--- pipeline_tag: sentence-similarity tags: - sentence-transformers - feature-extraction - sentence-similarity - mteb model-index: - name: binarize_False results: - task: type: Classification dataset: type: None name: MTEB AmazonCounterfactualClassification (en) config: en split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics: - type: accuracy value: 76.20895522388061 - type: ap value: 39.2507182700391 - type: f1 value: 70.1524994873644 - task: type: Classification dataset: type: None name: MTEB AmazonPolarityClassification config: default split: test revision: e2d317d38cd51312af73b3d32a06d1a08b442046 metrics: - type: accuracy value: 91.66092499999999 - type: ap value: 88.67291765528996 - type: f1 value: 91.65254265062715 - task: type: Classification dataset: type: None name: MTEB AmazonReviewsClassification (en) config: en split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics: - type: accuracy value: 46.768 - type: f1 value: 46.1529444051673 - task: type: Retrieval dataset: type: None name: MTEB ArguAna config: default split: test revision: c22ab2a51041ffd869aaddef7af8d8215647e41a metrics: - type: map_at_1 value: 24.964 - type: map_at_10 value: 39.891 - type: map_at_100 value: 41.015 - type: map_at_1000 value: 41.027 - type: map_at_20 value: 40.788999999999994 - type: map_at_3 value: 35.016999999999996 - type: map_at_5 value: 37.445 - type: mrr_at_1 value: 25.462 - type: mrr_at_10 value: 40.081 - type: mrr_at_100 value: 41.204 - type: mrr_at_1000 value: 41.216 - type: mrr_at_20 value: 40.979 - type: mrr_at_3 value: 35.171 - type: mrr_at_5 value: 37.66 - type: ndcg_at_1 value: 24.964 - type: ndcg_at_10 value: 48.815999999999995 - type: ndcg_at_100 value: 53.415 - type: ndcg_at_1000 value: 53.70399999999999 - type: ndcg_at_20 value: 51.983000000000004 - type: ndcg_at_3 value: 38.417 - type: ndcg_at_5 value: 42.833 - type: precision_at_1 value: 24.964 - type: precision_at_10 value: 7.774 - type: precision_at_100 value: 0.9740000000000001 - type: precision_at_1000 value: 0.1 - type: precision_at_20 value: 4.502 - type: precision_at_3 value: 16.098000000000003 - type: precision_at_5 value: 11.821 - type: recall_at_1 value: 24.964 - type: recall_at_10 value: 77.738 - type: recall_at_100 value: 97.368 - type: recall_at_1000 value: 99.57300000000001 - type: recall_at_20 value: 90.04299999999999 - type: recall_at_3 value: 48.293 - type: recall_at_5 value: 59.104 - task: type: Clustering dataset: type: None name: MTEB ArxivClusteringP2P config: default split: test revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d metrics: - type: v_measure value: 47.46642893138737 - type: v_measures value: [0.4630870464942426, 0.48179626796437086, 0.48112541416510324, 0.4785458846844729, 0.4667757763219518, 0.4888239384534906, 0.48913193407033156, 0.45400599455241203, 0.4796128193217837, 0.4826602649834829, 0.5534097832418009, 0.547017625264848, 0.5534875637912158, 0.5545166479145291, 0.551868078347376, 0.5565074707024643, 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ndcg_at_20 value: 53.53 - type: ndcg_at_3 value: 46.916999999999994 - type: ndcg_at_5 value: 49.282 - type: precision_at_1 value: 40.916000000000004 - type: precision_at_10 value: 9.9 - type: precision_at_100 value: 1.534 - type: precision_at_1000 value: 0.194 - type: precision_at_20 value: 5.722 - type: precision_at_3 value: 22.747 - type: precision_at_5 value: 16.338 - type: recall_at_1 value: 33.62 - type: recall_at_10 value: 63.768 - type: recall_at_100 value: 84.629 - type: recall_at_1000 value: 95.488 - type: recall_at_20 value: 70.127 - type: recall_at_3 value: 49.563 - type: recall_at_5 value: 56.467999999999996 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackEnglishRetrieval config: default split: test revision: ad9991cb51e31e31e430383c75ffb2885547b5f0 metrics: - type: map_at_1 value: 32.43 - type: map_at_10 value: 43.56 - type: map_at_100 value: 44.772 - type: map_at_1000 value: 44.894 - type: map_at_20 value: 44.207 - type: map_at_3 value: 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recall_at_5 value: 52.513 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGamingRetrieval config: default split: test revision: 4885aa143210c98657558c04aaf3dc47cfb54340 metrics: - type: map_at_1 value: 43.195 - type: map_at_10 value: 56.013000000000005 - type: map_at_100 value: 56.957 - type: map_at_1000 value: 57.006 - type: map_at_20 value: 56.596000000000004 - type: map_at_3 value: 52.807 - type: map_at_5 value: 54.555 - type: mrr_at_1 value: 49.592000000000006 - type: mrr_at_10 value: 59.399 - type: mrr_at_100 value: 59.995 - type: mrr_at_1000 value: 60.019999999999996 - type: mrr_at_20 value: 59.77400000000001 - type: mrr_at_3 value: 57.220000000000006 - type: mrr_at_5 value: 58.48100000000001 - type: ndcg_at_1 value: 49.592000000000006 - type: ndcg_at_10 value: 61.682 - type: ndcg_at_100 value: 65.33 - type: ndcg_at_1000 value: 66.29 - type: ndcg_at_20 value: 63.298 - type: ndcg_at_3 value: 56.538999999999994 - type: ndcg_at_5 value: 58.946 - type: 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28.927000000000003 - type: mrr_at_10 value: 37.396 - type: mrr_at_100 value: 38.267 - type: mrr_at_1000 value: 38.328 - type: mrr_at_20 value: 37.865 - type: mrr_at_3 value: 35.141 - type: mrr_at_5 value: 36.35 - type: ndcg_at_1 value: 28.927000000000003 - type: ndcg_at_10 value: 40.403 - type: ndcg_at_100 value: 45.241 - type: ndcg_at_1000 value: 47.278999999999996 - type: ndcg_at_20 value: 42.241 - type: ndcg_at_3 value: 35.754999999999995 - type: ndcg_at_5 value: 37.935 - type: precision_at_1 value: 28.927000000000003 - type: precision_at_10 value: 6.056 - type: precision_at_100 value: 0.893 - type: precision_at_1000 value: 0.11 - type: precision_at_20 value: 3.458 - type: precision_at_3 value: 14.915000000000001 - type: precision_at_5 value: 10.282 - type: recall_at_1 value: 27.254 - type: recall_at_10 value: 52.967 - type: recall_at_100 value: 75.224 - type: recall_at_1000 value: 90.617 - type: recall_at_20 value: 60.053 - type: recall_at_3 value: 40.548 - type: recall_at_5 value: 45.741 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackMathematicaRetrieval config: default split: test revision: 90fceea13679c63fe563ded68f3b6f06e50061de metrics: - type: map_at_1 value: 17.291999999999998 - type: map_at_10 value: 25.56 - type: map_at_100 value: 26.694000000000003 - type: map_at_1000 value: 26.813 - type: map_at_20 value: 26.169999999999998 - type: map_at_3 value: 23.151 - type: map_at_5 value: 24.535 - type: mrr_at_1 value: 21.517 - type: mrr_at_10 value: 30.097 - type: mrr_at_100 value: 31.087999999999997 - type: mrr_at_1000 value: 31.157 - type: mrr_at_20 value: 30.689 - type: mrr_at_3 value: 27.736 - type: mrr_at_5 value: 29.154000000000003 - type: ndcg_at_1 value: 21.517 - type: ndcg_at_10 value: 30.636000000000003 - type: ndcg_at_100 value: 36.015 - type: ndcg_at_1000 value: 38.800000000000004 - type: ndcg_at_20 value: 32.716 - type: ndcg_at_3 value: 26.316 - type: ndcg_at_5 value: 28.46 - type: precision_at_1 value: 21.517 - type: precision_at_10 value: 5.585 - type: precision_at_100 value: 0.938 - type: precision_at_1000 value: 0.132 - type: precision_at_20 value: 3.34 - type: precision_at_3 