--- library_name: sentence-transformers pipeline_tag: sentence-similarity tags: - feature-extraction - sentence-similarity - mteb - transformers - transformers.js license: apache-2.0 language: - en inference: false 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: 76.98507462686568 - type: ap value: 39.47222193126652 - type: f1 value: 70.5923611893019 - task: type: Classification dataset: type: mteb/amazon_polarity name: MTEB AmazonPolarityClassification config: default split: test revision: e2d317d38cd51312af73b3d32a06d1a08b442046 metrics: - type: accuracy value: 87.540175 - type: ap value: 83.16128207188409 - type: f1 value: 87.5231988227265 - task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (en) config: en split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics: - type: accuracy value: 46.80799999999999 - type: f1 value: 46.2632547445265 - task: type: Retrieval dataset: type: arguana name: MTEB ArguAna config: default split: test revision: None metrics: - type: map_at_1 value: 30.583 - type: map_at_10 value: 46.17 - type: map_at_100 value: 47.115 - type: map_at_1000 value: 47.121 - type: map_at_3 value: 41.489 - type: map_at_5 value: 44.046 - type: mrr_at_1 value: 30.939 - type: mrr_at_10 value: 46.289 - type: mrr_at_100 value: 47.241 - type: mrr_at_1000 value: 47.247 - type: mrr_at_3 value: 41.596 - type: mrr_at_5 value: 44.149 - type: ndcg_at_1 value: 30.583 - type: ndcg_at_10 value: 54.812000000000005 - type: ndcg_at_100 value: 58.605 - type: ndcg_at_1000 value: 58.753 - type: ndcg_at_3 value: 45.095 - type: ndcg_at_5 value: 49.744 - type: precision_at_1 value: 30.583 - type: precision_at_10 value: 8.243 - type: precision_at_100 value: 0.984 - type: precision_at_1000 value: 0.1 - type: precision_at_3 value: 18.516 - type: precision_at_5 value: 13.385 - type: recall_at_1 value: 30.583 - type: recall_at_10 value: 82.432 - type: recall_at_100 value: 98.43499999999999 - type: recall_at_1000 value: 99.57300000000001 - type: recall_at_3 value: 55.547999999999995 - type: recall_at_5 value: 66.927 - task: type: Clustering dataset: type: mteb/arxiv-clustering-p2p name: MTEB ArxivClusteringP2P config: default split: test revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d metrics: - type: v_measure value: 45.17830107652425 - task: type: Clustering dataset: type: mteb/arxiv-clustering-s2s name: MTEB ArxivClusteringS2S config: default split: test revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 metrics: - type: v_measure value: 35.90561364087807 - task: type: Reranking dataset: type: mteb/askubuntudupquestions-reranking name: MTEB AskUbuntuDupQuestions config: default split: test revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 metrics: - type: map value: 59.57222651819297 - type: mrr value: 73.19241085169062 - task: type: STS dataset: type: mteb/biosses-sts name: MTEB BIOSSES config: default split: test revision: d3fb88f8f02e40887cd149695127462bbcf29b4a metrics: - type: cos_sim_pearson value: 89.55181686367382 - type: cos_sim_spearman value: 87.18933606575987 - type: euclidean_pearson value: 87.78077503434338 - type: euclidean_spearman value: 87.18933606575987 - type: manhattan_pearson value: 87.75124980168601 - type: manhattan_spearman value: 86.79113422137638 - task: type: Classification dataset: type: mteb/banking77 name: MTEB Banking77Classification config: default split: test revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 metrics: - type: accuracy value: 81.09415584415585 - type: f1 value: 80.60088693212091 - task: type: Clustering dataset: type: mteb/biorxiv-clustering-p2p name: MTEB BiorxivClusteringP2P config: default split: test revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 metrics: - type: v_measure value: 36.57061229905462 - task: type: Clustering dataset: type: mteb/biorxiv-clustering-s2s name: MTEB BiorxivClusteringS2S config: default split: test revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 metrics: - type: v_measure value: 32.05342946608653 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackAndroidRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 34.376 - type: map_at_10 value: 45.214 - type: map_at_100 value: 46.635 - type: map_at_1000 value: 46.755 - type: map_at_3 value: 42.198 - type: map_at_5 value: 43.723 - type: mrr_at_1 value: 41.774 - type: mrr_at_10 value: 51.07000000000001 - type: mrr_at_100 value: 51.785000000000004 - type: mrr_at_1000 value: 51.824999999999996 - type: mrr_at_3 value: 48.808 - type: mrr_at_5 value: 50.11 - type: ndcg_at_1 value: 41.774 - type: ndcg_at_10 value: 51.105999999999995 - type: ndcg_at_100 value: 56.358 - type: ndcg_at_1000 value: 58.205 - type: ndcg_at_3 value: 46.965 - type: ndcg_at_5 value: 48.599 - type: precision_at_1 value: 41.774 - type: precision_at_10 value: 9.514 - type: precision_at_100 value: 1.508 - type: precision_at_1000 value: 0.196 - type: precision_at_3 value: 22.175 - type: precision_at_5 value: 15.508 - type: recall_at_1 value: 34.376 - type: recall_at_10 value: 61.748000000000005 - type: recall_at_100 value: 84.025 - type: recall_at_1000 value: 95.5 - type: recall_at_3 value: 49.378 - type: recall_at_5 value: 54.276 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackEnglishRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 32.394 - type: map_at_10 value: 42.707 - type: map_at_100 value: 43.893 - type: map_at_1000 value: 44.019000000000005 - type: map_at_3 value: 39.51 - type: map_at_5 value: 41.381 - type: mrr_at_1 value: 41.019 - type: mrr_at_10 value: 49.042 - type: mrr_at_100 value: 49.669000000000004 - type: mrr_at_1000 value: 49.712 - type: mrr_at_3 value: 46.921 - type: mrr_at_5 value: 48.192 - type: ndcg_at_1 value: 41.019 - type: ndcg_at_10 value: 48.46 - type: ndcg_at_100 value: 52.537 - type: ndcg_at_1000 value: 54.491 - type: ndcg_at_3 value: 44.232 - type: ndcg_at_5 value: 46.305 - type: precision_at_1 value: 41.019 - type: precision_at_10 value: 9.134 - type: precision_at_100 value: 1.422 - type: precision_at_1000 value: 0.188 - type: precision_at_3 value: 21.38 - type: precision_at_5 