--- library_name: sentence-transformers pipeline_tag: sentence-similarity tags: - feature-extraction - sentence-similarity - mteb model-index: - name: epoch_0_model results: - task: type: Classification dataset: type: mteb/amazon_counterfactual name: MTEB AmazonCounterfactualClassification (en) config: en split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics: - type: accuracy value: 78.67164179104476 - type: ap value: 42.7379383648841 - type: f1 value: 72.79997373883408 - task: type: Classification dataset: type: mteb/amazon_polarity name: MTEB AmazonPolarityClassification config: default split: test revision: e2d317d38cd51312af73b3d32a06d1a08b442046 metrics: - type: accuracy value: 90.413775 - type: ap value: 87.08812293673202 - type: f1 value: 90.39246586225426 - task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (en) config: en split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics: - type: accuracy value: 47.80799999999999 - type: f1 value: 47.25679462673503 - task: type: Retrieval dataset: type: arguana name: MTEB ArguAna config: default split: test revision: None metrics: - type: map_at_1 value: 30.37 - type: map_at_10 value: 45.748 - type: map_at_100 value: 46.617 - type: map_at_1000 value: 46.622 - type: map_at_3 value: 40.564 - type: map_at_5 value: 43.69 - type: mrr_at_1 value: 30.868000000000002 - type: mrr_at_10 value: 45.905 - type: mrr_at_100 value: 46.787 - type: mrr_at_1000 value: 46.792 - type: mrr_at_3 value: 40.717999999999996 - type: mrr_at_5 value: 43.851 - type: ndcg_at_1 value: 30.37 - type: ndcg_at_10 value: 54.662 - type: ndcg_at_100 value: 58.23700000000001 - type: ndcg_at_1000 value: 58.373 - type: ndcg_at_3 value: 44.069 - type: ndcg_at_5 value: 49.728 - type: precision_at_1 value: 30.37 - type: precision_at_10 value: 8.321000000000002 - type: precision_at_100 value: 0.985 - type: precision_at_1000 value: 0.1 - type: precision_at_3 value: 18.089 - type: precision_at_5 value: 13.613 - type: recall_at_1 value: 30.37 - type: recall_at_10 value: 83.21499999999999 - type: recall_at_100 value: 98.506 - type: recall_at_1000 value: 99.57300000000001 - type: recall_at_3 value: 54.266999999999996 - type: recall_at_5 value: 68.065 - task: type: Clustering dataset: type: mteb/arxiv-clustering-p2p name: MTEB ArxivClusteringP2P config: default split: test revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d metrics: - type: v_measure value: 45.85329429748079 - task: type: Clustering dataset: type: mteb/arxiv-clustering-s2s name: MTEB ArxivClusteringS2S config: default split: test revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 metrics: - type: v_measure value: 36.12666783330692 - task: type: Reranking dataset: type: mteb/askubuntudupquestions-reranking name: MTEB AskUbuntuDupQuestions config: default split: test revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 metrics: - type: map value: 57.58783867794241 - type: mrr value: 71.84078617596622 - task: type: STS dataset: type: mteb/biosses-sts name: MTEB BIOSSES config: default split: test revision: d3fb88f8f02e40887cd149695127462bbcf29b4a metrics: - type: cos_sim_pearson value: 87.92453139507079 - type: cos_sim_spearman value: 85.37122234964886 - type: euclidean_pearson value: 86.19345621799168 - type: euclidean_spearman value: 85.37122234964886 - type: manhattan_pearson value: 86.4685290616604 - type: manhattan_spearman value: 85.91400580167537 - task: type: Classification dataset: type: mteb/banking77 name: MTEB Banking77Classification config: default split: test revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 metrics: - type: accuracy value: 83.81818181818181 - type: f1 value: 83.76155217378863 - task: type: Clustering dataset: type: mteb/biorxiv-clustering-p2p name: MTEB BiorxivClusteringP2P config: default split: test revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 metrics: - type: v_measure value: 38.46362764203256 - task: type: Clustering dataset: type: mteb/biorxiv-clustering-s2s name: MTEB BiorxivClusteringS2S config: default split: test revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 metrics: - type: v_measure value: 33.13807021168658 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackAndroidRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 29.725 - type: map_at_10 value: 39.654 - type: map_at_100 value: 41.022 - type: map_at_1000 value: 41.144999999999996 - type: map_at_3 value: 36.819 - type: map_at_5 value: 38.376 - type: mrr_at_1 value: 36.195 - type: mrr_at_10 value: 45.171 - type: mrr_at_100 value: 45.987 - type: mrr_at_1000 value: 46.033 - type: mrr_at_3 value: 43.038 - type: mrr_at_5 value: 44.196000000000005 - type: ndcg_at_1 value: 36.195 - type: ndcg_at_10 value: 45.194 - type: ndcg_at_100 value: 50.516000000000005 - type: ndcg_at_1000 value: 52.739000000000004 - type: ndcg_at_3 value: 41.142 - type: ndcg_at_5 value: 42.973 - type: precision_at_1 value: 36.195 - type: precision_at_10 value: 8.312 - type: precision_at_100 value: 1.346 - type: precision_at_1000 value: 0.182 - type: precision_at_3 value: 19.599 - type: precision_at_5 value: 13.847999999999999 - type: recall_at_1 value: 29.725 - type: recall_at_10 value: 55.51199999999999 - type: recall_at_100 value: 78.182 - type: recall_at_1000 value: 92.727 - type: recall_at_3 value: 43.287 - type: recall_at_5 value: 48.732 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackEnglishRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 30.23 - type: map_at_10 value: 40.091 - type: map_at_100 value: 41.251 - type: map_at_1000 value: 41.384 - type: map_at_3 value: 37.247 - type: map_at_5 value: 38.865 - type: mrr_at_1 value: 38.279999999999994 - type: mrr_at_10 value: 46.288000000000004 - type: mrr_at_100 value: 47.022999999999996 - type: mrr_at_1000 value: 47.068 - type: mrr_at_3 value: 44.395 - type: mrr_at_5 value: 45.446 - type: ndcg_at_1 value: 38.279999999999994 - type: ndcg_at_10 value: 45.647 - type: ndcg_at_100 value: 49.851 - type: ndcg_at_1000 value: 51.991 - type: ndcg_at_3 value: 41.795 - type: ndcg_at_5 value: 43.578 - type: precision_at_1 value: 38.279999999999994 - type: precision_at_10 