value: 12.769 - type: precision_at_5 value: 9.254 - type: recall_at_1 value: 17.291999999999998 - type: recall_at_10 value: 41.677 - type: recall_at_100 value: 64.92999999999999 - type: recall_at_1000 value: 84.41300000000001 - type: recall_at_20 value: 49.18 - type: recall_at_3 value: 29.836000000000002 - type: recall_at_5 value: 35.284 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackPhysicsRetrieval config: default split: test revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4 metrics: - type: map_at_1 value: 29.215000000000003 - type: map_at_10 value: 39.919 - type: map_at_100 value: 41.209 - type: map_at_1000 value: 41.31 - type: map_at_20 value: 40.62 - type: map_at_3 value: 36.565 - type: map_at_5 value: 38.439 - type: mrr_at_1 value: 35.996 - type: mrr_at_10 value: 45.39 - type: mrr_at_100 value: 46.205 - type: mrr_at_1000 value: 46.247 - type: mrr_at_20 value: 45.867000000000004 - type: mrr_at_3 value: 42.782 - type: mrr_at_5 value: 44.235 - type: ndcg_at_1 value: 35.996 - type: ndcg_at_10 value: 46.032000000000004 - type: ndcg_at_100 value: 51.397999999999996 - type: ndcg_at_1000 value: 53.215 - type: ndcg_at_20 value: 48.128 - type: ndcg_at_3 value: 40.78 - type: ndcg_at_5 value: 43.187999999999995 - type: precision_at_1 value: 35.996 - type: precision_at_10 value: 8.402 - type: precision_at_100 value: 1.304 - type: precision_at_1000 value: 0.161 - type: precision_at_20 value: 4.913 - type: precision_at_3 value: 19.442 - type: precision_at_5 value: 13.84 - type: recall_at_1 value: 29.215000000000003 - type: recall_at_10 value: 58.846 - type: recall_at_100 value: 81.255 - type: recall_at_1000 value: 93.10300000000001 - type: recall_at_20 value: 66.193 - type: recall_at_3 value: 43.842 - type: recall_at_5 value: 50.157 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackProgrammersRetrieval config: default split: test revision: 6184bc1440d2dbc7612be22b50686b8826d22b32 metrics: - type: map_at_1 value: 28.654000000000003 - type: map_at_10 value: 38.635000000000005 - type: map_at_100 value: 39.898 - type: map_at_1000 value: 40.003 - type: map_at_20 value: 39.33 - type: map_at_3 value: 35.705999999999996 - type: map_at_5 value: 37.294 - type: mrr_at_1 value: 34.589 - type: mrr_at_10 value: 43.580000000000005 - type: mrr_at_100 value: 44.455 - type: mrr_at_1000 value: 44.505 - type: mrr_at_20 value: 44.088 - type: mrr_at_3 value: 41.419 - type: mrr_at_5 value: 42.635 - type: ndcg_at_1 value: 34.589 - type: ndcg_at_10 value: 44.021 - type: ndcg_at_100 value: 49.653999999999996 - type: ndcg_at_1000 value: 51.695 - type: ndcg_at_20 value: 46.190999999999995 - type: ndcg_at_3 value: 39.568999999999996 - type: ndcg_at_5 value: 41.53 - type: precision_at_1 value: 34.589 - type: precision_at_10 value: 7.865 - type: precision_at_100 value: 1.243 - type: precision_at_1000 value: 0.16 - type: precision_at_20 value: 4.618 - type: precision_at_3 value: 18.531 - type: precision_at_5 value: 13.081999999999999 - type: recall_at_1 value: 28.654000000000003 - type: recall_at_10 value: 54.785 - type: recall_at_100 value: 79.532 - type: recall_at_1000 value: 92.99199999999999 - type: recall_at_20 value: 62.605 - type: recall_at_3 value: 42.559000000000005 - type: recall_at_5 value: 47.664 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackRetrieval config: default split: test revision: f46a197baaae43b4f621051089b82a364682dfeb metrics: - type: map_at_1 value: 28.017500000000002 - type: map_at_10 value: 37.226000000000006 - type: map_at_100 value: 38.387249999999995 - type: map_at_1000 value: 38.497 - type: map_at_20 value: 37.8685 - type: map_at_3 value: 34.45716666666666 - type: map_at_5 value: 36.02891666666667 - type: mrr_at_1 value: 33.0525 - type: mrr_at_10 value: 41.375249999999994 - type: mrr_at_100 value: 42.214083333333335 - type: mrr_at_1000 value: 42.266416666666665 - type: mrr_at_20 value: 41.868833333333335 - type: mrr_at_3 value: 39.14641666666667 - type: mrr_at_5 value: 40.44550000000001 - type: ndcg_at_1 value: 33.0525 - type: ndcg_at_10 value: 42.40116666666667 - type: ndcg_at_100 value: 47.34408333333333 - type: ndcg_at_1000 value: 49.45733333333333 - type: ndcg_at_20 value: 44.33925 - type: ndcg_at_3 value: 37.934916666666666 - type: ndcg_at_5 value: 40.07458333333334 - type: precision_at_1 value: 33.0525 - type: precision_at_10 value: 7.330500000000001 - type: precision_at_100 value: 1.1537499999999998 - type: precision_at_1000 value: 0.1514166666666667 - type: precision_at_20 value: 4.298583333333333 - type: precision_at_3 value: 17.37725 - type: precision_at_5 value: 12.249500000000001 - type: recall_at_1 value: 28.017500000000002 - type: recall_at_10 value: 53.424416666666666 - type: recall_at_100 value: 75.08983333333332 - type: recall_at_1000 value: 89.7495 - type: recall_at_20 value: 60.53375000000001 - type: recall_at_3 value: 40.93975000000001 - type: recall_at_5 value: 46.51383333333333 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackStatsRetrieval config: default split: test revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a metrics: - type: map_at_1 value: 25.277 - type: map_at_10 value: 32.135000000000005 - type: map_at_100 value: 33.105000000000004 - type: map_at_1000 value: 33.194 - type: map_at_20 value: 32.696 - type: map_at_3 value: 30.173 - type: map_at_5 value: 31.291000000000004 - type: mrr_at_1 value: 28.221 - type: mrr_at_10 value: 34.915 - type: mrr_at_100 value: 35.812 - type: mrr_at_1000 value: 35.876000000000005 - type: mrr_at_20 value: 35.447 - type: mrr_at_3 value: 33.154 - type: mrr_at_5 value: 34.19 - type: ndcg_at_1 value: 28.221 - type: ndcg_at_10 value: 36.086 - type: ndcg_at_100 value: 40.778999999999996 - type: ndcg_at_1000 value: 43.024 - type: ndcg_at_20 value: 38.019 - type: ndcg_at_3 value: 32.57 - type: ndcg_at_5 value: 34.272000000000006 - type: precision_at_1 value: 28.221 - type: precision_at_10 value: 5.567 - type: precision_at_100 value: 0.84 - type: precision_at_1000 value: 0.11 - type: precision_at_20 value: 3.2520000000000002 - type: precision_at_3 value: 13.905999999999999 - type: precision_at_5 value: 9.54 - type: recall_at_1 value: 25.277 - type: recall_at_10 value: 45.426 - type: recall_at_100 value: 66.63900000000001 - type: recall_at_1000 value: 83.25 - type: recall_at_20 value: 52.723 - type: recall_at_3 value: 35.629 - type: recall_at_5 value: 39.916000000000004 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackTexRetrieval config: default split: test revision: 46989137a86843e03a6195de44b09deda022eec7 metrics: - type: map_at_1 value: 18.365000000000002 - type: map_at_10 value: 25.387999999999998 - type: map_at_100 value: 26.394000000000002 - type: map_at_1000 value: 26.509 - type: map_at_20 value: 25.927 - type: map_at_3 value: 23.182 - type: map_at_5 value: 24.383 - type: mrr_at_1 value: 22.402 - type: mrr_at_10 value: 29.465000000000003 - type: mrr_at_100 value: 30.330000000000002 - type: mrr_at_1000 value: 30.404999999999998 - type: mrr_at_20 value: 29.95 - type: mrr_at_3 value: 27.415 - type: mrr_at_5 value: 28.548000000000002 - type: ndcg_at_1 value: 22.402 - type: ndcg_at_10 value: 29.872 - type: ndcg_at_100 value: 34.747 - type: ndcg_at_1000 value: 37.592999999999996 - type: ndcg_at_20 