value: 15.096000000000002 - type: recall_at_1 value: 32.394 - type: recall_at_10 value: 58.11500000000001 - type: recall_at_100 value: 75.509 - type: recall_at_1000 value: 87.812 - type: recall_at_3 value: 45.476 - type: recall_at_5 value: 51.549 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGamingRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 43.47 - type: map_at_10 value: 55.871 - type: map_at_100 value: 56.745000000000005 - type: map_at_1000 value: 56.794 - type: map_at_3 value: 52.439 - type: map_at_5 value: 54.412000000000006 - type: mrr_at_1 value: 49.592000000000006 - type: mrr_at_10 value: 59.34199999999999 - type: mrr_at_100 value: 59.857000000000006 - type: mrr_at_1000 value: 59.88 - type: mrr_at_3 value: 56.897 - type: mrr_at_5 value: 58.339 - type: ndcg_at_1 value: 49.592000000000006 - type: ndcg_at_10 value: 61.67 - type: ndcg_at_100 value: 65.11099999999999 - type: ndcg_at_1000 value: 66.065 - type: ndcg_at_3 value: 56.071000000000005 - type: ndcg_at_5 value: 58.84700000000001 - type: precision_at_1 value: 49.592000000000006 - type: precision_at_10 value: 9.774 - type: precision_at_100 value: 1.2449999999999999 - type: precision_at_1000 value: 0.13699999999999998 - type: precision_at_3 value: 24.66 - type: precision_at_5 value: 16.878 - type: recall_at_1 value: 43.47 - type: recall_at_10 value: 75.387 - type: recall_at_100 value: 90.253 - type: recall_at_1000 value: 97.00800000000001 - type: recall_at_3 value: 60.616 - type: recall_at_5 value: 67.31899999999999 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGisRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 26.633000000000003 - type: map_at_10 value: 35.497 - type: map_at_100 value: 36.504 - type: map_at_1000 value: 36.574 - type: map_at_3 value: 33.115 - type: map_at_5 value: 34.536 - type: mrr_at_1 value: 28.927000000000003 - type: mrr_at_10 value: 37.778 - type: mrr_at_100 value: 38.634 - type: mrr_at_1000 value: 38.690000000000005 - type: mrr_at_3 value: 35.518 - type: mrr_at_5 value: 36.908 - type: ndcg_at_1 value: 28.927000000000003 - type: ndcg_at_10 value: 40.327 - type: ndcg_at_100 value: 45.321 - type: ndcg_at_1000 value: 47.214 - type: ndcg_at_3 value: 35.762 - type: ndcg_at_5 value: 38.153999999999996 - type: precision_at_1 value: 28.927000000000003 - type: precision_at_10 value: 6.045 - type: precision_at_100 value: 0.901 - type: precision_at_1000 value: 0.11 - type: precision_at_3 value: 15.140999999999998 - type: precision_at_5 value: 10.485999999999999 - type: recall_at_1 value: 26.633000000000003 - type: recall_at_10 value: 52.99 - type: recall_at_100 value: 76.086 - type: recall_at_1000 value: 90.46300000000001 - type: recall_at_3 value: 40.738 - type: recall_at_5 value: 46.449 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackMathematicaRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 17.521 - type: map_at_10 value: 25.130000000000003 - type: map_at_100 value: 26.176 - type: map_at_1000 value: 26.289 - type: map_at_3 value: 22.829 - type: map_at_5 value: 24.082 - type: mrr_at_1 value: 21.766 - type: mrr_at_10 value: 29.801 - type: mrr_at_100 value: 30.682 - type: mrr_at_1000 value: 30.75 - type: mrr_at_3 value: 27.633000000000003 - type: mrr_at_5 value: 28.858 - type: ndcg_at_1 value: 21.766 - type: ndcg_at_10 value: 30.026000000000003 - type: ndcg_at_100 value: 35.429 - type: ndcg_at_1000 value: 38.236 - type: ndcg_at_3 value: 25.968000000000004 - type: ndcg_at_5 value: 27.785 - type: precision_at_1 value: 21.766 - type: precision_at_10 value: 5.498 - type: precision_at_100 value: 0.9450000000000001 - type: precision_at_1000 value: 0.133 - type: precision_at_3 value: 12.687000000000001 - type: precision_at_5 value: 9.005 - type: recall_at_1 value: 17.521 - type: recall_at_10 value: 40.454 - type: recall_at_100 value: 64.828 - type: recall_at_1000 value: 84.83800000000001 - type: recall_at_3 value: 28.758 - type: recall_at_5 value: 33.617000000000004 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackPhysicsRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 30.564999999999998 - type: map_at_10 value: 40.664 - type: map_at_100 value: 41.995 - type: map_at_1000 value: 42.104 - type: map_at_3 value: 37.578 - type: map_at_5 value: 39.247 - type: mrr_at_1 value: 37.44 - type: mrr_at_10 value: 46.533 - type: mrr_at_100 value: 47.363 - type: mrr_at_1000 value: 47.405 - type: mrr_at_3 value: 44.224999999999994 - type: mrr_at_5 value: 45.549 - type: ndcg_at_1 value: 37.44 - type: ndcg_at_10 value: 46.574 - type: ndcg_at_100 value: 52.024 - type: ndcg_at_1000 value: 53.93900000000001 - type: ndcg_at_3 value: 41.722 - type: ndcg_at_5 value: 43.973 - type: precision_at_1 value: 37.44 - type: precision_at_10 value: 8.344999999999999 - type: precision_at_100 value: 1.278 - type: precision_at_1000 value: 0.16 - type: precision_at_3 value: 19.442 - type: precision_at_5 value: 13.802 - type: recall_at_1 value: 30.564999999999998 - type: recall_at_10 value: 58.207 - type: recall_at_100 value: 81.137 - type: recall_at_1000 value: 93.506 - type: recall_at_3 value: 44.606 - type: recall_at_5 value: 50.373000000000005 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackProgrammersRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 27.892 - type: map_at_10 value: 37.251 - type: map_at_100 value: 38.606 - type: map_at_1000 value: 38.716 - type: map_at_3 value: 34.312 - type: map_at_5 value: 35.791000000000004 - type: mrr_at_1 value: 34.247 - type: mrr_at_10 value: 42.696 - type: mrr_at_100 value: 43.659 - type: mrr_at_1000 value: 43.711 - type: mrr_at_3 value: 40.563 - type: mrr_at_5 value: 41.625 - type: ndcg_at_1 value: 34.247 - type: ndcg_at_10 value: 42.709 - type: ndcg_at_100 value: 48.422 - type: ndcg_at_1000 value: 50.544 - type: ndcg_at_3 value: 38.105 - type: ndcg_at_5 value: 39.846 - type: precision_at_1 value: 34.247 - type: precision_at_10 value: 7.66 - type: precision_at_100 value: 1.2109999999999999 - type: precision_at_1000 value: 0.157 - type: precision_at_3 value: 17.884 - type: precision_at_5 value: 12.489 - type: recall_at_1 