value: 8.522 - type: precision_at_100 value: 1.361 - type: precision_at_1000 value: 0.185 - type: precision_at_3 value: 20.297 - type: precision_at_5 value: 14.255 - type: recall_at_1 value: 30.23 - type: recall_at_10 value: 55.094 - type: recall_at_100 value: 72.887 - type: recall_at_1000 value: 86.295 - type: recall_at_3 value: 43.244 - type: recall_at_5 value: 48.507 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGamingRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 40.854 - type: map_at_10 value: 52.232 - type: map_at_100 value: 53.129000000000005 - type: map_at_1000 value: 53.185 - type: map_at_3 value: 49.094 - type: map_at_5 value: 50.834999999999994 - type: mrr_at_1 value: 46.708 - type: mrr_at_10 value: 56.021 - type: mrr_at_100 value: 56.584 - type: mrr_at_1000 value: 56.611999999999995 - type: mrr_at_3 value: 53.657 - type: mrr_at_5 value: 55.027 - type: ndcg_at_1 value: 46.708 - type: ndcg_at_10 value: 57.89 - type: ndcg_at_100 value: 61.541999999999994 - type: ndcg_at_1000 value: 62.754 - type: ndcg_at_3 value: 52.632 - type: ndcg_at_5 value: 55.104 - type: precision_at_1 value: 46.708 - type: precision_at_10 value: 9.122 - type: precision_at_100 value: 1.187 - type: precision_at_1000 value: 0.134 - type: precision_at_3 value: 23.072 - type: precision_at_5 value: 15.661 - type: recall_at_1 value: 40.854 - type: recall_at_10 value: 70.98 - type: recall_at_100 value: 86.947 - type: recall_at_1000 value: 95.62 - type: recall_at_3 value: 56.782999999999994 - type: recall_at_5 value: 62.980000000000004 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGisRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 26.366 - type: map_at_10 value: 33.674 - type: map_at_100 value: 34.58 - type: map_at_1000 value: 34.662 - type: map_at_3 value: 31.596999999999998 - type: map_at_5 value: 32.596000000000004 - type: mrr_at_1 value: 28.588 - type: mrr_at_10 value: 35.912 - type: mrr_at_100 value: 36.696 - type: mrr_at_1000 value: 36.760999999999996 - type: mrr_at_3 value: 33.823 - type: mrr_at_5 value: 34.829 - type: ndcg_at_1 value: 28.588 - type: ndcg_at_10 value: 38.031 - type: ndcg_at_100 value: 42.678 - type: ndcg_at_1000 value: 44.871 - type: ndcg_at_3 value: 33.815 - type: ndcg_at_5 value: 35.531 - type: precision_at_1 value: 28.588 - type: precision_at_10 value: 5.638 - type: precision_at_100 value: 0.8380000000000001 - type: precision_at_1000 value: 0.106 - type: precision_at_3 value: 13.974 - type: precision_at_5 value: 9.401 - type: recall_at_1 value: 26.366 - type: recall_at_10 value: 49.353 - type: recall_at_100 value: 71.194 - type: recall_at_1000 value: 87.842 - type: recall_at_3 value: 37.829 - type: recall_at_5 value: 41.976 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackMathematicaRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 16.634 - type: map_at_10 value: 23.271 - type: map_at_100 value: 24.366 - type: map_at_1000 value: 24.484 - type: map_at_3 value: 21.075 - type: map_at_5 value: 22.364 - type: mrr_at_1 value: 20.522000000000002 - type: mrr_at_10 value: 27.735 - type: mrr_at_100 value: 28.691 - type: mrr_at_1000 value: 28.762999999999998 - type: mrr_at_3 value: 25.518 - type: mrr_at_5 value: 26.762000000000004 - type: ndcg_at_1 value: 20.522000000000002 - type: ndcg_at_10 value: 27.791 - type: ndcg_at_100 value: 33.101 - type: ndcg_at_1000 value: 36.075 - type: ndcg_at_3 value: 23.74 - type: ndcg_at_5 value: 25.691000000000003 - type: precision_at_1 value: 20.522000000000002 - type: precision_at_10 value: 4.963 - type: precision_at_100 value: 0.873 - type: precision_at_1000 value: 0.128 - type: precision_at_3 value: 11.111 - type: precision_at_5 value: 8.01 - type: recall_at_1 value: 16.634 - type: recall_at_10 value: 37.498 - type: recall_at_100 value: 60.598 - type: recall_at_1000 value: 81.828 - type: recall_at_3 value: 26.136 - type: recall_at_5 value: 31.211 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackPhysicsRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 28.200999999999997 - type: map_at_10 value: 37.619 - type: map_at_100 value: 38.834999999999994 - type: map_at_1000 value: 38.951 - type: map_at_3 value: 35.119 - type: map_at_5 value: 36.559999999999995 - type: mrr_at_1 value: 33.782000000000004 - type: mrr_at_10 value: 43.033 - type: mrr_at_100 value: 43.761 - type: mrr_at_1000 value: 43.818 - type: mrr_at_3 value: 40.727999999999994 - type: mrr_at_5 value: 42.129 - type: ndcg_at_1 value: 33.782000000000004 - type: ndcg_at_10 value: 43.178 - type: ndcg_at_100 value: 48.27 - type: ndcg_at_1000 value: 50.559 - type: ndcg_at_3 value: 38.974 - type: ndcg_at_5 value: 41.019 - type: precision_at_1 value: 33.782000000000004 - type: precision_at_10 value: 7.575 - type: precision_at_100 value: 1.1820000000000002 - type: precision_at_1000 value: 0.154 - type: precision_at_3 value: 18.223 - type: precision_at_5 value: 12.742999999999999 - type: recall_at_1 value: 28.200999999999997 - type: recall_at_10 value: 54.089 - type: recall_at_100 value: 75.57000000000001 - type: recall_at_1000 value: 90.827 - type: recall_at_3 value: 42.435 - type: recall_at_5 value: 47.652 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackProgrammersRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 25.313000000000002 - type: map_at_10 value: 34.329 - type: map_at_100 value: 35.445 - type: map_at_1000 value: 35.556 - type: map_at_3 value: 31.659 - type: map_at_5 value: 32.981 - type: mrr_at_1 value: 30.822 - type: mrr_at_10 value: 39.084 - type: mrr_at_100 value: 39.97 - type: mrr_at_1000 value: 40.025 - type: mrr_at_3 value: 36.815 - type: mrr_at_5 value: 38.002 - type: ndcg_at_1 value: 30.822 - type: ndcg_at_10 value: 39.512 - type: ndcg_at_100 value: 44.925 - type: ndcg_at_1000 value: 47.274 - type: ndcg_at_3 value: 35.055 - type: ndcg_at_5 value: 36.788 - type: precision_at_1 value: 30.822 - type: precision_at_10 value: 7.1 - type: precision_at_100 value: 1.15 - type: precision_at_1000 value: 0.151 - type: precision_at_3 value: 16.476 - type: precision_at_5 value: 11.461 - type: recall_at_1 value: 25.313000000000002 - type: recall_at_10 value: 50.178 - type: recall_at_100 value: 74.312 - type: recall_at_1000 value: 90.50200000000001 - type: recall_at_3 value: 37.626 - type: recall_at_5 value: 42.34 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 25.502250000000004 - type: map_at_10 value: 33.655166666666666 - type: map_at_100 value: 34.72833333333333 - type: map_at_1000 value: 34.84375 - type: map_at_3 value: 31.253999999999998 - type: map_at_5 value: 32.55075 - type: mrr_at_1 value: 29.91975 - type: mrr_at_10 value: 37.65441666666667 - type: mrr_at_100 value: 38.464416666666665 - type: mrr_at_1000 value: 38.52591666666667 - type: mrr_at_3 value: 35.57858333333333 - type: mrr_at_5 value: 36.71083333333333 - type: ndcg_at_1 value: 29.91975 - type: ndcg_at_10 value: 38.47316666666667 - type: ndcg_at_100 value: 43.256416666666674 - type: ndcg_at_1000 value: 45.70658333333333 - type: ndcg_at_3 value: 34.350833333333334 - type: ndcg_at_5 value: 36.184583333333336 - type: precision_at_1 value: 29.91975 - type: precision_at_10 value: 6.5489999999999995 - type: precision_at_100 value: 1.0553333333333332 - type: precision_at_1000 value: 0.14516666666666667 - type: precision_at_3 value: 15.579083333333333 - type: precision_at_5 value: 10.851083333333332 - type: recall_at_1 value: 25.502250000000004 - type: recall_at_10 value: 48.7965 - type: recall_at_100 value: 69.93500000000002 - type: recall_at_1000 value: 87.17049999999999 - type: recall_at_3 value: 37.20433333333333 - type: recall_at_5 value: 42.00783333333333 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackStatsRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 23.777 - type: map_at_10 value: 29.932 - type: map_at_100 value: 30.778 - type: map_at_1000 value: 30.879 - type: map_at_3 value: 27.898 - type: map_at_5 value: 29.086000000000002 - type: mrr_at_1 value: 26.227 - type: mrr_at_10 value: 32.443 - type: mrr_at_100 value: 33.212 - type: mrr_at_1000 value: 33.29 - type: mrr_at_3 value: 30.419 - type: mrr_at_5 value: 31.616 - type: ndcg_at_1 value: 26.227 - type: ndcg_at_10 value: 33.774 - type: ndcg_at_100 value: 37.917 - type: ndcg_at_1000 value: 40.557 - type: ndcg_at_3 value: 29.875 - type: ndcg_at_5 value: 31.845000000000002 - type: precision_at_1 value: 26.227 - type: precision_at_10 value: 5.153 - type: precision_at_100 value: 0.784 - type: precision_at_1000 value: 0.108 - type: precision_at_3 value: 12.423 - type: precision_at_5 value: 8.773 - type: recall_at_1 value: 23.777 - type: recall_at_10 value: 43.142 - type: recall_at_100 value: 61.68900000000001 - type: recall_at_1000 value: 81.37100000000001 - type: recall_at_3 value: 32.582 - type: recall_at_5 value: 37.403 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackTexRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 16.659 - type: map_at_10 value: 22.926 - type: map_at_100 value: 23.837 - type: map_at_1000 value: 23.953 - type: map_at_3 value: 21.029999999999998 - type: map_at_5 value: 22.019 - type: mrr_at_1 value: 19.649 - type: mrr_at_10 value: 26.32 - type: mrr_at_100 value: 27.143 - type: mrr_at_1000 value: 27.222 - type: mrr_at_3 value: 24.484 - type: mrr_at_5 value: 25.468000000000004 - type: ndcg_at_1 value: 19.649 - type: ndcg_at_10 value: 26.941 - type: ndcg_at_100 value: 31.522 - type: ndcg_at_1000 value: 34.538999999999994 - type: ndcg_at_3 value: 23.419999999999998 - type: ndcg_at_5 value: 24.927 - type: precision_at_1 value: 19.649 - type: precision_at_10 value: 4.7010000000000005 - type: precision_at_100 value: 0.8130000000000001 - type: precision_at_1000 value: 0.124 - type: precision_at_3 value: 10.735999999999999 - type: precision_at_5 value: 7.591 - type: recall_at_1 value: 16.659 - type: recall_at_10 value: 35.721000000000004 - type: recall_at_100 value: 56.43 - type: recall_at_1000 value: 78.464 - type: recall_at_3 value: 25.878 - type: recall_at_5 value: 29.731999999999996 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackUnixRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 24.309 - type: map_at_10 value: 31.990000000000002 - type: map_at_100 value: 32.895 - type: map_at_1000 value: 33.0 - type: map_at_3 value: 29.848999999999997 - type: map_at_5 value: 30.942999999999998 - type: mrr_at_1 value: 28.638 - type: mrr_at_10 value: 36.036 - type: mrr_at_100 value: 36.787 - type: mrr_at_1000 value: 36.855 - type: mrr_at_3 value: 34.08 - type: mrr_at_5 value: 35.073 - type: ndcg_at_1 value: 28.638 - type: ndcg_at_10 value: 36.588 - type: ndcg_at_100 value: 41.152 - type: ndcg_at_1000 value: 43.769999999999996 - type: ndcg_at_3 value: 32.632 - type: ndcg_at_5 value: 34.249 - type: precision_at_1 value: 28.638 - type: precision_at_10 value: 5.942 - type: precision_at_100 value: 0.9249999999999999 - type: precision_at_1000 value: 0.127 - type: precision_at_3 value: 14.582999999999998 - type: precision_at_5 value: 9.944 - type: recall_at_1 value: 24.309 - type: recall_at_10 value: 46.725 - type: recall_at_100 value: 67.11 - type: recall_at_1000 value: 85.91499999999999 - type: recall_at_3 value: 35.72 - type: recall_at_5 value: 39.854 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWebmastersRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 22.997999999999998 - type: map_at_10 value: 30.564000000000004 - type: map_at_100 value: 32.06 - type: map_at_1000 value: 32.282 - type: map_at_3 value: 28.12 - type: map_at_5 value: 29.395 - type: mrr_at_1 value: 27.075 - type: mrr_at_10 value: 34.510999999999996 - type: mrr_at_100 value: 35.549 - type: mrr_at_1000 value: 35.616 - type: mrr_at_3 value: 32.444 - type: mrr_at_5 value: 33.589999999999996 - type: ndcg_at_1 value: 27.075 - type: ndcg_at_10 value: 35.582 - type: ndcg_at_100 value: 41.308 - type: ndcg_at_1000 value: 44.385999999999996 - type: ndcg_at_3 value: 31.467 - type: ndcg_at_5 value: 33.189 - type: precision_at_1 value: 27.075 - type: precision_at_10 value: 6.68 - type: precision_at_100 value: 1.427 - type: precision_at_1000 value: 0.231 - type: precision_at_3 value: 14.625 - type: precision_at_5 value: 10.356 - type: recall_at_1 value: 22.997999999999998 - type: recall_at_10 value: 45.196 - type: recall_at_100 value: 70.319 - type: recall_at_1000 value: 90.766 - type: recall_at_3 value: 33.487 - type: recall_at_5 value: 38.297 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWordpressRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 20.961 - type: map_at_10 value: 27.58 - type: map_at_100 value: 28.542 - type: map_at_1000 value: 28.644 - type: map_at_3 value: 25.541000000000004 - type: map_at_5 value: 26.589000000000002 - type: mrr_at_1 value: 22.551 - type: mrr_at_10 value: 29.298999999999996 - type: mrr_at_100 value: 30.17 - type: mrr_at_1000 value: 30.248 - type: mrr_at_3 value: 27.542 - type: mrr_at_5 value: 28.392 - type: ndcg_at_1 value: 22.551 - type: ndcg_at_10 value: 31.55 - type: ndcg_at_100 value: 36.295 - type: ndcg_at_1000 value: 38.964 - type: ndcg_at_3 value: 27.663 - type: ndcg_at_5 value: 29.321 - type: precision_at_1 value: 22.551 - type: precision_at_10 value: 4.88 - type: precision_at_100 value: 0.7779999999999999 - type: precision_at_1000 value: 0.11199999999999999 - type: precision_at_3 value: 11.83 - type: precision_at_5 value: 8.17 - type: recall_at_1 value: 20.961 - type: recall_at_10 value: 42.07 - type: recall_at_100 value: 63.982000000000006 - type: recall_at_1000 value: 83.889 - type: recall_at_3 value: 31.445 - type: recall_at_5 value: 35.410000000000004 - task: type: Retrieval dataset: type: climate-fever name: MTEB ClimateFEVER config: default split: test revision: None metrics: - type: map_at_1 value: 11.314 - type: map_at_10 value: 18.983 - type: map_at_100 value: 20.851 - type: map_at_1000 value: 21.066 - type: map_at_3 value: 16.014 - type: map_at_5 value: 17.569000000000003 - type: mrr_at_1 value: 25.277 - type: mrr_at_10 value: 36.657000000000004 - type: mrr_at_100 value: 37.646 - type: mrr_at_1000 value: 37.686 - type: mrr_at_3 value: 33.17 - type: mrr_at_5 value: 35.232 - type: ndcg_at_1 value: 25.277 - type: ndcg_at_10 value: 27.011000000000003 - type: ndcg_at_100 value: 34.418 - type: ndcg_at_1000 value: 38.089 - type: ndcg_at_3 value: 22.026 - type: ndcg_at_5 value: 23.866 - type: precision_at_1 value: 25.277 - type: precision_at_10 value: 8.397 - type: precision_at_100 value: 1.6320000000000001 - type: precision_at_1000 value: 0.22999999999999998 - type: precision_at_3 value: 16.156000000000002 - type: precision_at_5 value: 12.612000000000002 - type: recall_at_1 value: 11.314 - type: recall_at_10 value: 32.474 - type: recall_at_100 value: 57.926 - type: recall_at_1000 value: 78.387 - type: recall_at_3 value: 20.415 - type: recall_at_5 value: 25.407999999999998 - task: type: Retrieval dataset: type: dbpedia-entity name: MTEB DBPedia config: default split: test revision: None metrics: - type: map_at_1 value: 8.835999999999999 - type: map_at_10 value: 19.73 - type: map_at_100 value: 28.011000000000003 - type: map_at_1000 value: 29.519000000000002 - type: map_at_3 value: 14.249 - type: map_at_5 value: 16.472 - type: mrr_at_1 value: 67.0 - type: mrr_at_10 value: 74.632 - type: mrr_at_100 value: 74.97200000000001 - type: mrr_at_1000 value: 74.97500000000001 - type: mrr_at_3 value: 72.958 - type: mrr_at_5 value: 73.908 - type: ndcg_at_1 value: 55.875 - type: ndcg_at_10 value: 42.071999999999996 - type: ndcg_at_100 value: 46.091 - type: ndcg_at_1000 value: 52.737 - type: ndcg_at_3 value: 47.079 - type: ndcg_at_5 value: 43.788 - type: precision_at_1 value: 67.0 - type: precision_at_10 value: 33.45 - type: precision_at_100 value: 10.633 - type: precision_at_1000 value: 2.067 - type: precision_at_3 value: 49.583 - type: precision_at_5 value: 41.25 - type: recall_at_1 value: 8.835999999999999 - type: recall_at_10 value: 24.872 - type: recall_at_100 value: 51.427 - type: recall_at_1000 value: 72.17099999999999 - type: recall_at_3 value: 15.631999999999998 - type: recall_at_5 value: 18.956 - task: type: Classification dataset: type: mteb/emotion name: MTEB EmotionClassification config: default split: test revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 metrics: - type: accuracy value: 48.80500000000001 - type: f1 value: 43.91955883597831 - task: type: Retrieval dataset: type: fever name: MTEB FEVER config: default split: test revision: None metrics: - type: map_at_1 value: 61.480999999999995 - type: map_at_10 value: 72.162 - type: map_at_100 value: 72.487 - type: map_at_1000 value: 72.504 - type: map_at_3 value: 70.354 - type: map_at_5 value: 71.509 - type: mrr_at_1 value: 66.262 - type: mrr_at_10 value: 76.605 - type: mrr_at_100 value: 76.833 - type: mrr_at_1000 value: 76.839 - type: mrr_at_3 value: 74.977 - type: mrr_at_5 value: 76.06 - type: ndcg_at_1 value: 66.262 - type: ndcg_at_10 value: 77.323 - type: ndcg_at_100 value: 78.685 - type: ndcg_at_1000 value: 79.032 - type: ndcg_at_3 value: 74.015 - type: ndcg_at_5 value: 75.916 - type: precision_at_1 value: 66.262 - type: precision_at_10 value: 9.757 - type: precision_at_100 value: 1.059 - type: precision_at_1000 value: 0.11100000000000002 - type: precision_at_3 value: 29.032999999999998 - type: precision_at_5 value: 18.5 - type: recall_at_1 value: 61.480999999999995 - type: recall_at_10 value: 88.878 - type: recall_at_100 value: 94.719 - type: recall_at_1000 value: 97.066 - type: recall_at_3 value: 79.95100000000001 - type: recall_at_5 value: 84.691 - task: type: Retrieval dataset: type: fiqa name: MTEB FiQA2018 config: default split: test revision: None metrics: - type: map_at_1 value: 19.925 - type: map_at_10 value: 31.621 - type: map_at_100 value: 33.282000000000004 - type: map_at_1000 value: 33.455 - type: map_at_3 value: 27.504 - type: map_at_5 value: 29.921999999999997 - type: mrr_at_1 value: 39.660000000000004 - type: mrr_at_10 value: 47.366 - type: mrr_at_100 value: 48.179 - type: mrr_at_1000 value: 48.219 - type: mrr_at_3 value: 45.062000000000005 - type: mrr_at_5 value: 46.404 - type: ndcg_at_1 value: 39.660000000000004 - type: ndcg_at_10 value: 39.019 - type: ndcg_at_100 value: 45.286 - type: ndcg_at_1000 value: 48.370000000000005 - type: ndcg_at_3 value: 35.421 - type: ndcg_at_5 value: 36.767 - type: precision_at_1 value: 39.660000000000004 - type: precision_at_10 value: 10.494 - type: precision_at_100 value: 1.7069999999999999 - type: precision_at_1000 value: 0.22599999999999998 - type: precision_at_3 value: 23.200000000000003 - type: precision_at_5 value: 17.253 - type: recall_at_1 value: 19.925 - type: recall_at_10 value: 45.48 - type: recall_at_100 value: 68.585 - type: recall_at_1000 value: 87.128 - type: recall_at_3 value: 31.913000000000004 - type: recall_at_5 value: 38.107 - task: type: Retrieval dataset: type: hotpotqa name: MTEB HotpotQA config: default split: test revision: None metrics: - type: map_at_1 value: 37.961 - type: map_at_10 value: 55.010000000000005 - type: map_at_100 value: 55.896 - type: map_at_1000 value: 55.962 - type: map_at_3 value: 52.03 - type: map_at_5 value: 53.866 - type: mrr_at_1 value: 75.922 - type: mrr_at_10 value: 81.655 - type: mrr_at_100 value: 81.879 - type: mrr_at_1000 value: 81.889 - type: mrr_at_3 value: 80.657 - type: mrr_at_5 value: 81.291 - type: ndcg_at_1 value: 75.922 - type: ndcg_at_10 value: 64.119 - type: ndcg_at_100 value: 67.25 - type: ndcg_at_1000 value: 68.55499999999999 - type: ndcg_at_3 value: 59.792 - type: ndcg_at_5 value: 62.165000000000006 - type: precision_at_1 value: 75.922 - type: precision_at_10 value: 13.155 - type: precision_at_100 value: 1.5599999999999998 - type: precision_at_1000 value: 0.173 - type: precision_at_3 value: 37.461 - type: precision_at_5 value: 24.351 - type: recall_at_1 value: 37.961 - type: recall_at_10 value: 65.77300000000001 - type: recall_at_100 value: 78.015 - type: recall_at_1000 value: 86.685 - type: recall_at_3 value: 56.192 - type: recall_at_5 value: 60.878 - task: type: Classification dataset: type: mteb/imdb name: MTEB ImdbClassification config: default split: test revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 metrics: - type: accuracy value: 83.7804 - type: ap value: 78.89508987851809 - type: f1 value: 83.72392373438922 - task: type: Retrieval dataset: type: msmarco name: MTEB MSMARCO config: default split: dev revision: None metrics: - type: map_at_1 value: 23.807000000000002 - type: map_at_10 value: 36.411 - type: map_at_100 value: 37.574000000000005 - type: map_at_1000 value: 37.618 - type: map_at_3 value: 32.653 - type: map_at_5 value: 34.902 - type: mrr_at_1 value: 24.499000000000002 - type: mrr_at_10 value: 37.045 - type: mrr_at_100 value: 38.135999999999996 - type: mrr_at_1000 value: 38.175 - type: mrr_at_3 value: 33.326 - type: mrr_at_5 value: 35.561 - type: ndcg_at_1 value: 24.512999999999998 - type: ndcg_at_10 value: 43.328 - type: ndcg_at_100 value: 48.779 - type: ndcg_at_1000 value: 49.897999999999996 - type: ndcg_at_3 value: 35.713 - type: ndcg_at_5 value: 39.729 - type: precision_at_1 value: 24.512999999999998 - type: precision_at_10 value: 6.7379999999999995 - type: precision_at_100 value: 0.9450000000000001 - type: precision_at_1000 value: 0.104 - type: precision_at_3 value: 15.196000000000002 - type: precision_at_5 value: 11.158 - type: recall_at_1 value: 23.807000000000002 - type: recall_at_10 value: 64.488 - type: recall_at_100 value: 89.386 - type: recall_at_1000 value: 97.968 - type: recall_at_3 value: 43.891000000000005 - type: recall_at_5 value: 53.535 - task: type: Classification dataset: type: mteb/mtop_domain name: MTEB MTOPDomainClassification (en) config: en split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics: - type: accuracy value: 93.47013223894209 - type: f1 value: 93.15020887152107 - task: type: Classification dataset: type: mteb/mtop_intent name: MTEB MTOPIntentClassification (en) config: en split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics: - type: accuracy value: 75.27131782945737 - type: f1 value: 58.45703758149779 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (en) config: en split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 72.76395427034298 - type: f1 value: 70.6084399610629 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (en) config: en split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 76.69804976462676 - type: f1 value: 76.61599181962723 - task: type: Clustering dataset: type: mteb/medrxiv-clustering-p2p name: MTEB MedrxivClusteringP2P config: default split: test revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 metrics: - type: v_measure value: 32.7253797676744 - task: type: Clustering dataset: type: mteb/medrxiv-clustering-s2s name: MTEB MedrxivClusteringS2S config: default split: test revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 metrics: - type: v_measure value: 30.547731924629424 - task: type: Reranking dataset: type: mteb/mind_small name: MTEB MindSmallReranking config: default split: test revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 metrics: - type: map value: 31.286918745183772 - type: mrr value: 32.47449315230336 - task: type: Retrieval dataset: type: nfcorpus name: MTEB NFCorpus config: default split: test revision: None metrics: - type: map_at_1 value: 5.894 - type: map_at_10 value: 13.405000000000001 - type: map_at_100 value: 16.586000000000002 - type: map_at_1000 value: 17.919 - type: map_at_3 value: 10.066 - type: map_at_5 value: 11.679 - type: mrr_at_1 value: 45.201 - type: mrr_at_10 value: 54.018 - type: mrr_at_100 value: 54.581999999999994 - type: mrr_at_1000 value: 54.623 - type: mrr_at_3 value: 51.6 - type: mrr_at_5 value: 53.473000000000006 - type: ndcg_at_1 value: 43.189 - type: ndcg_at_10 value: 35.306 - type: ndcg_at_100 value: 31.505 - type: ndcg_at_1000 value: 39.991 - type: ndcg_at_3 value: 41.108 - type: ndcg_at_5 value: 39.039 - type: precision_at_1 value: 44.582 - type: precision_at_10 value: 26.161 - type: precision_at_100 value: 7.867 - type: precision_at_1000 value: 2.043 - type: precision_at_3 value: 39.112 - type: precision_at_5 value: 34.18 - type: recall_at_1 value: 5.894 - type: recall_at_10 value: 16.88 - type: recall_at_100 value: 30.671 - type: recall_at_1000 value: 61.42999999999999 - type: recall_at_3 value: 11.022 - type: recall_at_5 value: 13.697999999999999 - task: type: Retrieval dataset: type: nq name: MTEB NQ config: default split: test revision: None metrics: - type: map_at_1 value: 38.440999999999995 - type: map_at_10 value: 54.187 - type: map_at_100 