value: 31.653 - type: ndcg_at_3 value: 26.040999999999997 - type: ndcg_at_5 value: 27.755999999999997 - type: precision_at_1 value: 22.402 - type: precision_at_10 value: 5.337 - type: precision_at_100 value: 0.8959999999999999 - type: precision_at_1000 value: 0.13 - type: precision_at_20 value: 3.1850000000000005 - type: precision_at_3 value: 12.239 - type: precision_at_5 value: 8.692 - type: recall_at_1 value: 18.365000000000002 - type: recall_at_10 value: 39.283 - type: recall_at_100 value: 61.412 - type: recall_at_1000 value: 81.922 - type: recall_at_20 value: 45.917 - type: recall_at_3 value: 28.462 - type: recall_at_5 value: 33.040000000000006 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackUnixRetrieval config: default split: test revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53 metrics: - type: map_at_1 value: 29.687 - type: map_at_10 value: 37.667 - type: map_at_100 value: 38.76 - type: map_at_1000 value: 38.863 - type: map_at_20 value: 38.287 - type: map_at_3 value: 35.157 - type: map_at_5 value: 36.732 - type: mrr_at_1 value: 35.168 - type: mrr_at_10 value: 42.309999999999995 - type: mrr_at_100 value: 43.169999999999995 - type: mrr_at_1000 value: 43.227 - type: mrr_at_20 value: 42.826 - type: mrr_at_3 value: 40.065 - type: mrr_at_5 value: 41.549 - type: ndcg_at_1 value: 35.168 - type: ndcg_at_10 value: 42.463 - type: ndcg_at_100 value: 47.475 - type: ndcg_at_1000 value: 49.735 - type: ndcg_at_20 value: 44.440000000000005 - type: ndcg_at_3 value: 38.108 - type: ndcg_at_5 value: 40.507 - type: precision_at_1 value: 35.168 - type: precision_at_10 value: 6.847 - type: precision_at_100 value: 1.048 - type: precision_at_1000 value: 0.134 - type: precision_at_20 value: 3.9510000000000005 - type: precision_at_3 value: 16.884 - type: precision_at_5 value: 11.884 - type: recall_at_1 value: 29.687 - type: recall_at_10 value: 52.413 - type: recall_at_100 value: 74.21799999999999 - type: recall_at_1000 value: 90.022 - type: recall_at_20 value: 59.559 - type: recall_at_3 value: 40.717999999999996 - type: recall_at_5 value: 46.833999999999996 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWebmastersRetrieval config: default split: test revision: 160c094312a0e1facb97e55eeddb698c0abe3571 metrics: - type: map_at_1 value: 28.233000000000004 - type: map_at_10 value: 36.492000000000004 - type: map_at_100 value: 38.157999999999994 - type: map_at_1000 value: 38.391999999999996 - type: map_at_20 value: 37.336999999999996 - type: map_at_3 value: 33.833999999999996 - type: map_at_5 value: 35.225 - type: mrr_at_1 value: 33.399 - type: mrr_at_10 value: 40.983000000000004 - type: mrr_at_100 value: 42.065999999999995 - type: mrr_at_1000 value: 42.117 - type: mrr_at_20 value: 41.635 - type: mrr_at_3 value: 38.999 - type: mrr_at_5 value: 40.105000000000004 - type: ndcg_at_1 value: 33.399 - type: ndcg_at_10 value: 41.764 - type: ndcg_at_100 value: 47.894 - type: ndcg_at_1000 value: 50.304 - type: ndcg_at_20 value: 43.986999999999995 - type: ndcg_at_3 value: 37.861 - type: ndcg_at_5 value: 39.532000000000004 - type: precision_at_1 value: 33.399 - type: precision_at_10 value: 7.806 - type: precision_at_100 value: 1.609 - type: precision_at_1000 value: 0.244 - type: precision_at_20 value: 5.01 - type: precision_at_3 value: 17.655 - type: precision_at_5 value: 12.49 - type: recall_at_1 value: 28.233000000000004 - type: recall_at_10 value: 51.031000000000006 - type: recall_at_100 value: 78.597 - type: recall_at_1000 value: 93.907 - type: recall_at_20 value: 59.231 - type: recall_at_3 value: 39.018 - type: recall_at_5 value: 43.905 