--- tags: - mteb model-index: - name: bge-large-en results: - task: type: Classification dataset: type: mteb/amazon_counterfactual name: MTEB AmazonCounterfactualClassification (en) config: en split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics: - type: accuracy value: 76.94029850746269 - type: ap value: 40.00228964744091 - type: f1 value: 70.86088267934595 - task: type: Classification dataset: type: mteb/amazon_polarity name: MTEB AmazonPolarityClassification config: default split: test revision: e2d317d38cd51312af73b3d32a06d1a08b442046 metrics: - type: accuracy value: 91.93745 - type: ap value: 88.24758534667426 - type: f1 value: 91.91033034217591 - task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (en) config: en split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics: - type: accuracy value: 46.158 - type: f1 value: 45.78935185074774 - task: type: Retrieval dataset: type: arguana name: MTEB ArguAna config: default split: test revision: None metrics: - type: map_at_1 value: 39.972 - type: map_at_10 value: 54.874 - type: map_at_100 value: 55.53399999999999 - type: map_at_1000 value: 55.539 - type: map_at_3 value: 51.031000000000006 - type: map_at_5 value: 53.342999999999996 - type: mrr_at_1 value: 40.541 - type: mrr_at_10 value: 55.096000000000004 - type: mrr_at_100 value: 55.75599999999999 - type: mrr_at_1000 value: 55.761 - type: mrr_at_3 value: 51.221000000000004 - type: mrr_at_5 value: 53.568000000000005 - type: ndcg_at_1 value: 39.972 - type: ndcg_at_10 value: 62.456999999999994 - type: ndcg_at_100 value: 65.262 - type: ndcg_at_1000 value: 65.389 - type: ndcg_at_3 value: 54.673 - type: ndcg_at_5 value: 58.80499999999999 - type: precision_at_1 value: 39.972 - type: precision_at_10 value: 8.634 - type: precision_at_100 value: 0.9860000000000001 - type: precision_at_1000 value: 0.1 - type: precision_at_3 value: 21.740000000000002 - type: precision_at_5 value: 15.036 - type: recall_at_1 value: 39.972 - type: recall_at_10 value: 86.344 - type: recall_at_100 value: 98.578 - type: recall_at_1000 value: 99.57300000000001 - type: recall_at_3 value: 65.22 - type: recall_at_5 value: 75.178 - task: type: Clustering dataset: type: mteb/arxiv-clustering-p2p name: MTEB ArxivClusteringP2P config: default split: test revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d metrics: - type: v_measure value: 48.94652870403906 - task: type: Clustering dataset: type: mteb/arxiv-clustering-s2s name: MTEB ArxivClusteringS2S config: default split: test revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 metrics: - type: v_measure value: 43.17257160340209 - task: type: Reranking dataset: type: mteb/askubuntudupquestions-reranking name: MTEB AskUbuntuDupQuestions config: default split: test revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 metrics: - type: map value: 63.97867370559182 - type: mrr value: 77.00820032537484 - task: type: STS dataset: type: mteb/biosses-sts name: MTEB BIOSSES config: default split: test revision: d3fb88f8f02e40887cd149695127462bbcf29b4a metrics: - type: cos_sim_pearson value: 80.00986015960616 - type: cos_sim_spearman value: 80.36387933827882 - type: euclidean_pearson value: 80.32305287257296 - type: euclidean_spearman value: 82.0524720308763 - type: manhattan_pearson value: 80.19847473906454 - type: manhattan_spearman value: 81.87957652506985 - task: type: Classification dataset: type: mteb/banking77 name: MTEB Banking77Classification config: default split: test revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 metrics: - type: accuracy value: 88.00000000000001 - type: f1 value: 87.99039027511853 - task: type: Clustering dataset: type: mteb/biorxiv-clustering-p2p name: MTEB BiorxivClusteringP2P config: default split: test revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 metrics: - type: v_measure value: 41.36932844640705 - task: type: Clustering dataset: type: mteb/biorxiv-clustering-s2s name: MTEB BiorxivClusteringS2S config: default split: test revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 metrics: - type: v_measure value: 38.34983239611985 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackAndroidRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 32.257999999999996 - type: map_at_10 value: 42.937 - type: map_at_100 value: 44.406 - type: map_at_1000 value: 44.536 - type: map_at_3 value: 39.22 - type: map_at_5 value: 41.458 - type: mrr_at_1 value: 38.769999999999996 - type: mrr_at_10 value: 48.701 - type: mrr_at_100 value: 49.431000000000004 - type: mrr_at_1000 value: 49.476 - type: mrr_at_3 value: 45.875 - type: mrr_at_5 value: 47.67 - type: ndcg_at_1 value: 38.769999999999996 - type: ndcg_at_10 value: 49.35 - type: ndcg_at_100 value: 54.618 - type: ndcg_at_1000 value: 56.655 - type: ndcg_at_3 value: 43.826 - type: ndcg_at_5 value: 46.72 - type: precision_at_1 value: 38.769999999999996 - type: precision_at_10 value: 9.328 - type: precision_at_100 value: 1.484 - type: precision_at_1000 value: 0.196 - type: precision_at_3 value: 20.649 - type: precision_at_5 value: 15.25 - type: recall_at_1 value: 32.257999999999996 - type: recall_at_10 value: 61.849 - type: recall_at_100 value: 83.70400000000001 - type: recall_at_1000 value: 96.344 - type: recall_at_3 value: 46.037 - type: recall_at_5 value: 53.724000000000004 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackEnglishRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 32.979 - type: map_at_10 value: 43.376999999999995 - type: map_at_100 value: 44.667 - type: map_at_1000 value: 44.794 - type: map_at_3 value: 40.461999999999996 - type: map_at_5 value: 42.138 - type: mrr_at_1 value: 41.146 - type: mrr_at_10 value: 49.575 - type: mrr_at_100 value: 50.187000000000005 - type: mrr_at_1000 value: 50.231 - type: mrr_at_3 value: 47.601 - type: mrr_at_5 value: 48.786 - type: ndcg_at_1 value: 41.146 - type: ndcg_at_10 value: 48.957 - type: ndcg_at_100 value: 53.296 - type: ndcg_at_1000 value: 55.254000000000005 - type: ndcg_at_3 value: 45.235 - type: ndcg_at_5 value: 47.014 - type: precision_at_1 value: 41.146 - type: precision_at_10 value: 9.107999999999999 - type: precision_at_100 value: 1.481 - type: precision_at_1000 value: 0.193 - type: precision_at_3 value: 21.783 - type: precision_at_5 value: 15.274 - type: recall_at_1 value: 32.979 - type: recall_at_10 value: 58.167 - type: recall_at_100 value: 76.374 - type: recall_at_1000 value: 88.836 - type: recall_at_3 value: 46.838 - type: recall_at_5 value: 52.006 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGamingRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 40.326 - type: map_at_10 value: 53.468 - type: map_at_100 value: 54.454 - type: map_at_1000 value: 54.508 - type: map_at_3 value: 50.12799999999999 - type: map_at_5 value: 51.991 - type: mrr_at_1 value: 46.394999999999996 - type: mrr_at_10 value: 57.016999999999996 - type: mrr_at_100 value: 57.67099999999999 - type: mrr_at_1000 value: 57.699999999999996 - type: mrr_at_3 value: 54.65 - type: mrr_at_5 value: 56.101 - type: ndcg_at_1 value: 46.394999999999996 - type: ndcg_at_10 value: 59.507 - type: ndcg_at_100 value: 63.31099999999999 - type: ndcg_at_1000 value: 64.388 - type: ndcg_at_3 value: 54.04600000000001 - type: ndcg_at_5 value: 56.723 - type: precision_at_1 value: 46.394999999999996 - type: precision_at_10 value: 9.567 - type: precision_at_100 value: 1.234 - type: precision_at_1000 value: 0.13699999999999998 - type: precision_at_3 value: 24.117 - type: precision_at_5 value: 16.426 - type: recall_at_1 value: 40.326 - type: recall_at_10 value: 73.763 - type: recall_at_100 value: 89.927 - type: recall_at_1000 value: 97.509 - type: recall_at_3 value: 59.34 - type: recall_at_5 value: 65.915 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGisRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 26.661 - type: map_at_10 value: 35.522 - type: map_at_100 value: 36.619 - type: map_at_1000 value: 36.693999999999996 - type: map_at_3 value: 33.154 - type: map_at_5 value: 34.353 - type: mrr_at_1 value: 28.362 - type: mrr_at_10 value: 37.403999999999996 - type: mrr_at_100 value: 38.374 - type: mrr_at_1000 value: 38.428000000000004 - type: mrr_at_3 value: 35.235 - type: mrr_at_5 value: 36.269 - type: ndcg_at_1 value: 28.362 - type: ndcg_at_10 value: 40.431 - type: ndcg_at_100 value: 45.745999999999995 - type: ndcg_at_1000 value: 47.493 - type: ndcg_at_3 value: 35.733 - type: ndcg_at_5 value: 37.722 - type: precision_at_1 value: 28.362 - type: precision_at_10 value: 6.101999999999999 - type: precision_at_100 value: 0.922 - type: precision_at_1000 value: 0.11100000000000002 - type: precision_at_3 value: 15.140999999999998 - type: precision_at_5 value: 10.305 - type: recall_at_1 value: 26.661 - type: recall_at_10 value: 53.675 - type: recall_at_100 value: 77.891 - type: recall_at_1000 value: 90.72 - type: recall_at_3 value: 40.751 - type: recall_at_5 value: 45.517 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackMathematicaRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 18.886 - type: map_at_10 value: 27.288 - type: map_at_100 value: 28.327999999999996 - type: map_at_1000 value: 28.438999999999997 - type: map_at_3 value: 24.453 - type: map_at_5 value: 25.959 - type: mrr_at_1 value: 23.134 - type: mrr_at_10 value: 32.004 - type: mrr_at_100 value: 32.789 - type: mrr_at_1000 value: 32.857 - type: mrr_at_3 value: 29.084 - type: mrr_at_5 value: 30.614 - type: ndcg_at_1 value: 23.134 - type: ndcg_at_10 value: 32.852 - type: ndcg_at_100 value: 37.972 - type: ndcg_at_1000 value: 40.656 - type: ndcg_at_3 value: 27.435 - type: ndcg_at_5 value: 29.823 - type: precision_at_1 value: 23.134 - type: precision_at_10 value: 6.032 - type: precision_at_100 value: 0.9950000000000001 - type: precision_at_1000 value: 0.136 - type: precision_at_3 value: 13.017999999999999 - type: precision_at_5 value: 9.501999999999999 - type: recall_at_1 value: 18.886 - type: recall_at_10 value: 45.34 - type: recall_at_100 value: 67.947 - type: recall_at_1000 value: 86.924 - type: recall_at_3 value: 30.535 - type: recall_at_5 value: 36.451 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackPhysicsRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 28.994999999999997 - type: map_at_10 value: 40.04 - type: map_at_100 value: 41.435 - type: map_at_1000 value: 41.537 - type: map_at_3 value: 37.091 - type: map_at_5 value: 38.802 - type: mrr_at_1 value: 35.034 - type: mrr_at_10 value: 45.411 - type: mrr_at_100 value: 46.226 - type: mrr_at_1000 value: 46.27 - type: mrr_at_3 value: 43.086 - type: mrr_at_5 value: 44.452999999999996 - type: ndcg_at_1 value: 35.034 - type: ndcg_at_10 value: 46.076 - type: ndcg_at_100 value: 51.483000000000004 - type: ndcg_at_1000 value: 53.433 - type: ndcg_at_3 value: 41.304 - type: ndcg_at_5 value: 43.641999999999996 - type: precision_at_1 value: 35.034 - type: precision_at_10 value: 8.258000000000001 - type: precision_at_100 value: 1.268 - type: precision_at_1000 value: 0.161 - type: precision_at_3 value: 19.57 - type: precision_at_5 value: 13.782 - type: recall_at_1 value: 28.994999999999997 - type: recall_at_10 value: 58.538000000000004 - type: recall_at_100 value: 80.72399999999999 - type: recall_at_1000 value: 93.462 - type: recall_at_3 value: 45.199 - type: recall_at_5 value: 51.237 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackProgrammersRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 24.795 - type: map_at_10 value: 34.935 - type: map_at_100 value: 36.306 - type: map_at_1000 value: 36.417 - type: map_at_3 value: 31.831 - type: map_at_5 value: 33.626 - type: mrr_at_1 value: 30.479 - type: mrr_at_10 value: 40.225 - type: mrr_at_100 value: 41.055 - type: mrr_at_1000 value: 41.114 - type: mrr_at_3 value: 37.538 - type: mrr_at_5 value: 39.073 - type: ndcg_at_1 value: 30.479 - type: ndcg_at_10 value: 40.949999999999996 - type: ndcg_at_100 value: 46.525 - type: ndcg_at_1000 value: 48.892 - type: ndcg_at_3 value: 35.79 - type: ndcg_at_5 value: 38.237 - type: precision_at_1 value: 30.479 - type: precision_at_10 value: 7.6259999999999994 - type: precision_at_100 