - type: ndcg_at_1000 value: 42.942 - type: ndcg_at_3 value: 18.901 - type: ndcg_at_5 value: 17.974999999999998 - type: precision_at_1 value: 20.408 - type: precision_at_10 value: 17.347 - type: precision_at_100 value: 6.898 - type: precision_at_1000 value: 1.482 - type: precision_at_3 value: 21.088 - type: precision_at_5 value: 19.184 - type: recall_at_1 value: 1.521 - type: recall_at_10 value: 13.406 - type: recall_at_100 value: 43.418 - type: recall_at_1000 value: 80.247 - type: recall_at_3 value: 4.673 - type: recall_at_5 value: 7.247000000000001 - task: type: Classification dataset: type: mteb/toxic_conversations_50k name: MTEB ToxicConversationsClassification config: default split: test revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c metrics: - type: accuracy value: 71.9084 - type: ap value: 15.388385311898144 - type: f1 value: 55.760189174489426 - task: type: Classification dataset: type: mteb/tweet_sentiment_extraction name: MTEB TweetSentimentExtractionClassification config: default split: test revision: d604517c81ca91fe16a244d1248fc021f9ecee7a metrics: - type: accuracy value: 62.399547255234864 - type: f1 value: 62.61398519525303 - task: type: Clustering dataset: type: mteb/twentynewsgroups-clustering name: MTEB TwentyNewsgroupsClustering config: default split: test revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 metrics: - type: v_measure value: 53.041094760846164 - task: type: PairClassification dataset: type: mteb/twittersemeval2015-pairclassification name: MTEB TwitterSemEval2015 config: default split: test revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 metrics: - type: cos_sim_accuracy value: 87.92394349406926 - type: cos_sim_ap value: 79.93037248584875 - type: cos_sim_f1 value: 73.21063394683026 - type: cos_sim_precision value: 70.99652949925633 - type: cos_sim_recall value: 75.56728232189973 - type: dot_accuracy value: 87.80473266972642 - type: dot_ap value: 79.11055417163318 - type: dot_f1 value: 72.79587473273801 - type: dot_precision value: 69.55058880076905 - type: dot_recall value: 76.35883905013192 - type: euclidean_accuracy value: 87.91202241163496 - type: euclidean_ap value: 79.61955502404068 - type: euclidean_f1 value: 72.65956080647231 - type: euclidean_precision value: 70.778083562672 - type: euclidean_recall value: 74.64379947229551 - type: manhattan_accuracy value: 87.7749299636407 - type: manhattan_ap value: 79.33286131650932 - type: manhattan_f1 value: 72.44748412310699 - type: manhattan_precision value: 67.43974533879036 - type: manhattan_recall value: 78.25857519788919 - type: max_accuracy value: 87.92394349406926 - type: max_ap value: 79.93037248584875 - type: max_f1 value: 73.21063394683026 - task: type: PairClassification dataset: type: mteb/twitterurlcorpus-pairclassification name: MTEB TwitterURLCorpus config: default split: test revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf metrics: - type: cos_sim_accuracy value: 89.89987192921178 - type: cos_sim_ap value: 87.49525152555509 - type: cos_sim_f1 value: 80.05039276715578 - type: cos_sim_precision value: 77.15714285714286 - type: cos_sim_recall value: 83.1690791499846 - type: dot_accuracy value: 89.58163542515621 - type: dot_ap value: 86.87353801172357 - type: dot_f1 value: 79.50204384986993 - type: dot_precision value: 76.83522482401953 - type: dot_recall value: 82.36064059131506 - type: euclidean_accuracy value: 89.81255093724532 - type: euclidean_ap value: 87.41058010369022 - type: euclidean_f1 value: 79.94095829233214 - type: euclidean_precision value: 78.61396456751525 - type: euclidean_recall value: 81.3135201724669 - type: manhattan_accuracy value: 89.84553886754377 - type: manhattan_ap value: 87.41173628281432 - type: manhattan_f1 value: 79.9051922079846 - type: manhattan_precision value: 76.98016269444841 - type: manhattan_recall value: 83.06128734216199 - type: max_accuracy value: 89.89987192921178 - type: max_ap value: 87.49525152555509 - type: max_f1 value: 80.05039276715578 --- # Repetition Improves Language Model Embeddings Please refer to our paper: [https://arxiv.org/abs/2402.15449](https://arxiv.org/abs/2402.15449) And our GitHub: [https://github.com/jakespringer/echo-embeddings](https://github.com/jakespringer/echo-embeddings) We provide a description of the model as well as example usage in the above links.