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWordpressRetrieval config: default split: test revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4 metrics: - type: map_at_1 value: 22.988 - type: map_at_10 value: 30.219 - type: map_at_100 value: 31.258000000000003 - type: map_at_1000 value: 31.351000000000003 - type: map_at_20 value: 30.895 - type: map_at_3 value: 27.641 - type: map_at_5 value: 29.282000000000004 - type: mrr_at_1 value: 25.139 - type: mrr_at_10 value: 32.1 - type: mrr_at_100 value: 33.119 - type: mrr_at_1000 value: 33.178000000000004 - type: mrr_at_20 value: 32.747 - type: mrr_at_3 value: 29.759999999999998 - type: mrr_at_5 value: 31.174000000000003 - type: ndcg_at_1 value: 25.139 - type: ndcg_at_10 value: 34.519 - type: ndcg_at_100 value: 39.415 - type: ndcg_at_1000 value: 41.837999999999994 - type: ndcg_at_20 value: 36.867 - type: ndcg_at_3 value: 29.656 - type: ndcg_at_5 value: 32.323 - type: precision_at_1 value: 25.139 - type: precision_at_10 value: 5.287 - type: precision_at_100 value: 0.823 - type: precision_at_1000 value: 0.11399999999999999 - type: precision_at_20 value: 3.198 - type: precision_at_3 value: 12.323 - type: precision_at_5 value: 8.982999999999999 - type: recall_at_1 value: 22.988 - type: recall_at_10 value: 45.983000000000004 - type: recall_at_100 value: 67.55499999999999 - type: recall_at_1000 value: 85.795 - type: recall_at_20 value: 54.795 - type: recall_at_3 value: 33.266 - type: recall_at_5 value: 39.501 - task: type: Retrieval dataset: type: None name: MTEB ClimateFEVER config: default split: test revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380 metrics: - type: map_at_1 value: 9.466 - type: map_at_10 value: 15.967 - type: map_at_100 value: 17.804000000000002 - type: map_at_1000 value: 18.003 - type: map_at_20 value: 16.929 - type: map_at_3 value: 13.248 - type: map_at_5 value: 14.6 - type: mrr_at_1 value: 21.303 - type: mrr_at_10 value: 30.908 - type: mrr_at_100 value: 32.16 - type: mrr_at_1000 value: 32.211 - type: mrr_at_20 value: 31.721 - type: mrr_at_3 value: 27.6 - type: mrr_at_5 value: 29.402 - type: ndcg_at_1 value: 21.303 - type: ndcg_at_10 value: 22.972 - type: ndcg_at_100 value: 30.782999999999998 - type: ndcg_at_1000 value: 34.382000000000005 - type: ndcg_at_20 value: 25.983 - type: ndcg_at_3 value: 18.278 - type: ndcg_at_5 value: 19.894000000000002 - type: precision_at_1 value: 21.303 - type: precision_at_10 value: 7.225 - type: precision_at_100 value: 1.549 - type: precision_at_1000 value: 0.22100000000000003 - type: precision_at_20 value: 4.883 - type: precision_at_3 value: 13.442000000000002 - type: precision_at_5 value: 10.463000000000001 - type: recall_at_1 value: 9.466 - type: recall_at_10 value: 28.261999999999997 - type: recall_at_100 value: 55.541 - type: recall_at_1000 value: 75.723 - type: recall_at_20 value: 36.934 - type: recall_at_3 value: 16.862 - type: recall_at_5 value: 21.365000000000002 - task: type: Retrieval dataset: type: None name: MTEB DBPedia config: default split: test revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659 metrics: - type: map_at_1 value: 8.425 - type: map_at_10 value: 18.485 - type: map_at_100 value: 25.790000000000003 - type: map_at_1000 value: 27.205000000000002 - type: map_at_20 value: 21.201 - type: map_at_3 value: 13.26 - type: map_at_5 value: 15.328 - type: mrr_at_1 value: 62.0 - type: mrr_at_10 value: 70.954 - type: mrr_at_100 value: 71.311 - type: mrr_at_1000 value: 71.318 - type: mrr_at_20 value: 71.18100000000001 - type: mrr_at_3 value: 68.708 - type: mrr_at_5 value: 70.296 - type: ndcg_at_1 value: 50.0 - type: ndcg_at_10 