value: 1.203 - type: precision_at_1000 value: 0.157 - type: precision_at_3 value: 17.199 - type: precision_at_5 value: 12.466000000000001 - type: recall_at_1 value: 24.795 - type: recall_at_10 value: 53.421 - type: recall_at_100 value: 77.189 - type: recall_at_1000 value: 93.407 - type: recall_at_3 value: 39.051 - type: recall_at_5 value: 45.462 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 26.853499999999997 - type: map_at_10 value: 36.20433333333333 - type: map_at_100 value: 37.40391666666667 - type: map_at_1000 value: 37.515 - type: map_at_3 value: 33.39975 - type: map_at_5 value: 34.9665 - type: mrr_at_1 value: 31.62666666666667 - type: mrr_at_10 value: 40.436749999999996 - type: mrr_at_100 value: 41.260333333333335 - type: mrr_at_1000 value: 41.31525 - type: mrr_at_3 value: 38.06733333333332 - type: mrr_at_5 value: 39.41541666666667 - type: ndcg_at_1 value: 31.62666666666667 - type: ndcg_at_10 value: 41.63341666666667 - type: ndcg_at_100 value: 46.704166666666666 - type: ndcg_at_1000 value: 48.88483333333335 - type: ndcg_at_3 value: 36.896 - type: ndcg_at_5 value: 39.11891666666667 - type: precision_at_1 value: 31.62666666666667 - type: precision_at_10 value: 7.241083333333333 - type: precision_at_100 value: 1.1488333333333334 - type: precision_at_1000 value: 0.15250000000000002 - type: precision_at_3 value: 16.908333333333335 - type: precision_at_5 value: 11.942833333333333 - type: recall_at_1 value: 26.853499999999997 - type: recall_at_10 value: 53.461333333333336 - type: recall_at_100 value: 75.63633333333333 - type: recall_at_1000 value: 90.67016666666666 - type: recall_at_3 value: 40.24241666666667 - type: recall_at_5 value: 45.98608333333333 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackStatsRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 25.241999999999997 - type: map_at_10 value: 31.863999999999997 - type: map_at_100 value: 32.835 - type: map_at_1000 value: 32.928000000000004 - type: map_at_3 value: 29.694 - type: map_at_5 value: 30.978 - type: mrr_at_1 value: 28.374 - type: mrr_at_10 value: 34.814 - type: mrr_at_100 value: 35.596 - type: mrr_at_1000 value: 35.666 - type: mrr_at_3 value: 32.745000000000005 - type: mrr_at_5 value: 34.049 - type: ndcg_at_1 value: 28.374 - type: ndcg_at_10 value: 35.969 - type: ndcg_at_100 value: 40.708 - type: ndcg_at_1000 value: 43.08 - type: ndcg_at_3 value: 31.968999999999998 - type: ndcg_at_5 value: 34.069 - type: precision_at_1 value: 28.374 - type: precision_at_10 value: 5.583 - type: precision_at_100 value: 0.8630000000000001 - type: precision_at_1000 value: 0.11299999999999999 - type: precision_at_3 value: 13.547999999999998 - type: precision_at_5 value: 9.447999999999999 - type: recall_at_1 value: 25.241999999999997 - type: recall_at_10 value: 45.711 - type: recall_at_100 value: 67.482 - type: recall_at_1000 value: 85.13300000000001 - type: recall_at_3 value: 34.622 - type: recall_at_5 value: 40.043 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackTexRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 17.488999999999997 - type: map_at_10 value: 25.142999999999997 - type: map_at_100 value: 26.244 - type: map_at_1000 value: 26.363999999999997 - type: map_at_3 value: 22.654 - type: map_at_5 value: 24.017 - type: mrr_at_1 value: 21.198 - type: mrr_at_10 value: 28.903000000000002 - type: mrr_at_100 value: 29.860999999999997 - type: mrr_at_1000 value: 29.934 - type: mrr_at_3 value: 26.634999999999998 - type: mrr_at_5 value: 27.903 - type: ndcg_at_1 value: 21.198 - type: ndcg_at_10 value: 29.982999999999997 - type: ndcg_at_100 value: 35.275 - type: ndcg_at_1000 value: 38.074000000000005 - type: ndcg_at_3 value: 25.502999999999997 - type: ndcg_at_5 value: 27.557 - type: precision_at_1 value: 21.198 - type: precision_at_10 value: 5.502 - type: precision_at_100 value: 0.942 - type: precision_at_1000 value: 0.136 - type: precision_at_3 value: 12.044 - type: precision_at_5 value: 8.782 - type: recall_at_1 value: 17.488999999999997 - type: recall_at_10 value: 40.821000000000005 - type: recall_at_100 value: 64.567 - type: recall_at_1000 value: 84.452 - type: recall_at_3 value: 28.351 - type: recall_at_5 value: 33.645 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackUnixRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 27.066000000000003 - type: map_at_10 value: 36.134 - type: map_at_100 value: 37.285000000000004 - type: map_at_1000 value: 37.389 - type: map_at_3 value: 33.522999999999996 - type: map_at_5 value: 34.905 - type: mrr_at_1 value: 31.436999999999998 - type: mrr_at_10 value: 40.225 - type: mrr_at_100 value: 41.079 - type: mrr_at_1000 value: 41.138000000000005 - type: mrr_at_3 value: 38.074999999999996 - type: mrr_at_5 value: 39.190000000000005 - type: ndcg_at_1 value: 31.436999999999998 - type: ndcg_at_10 value: 41.494 - type: ndcg_at_100 value: 46.678999999999995 - type: ndcg_at_1000 value: 48.964 - type: ndcg_at_3 value: 36.828 - type: ndcg_at_5 value: 38.789 - type: precision_at_1 value: 31.436999999999998 - type: precision_at_10 value: 6.931 - type: precision_at_100 value: 1.072 - type: precision_at_1000 value: 0.13799999999999998 - type: precision_at_3 value: 16.729 - type: precision_at_5 value: 11.567 - type: recall_at_1 value: 27.066000000000003 - type: recall_at_10 value: 53.705000000000005 - type: recall_at_100 value: 75.968 - type: recall_at_1000 value: 91.937 - type: recall_at_3 value: 40.865 - type: recall_at_5 value: 45.739999999999995 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWebmastersRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 24.979000000000003 - type: map_at_10 value: 32.799 - type: map_at_100 value: 34.508 - type: map_at_1000 value: 34.719 - type: map_at_3 value: 29.947000000000003 - type: map_at_5 value: 31.584 - type: mrr_at_1 value: 30.237000000000002 - type: mrr_at_10 value: 37.651 - type: mrr_at_100 value: 38.805 - type: mrr_at_1000 value: 38.851 - type: mrr_at_3 value: 35.046 - type: mrr_at_5 value: 36.548 - type: ndcg_at_1 value: 30.237000000000002 - type: ndcg_at_10 value: 38.356 - type: ndcg_at_100 value: 44.906 - type: ndcg_at_1000 value: 47.299 - type: ndcg_at_3 value: 33.717999999999996 - type: ndcg_at_5 value: 35.946 - type: precision_at_1 value: 30.237000000000002 - type: precision_at_10 value: 7.292 - type: precision_at_100 value: 1.496 - type: precision_at_1000 value: 0.23600000000000002 - type: precision_at_3 value: 15.547 - type: precision_at_5 value: 11.344 - type: recall_at_1 value: 24.979000000000003 - type: recall_at_10 value: 48.624 - type: recall_at_100 value: 77.932 - type: recall_at_1000 value: 92.66499999999999 - type: recall_at_3 value: 35.217 - type: recall_at_5 value: 41.394 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWordpressRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 22.566 - type: map_at_10 value: 30.945 - type: map_at_100 value: 31.759999999999998 - type: map_at_1000 value: 31.855 - type: map_at_3 value: 28.64 - type: map_at_5 value: 29.787000000000003 - type: mrr_at_1 value: 24.954 - type: mrr_at_10 value: 33.311 - type: mrr_at_100 value: 34.050000000000004 - type: mrr_at_1000 value: 34.117999999999995 - type: mrr_at_3 value: 31.238 - type: mrr_at_5 value: 32.329 - type: ndcg_at_1 value: 24.954 - type: ndcg_at_10 value: 35.676 - type: ndcg_at_100 value: 39.931 - type: ndcg_at_1000 value: 42.43 - type: ndcg_at_3 value: 31.365 - type: ndcg_at_5 value: 33.184999999999995 - type: precision_at_1 value: 24.954 - type: precision_at_10 value: 5.564 - type: precision_at_100 value: 0.826 - type: precision_at_1000 value: 0.116 - type: precision_at_3 value: 13.555 - type: precision_at_5 value: 9.168 - type: recall_at_1 value: 22.566 - type: recall_at_10 value: 47.922 - type: recall_at_100 value: 67.931 - type: recall_at_1000 value: 86.653 - type: recall_at_3 value: 36.103 - type: recall_at_5 value: 40.699000000000005 - task: type: Retrieval dataset: type: climate-fever name: MTEB ClimateFEVER config: default split: test revision: None metrics: - type: map_at_1 value: 16.950000000000003 - type: map_at_10 value: 28.612 - type: map_at_100 value: 30.476999999999997 - type: map_at_1000 value: 30.674 - type: map_at_3 value: 24.262 - type: map_at_5 value: 26.554 - type: mrr_at_1 value: 38.241 - type: mrr_at_10 value: 50.43 - type: mrr_at_100 value: 51.059 - type: mrr_at_1000 value: 51.090999999999994 - type: mrr_at_3 value: 47.514 - type: mrr_at_5 value: 49.246 - type: ndcg_at_1 value: 38.241 - type: ndcg_at_10 value: 38.218 - type: ndcg_at_100 value: 45.003 - type: ndcg_at_1000 value: 48.269 - type: ndcg_at_3 value: 32.568000000000005 - type: ndcg_at_5 value: 34.400999999999996 - type: precision_at_1 value: 38.241 - type: precision_at_10 value: 11.674 - type: precision_at_100 value: 1.913 - type: precision_at_1000 value: 0.252 - type: precision_at_3 value: 24.387 - type: precision_at_5 value: 18.163 - type: recall_at_1 value: 16.950000000000003 - type: recall_at_10 value: 43.769000000000005 - type: recall_at_100 value: 66.875 - type: recall_at_1000 value: 84.92699999999999 - type: recall_at_3 value: 29.353 - type: recall_at_5 value: 35.467 - task: type: Retrieval dataset: type: dbpedia-entity name: MTEB DBPedia config: default split: test revision: None metrics: - type: map_at_1 value: 9.276 - type: map_at_10 value: 20.848 - type: map_at_100 value: 29.804000000000002 - type: map_at_1000 value: 31.398 - type: map_at_3 value: 14.886 - type: map_at_5 value: 17.516000000000002 - type: mrr_at_1 value: 71.0 - type: mrr_at_10 value: 78.724 - type: mrr_at_100 value: 78.976 - type: mrr_at_1000 value: 78.986 - type: mrr_at_3 value: 77.333 - type: mrr_at_5 value: 78.021 - type: ndcg_at_1 value: 57.875 - type: ndcg_at_10 value: 43.855 - type: ndcg_at_100 value: 48.99 - type: ndcg_at_1000 value: 56.141 - type: ndcg_at_3 value: 48.914 - type: ndcg_at_5 value: 45.961 - type: precision_at_1 value: 71.0 - type: precision_at_10 value: 34.575 - type: precision_at_100 value: 11.182 - type: precision_at_1000 value: 2.044 - type: precision_at_3 value: 52.5 - type: precision_at_5 value: 44.2 - type: recall_at_1 value: 9.276 - type: recall_at_10 value: 26.501 - type: recall_at_100 value: 55.72899999999999 - type: recall_at_1000 value: 78.532 - type: recall_at_3 value: 16.365 - type: recall_at_5 value: 20.154 - task: type: Classification dataset: type: mteb/emotion name: MTEB EmotionClassification config: default split: test revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 metrics: - type: accuracy value: 52.71 - type: f1 value: 47.74801556489574 - task: type: Retrieval dataset: type: fever name: MTEB FEVER config: default split: test revision: None metrics: - type: map_at_1 value: 73.405 - type: map_at_10 value: 82.822 - type: map_at_100 value: 83.042 - type: map_at_1000 value: 83.055 - type: map_at_3 value: 81.65299999999999 - type: map_at_5 value: 82.431 - type: mrr_at_1 value: 79.178 - type: mrr_at_10 value: 87.02 - type: mrr_at_100 value: 87.095 - type: mrr_at_1000 value: 87.09700000000001 - type: mrr_at_3 value: 86.309 - type: mrr_at_5 value: 86.824 - type: ndcg_at_1 value: 79.178 - type: ndcg_at_10 value: 86.72 - type: ndcg_at_100 value: 87.457 - type: ndcg_at_1000 value: 87.691 - type: ndcg_at_3 value: 84.974 - type: ndcg_at_5 value: 86.032 - type: precision_at_1 value: 79.178 - type: precision_at_10 value: 10.548 - type: precision_at_100 value: 1.113 - type: precision_at_1000 value: 0.11499999999999999 - type: precision_at_3 value: 32.848 - type: precision_at_5 value: 20.45 - type: recall_at_1 value: 73.405 - type: recall_at_10 value: 94.39699999999999 - type: recall_at_100 value: 97.219 - type: recall_at_1000 value: 98.675 - type: recall_at_3 value: 89.679 - type: recall_at_5 value: 92.392 - task: type: Retrieval dataset: type: fiqa name: MTEB FiQA2018 config: default split: test revision: None metrics: - type: map_at_1 value: 22.651 - type: map_at_10 value: 36.886 - type: map_at_100 value: 38.811 - type: map_at_1000 value: 38.981 - type: map_at_3 value: 32.538 - type: map_at_5 value: 34.763 - type: mrr_at_1 value: 44.444 - type: mrr_at_10 