--- tags: - mteb model-index: - name: xlm3b5_step3len260_b128g8_lr1e-5 results: - task: type: Classification dataset: type: mteb/amazon_counterfactual name: MTEB AmazonCounterfactualClassification (en) config: en split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics: - type: accuracy value: 69.01492537313432 - type: ap value: 30.936372983952477 - type: f1 value: 62.58864357716914 - task: type: Classification dataset: type: mteb/amazon_polarity name: MTEB AmazonPolarityClassification config: default split: test revision: e2d317d38cd51312af73b3d32a06d1a08b442046 metrics: - type: accuracy value: 95.088975 - type: ap value: 92.9329025853096 - type: f1 value: 95.0864056657106 - task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (en) config: en split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics: - type: accuracy value: 50.524 - type: f1 value: 49.93715365750685 - task: type: Retrieval dataset: type: arguana name: MTEB ArguAna config: default split: test revision: None metrics: - type: map_at_1 value: 17.781 - type: map_at_10 value: 30.854 - type: map_at_100 value: 32.344 - type: map_at_1000 value: 32.364 - type: map_at_3 value: 25.711000000000002 - type: map_at_5 value: 28.254 - type: mrr_at_1 value: 18.563 - type: mrr_at_10 value: 31.137999999999998 - type: mrr_at_100 value: 32.621 - type: mrr_at_1000 value: 32.641 - type: mrr_at_3 value: 25.984 - type: mrr_at_5 value: 28.53 - type: ndcg_at_1 value: 17.781 - type: ndcg_at_10 value: 39.206 - type: ndcg_at_100 value: 45.751 - type: ndcg_at_1000 value: 46.225 - type: ndcg_at_3 value: 28.313 - type: ndcg_at_5 value: 32.919 - type: precision_at_1 value: 17.781 - type: precision_at_10 value: 6.65 - type: precision_at_100 value: 0.9560000000000001 - type: precision_at_1000 value: 0.099 - type: precision_at_3 value: 11.949 - type: precision_at_5 value: 9.417 - type: recall_at_1 value: 17.781 - type: recall_at_10 value: 66.501 - type: recall_at_100 value: 95.59 - type: recall_at_1000 value: 99.21799999999999 - type: recall_at_3 value: 35.846000000000004 - type: recall_at_5 value: 47.083999999999996 - task: type: Clustering dataset: type: mteb/arxiv-clustering-p2p name: MTEB ArxivClusteringP2P config: default split: test revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d metrics: - type: v_measure value: 44.44154312957711 - task: type: Clustering dataset: type: mteb/arxiv-clustering-s2s name: MTEB ArxivClusteringS2S config: default split: test revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 metrics: - type: v_measure value: 34.189712542346385 - task: type: Reranking dataset: type: mteb/askubuntudupquestions-reranking name: MTEB AskUbuntuDupQuestions config: default split: test revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 metrics: - type: map value: 62.72571219134687 - type: mrr value: 76.3612979817966 - task: type: STS dataset: type: mteb/biosses-sts name: MTEB BIOSSES config: default split: test revision: d3fb88f8f02e40887cd149695127462bbcf29b4a metrics: - type: cos_sim_pearson value: 83.62762841254953 - type: cos_sim_spearman value: 80.72111639383013 - type: euclidean_pearson value: 82.63506732956259 - type: euclidean_spearman value: 81.177753304636 - type: manhattan_pearson value: 82.5891836637346 - type: manhattan_spearman value: 81.06811225217339 - task: type: Classification dataset: type: mteb/banking77 name: MTEB Banking77Classification config: default split: test revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 metrics: - type: accuracy value: 1.422077922077922 - type: f1 value: 0.06502366027548179 - task: type: Clustering dataset: type: mteb/biorxiv-clustering-p2p name: MTEB BiorxivClusteringP2P config: default split: test revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 metrics: - type: v_measure value: 37.82441952130262 - task: type: Clustering dataset: type: mteb/biorxiv-clustering-s2s name: MTEB BiorxivClusteringS2S config: default split: test revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 metrics: - type: v_measure value: 32.132057843418416 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackAndroidRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 34.23 - type: map_at_10 value: 46.763 - type: map_at_100 value: 48.454 - type: map_at_1000 value: 48.58 - type: map_at_3 value: 43.167 - type: map_at_5 value: 45.214 - type: mrr_at_1 value: 42.775 - type: mrr_at_10 value: 53.190000000000005 - type: mrr_at_100 value: 53.928 - type: mrr_at_1000 value: 53.964 - type: mrr_at_3 value: 51.168 - type: mrr_at_5 value: 52.434000000000005 - type: ndcg_at_1 value: 42.775 - type: ndcg_at_10 value: 53.376999999999995 - type: ndcg_at_100 value: 58.748 - type: ndcg_at_1000 value: 60.461 - type: ndcg_at_3 value: 48.929 - type: ndcg_at_5 value: 50.99399999999999 - type: precision_at_1 value: 42.775 - type: precision_at_10 value: 10.428999999999998 - type: precision_at_100 value: 1.678 - type: precision_at_1000 value: 0.215 - type: precision_at_3 value: 23.939 - type: precision_at_5 value: 17.082 - type: recall_at_1 value: 34.23 - type: recall_at_10 value: 64.96300000000001 - type: recall_at_100 value: 86.803 - type: recall_at_1000 value: 97.917 - type: recall_at_3 value: 51.815 - type: recall_at_5 value: 57.781000000000006 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackEnglishRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 28.935 - type: map_at_10 value: 39.574999999999996 - type: map_at_100 value: 40.891 - type: map_at_1000 value: 41.043 - type: map_at_3 value: 36.248999999999995 - type: map_at_5 value: 38.157999999999994 - type: mrr_at_1 value: 36.624 - type: mrr_at_10 value: 45.241 - type: mrr_at_100 value: 46.028000000000006 - type: mrr_at_1000 value: 46.082 - type: mrr_at_3 value: 42.93 - type: mrr_at_5 value: 44.417 - type: ndcg_at_1 value: 36.624 - type: ndcg_at_10 value: 45.423 - type: ndcg_at_100 value: 49.971 - type: ndcg_at_1000 value: 52.382 - type: ndcg_at_3 value: 41.019 - type: ndcg_at_5 value: 43.254 - type: precision_at_1 value: 36.624 - type: precision_at_10 