value: 27.892 - type: recall_at_10 value: 53.559 - type: recall_at_100 value: 78.018 - type: recall_at_1000 value: 92.07300000000001 - type: recall_at_3 value: 40.154 - type: recall_at_5 value: 45.078 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 27.29375 - type: map_at_10 value: 36.19533333333334 - type: map_at_100 value: 37.33183333333334 - type: map_at_1000 value: 37.44616666666667 - type: map_at_3 value: 33.49125 - type: map_at_5 value: 34.94166666666667 - type: mrr_at_1 value: 32.336666666666666 - type: mrr_at_10 value: 40.45983333333333 - type: mrr_at_100 value: 41.26533333333334 - type: mrr_at_1000 value: 41.321583333333336 - type: mrr_at_3 value: 38.23416666666667 - type: mrr_at_5 value: 39.48491666666666 - type: ndcg_at_1 value: 32.336666666666666 - type: ndcg_at_10 value: 41.39958333333333 - type: ndcg_at_100 value: 46.293 - type: ndcg_at_1000 value: 48.53425 - type: ndcg_at_3 value: 36.88833333333333 - type: ndcg_at_5 value: 38.90733333333333 - type: precision_at_1 value: 32.336666666666666 - type: precision_at_10 value: 7.175916666666667 - type: precision_at_100 value: 1.1311666666666669 - type: precision_at_1000 value: 0.15141666666666667 - type: precision_at_3 value: 16.841166666666666 - type: precision_at_5 value: 11.796583333333334 - type: recall_at_1 value: 27.29375 - type: recall_at_10 value: 52.514583333333334 - type: recall_at_100 value: 74.128 - type: recall_at_1000 value: 89.64125 - type: recall_at_3 value: 39.83258333333333 - type: recall_at_5 value: 45.126416666666664 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackStatsRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 24.62 - type: map_at_10 value: 31.517 - type: map_at_100 value: 32.322 - type: map_at_1000 value: 32.422000000000004 - type: map_at_3 value: 29.293999999999997 - type: map_at_5 value: 30.403999999999996 - type: mrr_at_1 value: 27.607 - type: mrr_at_10 value: 34.294999999999995 - type: mrr_at_100 value: 35.045 - type: mrr_at_1000 value: 35.114000000000004 - type: mrr_at_3 value: 32.311 - type: mrr_at_5 value: 33.369 - type: ndcg_at_1 value: 27.607 - type: ndcg_at_10 value: 35.853 - type: ndcg_at_100 value: 39.919 - type: ndcg_at_1000 value: 42.452 - type: ndcg_at_3 value: 31.702 - type: ndcg_at_5 value: 33.47 - type: precision_at_1 value: 27.607 - type: precision_at_10 value: 5.598 - type: precision_at_100 value: 0.83 - type: precision_at_1000 value: 0.11199999999999999 - type: precision_at_3 value: 13.700999999999999 - type: precision_at_5 value: 9.325 - type: recall_at_1 value: 24.62 - type: recall_at_10 value: 46.475 - type: recall_at_100 value: 64.891 - type: recall_at_1000 value: 83.524 - type: recall_at_3 value: 34.954 - type: recall_at_5 value: 39.471000000000004 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackTexRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 16.858999999999998 - type: map_at_10 value: 23.746000000000002 - type: map_at_100 value: 24.731 - type: map_at_1000 value: 24.86 - type: map_at_3 value: 21.603 - type: map_at_5 value: 22.811999999999998 - type: mrr_at_1 value: 20.578 - type: mrr_at_10 value: 27.618 - type: mrr_at_100 value: 28.459 - type: mrr_at_1000 value: 28.543000000000003 - type: mrr_at_3 value: 25.533 - type: mrr_at_5 value: 26.730999999999998 - type: ndcg_at_1 value: 20.578 - type: ndcg_at_10 value: 28.147 - type: ndcg_at_100 value: 32.946999999999996 - type: ndcg_at_1000 value: 36.048 - type: ndcg_at_3 value: 24.32 - type: ndcg_at_5 value: 26.131999999999998 - type: precision_at_1 value: 20.578 - type: precision_at_10 value: 5.061999999999999 - type: precision_at_100 value: 0.8789999999999999 - type: precision_at_1000 value: 0.132 - type: precision_at_3 value: 11.448 - type: precision_at_5 value: 8.251999999999999 - type: recall_at_1 value: 16.858999999999998 - type: recall_at_10 value: 37.565 - type: recall_at_100 value: 59.239 - type: recall_at_1000 value: 81.496 - type: recall_at_3 value: 26.865 - type: recall_at_5 value: 31.581 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackUnixRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 26.11 - type: map_at_10 value: 34.214 - type: map_at_100 value: 35.291 - type: map_at_1000 value: 35.400999999999996 - type: map_at_3 value: 31.541000000000004 - type: map_at_5 value: 33.21 - type: mrr_at_1 value: 30.97 - type: mrr_at_10 value: 38.522 - type: mrr_at_100 value: 39.37 - type: mrr_at_1000 value: 39.437 - type: mrr_at_3 value: 36.193999999999996 - type: mrr_at_5 value: 37.691 - type: ndcg_at_1 value: 30.97 - type: ndcg_at_10 value: 39.2 - type: ndcg_at_100 value: 44.267 - type: ndcg_at_1000 value: 46.760000000000005 - type: ndcg_at_3 value: 34.474 - type: ndcg_at_5 value: 37.016 - type: precision_at_1 value: 30.97 - type: precision_at_10 value: 6.521000000000001 - type: precision_at_100 value: 1.011 - type: precision_at_1000 value: 0.135 - type: precision_at_3 value: 15.392 - type: precision_at_5 value: 11.026 - type: recall_at_1 value: 26.11 - type: recall_at_10 value: 50.14999999999999 - type: recall_at_100 value: 72.398 - type: recall_at_1000 value: 89.764 - type: recall_at_3 value: 37.352999999999994 - type: recall_at_5 value: 43.736000000000004 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWebmastersRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 25.514 - type: map_at_10 value: 34.278999999999996 - type: map_at_100 value: 35.847 - type: map_at_1000 value: 36.086 - type: map_at_3 value: 31.563999999999997 - type: map_at_5 value: 32.903999999999996 - type: mrr_at_1 value: 30.830000000000002 - type: mrr_at_10 value: 38.719 - type: mrr_at_100 value: 39.678999999999995 - type: mrr_at_1000 value: 39.741 - type: mrr_at_3 value: 36.265 - type: mrr_at_5 value: 37.599 - type: ndcg_at_1 value: 30.830000000000002 - type: ndcg_at_10 value: 39.997 - type: ndcg_at_100 value: 45.537 - type: ndcg_at_1000 value: 48.296 - type: ndcg_at_3 value: 35.429 - type: ndcg_at_5 value: 37.3 - type: precision_at_1 value: 30.830000000000002 - type: precision_at_10 value: 7.747 - type: precision_at_100 value: 1.516 - type: precision_at_1000 value: 0.24 - type: precision_at_3 value: 16.601 - type: precision_at_5 value: 11.818 - type: recall_at_1 value: 25.514 - type: recall_at_10 value: 50.71600000000001 - type: recall_at_100 value: 75.40299999999999 - type: recall_at_1000 value: 93.10300000000001 - type: recall_at_3 value: 37.466 - type: recall_at_5 value: 42.677 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWordpressRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 21.571 - type: map_at_10 value: 28.254 - type: map_at_100 value: 29.237000000000002 - type: map_at_1000 value: 29.334 - type: map_at_3 value: 25.912000000000003 - type: map_at_5 value: 26.798 - type: mrr_at_1 value: 23.29 - type: mrr_at_10 value: 30.102 - type: mrr_at_100 value: 30.982 - type: mrr_at_1000 value: 31.051000000000002 - type: mrr_at_3 value: 27.942 - type: mrr_at_5 value: 28.848000000000003 - type: ndcg_at_1 value: 23.29 - type: ndcg_at_10 value: 32.726 - type: ndcg_at_100 value: 37.644 - type: ndcg_at_1000 value: 40.161 - type: ndcg_at_3 value: 27.91 - type: ndcg_at_5 value: 29.461 - type: precision_at_1 value: 23.29 - type: precision_at_10 value: 5.213 - type: precision_at_100 value: 0.828 - type: precision_at_1000 value: 0.117 - type: precision_at_3 value: 11.583 - type: precision_at_5 value: 7.8740000000000006 - type: recall_at_1 value: 21.571 - type: recall_at_10 value: 44.809 - type: recall_at_100 value: 67.74900000000001 - type: recall_at_1000 value: 86.60799999999999 - type: recall_at_3 value: 31.627 - type: recall_at_5 value: 35.391 - task: type: Retrieval dataset: type: climate-fever name: MTEB ClimateFEVER config: default split: test revision: None metrics: - type: map_at_1 value: 9.953 - type: map_at_10 value: 17.183 - type: map_at_100 value: 18.926000000000002 - type: map_at_1000 value: 19.105 - type: map_at_3 value: 14.308000000000002 - type: map_at_5 value: 15.738 - type: mrr_at_1 value: 22.02 - type: mrr_at_10 value: 33.181 - type: mrr_at_100 value: 34.357 - type: mrr_at_1000 value: 34.398 - type: mrr_at_3 value: 29.793999999999997 - type: mrr_at_5 value: 31.817 - type: ndcg_at_1 value: 22.02 - type: ndcg_at_10 value: 24.712 - type: ndcg_at_100 value: 32.025 - type: ndcg_at_1000 value: 35.437000000000005 - type: ndcg_at_3 value: 19.852 - type: ndcg_at_5 value: 21.565 - type: precision_at_1 value: 22.02 - type: precision_at_10 value: 7.779 - type: precision_at_100 value: 1.554 - type: precision_at_1000 value: 0.219 - type: precision_at_3 value: 14.832 - type: precision_at_5 value: 11.453000000000001 - type: recall_at_1 value: 9.953 - type: recall_at_10 value: 30.375000000000004 - type: recall_at_100 value: 55.737 - type: recall_at_1000 value: 75.071 - type: recall_at_3 value: 18.529999999999998 - type: recall_at_5 value: 23.313 - task: type: Retrieval dataset: type: dbpedia-entity name: MTEB DBPedia config: default split: test revision: None metrics: - type: map_at_1 value: 8.651 - type: map_at_10 value: 19.674 - type: map_at_100 value: 27.855999999999998 - type: map_at_1000 value: 29.348000000000003 - type: map_at_3 value: 14.247000000000002 - type: map_at_5 value: 16.453 - type: mrr_at_1 value: 61.75000000000001 - type: mrr_at_10 value: 71.329 - type: mrr_at_100 value: 71.69200000000001 - type: mrr_at_1000 value: 71.699 - type: mrr_at_3 value: 69.042 - type: mrr_at_5 value: 70.679 - type: ndcg_at_1 value: 50.125 - type: ndcg_at_10 value: 40.199 - type: ndcg_at_100 value: 45.378 - type: ndcg_at_1000 value: 52.376999999999995 - type: ndcg_at_3 value: 44.342 - type: ndcg_at_5 value: 41.730000000000004 - type: precision_at_1 value: 61.75000000000001 - type: precision_at_10 value: 32.2 - type: precision_at_100 value: 10.298 - type: precision_at_1000 value: 1.984 - type: precision_at_3 value: 48.667 - type: precision_at_5 value: 40.5 - type: recall_at_1 value: 8.651 - type: recall_at_10 value: 25.607000000000003 - type: recall_at_100 value: 53.062 - type: recall_at_1000 value: 74.717 - type: recall_at_3 value: 15.661 - type: recall_at_5 value: 19.409000000000002 - task: type: Classification dataset: type: mteb/emotion name: MTEB EmotionClassification config: default split: test revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 metrics: - type: accuracy value: 47.64500000000001 - type: f1 value: 43.71011316507787 - task: type: Retrieval dataset: type: fever name: MTEB FEVER config: default split: test revision: None metrics: - type: map_at_1 value: 54.613 - type: map_at_10 value: 68.02 - type: map_at_100 value: 68.366 - type: map_at_1000 value: 68.379 - type: map_at_3 value: 65.753 - type: map_at_5 value: 67.242 - type: mrr_at_1 value: 59.001000000000005 - type: mrr_at_10 value: 72.318 - type: mrr_at_100 value: 72.558 - type: mrr_at_1000 value: 72.56099999999999 - type: mrr_at_3 value: 70.22699999999999 - type: mrr_at_5 value: 71.655 - type: ndcg_at_1 value: 59.001000000000005 - type: ndcg_at_10 value: 74.386 - type: ndcg_at_100 value: 75.763 - type: ndcg_at_1000 value: 76.03 - type: ndcg_at_3 value: 70.216 - type: ndcg_at_5 value: 72.697 - type: precision_at_1 value: 59.001000000000005 - type: precision_at_10 value: 9.844 - type: precision_at_100 value: 1.068 - type: precision_at_1000 value: 0.11100000000000002 - type: precision_at_3 value: 28.523 - type: precision_at_5 value: 18.491 - type: recall_at_1 value: 54.613 - type: recall_at_10 value: 89.669 - type: recall_at_100 value: 95.387 - type: recall_at_1000 value: 97.129 - type: recall_at_3 value: 78.54100000000001 - type: recall_at_5 value: 84.637 - task: type: Retrieval dataset: type: fiqa name: MTEB FiQA2018 config: default split: test revision: None metrics: - type: map_at_1 value: 20.348 - type: map_at_10 value: 32.464999999999996 - type: map_at_100 value: 34.235 - type: map_at_1000 value: 34.410000000000004 - type: map_at_3 value: 28.109 - type: map_at_5 value: 30.634 - type: mrr_at_1 value: 38.889 - type: mrr_at_10 value: 47.131 - type: mrr_at_100 value: 48.107 - type: mrr_at_1000 value: 48.138 - type: mrr_at_3 value: 44.599 - type: mrr_at_5 value: 46.181 - type: ndcg_at_1 value: 38.889 - type: ndcg_at_10 value: 39.86 - type: ndcg_at_100 value: 46.619 - type: ndcg_at_1000 value: 49.525999999999996 - type: ndcg_at_3 value: 35.768 - type: ndcg_at_5 value: 37.4 - type: precision_at_1 value: 38.889 - type: precision_at_10 value: 11.003 - type: precision_at_100 value: 1.796 - type: precision_at_1000 value: 0.233 - type: precision_at_3 value: 23.714 - type: precision_at_5 value: 17.901 - type: recall_at_1 value: 20.348 - type: recall_at_10 value: 46.781 - type: recall_at_100 value: 71.937 - type: recall_at_1000 value: 89.18599999999999 - type: recall_at_3 value: 32.16 - type: recall_at_5 value: 38.81 - task: type: Retrieval dataset: type: hotpotqa name: MTEB HotpotQA config: default split: test revision: None metrics: - type: map_at_1 value: 37.198 - type: map_at_10 value: 54.065 - type: map_at_100 value: 54.984 - type: map_at_1000 value: 55.05 - type: map_at_3 value: 50.758 - type: map_at_5 value: 52.758 - type: mrr_at_1 value: 74.396 - type: mrr_at_10 value: 81.352 - type: mrr_at_100 value: 81.562 - type: mrr_at_1000 value: 81.57 - type: mrr_at_3 value: 80.30199999999999 - type: mrr_at_5 value: 80.963 - type: ndcg_at_1 value: 74.396 - type: ndcg_at_10 value: 63.70099999999999 - type: ndcg_at_100 value: 66.874 - type: ndcg_at_1000 value: 68.171 - type: ndcg_at_3 value: 58.916999999999994 - type: ndcg_at_5 value: 61.495999999999995 - type: precision_at_1 value: 74.396 - type: precision_at_10 value: 13.228000000000002 - type: precision_at_100 value: 1.569 - type: precision_at_1000 value: 0.174 - type: precision_at_3 value: 37.007 - type: precision_at_5 value: 24.248 - type: recall_at_1 value: 37.198 - type: recall_at_10 value: 66.13799999999999 - type: recall_at_100 value: 78.45400000000001 - type: recall_at_1000 value: 87.04899999999999 - type: recall_at_3 value: 55.510000000000005 - type: recall_at_5 value: 60.621 - task: type: Classification dataset: type: mteb/imdb name: MTEB ImdbClassification config: default split: test revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 metrics: - type: accuracy value: 86.32240000000002 - type: ap value: 81.37708984744188 - type: f1 value: 86.29645005523952 - task: type: Retrieval dataset: type: msmarco name: MTEB MSMARCO config: default split: dev revision: None metrics: - type: map_at_1 value: 16.402 - type: map_at_10 value: 28.097 - type: map_at_100 value: 29.421999999999997 - type: map_at_1000 value: 29.476999999999997 - type: map_at_3 value: 24.015 - type: map_at_5 value: 26.316 - type: mrr_at_1 value: 16.905 - type: mrr_at_10 value: 28.573999999999998 - type: mrr_at_100 value: 29.862 - type: mrr_at_1000 value: 29.912 - type: mrr_at_3 value: 24.589 - type: mrr_at_5 value: 26.851000000000003 - type: ndcg_at_1 value: 16.905 - type: ndcg_at_10 value: 34.99 - type: ndcg_at_100 value: 41.419 - type: ndcg_at_1000 value: 42.815999999999995 - type: ndcg_at_3 value: 26.695 - type: ndcg_at_5 value: 30.789 - type: precision_at_1 value: 16.905 - type: precision_at_10 value: 5.891 - type: precision_at_100 value: 0.91 - type: precision_at_1000 value: 0.10300000000000001 - type: precision_at_3 value: 11.724 - type: precision_at_5 value: 9.097 - type: recall_at_1 value: 16.402 - type: recall_at_10 value: 56.462999999999994 - type: recall_at_100 value: 86.246 - type: recall_at_1000 value: 96.926 - type: recall_at_3 value: 33.897 - type: recall_at_5 value: 43.718 - task: type: Classification dataset: type: mteb/mtop_domain name: MTEB MTOPDomainClassification (en) config: en split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics: - type: accuracy value: 92.35978112175103 - type: f1 value: 92.04704651024416 - task: type: Classification dataset: type: mteb/mtop_intent name: MTEB MTOPIntentClassification (en) config: en split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics: - type: accuracy value: 65.20063839489283 - type: f1 value: 45.34047546059121 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (en) config: en split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 67.74714189643578 - type: f1 value: 65.36156843270334 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (en) config: en split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 74.03160726294554 - type: f1 value: 73.42899064973165 - task: type: Clustering dataset: type: mteb/medrxiv-clustering-p2p name: MTEB MedrxivClusteringP2P config: default split: test revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 metrics: - type: v_measure value: 31.347360980344476 - task: type: Clustering dataset: type: mteb/medrxiv-clustering-s2s name: MTEB MedrxivClusteringS2S config: default split: test revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 metrics: - type: v_measure value: 29.56022733162805 - task: type: Reranking dataset: type: mteb/mind_small name: MTEB MindSmallReranking config: default split: test revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 metrics: - type: map value: 30.60132765358296 - type: mrr value: 31.710892632824468 - task: type: Retrieval dataset: type: nfcorpus name: MTEB NFCorpus config: default split: test revision: None metrics: - type: map_at_1 value: 5.827999999999999 - type: map_at_10 value: 13.547 - type: map_at_100 value: 16.869 - type: map_at_1000 value: 18.242 - type: map_at_3 value: 9.917 - type: map_at_5 value: 11.648 - type: mrr_at_1 value: 46.44 - type: mrr_at_10 value: 55.062 - type: mrr_at_100 value: 55.513999999999996 - type: mrr_at_1000 value: 55.564 - type: mrr_at_3 value: 52.735 - type: mrr_at_5 value: 54.391 - type: ndcg_at_1 value: 44.582 - type: ndcg_at_10 value: 35.684 - type: ndcg_at_100 value: 31.913999999999998 - type: ndcg_at_1000 value: 40.701 - type: ndcg_at_3 value: 40.819 - type: ndcg_at_5 value: 39.117000000000004 - type: precision_at_1 value: 46.129999999999995 - type: precision_at_10 value: 26.687 - type: precision_at_100 value: 8.062 - type: precision_at_1000 value: 2.073 - type: precision_at_3 value: 38.493 - type: precision_at_5 value: 34.241 - type: recall_at_1 value: 5.827999999999999 - type: recall_at_10 value: 17.391000000000002 - type: recall_at_100 value: 31.228 - type: recall_at_1000 value: 63.943000000000005 - type: recall_at_3 value: 10.81 - type: recall_at_5 value: 13.618 - task: type: Retrieval dataset: type: nq name: MTEB NQ config: default split: test revision: None metrics: - type: map_at_1 value: 24.02 - type: map_at_10 value: 40.054 - type: map_at_100 value: 41.318 - type: map_at_1000 value: 41.343999999999994 - type: map_at_3 value: 35.221999999999994 - type: map_at_5 value: 38.057 - type: mrr_at_1 value: 27.230999999999998 - type: mrr_at_10 value: 42.315999999999995 - type: mrr_at_100 value: 43.254 - type: mrr_at_1000 value: 43.272 - type: mrr_at_3 value: 38.176 - type: mrr_at_5 value: 40.64 - type: ndcg_at_1 value: 27.230999999999998 - type: ndcg_at_10 value: 48.551 - type: ndcg_at_100 value: 53.737 - type: ndcg_at_1000 value: 54.313 - type: ndcg_at_3 value: 39.367999999999995 - type: ndcg_at_5 value: 44.128 - type: precision_at_1 value: 27.230999999999998 - type: precision_at_10 value: 8.578 - type: precision_at_100 value: 1.145 - type: precision_at_1000 value: 0.12 - type: precision_at_3 value: 18.704 - type: precision_at_5 value: 13.927999999999999 - type: recall_at_1 value: 24.02 - type: recall_at_10 value: 72.258 - type: recall_at_100 value: 94.489 - type: recall_at_1000 value: 98.721 - type: recall_at_3 value: 48.373 - type: recall_at_5 value: 59.388 - task: type: Retrieval dataset: type: quora name: MTEB QuoraRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 70.476 - type: map_at_10 value: 84.41300000000001 - type: map_at_100 value: 85.036 - type: map_at_1000 value: 85.055 - type: map_at_3 value: 81.45599999999999 - type: map_at_5 value: 83.351 - type: mrr_at_1 value: 81.07 - type: mrr_at_10 value: 87.408 - type: mrr_at_100 value: 87.509 - type: mrr_at_1000 value: 87.51 - type: mrr_at_3 value: 86.432 - type: mrr_at_5 value: 87.128 - type: ndcg_at_1 value: 81.13 - type: ndcg_at_10 value: 88.18599999999999 - type: ndcg_at_100 value: 89.401 - type: ndcg_at_1000 value: 89.515 - type: ndcg_at_3 value: 85.332 - type: ndcg_at_5 value: 86.97 - type: precision_at_1 value: 81.13 - type: precision_at_10 value: 13.361 - type: precision_at_100 value: 1.5230000000000001 - type: precision_at_1000 value: 0.156 - type: precision_at_3 value: 37.31 - type: precision_at_5 value: 24.548000000000002 - type: recall_at_1 value: 70.476 - type: recall_at_10 value: 95.3 - type: recall_at_100 value: 99.46000000000001 - type: recall_at_1000 value: 99.96000000000001 - type: recall_at_3 value: 87.057 - type: recall_at_5 value: 91.739 - task: type: Clustering dataset: type: mteb/reddit-clustering name: MTEB RedditClustering config: default split: test revision: 24640382cdbf8abc73003fb0fa6d111a705499eb metrics: - type: v_measure value: 55.36775089400664 - task: type: Clustering dataset: type: mteb/reddit-clustering-p2p name: MTEB RedditClusteringP2P config: default split: test revision: 282350215ef01743dc01b456c7f5241fa8937f16 metrics: - type: v_measure value: 60.05041008018361 - task: type: Retrieval dataset: type: scidocs name: MTEB SCIDOCS config: default split: test revision: None metrics: - type: map_at_1 value: 4.743 - type: map_at_10 value: 12.171 - type: map_at_100 value: 14.174999999999999 - type: map_at_1000 value: 14.446 - type: map_at_3 value: 8.698 - type: map_at_5 value: 10.444 - type: mrr_at_1 value: 23.400000000000002 - type: mrr_at_10 value: 34.284 - type: mrr_at_100 value: 35.400999999999996 - type: mrr_at_1000 value: 35.451 - type: mrr_at_3 value: 31.167 - type: mrr_at_5 value: 32.946999999999996 - type: ndcg_at_1 value: 23.400000000000002 - type: ndcg_at_10 value: 20.169999999999998 - type: ndcg_at_100 value: 27.967 - type: ndcg_at_1000 value: 32.982 - type: ndcg_at_3 value: 19.308 - type: ndcg_at_5 value: 16.837 - type: precision_at_1 value: 23.400000000000002 - type: precision_at_10 value: 10.41 - type: precision_at_100 value: 2.162 - type: precision_at_1000 value: 0.338 - type: precision_at_3 value: 18.067 - type: precision_at_5 value: 14.78 - type: recall_at_1 value: 4.743 - type: recall_at_10 value: 21.098 - type: recall_at_100 value: 43.85 - type: recall_at_1000 value: 68.60000000000001 - type: recall_at_3 value: 10.993 - type: recall_at_5 value: 14.998000000000001 - task: type: STS dataset: type: mteb/sickr-sts name: MTEB SICK-R config: default split: test revision: a6ea5a8cab320b040a23452cc28066d9beae2cee metrics: - type: cos_sim_pearson value: 81.129376905658 - type: cos_sim_spearman value: 74.18938626206575 - type: euclidean_pearson value: 77.95192851803141 - type: euclidean_spearman value: 74.18938626206575 - type: manhattan_pearson value: 77.97718819383338 - type: manhattan_spearman value: 74.20580317409417 - task: type: STS dataset: type: mteb/sts12-sts name: MTEB STS12 config: default split: test revision: a0d554a64d88156834ff5ae9920b964011b16384 metrics: - type: cos_sim_pearson value: 78.36913772828827 - type: cos_sim_spearman value: 73.22311186990363 - type: euclidean_pearson value: 74.45263405031004 - type: euclidean_spearman value: 73.22311186990363 - type: manhattan_pearson value: 74.56201270071791 - type: manhattan_spearman value: 73.26490493774821 - task: type: STS dataset: type: mteb/sts13-sts name: MTEB STS13 config: default split: test revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca metrics: - type: cos_sim_pearson value: 84.79920796384403 - type: cos_sim_spearman value: 84.77145185366201 - type: euclidean_pearson value: 83.90638366191354 - type: euclidean_spearman value: 84.77145185366201 - type: manhattan_pearson value: 83.83788216629048 - type: manhattan_spearman value: 84.70515987131665 - task: type: STS dataset: type: mteb/sts14-sts name: MTEB STS14 config: default split: test revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 metrics: - type: cos_sim_pearson value: 83.18883765092875 - type: cos_sim_spearman value: 79.9948128016449 - type: euclidean_pearson value: 81.57436738666773 - type: euclidean_spearman value: 79.9948128016449 - type: manhattan_pearson value: 81.55274202648187 - type: manhattan_spearman value: 79.99854975019382 - task: type: STS dataset: type: mteb/sts15-sts name: MTEB STS15 config: default