value: 53.168000000000006 - type: mrr_at_100 value: 53.839000000000006 - type: mrr_at_1000 value: 53.869 - type: mrr_at_3 value: 50.54 - type: mrr_at_5 value: 52.068000000000005 - type: ndcg_at_1 value: 44.444 - type: ndcg_at_10 value: 44.994 - type: ndcg_at_100 value: 51.599 - type: ndcg_at_1000 value: 54.339999999999996 - type: ndcg_at_3 value: 41.372 - type: ndcg_at_5 value: 42.149 - type: precision_at_1 value: 44.444 - type: precision_at_10 value: 12.407 - type: precision_at_100 value: 1.9269999999999998 - type: precision_at_1000 value: 0.242 - type: precision_at_3 value: 27.726 - type: precision_at_5 value: 19.814999999999998 - type: recall_at_1 value: 22.651 - type: recall_at_10 value: 52.075 - type: recall_at_100 value: 76.51400000000001 - type: recall_at_1000 value: 92.852 - type: recall_at_3 value: 37.236000000000004 - type: recall_at_5 value: 43.175999999999995 - task: type: Retrieval dataset: type: hotpotqa name: MTEB HotpotQA config: default split: test revision: None metrics: - type: map_at_1 value: 40.777 - type: map_at_10 value: 66.79899999999999 - type: map_at_100 value: 67.65299999999999 - type: map_at_1000 value: 67.706 - type: map_at_3 value: 63.352 - type: map_at_5 value: 65.52900000000001 - type: mrr_at_1 value: 81.553 - type: mrr_at_10 value: 86.983 - type: mrr_at_100 value: 87.132 - type: mrr_at_1000 value: 87.136 - type: mrr_at_3 value: 86.156 - type: mrr_at_5 value: 86.726 - type: ndcg_at_1 value: 81.553 - type: ndcg_at_10 value: 74.64 - type: ndcg_at_100 value: 77.459 - type: ndcg_at_1000 value: 78.43 - type: ndcg_at_3 value: 69.878 - type: ndcg_at_5 value: 72.59400000000001 - type: precision_at_1 value: 81.553 - type: precision_at_10 value: 15.654000000000002 - type: precision_at_100 value: 1.783 - type: precision_at_1000 value: 0.191 - type: precision_at_3 value: 45.199 - type: precision_at_5 value: 29.267 - type: recall_at_1 value: 40.777 - type: recall_at_10 value: 78.271 - type: recall_at_100 value: 89.129 - type: recall_at_1000 value: 95.49 - type: recall_at_3 value: 67.79899999999999 - type: recall_at_5 value: 73.167 - task: type: Classification dataset: type: mteb/imdb name: MTEB ImdbClassification config: default split: test revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 metrics: - type: accuracy value: 93.5064 - type: ap value: 90.25495114444111 - type: f1 value: 93.5012434973381 - task: type: Retrieval dataset: type: msmarco name: MTEB MSMARCO config: default split: dev revision: None metrics: - type: map_at_1 value: 23.301 - type: map_at_10 value: 35.657 - type: map_at_100 value: 36.797000000000004 - type: map_at_1000 value: 36.844 - type: map_at_3 value: 31.743 - type: map_at_5 value: 34.003 - type: mrr_at_1 value: 23.854 - type: mrr_at_10 value: 36.242999999999995 - type: mrr_at_100 value: 37.32 - type: mrr_at_1000 value: 37.361 - type: mrr_at_3 value: 32.4 - type: mrr_at_5 value: 34.634 - type: ndcg_at_1 value: 23.868000000000002 - type: ndcg_at_10 value: 42.589 - type: ndcg_at_100 value: 48.031 - type: ndcg_at_1000 value: 49.189 - type: ndcg_at_3 value: 34.649 - type: ndcg_at_5 value: 38.676 - type: precision_at_1 value: 23.868000000000002 - type: precision_at_10 value: 6.6850000000000005 - type: precision_at_100 value: 0.9400000000000001 - type: precision_at_1000 value: 0.104 - type: precision_at_3 value: 14.651 - type: precision_at_5 value: 10.834000000000001 - type: recall_at_1 value: 23.301 - type: recall_at_10 value: 63.88700000000001 - type: recall_at_100 value: 88.947 - type: recall_at_1000 value: 97.783 - type: recall_at_3 value: 42.393 - type: recall_at_5 value: 52.036 - task: type: Classification dataset: type: mteb/mtop_domain name: MTEB MTOPDomainClassification (en) config: en split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics: - type: accuracy value: 94.64888280893753 - type: f1 value: 94.41310774203512 - task: type: Classification dataset: type: mteb/mtop_intent name: MTEB MTOPIntentClassification (en) config: en split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics: - type: accuracy value: 79.72184222526221 - type: f1 value: 61.522034067350106 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (en) config: en split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 79.60659045057163 - type: f1 value: 77.268649687049 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (en) config: en split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 81.83254875588432 - type: f1 value: 81.61520635919082 - task: type: Clustering dataset: type: mteb/medrxiv-clustering-p2p name: MTEB MedrxivClusteringP2P config: default split: test revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 metrics: - type: v_measure value: 36.31529875009507 - task: type: Clustering dataset: type: mteb/medrxiv-clustering-s2s name: MTEB MedrxivClusteringS2S config: default split: test revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 metrics: - type: v_measure value: 31.734233714415073 - task: type: Reranking dataset: type: mteb/mind_small name: MTEB MindSmallReranking config: default split: test revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 metrics: - type: map value: 30.994501713009452 - type: mrr value: 32.13512850703073 - task: type: Retrieval dataset: type: nfcorpus name: MTEB NFCorpus config: default split: test revision: None metrics: - type: map_at_1 value: 6.603000000000001 - type: map_at_10 value: 13.767999999999999 - type: map_at_100 value: 17.197000000000003 - type: map_at_1000 value: 18.615000000000002 - type: map_at_3 value: 10.567 - type: map_at_5 value: 12.078999999999999 - type: mrr_at_1 value: 44.891999999999996 - type: mrr_at_10 value: 53.75299999999999 - type: mrr_at_100 value: 54.35 - type: mrr_at_1000 value: 54.388000000000005 - type: mrr_at_3 value: 51.495999999999995 - type: mrr_at_5 value: 52.688 - type: ndcg_at_1 value: 43.189 - type: ndcg_at_10 value: 34.567 - type: ndcg_at_100 value: 32.273 - type: ndcg_at_1000 value: 41.321999999999996 - type: ndcg_at_3 value: 40.171 - type: ndcg_at_5 value: 37.502 - type: precision_at_1 value: 44.582 - type: precision_at_10 value: 25.139 - type: precision_at_100 value: 7.739999999999999 - type: precision_at_1000 value: 2.054 - type: precision_at_3 value: 37.152 - type: precision_at_5 value: 31.826999999999998 - type: recall_at_1 value: 6.603000000000001 - type: recall_at_10 value: 17.023 - type: recall_at_100 value: 32.914 - type: recall_at_1000 value: 64.44800000000001 - type: recall_at_3 value: 11.457 - type: recall_at_5 value: 13.816 - task: type: Retrieval dataset: type: nq name: MTEB NQ config: default split: test revision: None metrics: - type: map_at_1 value: 30.026000000000003 - type: map_at_10 value: 45.429 - type: map_at_100 value: 46.45 - type: map_at_1000 value: 46.478 - type: map_at_3 value: 41.147 - type: map_at_5 value: 43.627 - type: mrr_at_1 value: 33.951 - type: mrr_at_10 value: 47.953 - type: mrr_at_100 value: 48.731 - type: mrr_at_1000 value: 48.751 - type: mrr_at_3 value: 44.39 - type: mrr_at_5 value: 46.533 - type: ndcg_at_1 value: 33.951 - type: ndcg_at_10 value: 53.24100000000001 - type: ndcg_at_100 value: 57.599999999999994 - type: ndcg_at_1000 value: 58.270999999999994 - type: ndcg_at_3 value: 45.190999999999995 - type: ndcg_at_5 value: 49.339 - type: precision_at_1 value: 33.951 - type: precision_at_10 value: 8.856 - type: precision_at_100 value: 1.133 - type: precision_at_1000 value: 0.12 - type: precision_at_3 value: 20.713 - type: precision_at_5 value: 14.838000000000001 - type: recall_at_1 value: 30.026000000000003 - type: recall_at_10 value: 74.512 - type: recall_at_100 value: 93.395 - type: recall_at_1000 value: 98.402 - type: recall_at_3 value: 53.677 - type: recall_at_5 value: 63.198 - task: type: Retrieval dataset: type: quora name: MTEB QuoraRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 71.41300000000001 - type: map_at_10 value: 85.387 - type: map_at_100 value: 86.027 - type: map_at_1000 value: 86.041 - type: map_at_3 value: 82.543 - type: map_at_5 value: 84.304 - type: mrr_at_1 value: 82.35 - type: mrr_at_10 value: 88.248 - type: mrr_at_100 value: 88.348 - type: mrr_at_1000 value: 88.349 - type: mrr_at_3 value: 87.348 - type: mrr_at_5 value: 87.96300000000001 - type: ndcg_at_1 value: 82.37 - type: ndcg_at_10 value: 88.98 - type: ndcg_at_100 value: 90.16499999999999 - type: ndcg_at_1000 value: 90.239 - type: ndcg_at_3 value: 86.34100000000001 - type: ndcg_at_5 value: 87.761 - type: precision_at_1 value: 82.37 - type: precision_at_10 value: 13.471 - type: precision_at_100 value: 1.534 - type: precision_at_1000 value: 0.157 - type: precision_at_3 value: 37.827 - type: precision_at_5 value: 24.773999999999997 - type: recall_at_1 value: 71.41300000000001 - type: recall_at_10 value: 95.748 - type: recall_at_100 value: 99.69200000000001 - type: recall_at_1000 value: 99.98 - type: recall_at_3 value: 87.996 - type: recall_at_5 value: 92.142 - task: type: Clustering dataset: type: mteb/reddit-clustering name: MTEB RedditClustering config: default split: test revision: 24640382cdbf8abc73003fb0fa6d111a705499eb metrics: - type: v_measure value: 56.96878497780007 - task: type: Clustering dataset: type: mteb/reddit-clustering-p2p name: MTEB RedditClusteringP2P config: default split: test revision: 282350215ef01743dc01b456c7f5241fa8937f16 metrics: - type: v_measure value: 65.31371347128074 - task: type: Retrieval dataset: type: scidocs name: MTEB SCIDOCS config: default split: test revision: None metrics: - type: map_at_1 value: 5.287 - type: map_at_10 value: 13.530000000000001 - type: map_at_100 value: 15.891 - type: map_at_1000 value: 16.245 - type: map_at_3 value: 9.612 - type: map_at_5 value: 11.672 - type: mrr_at_1 value: 26.0 - type: mrr_at_10 value: 37.335 - type: mrr_at_100 value: 38.443 - type: mrr_at_1000 value: 38.486 - type: mrr_at_3 value: 33.783 - type: mrr_at_5 value: 36.028 - type: ndcg_at_1 value: 26.0 - type: ndcg_at_10 value: 22.215 - type: ndcg_at_100 value: 31.101 - type: ndcg_at_1000 value: 36.809 - type: ndcg_at_3 value: 21.104 - type: ndcg_at_5 value: 18.759999999999998 - type: precision_at_1 value: 26.0 - type: precision_at_10 value: 11.43 - type: precision_at_100 value: 2.424 - type: precision_at_1000 value: 0.379 - type: precision_at_3 value: 19.7 - type: precision_at_5 value: 16.619999999999997 - type: recall_at_1 value: 5.287 - type: recall_at_10 value: 23.18 - type: recall_at_100 value: 49.208 - type: recall_at_1000 value: 76.85300000000001 - type: recall_at_3 value: 11.991999999999999 - type: recall_at_5 value: 16.85 - task: type: STS dataset: type: mteb/sickr-sts name: MTEB SICK-R config: default split: test revision: a6ea5a8cab320b040a23452cc28066d9beae2cee metrics: - type: cos_sim_pearson value: 83.87834913790886 - type: cos_sim_spearman value: 81.04583513112122 - type: euclidean_pearson value: 81.20484174558065 - type: euclidean_spearman value: 80.76430832561769 - type: manhattan_pearson value: 81.21416730978615 - type: manhattan_spearman value: 80.7797637394211 - task: type: STS dataset: type: mteb/sts12-sts name: MTEB STS12 config: default split: test revision: a0d554a64d88156834ff5ae9920b964011b16384 metrics: - type: cos_sim_pearson value: 86.56143998865157 - type: cos_sim_spearman value: 79.75387012744471 - type: euclidean_pearson value: 83.7877519997019 - type: euclidean_spearman value: 79.90489748003296 - type: manhattan_pearson value: 83.7540590666095 - type: manhattan_spearman value: 79.86434577931573 - task: type: STS dataset: type: mteb/sts13-sts name: MTEB STS13 config: default split: test revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca metrics: - type: cos_sim_pearson value: 83.92102564177941 - type: cos_sim_spearman value: 84.98234585939103 - type: euclidean_pearson value: 84.47729567593696 - type: euclidean_spearman value: 85.09490696194469 - type: manhattan_pearson value: 84.38622951588229 - type: manhattan_spearman value: 85.02507171545574 - task: type: STS dataset: type: mteb/sts14-sts name: MTEB STS14 config: default split: test revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 