value: 8.86 - type: precision_at_100 value: 1.458 - type: precision_at_1000 value: 0.198 - type: precision_at_3 value: 20.276 - type: precision_at_5 value: 14.573 - type: recall_at_1 value: 28.935 - type: recall_at_10 value: 55.745999999999995 - type: recall_at_100 value: 74.977 - type: recall_at_1000 value: 90.505 - type: recall_at_3 value: 42.575 - type: recall_at_5 value: 48.902 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGamingRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 38.828 - type: map_at_10 value: 50.888999999999996 - type: map_at_100 value: 52.001 - type: map_at_1000 value: 52.054 - type: map_at_3 value: 47.638999999999996 - type: map_at_5 value: 49.423 - type: mrr_at_1 value: 44.765 - type: mrr_at_10 value: 54.408 - type: mrr_at_100 value: 55.116 - type: mrr_at_1000 value: 55.144000000000005 - type: mrr_at_3 value: 52.038 - type: mrr_at_5 value: 53.323 - type: ndcg_at_1 value: 44.765 - type: ndcg_at_10 value: 56.724 - type: ndcg_at_100 value: 61.058 - type: ndcg_at_1000 value: 62.125 - type: ndcg_at_3 value: 51.324000000000005 - type: ndcg_at_5 value: 53.805 - type: precision_at_1 value: 44.765 - type: precision_at_10 value: 9.248000000000001 - type: precision_at_100 value: 1.234 - type: precision_at_1000 value: 0.136 - type: precision_at_3 value: 23.093 - type: precision_at_5 value: 15.799 - type: recall_at_1 value: 38.828 - type: recall_at_10 value: 70.493 - type: recall_at_100 value: 89.293 - type: recall_at_1000 value: 96.872 - type: recall_at_3 value: 55.74400000000001 - type: recall_at_5 value: 61.95 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGisRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 22.085 - type: map_at_10 value: 30.070000000000004 - type: map_at_100 value: 31.206 - type: map_at_1000 value: 31.291999999999998 - type: map_at_3 value: 27.011000000000003 - type: map_at_5 value: 28.854999999999997 - type: mrr_at_1 value: 23.842 - type: mrr_at_10 value: 31.755 - type: mrr_at_100 value: 32.778 - type: mrr_at_1000 value: 32.845 - type: mrr_at_3 value: 28.851 - type: mrr_at_5 value: 30.574 - type: ndcg_at_1 value: 23.842 - type: ndcg_at_10 value: 35.052 - type: ndcg_at_100 value: 40.550999999999995 - type: ndcg_at_1000 value: 42.789 - type: ndcg_at_3 value: 29.096 - type: ndcg_at_5 value: 32.251000000000005 - type: precision_at_1 value: 23.842 - type: precision_at_10 value: 5.605 - type: precision_at_100 value: 0.877 - type: precision_at_1000 value: 0.11100000000000002 - type: precision_at_3 value: 12.316 - type: precision_at_5 value: 9.13 - type: recall_at_1 value: 22.085 - type: recall_at_10 value: 48.815999999999995 - type: recall_at_100 value: 74.039 - type: recall_at_1000 value: 90.872 - type: recall_at_3 value: 33.098 - type: recall_at_5 value: 40.647 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackMathematicaRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 14.088999999999999 - type: map_at_10 value: 21.526 - type: map_at_100 value: 22.832 - type: map_at_1000 value: 22.958000000000002 - type: map_at_3 value: 18.747 - type: map_at_5 value: 20.396 - type: mrr_at_1 value: 17.662 - type: mrr_at_10 value: 25.513 - type: mrr_at_100 value: 26.621 - type: mrr_at_1000 value: 26.698 - type: mrr_at_3 value: 22.658 - type: mrr_at_5 value: 24.449 - type: ndcg_at_1 value: 17.662 - type: ndcg_at_10 value: 26.506999999999998 - type: ndcg_at_100 value: 32.782 - type: ndcg_at_1000 value: 35.709999999999994 - type: ndcg_at_3 value: 21.279 - type: ndcg_at_5 value: 23.998 - type: precision_at_1 value: 17.662 - type: precision_at_10 value: 5.124 - type: precision_at_100 value: 0.951 - type: precision_at_1000 value: 0.133 - type: precision_at_3 value: 10.323 - type: precision_at_5 value: 8.158999999999999 - type: recall_at_1 value: 14.088999999999999 - type: recall_at_10 value: 37.874 - type: recall_at_100 value: 65.34100000000001 - type: recall_at_1000 value: 86.06099999999999 - type: recall_at_3 value: 23.738999999999997 - type: recall_at_5 value: 30.359 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackPhysicsRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 24.75 - type: map_at_10 value: 34.156 - type: map_at_100 value: 35.638999999999996 - type: map_at_1000 value: 35.754999999999995 - type: map_at_3 value: 31.047000000000004 - type: map_at_5 value: 32.823 - type: mrr_at_1 value: 30.991000000000003 - type: mrr_at_10 value: 39.509 - type: mrr_at_100 value: 40.582 - type: mrr_at_1000 value: 40.636 - type: mrr_at_3 value: 37.103 - type: mrr_at_5 value: 38.503 - type: ndcg_at_1 value: 30.991000000000003 - type: ndcg_at_10 value: 39.719 - type: ndcg_at_100 value: 45.984 - type: ndcg_at_1000 value: 48.293 - type: ndcg_at_3 value: 34.92 - type: ndcg_at_5 value: 37.253 - type: precision_at_1 value: 30.991000000000003 - type: precision_at_10 value: 7.3340000000000005 - type: precision_at_100 value: 1.225 - type: precision_at_1000 value: 0.16 - type: precision_at_3 value: 16.586000000000002 - type: precision_at_5 value: 12.127 - type: recall_at_1 value: 24.75 - type: recall_at_10 value: 51.113 - type: recall_at_100 value: 77.338 - type: recall_at_1000 value: 92.764 - type: recall_at_3 value: 37.338 - type: recall_at_5 value: 43.437 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackProgrammersRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 23.158 - type: map_at_10 value: 32.877 - type: map_at_100 value: 34.226 - type: map_at_1000 value: 34.35 - type: map_at_3 value: 29.43 - type: map_at_5 value: 31.319000000000003 - type: mrr_at_1 value: 29.224 - type: mrr_at_10 value: 38.080000000000005 - type: mrr_at_100 value: 39.04 - type: mrr_at_1000 value: 39.097 - type: mrr_at_3 value: 35.407 - type: mrr_at_5 value: 36.771 - type: ndcg_at_1 value: 29.224 - type: ndcg_at_10 value: 38.805 - type: ndcg_at_100 value: 44.746 - type: ndcg_at_1000 value: 47.038000000000004 - type: ndcg_at_3 value: 33.269 - type: ndcg_at_5 value: 35.611 - type: precision_at_1 value: 29.224 - type: precision_at_10 value: 7.454 - type: precision_at_100 value: 