split: test revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 metrics: - type: cos_sim_pearson value: 86.89669110871021 - type: cos_sim_spearman value: 87.26758456901442 - type: euclidean_pearson value: 86.62614163641416 - type: euclidean_spearman value: 87.26758456901442 - type: manhattan_pearson value: 86.58584490012353 - type: manhattan_spearman value: 87.20340001562076 - task: type: STS dataset: type: mteb/sts16-sts name: MTEB STS16 config: default split: test revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 metrics: - type: cos_sim_pearson value: 81.983023415916 - type: cos_sim_spearman value: 82.31169002657151 - type: euclidean_pearson value: 81.52305092886222 - type: euclidean_spearman value: 82.31169002657151 - type: manhattan_pearson value: 81.63024996600281 - type: manhattan_spearman value: 82.44579116264026 - 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: 89.27779520541694 - type: cos_sim_spearman value: 89.54137104681308 - type: euclidean_pearson value: 88.99136079955996 - type: euclidean_spearman value: 89.54137104681308 - type: manhattan_pearson value: 88.95980417618277 - type: manhattan_spearman value: 89.55178819334718 - 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: 66.50806758829178 - type: cos_sim_spearman value: 65.92675365587571 - type: euclidean_pearson value: 67.09216876696559 - type: euclidean_spearman value: 65.92675365587571 - type: manhattan_pearson value: 67.37398716891478 - type: manhattan_spearman value: 66.34811143508206 - task: type: STS dataset: type: mteb/stsbenchmark-sts name: MTEB STSBenchmark config: default split: test revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 metrics: - type: cos_sim_pearson value: 84.557575753862 - type: cos_sim_spearman value: 83.95859527071087 - type: euclidean_pearson value: 83.77287626715369 - type: euclidean_spearman value: 83.95859527071087 - type: manhattan_pearson value: 83.7898033034244 - type: manhattan_spearman value: 83.94860981294184 - task: type: Reranking dataset: type: mteb/scidocs-reranking name: MTEB SciDocsRR config: default split: test revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab metrics: - type: map value: 79.90679624144718 - type: mrr value: 94.33150183150182 - task: type: Retrieval dataset: type: scifact name: MTEB SciFact config: default split: test revision: None metrics: - type: map_at_1 value: 56.81699999999999 - type: map_at_10 value: 67.301 - type: map_at_100 value: 67.73599999999999 - type: map_at_1000 value: 67.757 - type: map_at_3 value: 64.865 - type: map_at_5 value: 66.193 - type: mrr_at_1 value: 59.667 - type: mrr_at_10 value: 68.324 - type: mrr_at_100 value: 68.66 - type: mrr_at_1000 value: 68.676 - type: mrr_at_3 value: 66.556 - type: mrr_at_5 value: 67.472 - type: ndcg_at_1 value: 59.667 - type: ndcg_at_10 value: 71.982 - type: ndcg_at_100 value: 74.149 - type: ndcg_at_1000 value: 74.60799999999999 - type: ndcg_at_3 value: 67.796 - type: ndcg_at_5 value: 69.64099999999999 - type: precision_at_1 value: 59.667 - type: precision_at_10 value: 9.633 - type: precision_at_100 value: 1.08 - type: precision_at_1000 value: 0.11199999999999999 - type: precision_at_3 value: 26.889000000000003 - type: precision_at_5 value: 17.467 - type: recall_at_1 value: 56.81699999999999 - type: recall_at_10 value: 85.18900000000001 - type: recall_at_100 value: 95.6 - type: recall_at_1000 value: 99.0 - type: recall_at_3 value: 73.617 - type: recall_at_5 value: 78.444 - task: type: PairClassification dataset: type: mteb/sprintduplicatequestions-pairclassification name: MTEB SprintDuplicateQuestions config: default split: test revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 metrics: - type: cos_sim_accuracy value: 99.83465346534653 - type: cos_sim_ap value: 95.93387984443646 - type: cos_sim_f1 value: 91.49261334691798 - type: cos_sim_precision value: 93.25025960539979 - type: cos_sim_recall value: 89.8 - type: dot_accuracy value: 99.83465346534653 - type: dot_ap value: 95.93389375761485 - type: dot_f1 value: 91.49261334691798 - type: dot_precision value: 93.25025960539979 - type: dot_recall value: 89.8 - type: euclidean_accuracy value: 99.83465346534653 - type: euclidean_ap value: 95.93389375761487 - type: euclidean_f1 value: 91.49261334691798 - type: euclidean_precision value: 93.25025960539979 - type: euclidean_recall value: 89.8 - type: manhattan_accuracy value: 99.83564356435643 - type: manhattan_ap value: 95.89877504534601 - type: manhattan_f1 value: 91.53061224489795 - type: manhattan_precision value: 93.4375 - type: manhattan_recall value: 89.7 - type: max_accuracy value: 99.83564356435643 - type: max_ap value: 95.93389375761487 - type: max_f1 value: 91.53061224489795 - task: type: Clustering dataset: type: mteb/stackexchange-clustering name: MTEB StackExchangeClustering config: default split: test revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 metrics: - type: v_measure value: 62.2780055191805 - task: type: Clustering dataset: type: mteb/stackexchange-clustering-p2p name: MTEB StackExchangeClusteringP2P config: default split: test revision: 815ca46b2622cec33ccafc3735d572c266efdb44 metrics: - type: v_measure value: 33.94461701798904 - task: type: Reranking dataset: type: mteb/stackoverflowdupquestions-reranking name: MTEB StackOverflowDupQuestions config: default split: test revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 metrics: - type: map value: 49.865789666749535 - type: mrr value: 50.61783804430863 - task: type: Summarization dataset: type: mteb/summeval name: MTEB SummEval config: default split: test revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c metrics: - type: cos_sim_pearson value: 29.97703436199298 - type: cos_sim_spearman value: 30.71880290978946 - type: dot_pearson value: 29.977036284086818 - type: dot_spearman value: 30.71880290978946 - task: type: Retrieval dataset: type: trec-covid name: MTEB TRECCOVID config: default split: test revision: None metrics: - type: map_at_1 value: 0.22799999999999998 - type: map_at_10 value: 1.559 - type: map_at_100 value: 8.866 - type: map_at_1000 