metrics: - type: cos_sim_pearson value: 80.1891164763377 - type: cos_sim_spearman value: 80.7997969966883 - type: euclidean_pearson value: 80.48572256162396 - type: euclidean_spearman value: 80.57851903536378 - type: manhattan_pearson value: 80.4324819433651 - type: manhattan_spearman value: 80.5074526239062 - task: type: STS dataset: type: mteb/sts15-sts name: MTEB STS15 config: default split: test revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 metrics: - type: cos_sim_pearson value: 82.64319975116025 - type: cos_sim_spearman value: 84.88671197763652 - type: euclidean_pearson value: 84.74692193293231 - type: euclidean_spearman value: 85.27151722073653 - type: manhattan_pearson value: 84.72460516785438 - type: manhattan_spearman value: 85.26518899786687 - task: type: STS dataset: type: mteb/sts16-sts name: MTEB STS16 config: default split: test revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 metrics: - type: cos_sim_pearson value: 83.24687565822381 - type: cos_sim_spearman value: 85.60418454111263 - type: euclidean_pearson value: 84.85829740169851 - type: euclidean_spearman value: 85.66378014138306 - type: manhattan_pearson value: 84.84672408808835 - type: manhattan_spearman value: 85.63331924364891 - 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: 84.87758895415485 - type: cos_sim_spearman value: 85.8193745617297 - type: euclidean_pearson value: 85.78719118848134 - type: euclidean_spearman value: 84.35797575385688 - type: manhattan_pearson value: 85.97919844815692 - type: manhattan_spearman value: 84.58334745175151 - 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: 67.27076035963599 - type: cos_sim_spearman value: 67.21433656439973 - type: euclidean_pearson value: 68.07434078679324 - type: euclidean_spearman value: 66.0249731719049 - type: manhattan_pearson value: 67.95495198947476 - type: manhattan_spearman value: 65.99893908331886 - task: type: STS dataset: type: mteb/stsbenchmark-sts name: MTEB STSBenchmark config: default split: test revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 metrics: - type: cos_sim_pearson value: 82.22437747056817 - type: cos_sim_spearman value: 85.0995685206174 - type: euclidean_pearson value: 84.08616925603394 - type: euclidean_spearman value: 84.89633925691658 - type: manhattan_pearson value: 84.08332675923133 - type: manhattan_spearman value: 84.8858228112915 - task: type: Reranking dataset: type: mteb/scidocs-reranking name: MTEB SciDocsRR config: default split: test revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab metrics: - type: map value: 87.6909022589666 - type: mrr value: 96.43341952165481 - task: type: Retrieval dataset: type: scifact name: MTEB SciFact config: default split: test revision: None metrics: - type: map_at_1 value: 57.660999999999994 - type: map_at_10 value: 67.625 - type: map_at_100 value: 68.07600000000001 - type: map_at_1000 value: 68.10199999999999 - type: map_at_3 value: 64.50399999999999 - type: map_at_5 value: 66.281 - type: mrr_at_1 value: 61.0 - type: mrr_at_10 value: 68.953 - type: mrr_at_100 value: 69.327 - type: mrr_at_1000 value: 69.352 - type: mrr_at_3 value: 66.833 - type: mrr_at_5 value: 68.05 - type: ndcg_at_1 value: 61.0 - type: ndcg_at_10 value: 72.369 - type: ndcg_at_100 value: 74.237 - type: ndcg_at_1000 value: 74.939 - type: ndcg_at_3 value: 67.284 - type: ndcg_at_5 value: 69.72500000000001 - type: precision_at_1 value: 61.0 - type: precision_at_10 value: 9.733 - type: precision_at_100 value: 1.0670000000000002 - type: precision_at_1000 value: 0.11199999999999999 - type: precision_at_3 value: 26.222 - type: precision_at_5 value: 17.4 - type: recall_at_1 value: 57.660999999999994 - type: recall_at_10 value: 85.656 - type: recall_at_100 value: 93.833 - type: recall_at_1000 value: 99.333 - type: recall_at_3 value: 71.961 - type: recall_at_5 value: 78.094 - task: type: PairClassification dataset: type: mteb/sprintduplicatequestions-pairclassification name: MTEB SprintDuplicateQuestions config: default split: test revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 metrics: - type: cos_sim_accuracy value: 99.86930693069307 - type: cos_sim_ap value: 96.76685487950894 - type: cos_sim_f1 value: 93.44587884806354 - type: cos_sim_precision value: 92.80078895463511 - type: cos_sim_recall value: 94.1 - type: dot_accuracy value: 99.54356435643564 - type: dot_ap value: 81.18659960405607 - type: dot_f1 value: 75.78008915304605 - type: dot_precision value: 75.07360157016683 - type: dot_recall value: 76.5 - type: euclidean_accuracy value: 99.87326732673267 - type: euclidean_ap value: 96.8102411908941 - type: euclidean_f1 value: 93.6127744510978 - type: euclidean_precision value: 93.42629482071713 - type: euclidean_recall value: 93.8 - type: manhattan_accuracy value: 99.87425742574257 - type: manhattan_ap value: 96.82857341435529 - type: manhattan_f1 value: 93.62129583124059 - type: manhattan_precision value: 94.04641775983855 - type: manhattan_recall value: 93.2 - type: max_accuracy value: 99.87425742574257 - type: max_ap value: 96.82857341435529 - type: max_f1 value: 93.62129583124059 - task: type: Clustering dataset: type: mteb/stackexchange-clustering name: MTEB StackExchangeClustering config: default split: test revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 metrics: - type: v_measure value: 65.92560972698926 - task: type: Clustering dataset: type: mteb/stackexchange-clustering-p2p name: MTEB StackExchangeClusteringP2P config: default split: test revision: 815ca46b2622cec33ccafc3735d572c266efdb44 metrics: - type: v_measure value: 34.92797240259008 - task: type: Reranking dataset: type: mteb/stackoverflowdupquestions-reranking name: MTEB StackOverflowDupQuestions config: default split: test revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 metrics: - type: map value: 55.244624045597654 - type: mrr value: 56.185303666921314 - task: type: Summarization dataset: type: mteb/summeval name: MTEB SummEval config: default split: test revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c