1.221 - type: precision_at_1000 value: 0.16199999999999998 - type: precision_at_3 value: 16.134 - type: precision_at_5 value: 11.895 - type: recall_at_1 value: 23.158 - type: recall_at_10 value: 51.487 - type: recall_at_100 value: 77.464 - type: recall_at_1000 value: 92.525 - type: recall_at_3 value: 35.478 - type: recall_at_5 value: 41.722 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 24.456916666666668 - type: map_at_10 value: 33.5495 - type: map_at_100 value: 34.86808333333333 - type: map_at_1000 value: 34.98908333333333 - type: map_at_3 value: 30.59158333333334 - type: map_at_5 value: 32.24916666666667 - type: mrr_at_1 value: 29.387250000000005 - type: mrr_at_10 value: 37.73958333333333 - type: mrr_at_100 value: 38.6595 - type: mrr_at_1000 value: 38.718250000000005 - type: mrr_at_3 value: 35.31658333333333 - type: mrr_at_5 value: 36.69441666666667 - type: ndcg_at_1 value: 29.387250000000005 - type: ndcg_at_10 value: 38.910333333333334 - type: ndcg_at_100 value: 44.40241666666666 - type: ndcg_at_1000 value: 46.72008333333334 - type: ndcg_at_3 value: 34.045583333333326 - type: ndcg_at_5 value: 36.33725 - type: precision_at_1 value: 29.387250000000005 - type: precision_at_10 value: 7.034666666666668 - type: precision_at_100 value: 1.1698333333333333 - type: precision_at_1000 value: 0.15599999999999997 - type: precision_at_3 value: 15.866416666666666 - type: precision_at_5 value: 11.456333333333331 - type: recall_at_1 value: 24.456916666666668 - type: recall_at_10 value: 50.47758333333333 - type: recall_at_100 value: 74.52275 - type: recall_at_1000 value: 90.7105 - type: recall_at_3 value: 36.86275 - type: recall_at_5 value: 42.76533333333333 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackStatsRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 19.356 - type: map_at_10 value: 25.378 - type: map_at_100 value: 26.349 - type: map_at_1000 value: 26.451 - type: map_at_3 value: 23.403 - type: map_at_5 value: 24.614 - type: mrr_at_1 value: 22.086 - type: mrr_at_10 value: 28.072000000000003 - type: mrr_at_100 value: 28.887 - type: mrr_at_1000 value: 28.965999999999998 - type: mrr_at_3 value: 26.074 - type: mrr_at_5 value: 27.293 - type: ndcg_at_1 value: 22.086 - type: ndcg_at_10 value: 29.107 - type: ndcg_at_100 value: 34.0 - type: ndcg_at_1000 value: 36.793 - type: ndcg_at_3 value: 25.407999999999998 - type: ndcg_at_5 value: 27.375 - type: precision_at_1 value: 22.086 - type: precision_at_10 value: 4.678 - type: precision_at_100 value: 0.7779999999999999 - type: precision_at_1000 value: 0.11 - type: precision_at_3 value: 10.992 - type: precision_at_5 value: 7.853000000000001 - type: recall_at_1 value: 19.356 - type: recall_at_10 value: 37.913999999999994 - type: recall_at_100 value: 60.507999999999996 - type: recall_at_1000 value: 81.459 - type: recall_at_3 value: 27.874 - type: recall_at_5 value: 32.688 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackTexRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 16.008 - type: map_at_10 value: 22.431 - type: map_at_100 value: 23.61 - type: map_at_1000 value: 23.743 - type: map_at_3 value: 20.358 - type: map_at_5 value: 21.371000000000002 - type: mrr_at_1 value: 19.752 - type: mrr_at_10 value: 26.333000000000002 - type: mrr_at_100 value: 27.297 - type: mrr_at_1000 value: 27.378000000000004 - type: mrr_at_3 value: 24.358 - type: mrr_at_5 value: 25.354 - type: ndcg_at_1 value: 19.752 - type: ndcg_at_10 value: 26.712000000000003 - type: ndcg_at_100 value: 32.294 - type: ndcg_at_1000 value: 35.410000000000004 - type: ndcg_at_3 value: 22.974 - type: ndcg_at_5 value: 24.412 - type: precision_at_1 value: 19.752 - type: precision_at_10 value: 4.986 - type: precision_at_100 value: 0.924 - type: precision_at_1000 value: 0.13699999999999998 - type: precision_at_3 value: 10.966 - type: precision_at_5 value: 7.832 - type: recall_at_1 value: 16.008 - type: recall_at_10 value: 35.716 - type: recall_at_100 value: 60.76200000000001 - type: recall_at_1000 value: 83.204 - type: recall_at_3 value: 25.092 - type: recall_at_5 value: 28.858 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackUnixRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 24.743000000000002 - type: map_at_10 value: 34.492 - type: map_at_100 value: 35.716 - type: map_at_1000 value: 35.815999999999995 - type: map_at_3 value: 31.201 - type: map_at_5 value: 32.926 - type: mrr_at_1 value: 29.384 - type: mrr_at_10 value: 38.333 - type: mrr_at_100 value: 39.278 - type: mrr_at_1000 value: 39.330999999999996 - type: mrr_at_3 value: 35.65 - type: mrr_at_5 value: 36.947 - type: ndcg_at_1 value: 29.384 - type: ndcg_at_10 value: 40.195 - type: ndcg_at_100 value: 45.686 - type: ndcg_at_1000 value: 47.906 - type: ndcg_at_3 value: 34.477000000000004 - type: ndcg_at_5 value: 36.89 - type: precision_at_1 value: 29.384 - type: precision_at_10 value: 7.164 - type: precision_at_100 value: 1.111 - type: precision_at_1000 value: 0.13999999999999999 - type: precision_at_3 value: 15.983 - type: precision_at_5 value: 11.418000000000001 - type: recall_at_1 value: 24.743000000000002 - type: recall_at_10 value: 53.602000000000004 - type: recall_at_100 value: 77.266 - type: recall_at_1000 value: 92.857 - type: recall_at_3 value: 37.921 - type: recall_at_5 value: 44.124 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWebmastersRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 26.531 - type: map_at_10 value: 35.933 - type: map_at_100 value: 37.913000000000004 - type: map_at_1000 value: 38.146 - type: map_at_3 value: 32.713 - type: map_at_5 value: 34.339999999999996 - type: mrr_at_1 value: 32.806000000000004 - type: mrr_at_10 value: 41.728 - type: mrr_at_100 value: 42.731 - type: mrr_at_1000 value: 42.777 - type: mrr_at_3 value: 39.065 - type: mrr_at_5 value: 40.467999999999996 - type: ndcg_at_1 value: 32.806000000000004 - type: ndcg_at_10 value: 42.254999999999995 - type: ndcg_at_100 value: 48.687999999999995 - type: ndcg_at_1000 value: 50.784 - type: ndcg_at_3 value: 37.330999999999996 - type: ndcg_at_5 value: 39.305 - type: precision_at_1 value: 32.806000000000004 - type: precision_at_10 value: 8.34 - type: precision_at_100 value: 1.7209999999999999 - type: precision_at_1000 value: 0.252 - type: precision_at_3 value: 17.589 - type: precision_at_5 value: 12.845999999999998 - type: recall_at_1 value: 26.531 - type: recall_at_10 value: 53.266000000000005 - type: recall_at_100 value: 81.49499999999999 - type: recall_at_1000 value: 94.506 - type: recall_at_3 value: 38.848 - type: recall_at_5 value: 44.263000000000005 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWordpressRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 20.77 - type: map_at_10 value: 28.504 - type: map_at_100 value: 29.580000000000002 - type: map_at_1000 value: 29.681 - type: map_at_3 value: 26.134 - type: map_at_5 value: 27.551 - type: mrr_at_1 value: 22.736 - type: mrr_at_10 value: 30.713 - type: mrr_at_100 value: 31.628 - type: mrr_at_1000 value: 31.701 - type: mrr_at_3 value: 28.497 - type: mrr_at_5 value: 29.799999999999997 - type: ndcg_at_1 value: 22.736 - type: ndcg_at_10 value: 33.048 - type: ndcg_at_100 value: 38.321 - type: ndcg_at_1000 value: 40.949999999999996 - type: ndcg_at_3 value: 28.521 - type: ndcg_at_5 value: 30.898999999999997 - type: precision_at_1 value: 22.736 - type: precision_at_10 value: 5.194 - type: precision_at_100 value: 0.86 - type: precision_at_1000 value: 0.11800000000000001 - type: precision_at_3 value: 12.2 - type: precision_at_5 value: 8.762 - type: recall_at_1 value: 20.77 - type: recall_at_10 value: 44.741 - type: recall_at_100 value: 68.987 - type: recall_at_1000 value: 88.984 - type: recall_at_3 value: 32.830999999999996 - type: recall_at_5 value: 38.452999999999996 - task: type: Retrieval dataset: type: climate-fever name: MTEB ClimateFEVER config: default split: test revision: None metrics: - type: map_at_1 value: 9.646 - type: map_at_10 value: 17.432 - type: map_at_100 value: 19.347 - type: map_at_1000 value: 19.555 - type: map_at_3 value: 14.355 - type: map_at_5 value: 15.83 - type: mrr_at_1 value: 21.433 - type: mrr_at_10 value: 32.583 - type: mrr_at_100 value: 33.708 - type: mrr_at_1000 value: 33.751999999999995 - type: mrr_at_3 value: 28.979 - type: mrr_at_5 value: 30.979 - type: ndcg_at_1 value: 21.433 - type: ndcg_at_10 value: 25.025 - type: ndcg_at_100 value: 32.818999999999996 - type: ndcg_at_1000 value: 36.549 - type: ndcg_at_3 value: 19.689 - type: ndcg_at_5 value: 21.462 - type: precision_at_1 value: 21.433 - type: precision_at_10 value: 8.085 - type: precision_at_100 value: 1.6340000000000001 - type: precision_at_1000 value: 0.233 - type: precision_at_3 value: 14.832 - type: precision_at_5 value: 11.530999999999999 - type: recall_at_1 value: 9.646 - type: recall_at_10 value: 31.442999999999998 - type: recall_at_100 value: 58.48 - type: recall_at_1000 value: 79.253 - type: recall_at_3 value: 18.545 - type: recall_at_5 value: 23.362 - task: type: Retrieval dataset: type: dbpedia-entity name: MTEB DBPedia config: default split: test revision: None metrics: - type: map_at_1 value: 8.48 - type: map_at_10 value: 18.127 - type: map_at_100 value: 25.563999999999997 - type: map_at_1000 value: 27.386 - type: map_at_3 value: 13.189 - type: map_at_5 value: 15.417 - type: mrr_at_1 value: 63.74999999999999 - type: mrr_at_10 value: 71.34899999999999 - type: mrr_at_100 value: 71.842 - type: mrr_at_1000 value: 71.851 - type: mrr_at_3 value: 69.167 - type: mrr_at_5 value: 70.479 - type: ndcg_at_1 value: 51.87500000000001 - type: ndcg_at_10 value: 38.792 - type: ndcg_at_100 value: 43.889 - type: ndcg_at_1000 value: 51.561 - type: ndcg_at_3 value: 42.686 - type: ndcg_at_5 value: 40.722 - type: precision_at_1 value: 63.74999999999999 - type: precision_at_10 value: 30.375000000000004 - type: precision_at_100 value: 10.103 - type: precision_at_1000 value: 2.257 - type: precision_at_3 value: 45.167 - type: precision_at_5 value: 38.95 - type: recall_at_1 value: 8.48 - type: recall_at_10 value: 23.008 - type: recall_at_100 value: 48.875 - type: recall_at_1000 value: 73.402 - type: recall_at_3 value: 14.377 - type: recall_at_5 value: 17.819 - task: type: Classification dataset: type: mteb/emotion name: MTEB EmotionClassification config: default split: test revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 metrics: - type: accuracy value: 47.605 - type: f1 value: 42.345081371303316 - task: type: Retrieval dataset: type: fever name: MTEB FEVER config: default split: test revision: None metrics: - type: map_at_1 value: 62.247 - type: map_at_10 value: 72.782 - type: map_at_100 value: 73.095 - type: map_at_1000 value: 73.112 - type: map_at_3 value: 70.928 - type: map_at_5 value: 72.173 - type: mrr_at_1 value: 67.372 - type: mrr_at_10 value: 77.538 - type: mrr_at_100 value: 77.741 - type: mrr_at_1000 value: 77.74600000000001 - type: mrr_at_3 value: 75.938 - type: mrr_at_5 value: 77.054 - type: ndcg_at_1 value: 67.372 - type: ndcg_at_10 value: 78.001 - type: ndcg_at_100 value: 79.295 - type: ndcg_at_1000 value: 79.648 - type: ndcg_at_3 value: 74.71 - type: ndcg_at_5 value: 76.712 - type: precision_at_1 value: 67.372 - type: precision_at_10 value: 9.844999999999999 - type: precision_at_100 value: 1.065 - type: precision_at_1000 value: 0.11100000000000002 - type: precision_at_3 value: 29.308 - type: precision_at_5 value: 18.731 - type: recall_at_1 value: 62.247 - type: recall_at_10 value: 89.453 - type: recall_at_100 value: 94.998 - type: recall_at_1000 value: 97.385 - type: recall_at_3 value: 80.563 - type: recall_at_5 value: 85.58099999999999 - task: type: Retrieval dataset: type: fiqa name: MTEB FiQA2018 config: default split: test revision: None metrics: - type: map_at_1 value: 22.587 - type: map_at_10 value: 37.316 - type: map_at_100 value: 39.542 - type: map_at_1000 value: 39.701 - type: map_at_3 value: 32.332 - type: map_at_5 value: 35.172 - type: mrr_at_1 value: 42.437999999999995 - type: mrr_at_10 value: 51.98500000000001 - type: mrr_at_100 value: 52.910999999999994 - type: mrr_at_1000 value: 52.944 - type: mrr_at_3 value: 49.691 - type: mrr_at_5 value: 51.15 - type: ndcg_at_1 value: 42.437999999999995 - type: ndcg_at_10 value: 45.016 - type: ndcg_at_100 value: 52.541000000000004 - type: ndcg_at_1000 value: 54.99699999999999 - type: ndcg_at_3 value: 41.175 - type: ndcg_at_5 value: 42.647 - type: precision_at_1 value: 42.437999999999995 - type: precision_at_10 value: 12.855 - type: precision_at_100 value: 2.049 - type: precision_at_1000 value: 0.247 - type: precision_at_3 value: 27.675 - type: precision_at_5 value: 20.617 - type: recall_at_1 value: 22.587 - type: recall_at_10 value: 51.547 - type: recall_at_100 value: 78.88 - type: recall_at_1000 value: 93.741 - type: recall_at_3 value: 37.256 - type: recall_at_5 value: 44.295 - task: type: Retrieval dataset: type: hotpotqa name: MTEB HotpotQA config: default split: test revision: None metrics: - type: map_at_1 value: 32.451 - type: map_at_10 value: 48.082 - type: map_at_100 value: 49.08 - type: map_at_1000 value: 49.163000000000004 - type: map_at_3 value: 44.766 - type: map_at_5 value: 46.722 - type: mrr_at_1 value: 64.902 - type: mrr_at_10 value: 72.195 - type: mrr_at_100 value: 72.572 - type: mrr_at_1000 value: 72.589 - type: mrr_at_3 value: 70.774 - type: mrr_at_5 value: 71.611 - type: ndcg_at_1 value: 64.902 - type: ndcg_at_10 value: 57.14399999999999 - type: ndcg_at_100 value: 60.916000000000004 - type: ndcg_at_1000 value: 62.649 - type: ndcg_at_3 value: 52.09 - type: ndcg_at_5 value: 54.70399999999999 - type: precision_at_1 value: 64.902 - type: precision_at_10 value: 12.136 - type: precision_at_100 value: 1.51 - type: precision_at_1000 value: 0.174 - type: precision_at_3 value: 32.933 - type: precision_at_5 value: 21.823 - type: recall_at_1 value: 32.451 - type: recall_at_10 value: 60.682 - type: recall_at_100 value: 75.523 - type: recall_at_1000 value: 87.063 - type: recall_at_3 value: 49.399 - type: recall_at_5 value: 54.55799999999999 - task: type: Classification dataset: type: mteb/imdb name: MTEB ImdbClassification config: default split: test revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 metrics: - type: accuracy value: 89.48759999999997 - type: ap value: 85.15533983465178 - type: f1 value: 89.46732838870311 - task: type: Retrieval dataset: type: msmarco name: MTEB MSMARCO config: default split: dev revision: None metrics: - type: map_at_1 value: 17.942 - type: map_at_10 value: 29.755 - type: map_at_100 value: 31.008000000000003 - type: map_at_1000 value: 31.067 - type: map_at_3 value: 25.959 - type: map_at_5 value: 28.044999999999998 - type: mrr_at_1 value: 18.467 - type: mrr_at_10 value: 30.253000000000004 - type: mrr_at_100 value: 31.461 - type: mrr_at_1000 value: 31.513 - type: mrr_at_3 value: 26.528000000000002 - type: mrr_at_5 value: 28.588 - type: ndcg_at_1 value: 18.467 - type: ndcg_at_10 value: 36.510999999999996 - type: ndcg_at_100 value: 42.748999999999995 - type: ndcg_at_1000 value: 44.188 - type: ndcg_at_3 value: 28.752 - type: ndcg_at_5 value: 32.462 - type: precision_at_1 value: 18.467 - type: precision_at_10 value: 6.006 - type: precision_at_100 value: 0.9169999999999999 - type: precision_at_1000 value: 0.104 - type: precision_at_3 value: 12.55 - type: precision_at_5 value: 9.395000000000001 - type: recall_at_1 value: 17.942 - type: recall_at_10 value: 57.440000000000005 - type: recall_at_100 value: 86.66199999999999 - type: recall_at_1000 value: 97.613 - type: recall_at_3 value: 36.271 - type: recall_at_5 value: 45.167 - task: type: Classification dataset: type: mteb/mtop_domain name: MTEB MTOPDomainClassification (en) config: en split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics: - type: accuracy value: 36.3657090743274 - type: f1 value: 27.22838800222161 - task: type: Classification dataset: type: mteb/mtop_intent name: MTEB MTOPIntentClassification (en) config: en split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics: - type: accuracy value: 1.0168718650250799 - type: f1 value: 0.0674636098084213 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (en) config: en split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 1.8829858776059176 - type: f1 value: 0.08021151737444676 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (en) config: en split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 8.681909885675857 - type: f1 value: 2.752826896423761 - task: type: Clustering dataset: type: mteb/medrxiv-clustering-p2p name: MTEB MedrxivClusteringP2P config: default split: test revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 metrics: - type: v_measure value: 33.88016176143737 - task: type: Clustering dataset: type: mteb/medrxiv-clustering-s2s name: MTEB MedrxivClusteringS2S config: default split: test revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 metrics: - type: v_measure value: 32.07643038274053 - task: type: Reranking dataset: type: mteb/mind_small name: MTEB MindSmallReranking config: default split: test revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 metrics: - type: map value: 30.81344342001539 - type: mrr value: 31.82078962760685 - task: type: Retrieval dataset: type: nfcorpus name: MTEB NFCorpus config: default split: test revision: None metrics: - type: map_at_1 value: 4.617 - type: map_at_10 value: 11.501 - type: map_at_100 value: 14.729999999999999 - type: map_at_1000 value: 16.209 - type: map_at_3 value: 8.275 - type: map_at_5 value: 9.853000000000002 - type: mrr_at_1 value: 41.486000000000004 - type: mrr_at_10 value: 51.471999999999994 - type: mrr_at_100 value: 52.020999999999994 - type: mrr_at_1000 value: 52.066 - type: mrr_at_3 value: 49.484 - type: mrr_at_5 value: 50.660000000000004 - type: ndcg_at_1 value: 38.854 - type: ndcg_at_10 value: 31.567 - type: ndcg_at_100 value: 29.842999999999996 - type: ndcg_at_1000 value: 38.995000000000005 - type: ndcg_at_3 value: 36.785000000000004 - type: ndcg_at_5 value: 34.955000000000005 - type: precision_at_1 value: 40.867 - type: precision_at_10 value: 23.591 - type: precision_at_100 value: 7.771 - type: precision_at_1000 value: 2.11 - type: precision_at_3 value: 35.397 - type: precision_at_5 value: 30.959999999999997 - type: recall_at_1 value: 4.617 - type: recall_at_10 value: 15.609 - type: recall_at_100 value: 31.313999999999997 - type: recall_at_1000 value: 63.085 - type: recall_at_3 value: 9.746 - type: recall_at_5 value: 12.295 - task: type: Retrieval dataset: type: nq name: MTEB NQ config: default split: test revision: None metrics: - type: map_at_1 value: 28.797 - type: map_at_10 value: 44.822 - type: map_at_100 value: 45.891999999999996 - type: map_at_1000 value: 45.919 - type: map_at_3 value: 40.237 - type: map_at_5 value: 42.913000000000004 - type: mrr_at_1 value: 32.561 - type: mrr_at_10 value: 46.982 - type: mrr_at_100 value: 47.827 - type: mrr_at_1000 value: 47.843999999999994 - type: mrr_at_3 value: 43.26 - type: mrr_at_5 value: 45.527 - type: ndcg_at_1 value: 32.532 - type: ndcg_at_10 value: 52.832 - type: ndcg_at_100 value: 57.343999999999994 - type: ndcg_at_1000 value: 57.93899999999999 - type: ndcg_at_3 value: 44.246 - type: ndcg_at_5 value: 48.698 - type: precision_at_1 value: 32.532 - type: precision_at_10 value: 9.003 - type: precision_at_100 value: 1.1480000000000001 - type: precision_at_1000 value: 0.12 - type: precision_at_3 value: 20.605999999999998 - type: precision_at_5 value: 14.954 - type: recall_at_1 value: 28.797 - type: recall_at_10 value: 75.065 - type: recall_at_100 value: 94.6 - type: recall_at_1000 value: 98.967 - type: recall_at_3 value: 52.742 - type: recall_at_5 value: 63.012 - task: type: Retrieval dataset: type: quora name: MTEB QuoraRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 69.84700000000001 - type: map_at_10 value: 83.91499999999999 - type: map_at_100 value: 84.568 - type: map_at_1000 value: 84.584 - type: map_at_3 value: 80.87299999999999 - type: map_at_5 value: 82.76299999999999 - type: mrr_at_1 value: 80.4 - type: mrr_at_10 value: 86.843 - type: mrr_at_100 value: 86.956 - type: mrr_at_1000 value: 86.957 - type: mrr_at_3 value: 85.843 - type: mrr_at_5 value: 86.521 - type: ndcg_at_1 value: 80.4 - type: ndcg_at_10 value: 87.787 - type: ndcg_at_100 value: 89.039 - type: ndcg_at_1000 value: 89.137 - type: ndcg_at_3 value: 84.76700000000001 - type: ndcg_at_5 value: 86.413 - type: precision_at_1 value: 80.4 - type: precision_at_10 value: 13.391 - type: precision_at_100 value: 1.533 - type: precision_at_1000 value: 0.157 - type: precision_at_3 value: 37.123 - type: precision_at_5 value: 24.462 - type: recall_at_1 value: 69.84700000000001 - type: recall_at_10 value: 95.296 - type: recall_at_100 value: 99.543 - type: recall_at_1000 value: 99.98700000000001 - type: recall_at_3 value: 86.75 - type: recall_at_5 value: 91.33099999999999 - task: type: Clustering dataset: type: mteb/reddit-clustering name: MTEB RedditClustering config: default split: test revision: 24640382cdbf8abc73003fb0fa6d111a705499eb metrics: - type: v_measure value: 54.24501738730203 - task: type: Clustering dataset: type: mteb/reddit-clustering-p2p name: MTEB RedditClusteringP2P config: default split: test revision: 282350215ef01743dc01b456c7f5241fa8937f16 metrics: - type: v_measure value: 61.28243705082983 - task: type: Retrieval dataset: type: scidocs name: MTEB SCIDOCS config: default split: test revision: None metrics: - type: map_at_1 value: 3.473 - type: map_at_10 value: 8.944 - type: map_at_100 value: 11.21 - type: map_at_1000 value: 11.601 - type: map_at_3 value: 6.167 - type: map_at_5 value: 7.438000000000001 - type: mrr_at_1 value: 17.1 - type: mrr_at_10 value: 26.487 - type: mrr_at_100 value: 27.888 - type: mrr_at_1000 value: 27.961000000000002 - type: mrr_at_3 value: 23.25 - type: mrr_at_5 value: 24.91 - type: ndcg_at_1 value: 17.1 - type: ndcg_at_10 value: 15.615000000000002 - type: ndcg_at_100 value: 24.667 - type: ndcg_at_1000 value: 31.467 - type: ndcg_at_3 value: 14.035 - type: ndcg_at_5 value: 12.443 - type: precision_at_1 value: 17.1 - type: precision_at_10 value: 8.4 - type: precision_at_100 value: 2.149 - type: precision_at_1000 value: 0.378 - type: precision_at_3 value: 13.200000000000001 - type: precision_at_5 value: 11.06 - type: recall_at_1 value: 3.473 - type: recall_at_10 value: 17.087 - type: recall_at_100 value: 43.641999999999996 - type: recall_at_1000 value: 76.7 - type: recall_at_3 value: 8.037999999999998 - type: recall_at_5 value: 11.232000000000001 - task: type: STS dataset: type: mteb/sickr-sts name: MTEB SICK-R config: default split: test revision: a6ea5a8cab320b040a23452cc28066d9beae2cee metrics: - type: cos_sim_pearson value: 86.07032781899852 - type: cos_sim_spearman value: 81.86668245459153 - type: euclidean_pearson value: 83.75572948495356 - type: euclidean_spearman value: 81.88575221829207 - type: manhattan_pearson value: 83.73171218997966 - type: manhattan_spearman value: 81.85928771458329 - task: type: STS dataset: type: mteb/sts12-sts name: MTEB STS12 config: default split: test revision: a0d554a64d88156834ff5ae9920b964011b16384 metrics: - type: cos_sim_pearson value: 80.29008828604368 - type: cos_sim_spearman value: 70.7510437896188 - type: euclidean_pearson value: 76.65867322096001 - type: euclidean_spearman value: 70.53984435296805 - type: manhattan_pearson value: 76.6398826461678 - type: manhattan_spearman value: 70.55153706770477 - task: type: STS dataset: type: mteb/sts13-sts name: MTEB STS13 config: default split: test revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca metrics: - type: cos_sim_pearson value: 83.55610063096913 - type: cos_sim_spearman value: 84.36676850545378 - type: euclidean_pearson value: 82.81438612985889 - type: euclidean_spearman value: 84.182693686057 - type: manhattan_pearson value: 82.8355239074719 - type: manhattan_spearman value: 84.19280249146543 - task: type: STS dataset: type: mteb/sts14-sts name: MTEB STS14 config: default split: test revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 metrics: - type: cos_sim_pearson value: 78.94275022740113 - type: cos_sim_spearman value: 74.50851813226338 - type: euclidean_pearson value: 77.30867917552419 - type: euclidean_spearman value: 74.55661368823343 - type: manhattan_pearson value: 77.31883134876524 - type: manhattan_spearman value: 74.58999819014154 - task: type: STS dataset: type: mteb/sts15-sts name: MTEB STS15 config: default split: test revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 metrics: - type: cos_sim_pearson value: 85.62907185533146 - type: cos_sim_spearman value: 86.40667080261993 - type: euclidean_pearson value: 85.15184748925726 - type: euclidean_spearman value: 86.33853519247509 - type: manhattan_pearson value: 85.21542426870172 - type: manhattan_spearman value: 86.4076178438401 - task: type: STS dataset: type: mteb/sts16-sts name: MTEB STS16 config: default split: test revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 metrics: - type: cos_sim_pearson value: 83.42449758804275 - type: cos_sim_spearman value: 84.7411616479609 - type: euclidean_pearson value: 83.56616729612806 - type: euclidean_spearman value: 84.44493050289694 - type: manhattan_pearson value: 83.50906591764574 - type: manhattan_spearman value: 84.39704993090794 - 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: 88.84843806728331 - type: cos_sim_spearman value: 89.03139214250334 - type: euclidean_pearson value: 89.63615835813032 - type: euclidean_spearman value: 89.33022202130817 - type: manhattan_pearson value: 89.67071925715891 - type: manhattan_spearman value: 89.29339683171531 - 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: 65.65559857216783 - type: cos_sim_spearman value: 65.86805861979079 - type: euclidean_pearson value: 66.69697475461513 - type: euclidean_spearman value: 66.07735691378713 - type: manhattan_pearson value: 66.63427637906918 - type: manhattan_spearman value: 65.95720565040364 - task: type: STS dataset: type: mteb/stsbenchmark-sts name: MTEB STSBenchmark config: default split: test revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 metrics: - type: cos_sim_pearson value: 86.06435608928308 - type: cos_sim_spearman value: 86.46139340079428 - type: euclidean_pearson value: 86.4874804471064 - type: euclidean_spearman value: 86.19390771731406 - type: manhattan_pearson value: 86.51184704840284 - type: manhattan_spearman value: 86.19094101171963 - task: type: Reranking dataset: type: mteb/scidocs-reranking name: MTEB SciDocsRR config: default split: test revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab metrics: - type: map value: 85.10723925640346 - type: mrr value: 95.62579305226365 - task: type: Retrieval dataset: type: scifact name: MTEB SciFact config: default split: test revision: None metrics: - type: map_at_1 value: 56.233 - type: map_at_10 value: 64.94 - type: map_at_100 value: 65.508 - type: map_at_1000 value: 65.537 - type: map_at_3 value: 62.121 - type: map_at_5 value: 63.92400000000001 - type: mrr_at_1 value: 58.667 - type: mrr_at_10 value: 66.352 - type: mrr_at_100 value: 66.751 - type: mrr_at_1000 value: 66.777 - type: mrr_at_3 value: 64.22200000000001 - type: mrr_at_5 value: 65.656 - type: ndcg_at_1 value: 58.667 - type: ndcg_at_10 value: 69.318 - type: ndcg_at_100 value: 71.822 - type: ndcg_at_1000 value: 72.578 - type: ndcg_at_3 value: 64.532 - type: ndcg_at_5 value: 67.292 - type: precision_at_1 value: 58.667 - type: precision_at_10 value: 9.133 - type: precision_at_100 value: 1.05 - type: precision_at_1000 value: 0.11199999999999999 - type: precision_at_3 value: 24.889 - type: precision_at_5 value: 16.733 - type: recall_at_1 value: 56.233 - type: recall_at_10 value: 81.206 - type: recall_at_100 value: 92.80000000000001 - type: recall_at_1000 value: 98.667 - type: recall_at_3 value: 68.672 - type: recall_at_5 value: 75.378 - task: type: PairClassification dataset: type: mteb/sprintduplicatequestions-pairclassification name: MTEB SprintDuplicateQuestions config: default split: test revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 metrics: - type: cos_sim_accuracy value: 99.56336633663366 - type: cos_sim_ap value: 86.13024319858586 - type: cos_sim_f1 value: 76.80157946692991 - type: cos_sim_precision value: 75.82846003898635 - type: cos_sim_recall value: 77.8 - type: dot_accuracy value: 99.56336633663366 - type: dot_ap value: 86.13028343072267 - type: dot_f1 value: 76.80157946692991 - type: dot_precision value: 75.82846003898635 - type: dot_recall value: 77.8 - type: euclidean_accuracy value: 99.56336633663366 - type: euclidean_ap value: 86.13029040641543 - type: euclidean_f1 value: 76.80157946692991 - type: euclidean_precision value: 75.82846003898635 - type: euclidean_recall value: 77.8 - type: manhattan_accuracy value: 99.56534653465347 - type: manhattan_ap value: 86.24817068330776 - type: manhattan_f1 value: 77.13580246913581 - type: manhattan_precision value: 76.19512195121952 - type: manhattan_recall value: 78.10000000000001 - type: max_accuracy value: 99.56534653465347 - type: max_ap value: 86.24817068330776 - type: max_f1 value: 77.13580246913581 - task: type: Clustering dataset: type: mteb/stackexchange-clustering name: MTEB StackExchangeClustering config: default split: test revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 metrics: - type: v_measure value: 64.69564559409538 - task: type: Clustering dataset: type: mteb/stackexchange-clustering-p2p name: MTEB StackExchangeClusteringP2P config: default split: test revision: 815ca46b2622cec33ccafc3735d572c266efdb44 metrics: - type: v_measure value: 34.23127531581388 - task: type: Reranking dataset: type: mteb/stackoverflowdupquestions-reranking name: MTEB StackOverflowDupQuestions config: default split: test revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 metrics: - type: map value: 49.845357053686975 - type: mrr value: 50.59803656311009 - task: type: Summarization dataset: type: mteb/summeval name: MTEB SummEval config: default split: test revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c metrics: - type: cos_sim_pearson value: 29.02241691876377 - type: cos_sim_spearman