value: 55.022000000000006 - type: map_at_1000 value: 55.044000000000004 - type: map_at_3 value: 50.174 - type: map_at_5 value: 52.61 - type: mrr_at_1 value: 42.903000000000006 - type: mrr_at_10 value: 56.699 - type: mrr_at_100 value: 57.31 - type: mrr_at_1000 value: 57.325 - type: mrr_at_3 value: 53.63099999999999 - type: mrr_at_5 value: 55.596000000000004 - type: ndcg_at_1 value: 42.903000000000006 - type: ndcg_at_10 value: 61.434 - type: ndcg_at_100 value: 64.852 - type: ndcg_at_1000 value: 65.36 - type: ndcg_at_3 value: 54.193000000000005 - type: ndcg_at_5 value: 58.15 - type: precision_at_1 value: 42.903000000000006 - type: precision_at_10 value: 9.623 - type: precision_at_100 value: 1.1560000000000001 - type: precision_at_1000 value: 0.12 - type: precision_at_3 value: 24.034 - type: precision_at_5 value: 16.779 - type: recall_at_1 value: 38.440999999999995 - type: recall_at_10 value: 80.72399999999999 - type: recall_at_100 value: 95.329 - type: recall_at_1000 value: 99.059 - type: recall_at_3 value: 62.343 - type: recall_at_5 value: 71.304 - task: type: Retrieval dataset: type: quora name: MTEB QuoraRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 70.85000000000001 - type: map_at_10 value: 84.54 - type: map_at_100 value: 85.148 - type: map_at_1000 value: 85.168 - type: map_at_3 value: 81.631 - type: map_at_5 value: 83.45700000000001 - type: mrr_at_1 value: 81.58 - type: mrr_at_10 value: 87.732 - type: mrr_at_100 value: 87.825 - type: mrr_at_1000 value: 87.82600000000001 - type: mrr_at_3 value: 86.783 - type: mrr_at_5 value: 87.437 - type: ndcg_at_1 value: 81.56 - type: ndcg_at_10 value: 88.32900000000001 - type: ndcg_at_100 value: 89.513 - type: ndcg_at_1000 value: 89.63799999999999 - type: ndcg_at_3 value: 85.51100000000001 - type: ndcg_at_5 value: 87.062 - type: precision_at_1 value: 81.56 - type: precision_at_10 value: 13.349 - type: precision_at_100 value: 1.518 - type: precision_at_1000 value: 0.156 - type: precision_at_3 value: 37.293 - type: precision_at_5 value: 24.502 - type: recall_at_1 value: 70.85000000000001 - type: recall_at_10 value: 95.351 - type: recall_at_100 value: 99.405 - type: recall_at_1000 value: 99.958 - type: recall_at_3 value: 87.184 - type: recall_at_5 value: 91.625 - task: type: Clustering dataset: type: mteb/reddit-clustering name: MTEB RedditClustering config: default split: test revision: 24640382cdbf8abc73003fb0fa6d111a705499eb metrics: - type: v_measure value: 56.81818576893834 - task: type: Clustering dataset: type: mteb/reddit-clustering-p2p name: MTEB RedditClusteringP2P config: default split: test revision: 282350215ef01743dc01b456c7f5241fa8937f16 metrics: - type: v_measure value: 61.57033658868022 - task: type: Retrieval dataset: type: scidocs name: MTEB SCIDOCS config: default split: test revision: None metrics: - type: map_at_1 value: 4.468 - type: map_at_10 value: 11.109 - type: map_at_100 value: 12.921 - type: map_at_1000 value: 13.187999999999999 - type: map_at_3 value: 8.094999999999999 - type: map_at_5 value: 9.664 - type: mrr_at_1 value: 22.1 - type: mrr_at_10 value: 32.482 - type: mrr_at_100 value: 33.558 - type: mrr_at_1000 value: 33.623999999999995 - type: mrr_at_3 value: 29.25 - type: mrr_at_5 value: 31.080000000000002 - type: ndcg_at_1 value: 22.1 - type: ndcg_at_10 value: 18.695999999999998 - type: ndcg_at_100 value: 25.749 - type: ndcg_at_1000 value: 30.711 - type: ndcg_at_3 value: 17.974 - type: ndcg_at_5 value: 15.684000000000001 - type: precision_at_1 value: 22.1 - type: precision_at_10 value: 9.56 - type: precision_at_100 value: 1.966 - type: precision_at_1000 value: 0.316 - type: precision_at_3 value: 16.667 - type: precision_at_5 value: 13.68 - type: recall_at_1 value: 4.468 - type: recall_at_10 value: 19.373 - type: recall_at_100 value: 39.853 - type: recall_at_1000 value: 64.118 - type: recall_at_3 value: 10.133000000000001 - type: recall_at_5 value: 13.877999999999998 - task: type: STS dataset: type: mteb/sickr-sts name: MTEB SICK-R config: default split: test revision: a6ea5a8cab320b040a23452cc28066d9beae2cee metrics: - type: cos_sim_pearson value: 80.11452150923512 - type: cos_sim_spearman value: 77.3007421887329 - type: euclidean_pearson value: 78.2493681078981 - type: euclidean_spearman value: 77.3007432741821 - type: manhattan_pearson value: 78.19716818242554 - type: manhattan_spearman value: 77.26439033199102 - task: type: STS dataset: type: mteb/sts12-sts name: MTEB STS12 config: default split: test revision: a0d554a64d88156834ff5ae9920b964011b16384 metrics: - type: cos_sim_pearson value: 82.70293570563516 - type: cos_sim_spearman value: 77.97040896962338 - type: euclidean_pearson value: 77.98827330337348 - type: euclidean_spearman value: 77.9704358930525 - type: manhattan_pearson value: 78.06991702207395 - type: manhattan_spearman value: 78.03857843100195 - task: type: STS dataset: type: mteb/sts13-sts name: MTEB STS13 config: default split: test revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca metrics: - type: cos_sim_pearson value: 77.81236960157503 - type: cos_sim_spearman value: 79.38801416063187 - type: euclidean_pearson value: 79.35003045476847 - type: euclidean_spearman value: 79.38797289536578 - type: manhattan_pearson value: 79.33155563344724 - type: manhattan_spearman value: 79.3858955436803 - task: type: STS dataset: type: mteb/sts14-sts name: MTEB STS14 config: default split: test revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 metrics: - type: cos_sim_pearson value: 77.35604880089507 - type: cos_sim_spearman value: 78.17327332594571 - type: euclidean_pearson value: 77.30302038209295 - type: euclidean_spearman value: 78.17327332594571 - type: manhattan_pearson value: 77.31323781935417 - type: manhattan_spearman value: 78.20141256686921 - task: type: STS dataset: type: mteb/sts15-sts name: MTEB STS15 config: default split: test revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 metrics: - type: cos_sim_pearson value: 84.29348597583 - type: cos_sim_spearman value: 85.50877410088334 - type: euclidean_pearson value: 85.22367284169081 - type: euclidean_spearman value: 85.50877410088334 - type: manhattan_pearson value: 85.17979979737612 - type: manhattan_spearman value: 85.46459282596254 - task: type: STS dataset: type: mteb/sts16-sts name: MTEB STS16 config: default split: test revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 metrics: - type: cos_sim_pearson value: 83.16190794761513 - type: cos_sim_spearman value: 84.94610605287254 - type: euclidean_pearson value: 83.95587174131369 - type: euclidean_spearman value: 84.94610605287254 - type: manhattan_pearson value: 83.99025745366798 - type: manhattan_spearman value: 84.98123107148953 - 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: 85.3047190687711 - type: cos_sim_spearman value: 85.86642469958113 - type: euclidean_pearson value: 86.74377658528041 - type: euclidean_spearman value: 85.86642469958113 - type: manhattan_pearson value: 86.56967885987439 - type: manhattan_spearman value: 85.63613272583275 - task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (en) config: en split: test revision: eea2b4fe26a775864c896887d910b76a8098ad3f metrics: - type: cos_sim_pearson value: 64.8298932792099 - type: cos_sim_spearman value: 64.27626667878636 - type: euclidean_pearson value: 66.01603861201576 - type: euclidean_spearman value: 64.27626667878636 - type: manhattan_pearson value: 66.31232809448106 - type: manhattan_spearman value: 64.46190921631559 - task: type: STS dataset: type: mteb/stsbenchmark-sts name: MTEB STSBenchmark config: default split: test revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 metrics: - type: cos_sim_pearson value: 82.73696291316243 - type: cos_sim_spearman value: 83.41508337893958 - type: euclidean_pearson value: 82.8827053024064 - type: euclidean_spearman value: 83.41508337893958 - type: manhattan_pearson value: 82.85613329045803 - type: manhattan_spearman value: 83.40522047443645 - task: type: Reranking dataset: type: mteb/scidocs-reranking name: MTEB SciDocsRR config: default split: test revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab metrics: - type: map value: 75.51490079179645 - type: mrr value: 92.6809655486126 - task: type: Retrieval dataset: type: scifact name: MTEB SciFact config: default split: test revision: None metrics: - type: map_at_1 value: 58.594 - type: map_at_10 value: 67.208 - type: map_at_100 value: 67.702 - type: map_at_1000 value: 67.73 - type: map_at_3 value: 64.815 - type: map_at_5 value: 65.946 - type: mrr_at_1 value: 61.667 - type: mrr_at_10 value: 68.52000000000001 - type: mrr_at_100 value: 68.888 - type: mrr_at_1000 value: 68.911 - type: mrr_at_3 value: 66.833 - type: mrr_at_5 value: 67.617 - type: ndcg_at_1 value: 61.667 - type: ndcg_at_10 value: 71.511 - type: ndcg_at_100 value: 73.765 - type: ndcg_at_1000 value: 74.40299999999999 - type: ndcg_at_3 value: 67.411 - type: ndcg_at_5 value: 68.88 - type: precision_at_1 value: 61.667 - type: precision_at_10 value: 9.433 - 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: 16.866999999999997 - type: recall_at_1 value: 58.594 - type: recall_at_10 value: 83.439 - type: recall_at_100 value: 94.1 - type: recall_at_1000 value: 99.0 - type: recall_at_3 value: 71.922 - type: recall_at_5 value: 75.678 - task: type: PairClassification dataset: type: mteb/sprintduplicatequestions-pairclassification name: MTEB SprintDuplicateQuestions config: default split: test revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 metrics: - type: cos_sim_accuracy value: 99.7990099009901 - type: cos_sim_ap value: 94.8316184070519 - type: cos_sim_f1 value: 89.75265017667844 - type: cos_sim_precision value: 90.62181447502549 - type: cos_sim_recall value: 88.9 - type: dot_accuracy value: 99.7990099009901 - type: dot_ap value: 94.831611518794 - type: dot_f1 value: 89.75265017667844 - type: dot_precision value: 90.62181447502549 - type: dot_recall value: 88.9 - type: euclidean_accuracy value: 99.7990099009901 - type: euclidean_ap value: 94.83161335144017 - type: euclidean_f1 value: 89.75265017667844 - type: euclidean_precision value: 90.62181447502549 - type: euclidean_recall value: 88.9 - type: manhattan_accuracy value: 99.8 - type: manhattan_ap value: 94.84210829841739 - type: manhattan_f1 value: 89.60905349794238 - type: manhattan_precision value: 92.26694915254238 - type: manhattan_recall value: 87.1 - type: max_accuracy value: 99.8 - type: max_ap value: 94.84210829841739 - type: max_f1 value: 89.75265017667844 - task: type: Clustering dataset: type: mteb/stackexchange-clustering name: MTEB StackExchangeClustering config: default split: test revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 metrics: - type: v_measure value: 63.18343792633894 - task: type: Clustering dataset: type: mteb/stackexchange-clustering-p2p name: MTEB StackExchangeClusteringP2P config: default split: test revision: 815ca46b2622cec33ccafc3735d572c266efdb44 metrics: - type: v_measure value: 33.50944549814364 - task: type: Reranking dataset: type: mteb/stackoverflowdupquestions-reranking name: MTEB StackOverflowDupQuestions config: default split: test revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 metrics: - type: map value: 48.89100016028111 - type: mrr value: 49.607630931160344 - task: type: Summarization dataset: type: mteb/summeval name: MTEB SummEval config: default split: test revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c metrics: - type: cos_sim_pearson value: 30.628145384101522 - type: cos_sim_spearman value: 31.275306930726675 - type: dot_pearson value: 30.62814883550051 - type: dot_spearman value: 31.275306930726675 - task: type: Retrieval dataset: type: trec-covid name: MTEB TRECCOVID config: default split: test revision: None metrics: - type: map_at_1 value: 0.26 - type: map_at_10 value: 2.163 - type: map_at_100 value: 12.29 - type: map_at_1000 value: 29.221999999999998 - type: map_at_3 value: 0.729 - type: map_at_5 value: 1.161 - type: mrr_at_1 value: 96.0 - type: mrr_at_10 value: 98.0 - type: mrr_at_100 value: 98.0 - type: mrr_at_1000 value: 98.0 - type: mrr_at_3 value: 98.0 - type: mrr_at_5 value: 98.0 - type: ndcg_at_1 value: 89.0 - type: ndcg_at_10 value: 82.312 - type: ndcg_at_100 value: 61.971 - type: ndcg_at_1000 value: 54.065 - type: ndcg_at_3 value: 87.87700000000001 - type: ndcg_at_5 value: 85.475 - type: precision_at_1 value: 96.0 - type: precision_at_10 value: 87.4 - type: precision_at_100 value: 64.02 - type: precision_at_1000 value: 24.093999999999998 - type: precision_at_3 value: 94.0 - type: precision_at_5 value: 90.8 - type: recall_at_1 value: 0.26 - type: recall_at_10 value: 2.302 - type: recall_at_100 value: 15.148 - type: recall_at_1000 value: 50.55 - type: recall_at_3 value: 0.744 - type: recall_at_5 value: 1.198 - task: type: Retrieval dataset: type: webis-touche2020 name: MTEB Touche2020 config: default split: test revision: None metrics: - type: map_at_1 value: 2.217 - type: map_at_10 value: 11.378 - type: map_at_100 value: 18.022 - type: map_at_1000 value: 19.544 - type: map_at_3 value: 6.079 - type: map_at_5 value: 8.559 - type: mrr_at_1 value: 28.571 - type: mrr_at_10 value: 48.423 - type: mrr_at_100 value: 49.028 - type: mrr_at_1000 value: 49.028 - type: mrr_at_3 value: 44.897999999999996 - type: mrr_at_5 value: 46.531 - type: ndcg_at_1 value: 25.509999999999998 - type: ndcg_at_10 value: 27.860000000000003 - type: ndcg_at_100 value: 39.34 - type: ndcg_at_1000 value: 50.21 - type: ndcg_at_3 value: 30.968 - type: ndcg_at_5 value: 29.541 - type: precision_at_1 value: 28.571 - type: precision_at_10 value: 25.918000000000003 - type: precision_at_100 value: 8.184 - type: precision_at_1000 value: 1.545 - type: precision_at_3 value: 35.374 - type: precision_at_5 value: 31.837 - type: recall_at_1 value: 2.217 - type: recall_at_10 value: 18.511 - type: recall_at_100 value: 50.178 - type: recall_at_1000 value: 83.07600000000001 - type: recall_at_3 value: 7.811999999999999 - type: recall_at_5 value: 11.684 - task: type: Classification dataset: type: mteb/toxic_conversations_50k name: MTEB ToxicConversationsClassification config: default split: test revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c metrics: - type: accuracy value: 71.386 - type: ap value: 14.58573366644018 - type: f1 value: 55.0170316975105 - task: type: Classification dataset: type: mteb/tweet_sentiment_extraction name: MTEB TweetSentimentExtractionClassification config: default split: test revision: d604517c81ca91fe16a244d1248fc021f9ecee7a metrics: - type: accuracy value: 60.868704018109796 - type: f1 value: 61.175908652496624 - task: type: Clustering dataset: type: mteb/twentynewsgroups-clustering name: MTEB TwentyNewsgroupsClustering config: default split: test revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 metrics: - type: v_measure value: 48.72082824812323 - task: type: PairClassification dataset: type: mteb/twittersemeval2015-pairclassification name: MTEB TwitterSemEval2015 config: default split: test revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 metrics: - type: cos_sim_accuracy value: 85.43839780652083 - type: cos_sim_ap value: 72.55258980537292 - type: cos_sim_f1 value: 66.4145419055752 - type: cos_sim_precision value: 61.765373269798054 - type: cos_sim_recall value: 71.82058047493403 - type: dot_accuracy value: 85.43839780652083 - type: dot_ap value: 72.55256370197756 - type: dot_f1 value: 66.4145419055752 - type: dot_precision value: 61.765373269798054 - type: dot_recall value: 71.82058047493403 - type: euclidean_accuracy value: 85.43839780652083 - type: euclidean_ap value: 72.55259011957311 - type: euclidean_f1 value: 66.4145419055752 - type: euclidean_precision value: 61.765373269798054 - type: euclidean_recall value: 71.82058047493403 - type: manhattan_accuracy value: 85.40263455921799 - type: manhattan_ap value: 72.47856062032 - type: manhattan_f1 value: 66.39413249969942 - type: manhattan_precision value: 60.989617848464775 - type: manhattan_recall value: 72.84960422163589 - type: max_accuracy value: 85.43839780652083 - type: max_ap value: 72.55259011957311 - type: max_f1 value: 66.4145419055752 - task: type: PairClassification dataset: type: mteb/twitterurlcorpus-pairclassification name: MTEB TwitterURLCorpus config: default split: test revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf metrics: - type: cos_sim_accuracy value: 89.24981565568363 - type: cos_sim_ap value: 86.38437585690401 - type: cos_sim_f1 value: 78.79039565086076 - type: cos_sim_precision value: 77.29629629629629 - type: cos_sim_recall value: 80.34339390206344 - type: dot_accuracy value: 89.24981565568363 - type: dot_ap value: 86.38437587564587 - type: dot_f1 value: 78.79039565086076 - type: dot_precision value: 77.29629629629629 - type: dot_recall value: 80.34339390206344 - type: euclidean_accuracy value: 89.24981565568363 - type: euclidean_ap value: 86.38437691024106 - type: euclidean_f1 value: 78.79039565086076 - type: euclidean_precision value: 77.29629629629629 - type: euclidean_recall value: 80.34339390206344 - type: manhattan_accuracy value: 89.25563705514806 - type: manhattan_ap value: 86.35729146774388 - type: manhattan_f1 value: 78.7238059278837 - type: manhattan_precision value: 77.23938653034007 - type: manhattan_recall value: 80.26639975361873 - type: max_accuracy value: 89.25563705514806 - type: max_ap value: 86.38437691024106 - type: max_f1 value: 78.79039565086076 --- # nomic-embed-text-v1-ablated: A Reproducible Long Context (8192) Text Embedder `nomic-embed-text-v1-ablated` is 8192 context length text encoder. This is a checkpoint trained after modifying the training dataset to be different from the dataset used to train our [final model](https://huggingface.co/nomic-ai/nomic-embed-text-v1). The purpose of releasing this checkpoint is to understand the impact that subsets of our training data had on model outcomes. This release is part of our commitment to open-source training artifacts from our Nomic Embed Text tech report [here](https://arxiv.org/pdf/2402.01613) If you want to use a model to extract embeddings, we suggest using [nomic-embed-text-v1](https://huggingface.co/nomic-ai/nomic-embed-text-v1). # Join the Nomic Community - Nomic: [https://nomic.ai](https://nomic.ai) - Discord: [https://discord.gg/myY5YDR8z8](https://discord.gg/myY5YDR8z8) - Twitter: [https://twitter.com/nomic_ai](https://twitter.com/nomic_ai)