metrics: - type: cos_sim_pearson value: 31.02491987312937 - type: cos_sim_spearman value: 32.055592206679734 - type: dot_pearson value: 24.731627575422557 - type: dot_spearman value: 24.308029077069733 - task: type: Retrieval dataset: type: trec-covid name: MTEB TRECCOVID config: default split: test revision: None metrics: - type: map_at_1 value: 0.231 - type: map_at_10 value: 1.899 - type: map_at_100 value: 9.498 - type: map_at_1000 value: 20.979999999999997 - type: map_at_3 value: 0.652 - type: map_at_5 value: 1.069 - type: mrr_at_1 value: 88.0 - type: mrr_at_10 value: 93.4 - type: mrr_at_100 value: 93.4 - type: mrr_at_1000 value: 93.4 - type: mrr_at_3 value: 93.0 - type: mrr_at_5 value: 93.4 - type: ndcg_at_1 value: 86.0 - type: ndcg_at_10 value: 75.375 - type: ndcg_at_100 value: 52.891999999999996 - type: ndcg_at_1000 value: 44.952999999999996 - type: ndcg_at_3 value: 81.05 - type: ndcg_at_5 value: 80.175 - type: precision_at_1 value: 88.0 - type: precision_at_10 value: 79.0 - type: precision_at_100 value: 53.16 - type: precision_at_1000 value: 19.408 - type: precision_at_3 value: 85.333 - type: precision_at_5 value: 84.0 - type: recall_at_1 value: 0.231 - type: recall_at_10 value: 2.078 - type: recall_at_100 value: 12.601 - type: recall_at_1000 value: 41.296 - type: recall_at_3 value: 0.6779999999999999 - type: recall_at_5 value: 1.1360000000000001 - task: type: Retrieval dataset: type: webis-touche2020 name: MTEB Touche2020 config: default split: test revision: None metrics: - type: map_at_1 value: 2.782 - type: map_at_10 value: 10.204 - type: map_at_100 value: 16.176 - type: map_at_1000 value: 17.456 - type: map_at_3 value: 5.354 - type: map_at_5 value: 7.503 - type: mrr_at_1 value: 40.816 - type: mrr_at_10 value: 54.010000000000005 - type: mrr_at_100 value: 54.49 - type: mrr_at_1000 value: 54.49 - type: mrr_at_3 value: 48.980000000000004 - type: mrr_at_5 value: 51.735 - type: ndcg_at_1 value: 36.735 - type: ndcg_at_10 value: 26.61 - type: ndcg_at_100 value: 36.967 - type: ndcg_at_1000 value: 47.274 - type: ndcg_at_3 value: 30.363 - type: ndcg_at_5 value: 29.448999999999998 - type: precision_at_1 value: 40.816 - type: precision_at_10 value: 23.878 - type: precision_at_100 value: 7.693999999999999 - type: precision_at_1000 value: 1.4489999999999998 - type: precision_at_3 value: 31.293 - type: precision_at_5 value: 29.796 - type: recall_at_1 value: 2.782 - type: recall_at_10 value: 16.485 - type: recall_at_100 value: 46.924 - type: recall_at_1000 value: 79.365 - type: recall_at_3 value: 6.52 - type: recall_at_5 value: 10.48 - task: type: Classification dataset: type: mteb/toxic_conversations_50k name: MTEB ToxicConversationsClassification config: default split: test revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c metrics: - type: accuracy value: 70.08300000000001 - type: ap value: 13.91559884590195 - type: f1 value: 53.956838444291364 - task: type: Classification dataset: type: mteb/tweet_sentiment_extraction name: MTEB TweetSentimentExtractionClassification config: default split: test revision: d604517c81ca91fe16a244d1248fc021f9ecee7a metrics: - type: accuracy value: 59.34069043576683 - type: f1 value: 59.662041994618406 - task: type: Clustering dataset: type: mteb/twentynewsgroups-clustering name: MTEB TwentyNewsgroupsClustering config: default split: test revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 metrics: - type: v_measure value: 53.70780611078653 - task: type: PairClassification dataset: type: mteb/twittersemeval2015-pairclassification name: MTEB TwitterSemEval2015 config: default split: test revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 metrics: - type: cos_sim_accuracy value: 87.10734934732073 - type: cos_sim_ap value: 77.58349999516054 - type: cos_sim_f1 value: 70.25391395868965 - type: cos_sim_precision value: 70.06035161374967 - type: cos_sim_recall value: 70.44854881266491 - type: dot_accuracy value: 80.60439887941826 - type: dot_ap value: 54.52935200483575 - type: dot_f1 value: 54.170444242973716 - type: dot_precision value: 47.47715534366309 - type: dot_recall value: 63.06068601583114 - type: euclidean_accuracy value: 87.26828396018358 - type: euclidean_ap value: 78.00158454104036 - type: euclidean_f1 value: 70.70292457670601 - type: euclidean_precision value: 68.79680479281079 - type: euclidean_recall value: 72.71767810026385 - type: manhattan_accuracy value: 87.11330988853788 - type: manhattan_ap value: 77.92527099601855 - type: manhattan_f1 value: 70.76488706365502 - type: manhattan_precision value: 68.89055472263868 - type: manhattan_recall value: 72.74406332453826 - type: max_accuracy value: 87.26828396018358 - type: max_ap value: 78.00158454104036 - type: max_f1 value: 70.76488706365502 - task: type: PairClassification dataset: type: mteb/twitterurlcorpus-pairclassification name: MTEB TwitterURLCorpus config: default split: test revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf metrics: - type: cos_sim_accuracy value: 87.80804905499282 - type: cos_sim_ap value: 83.06187782630936 - type: cos_sim_f1 value: 74.99716435403985 - type: cos_sim_precision value: 73.67951860931579 - type: cos_sim_recall value: 76.36279642747151 - type: dot_accuracy value: 81.83141227151008 - type: dot_ap value: 67.18241090841795 - type: dot_f1 value: 62.216037571751606 - type: dot_precision value: 56.749381227391005 - type: dot_recall value: 68.84816753926701 - type: euclidean_accuracy value: 87.91671517832887 - type: euclidean_ap value: 83.56538942001427 - type: euclidean_f1 value: 75.7327253337256 - type: euclidean_precision value: 72.48856036606828 - type: euclidean_recall value: 79.28087465352634 - type: manhattan_accuracy value: 87.86626304963713 - type: manhattan_ap value: 83.52939841172832 - type: manhattan_f1 value: 75.73635656329888 - type: manhattan_precision value: 72.99150182103836 - type: manhattan_recall value: 78.69571912534647 - type: max_accuracy value: 87.91671517832887 - type: max_ap value: 83.56538942001427 - type: max_f1 value: 75.73635656329888 ---