value: 23.071 - type: map_at_3 value: 0.592 - type: map_at_5 value: 0.906 - type: mrr_at_1 value: 84.0 - type: mrr_at_10 value: 88.567 - type: mrr_at_100 value: 88.748 - type: mrr_at_1000 value: 88.748 - type: mrr_at_3 value: 87.667 - type: mrr_at_5 value: 88.067 - type: ndcg_at_1 value: 73.0 - type: ndcg_at_10 value: 62.202999999999996 - type: ndcg_at_100 value: 49.66 - type: ndcg_at_1000 value: 48.760999999999996 - type: ndcg_at_3 value: 67.52 - type: ndcg_at_5 value: 64.80799999999999 - type: precision_at_1 value: 84.0 - type: precision_at_10 value: 65.4 - type: precision_at_100 value: 51.72 - type: precision_at_1000 value: 22.014 - type: precision_at_3 value: 74.0 - type: precision_at_5 value: 69.19999999999999 - type: recall_at_1 value: 0.22799999999999998 - type: recall_at_10 value: 1.7680000000000002 - type: recall_at_100 value: 12.581999999999999 - type: recall_at_1000 value: 46.883 - type: recall_at_3 value: 0.618 - type: recall_at_5 value: 0.9690000000000001 - task: type: Retrieval dataset: type: webis-touche2020 name: MTEB Touche2020 config: default split: test revision: None metrics: - type: map_at_1 value: 1.295 - type: map_at_10 value: 7.481 - type: map_at_100 value: 13.120999999999999 - type: map_at_1000 value: 14.863999999999999 - type: map_at_3 value: 3.266 - type: map_at_5 value: 4.662 - type: mrr_at_1 value: 14.285999999999998 - type: mrr_at_10 value: 31.995 - type: mrr_at_100 value: 33.415 - type: mrr_at_1000 value: 33.432 - type: mrr_at_3 value: 27.551 - type: mrr_at_5 value: 30.306 - type: ndcg_at_1 value: 11.224 - type: ndcg_at_10 value: 19.166 - type: ndcg_at_100 value: 31.86 - type: ndcg_at_1000 value: 44.668 - type: ndcg_at_3 value: 17.371 - type: ndcg_at_5 value: 18.567 - type: precision_at_1 value: 14.285999999999998 - type: precision_at_10 value: 18.98 - type: precision_at_100 value: 7.041 - type: precision_at_1000 value: 1.555 - type: precision_at_3 value: 19.728 - type: precision_at_5 value: 20.816000000000003 - type: recall_at_1 value: 1.295 - type: recall_at_10 value: 14.482000000000001 - type: recall_at_100 value: 45.149 - type: recall_at_1000 value: 84.317 - type: recall_at_3 value: 4.484 - type: recall_at_5 value: 7.7170000000000005 - task: type: Classification dataset: type: mteb/toxic_conversations_50k name: MTEB ToxicConversationsClassification config: default split: test revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c metrics: - type: accuracy value: 72.96340000000001 - type: ap value: 15.62835559397026 - type: f1 value: 56.42561616707867 - task: type: Classification dataset: type: mteb/tweet_sentiment_extraction name: MTEB TweetSentimentExtractionClassification config: default split: test revision: d604517c81ca91fe16a244d1248fc021f9ecee7a metrics: - type: accuracy value: 55.280135823429546 - type: f1 value: 55.61428067547153 - task: type: Clustering dataset: type: mteb/twentynewsgroups-clustering name: MTEB TwentyNewsgroupsClustering config: default split: test revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 metrics: - type: v_measure value: 45.426677723253555 - task: type: PairClassification dataset: type: mteb/twittersemeval2015-pairclassification name: MTEB TwitterSemEval2015 config: default split: test revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 metrics: - type: cos_sim_accuracy value: 84.57411933003517 - type: cos_sim_ap value: 69.68254951354992 - type: cos_sim_f1 value: 65.05232416646386 - type: cos_sim_precision value: 60.36585365853659 - type: cos_sim_recall value: 70.52770448548813 - type: dot_accuracy value: 84.57411933003517 - type: dot_ap value: 69.68256519978905 - type: dot_f1 value: 65.05232416646386 - type: dot_precision value: 60.36585365853659 - type: dot_recall value: 70.52770448548813 - type: euclidean_accuracy value: 84.57411933003517 - type: euclidean_ap value: 69.6825655240522 - type: euclidean_f1 value: 65.05232416646386 - type: euclidean_precision value: 60.36585365853659 - type: euclidean_recall value: 70.52770448548813 - type: manhattan_accuracy value: 84.5502771651666 - type: manhattan_ap value: 69.61700491283233 - type: manhattan_f1 value: 64.83962148211872 - type: manhattan_precision value: 60.68553025074765 - type: manhattan_recall value: 69.6042216358839 - type: max_accuracy value: 84.57411933003517 - type: max_ap value: 69.6825655240522 - type: max_f1 value: 65.05232416646386 - task: type: PairClassification dataset: type: mteb/twitterurlcorpus-pairclassification name: MTEB TwitterURLCorpus config: default split: test revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf metrics: - type: cos_sim_accuracy value: 88.80350836341057 - type: cos_sim_ap value: 85.41051415803449 - type: cos_sim_f1 value: 77.99305633329602 - type: cos_sim_precision value: 75.70113776360607 - type: cos_sim_recall value: 80.42808746535263 - type: dot_accuracy value: 88.80350836341057 - type: dot_ap value: 85.41051488820463 - type: dot_f1 value: 77.99305633329602 - type: dot_precision value: 75.70113776360607 - type: dot_recall value: 80.42808746535263 - type: euclidean_accuracy value: 88.80350836341057 - type: euclidean_ap value: 85.41051374760137 - type: euclidean_f1 value: 77.99305633329602 - type: euclidean_precision value: 75.70113776360607 - type: euclidean_recall value: 80.42808746535263 - type: manhattan_accuracy value: 88.74529436876625 - type: manhattan_ap value: 85.38380242074525 - type: manhattan_f1 value: 78.02957839746892 - type: manhattan_precision value: 74.71466816964914 - type: manhattan_recall value: 81.65229442562365 - type: max_accuracy value: 88.80350836341057 - type: max_ap value: 85.41051488820463 - type: max_f1 value: 78.02957839746892 --- # nomic-embed-text-v1-unsupervised: A Reproducible Long Context (8192) Text Embedder `nomic-embed-text-v1-unsupervised` is 8192 context length text encoder. This is a checkpoint after contrastive pretraining from multi-stage contrastive training of the [final model](https://huggingface.co/nomic-ai/nomic-embed-text-v1). The purpose of releasing this checkpoint is 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)