value: 29.017719340560923 - type: dot_pearson value: 29.59373129445045 - type: dot_spearman value: 29.616196388331968 - task: type: Retrieval dataset: type: trec-covid name: MTEB TRECCOVID config: default split: test revision: None metrics: - type: map_at_1 value: 0.157 - type: map_at_10 value: 0.9440000000000001 - type: map_at_100 value: 4.61 - type: map_at_1000 value: 11.488 - type: map_at_3 value: 0.396 - type: map_at_5 value: 0.569 - type: mrr_at_1 value: 57.99999999999999 - type: mrr_at_10 value: 71.672 - type: mrr_at_100 value: 71.707 - type: mrr_at_1000 value: 71.707 - type: mrr_at_3 value: 68.333 - type: mrr_at_5 value: 70.533 - type: ndcg_at_1 value: 54.0 - type: ndcg_at_10 value: 45.216 - type: ndcg_at_100 value: 32.623999999999995 - type: ndcg_at_1000 value: 33.006 - type: ndcg_at_3 value: 51.76500000000001 - type: ndcg_at_5 value: 47.888999999999996 - type: precision_at_1 value: 57.99999999999999 - type: precision_at_10 value: 48.0 - type: precision_at_100 value: 32.74 - type: precision_at_1000 value: 14.588000000000001 - type: precision_at_3 value: 55.333 - type: precision_at_5 value: 51.2 - type: recall_at_1 value: 0.157 - type: recall_at_10 value: 1.212 - type: recall_at_100 value: 7.868 - type: recall_at_1000 value: 31.583 - type: recall_at_3 value: 0.443 - type: recall_at_5 value: 0.6779999999999999 - task: type: Retrieval dataset: type: webis-touche2020 name: MTEB Touche2020 config: default split: test revision: None metrics: - type: map_at_1 value: 1.545 - type: map_at_10 value: 4.6690000000000005 - type: map_at_100 value: 8.982 - type: map_at_1000 value: 10.453999999999999 - type: map_at_3 value: 2.35 - type: map_at_5 value: 3.168 - type: mrr_at_1 value: 18.367 - type: mrr_at_10 value: 28.599999999999998 - type: mrr_at_100 value: 30.287 - type: mrr_at_1000 value: 30.339 - type: mrr_at_3 value: 24.490000000000002 - type: mrr_at_5 value: 27.040999999999997 - type: ndcg_at_1 value: 17.347 - type: ndcg_at_10 value: 13.868 - type: ndcg_at_100 value: 25.499 - type: ndcg_at_1000 value: 37.922 - type: ndcg_at_3 value: 13.746 - type: ndcg_at_5 value: 13.141 - type: precision_at_1 value: 18.367 - type: precision_at_10 value: 12.653 - type: precision_at_100 value: 5.776 - type: precision_at_1000 value: 1.3860000000000001 - type: precision_at_3 value: 13.605 - type: precision_at_5 value: 13.061 - type: recall_at_1 value: 1.545 - type: recall_at_10 value: 9.305 - type: recall_at_100 value: 38.084 - type: recall_at_1000 value: 75.897 - type: recall_at_3 value: 2.903 - type: recall_at_5 value: 4.8919999999999995 - task: type: Classification dataset: type: mteb/toxic_conversations_50k name: MTEB ToxicConversationsClassification config: default split: test revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c metrics: - type: accuracy value: 71.23839999999998 - type: ap value: 14.810293385203243 - type: f1 value: 55.08401453918053 - task: type: Classification dataset: type: mteb/tweet_sentiment_extraction name: MTEB TweetSentimentExtractionClassification config: default split: test revision: d604517c81ca91fe16a244d1248fc021f9ecee7a metrics: - type: accuracy value: 58.21448783248444 - type: f1 value: 58.57246320620639 - task: type: Clustering dataset: type: mteb/twentynewsgroups-clustering name: MTEB TwentyNewsgroupsClustering config: default split: test revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 metrics: - type: v_measure value: 49.314744135178934 - task: type: PairClassification dataset: type: mteb/twittersemeval2015-pairclassification name: MTEB TwitterSemEval2015 config: default split: test revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 metrics: - type: cos_sim_accuracy value: 84.13899982118377 - type: cos_sim_ap value: 68.03329474978145 - type: cos_sim_f1 value: 63.31192005710206 - type: cos_sim_precision value: 57.6473136915078 - type: cos_sim_recall value: 70.21108179419525 - type: dot_accuracy value: 84.13899982118377 - type: dot_ap value: 68.03324775052695 - type: dot_f1 value: 63.31192005710206 - type: dot_precision value: 57.6473136915078 - type: dot_recall value: 70.21108179419525 - type: euclidean_accuracy value: 84.13899982118377 - type: euclidean_ap value: 68.03331114508686 - type: euclidean_f1 value: 63.31192005710206 - type: euclidean_precision value: 57.6473136915078 - type: euclidean_recall value: 70.21108179419525 - type: manhattan_accuracy value: 84.12111819753234 - type: manhattan_ap value: 67.97378509663328 - type: manhattan_f1 value: 63.38468945594607 - type: manhattan_precision value: 58.2779991146525 - type: manhattan_recall value: 69.47229551451187 - type: max_accuracy value: 84.13899982118377 - type: max_ap value: 68.03331114508686 - type: max_f1 value: 63.38468945594607 - task: type: PairClassification dataset: type: mteb/twitterurlcorpus-pairclassification name: MTEB TwitterURLCorpus config: default split: test revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf metrics: - type: cos_sim_accuracy value: 87.68774013272791 - type: cos_sim_ap value: 83.51733662214374 - type: cos_sim_f1 value: 75.82190771045259 - type: cos_sim_precision value: 72.72341628959276 - type: cos_sim_recall value: 79.19618109023713 - type: dot_accuracy value: 87.68774013272791 - type: dot_ap value: 83.5173527754126 - type: dot_f1 value: 75.82190771045259 - type: dot_precision value: 72.72341628959276 - type: dot_recall value: 79.19618109023713 - type: euclidean_accuracy value: 87.68774013272791 - type: euclidean_ap value: 83.51734651146224 - type: euclidean_f1 value: 75.82190771045259 - type: euclidean_precision value: 72.72341628959276 - type: euclidean_recall value: 79.19618109023713 - type: manhattan_accuracy value: 87.67221640082276 - type: manhattan_ap value: 83.51179463759505 - type: manhattan_f1 value: 75.76243980738361 - type: manhattan_precision value: 71.99112590127565 - type: manhattan_recall value: 79.95072374499537 - type: max_accuracy value: 87.68774013272791 - type: max_ap value: 83.5173527754126 - type: max_f1 value: 75.82190771045259 ---