value: 37.972 - type: ndcg_at_100 value: 42.725 - type: ndcg_at_1000 value: 49.617 - type: ndcg_at_20 value: 37.478 - type: ndcg_at_3 value: 42.378 - type: ndcg_at_5 value: 39.678000000000004 - type: precision_at_1 value: 62.0 - type: precision_at_10 value: 30.175 - type: precision_at_100 value: 9.56 - type: precision_at_1000 value: 1.8350000000000002 - type: precision_at_20 value: 22.400000000000002 - type: precision_at_3 value: 46.083 - type: precision_at_5 value: 38.65 - type: recall_at_1 value: 8.425 - type: recall_at_10 value: 24.52 - type: recall_at_100 value: 49.79 - type: recall_at_1000 value: 71.27799999999999 - type: recall_at_20 value: 30.938 - type: recall_at_3 value: 14.466999999999999 - type: recall_at_5 value: 18.13 - task: type: Classification dataset: type: None name: MTEB EmotionClassification config: default split: test revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 metrics: - type: accuracy value: 43.615 - type: f1 value: 40.05868641887659 - task: type: Retrieval dataset: type: None name: MTEB FEVER config: default split: test revision: bea83ef9e8fb933d90a2f1d5515737465d613e12 metrics: - type: map_at_1 value: 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TwitterSemEval2015 config: default split: test revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 metrics: - type: cos_sim_accuracy value: 83.78732788937235 - type: cos_sim_ap value: 66.7369597819357 - type: cos_sim_f1 value: 61.900121802679664 - type: cos_sim_precision value: 57.48868778280543 - type: cos_sim_recall value: 67.04485488126649 - type: dot_accuracy value: 83.77540680693807 - type: dot_ap value: 66.7494206279536 - type: dot_f1 value: 61.906496660595025 - type: dot_precision value: 57.34533183352081 - type: dot_recall value: 67.25593667546174 - type: euclidean_accuracy value: 83.78136734815521 - type: euclidean_ap value: 66.72851072777382 - type: euclidean_f1 value: 61.89545676599902 - type: euclidean_precision value: 57.617098681218735 - type: euclidean_recall value: 66.86015831134564 - type: manhattan_accuracy value: 83.69195922989807 - type: manhattan_ap value: 66.67869948457852 - type: manhattan_f1 value: 61.948212083847096 - type: manhattan_precision value: 58.14814814814815 - type: manhattan_recall value: 66.2796833773087 - type: max_accuracy value: 83.78732788937235 - type: max_ap value: 66.7494206279536 - type: max_f1 value: 61.948212083847096 - task: type: PairClassification dataset: type: None name: MTEB TwitterURLCorpus config: default split: test revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf metrics: - type: cos_sim_accuracy value: 89.06935227228627 - type: cos_sim_ap value: 86.01490350477971 - type: cos_sim_f1 value: 78.5821414200534 - type: cos_sim_precision value: 74.85539061955538 - type: cos_sim_recall value: 82.69941484447182 - type: dot_accuracy value: 89.06741180579812 - type: dot_ap value: 86.00939130135514 - type: dot_f1 value: 78.5863394982604 - type: dot_precision value: 74.93888384438081 - type: dot_recall value: 82.60702186633816 - type: euclidean_accuracy value: 89.06547133930997 - type: euclidean_ap value: 86.01611265260871 - type: euclidean_f1 value: 78.5754075834664 - type: euclidean_precision value: 75.89497094483106 - type: euclidean_recall value: 81.45210963966738 - type: manhattan_accuracy value: 89.03636434198782 - type: manhattan_ap value: 85.98483745706906 - type: manhattan_f1 value: 78.52461404019809 - type: manhattan_precision value: 74.48880906327715 - type: manhattan_recall value: 83.02279026793964 - type: max_accuracy value: 89.06935227228627 - type: max_ap value: 86.01611265260871 - type: max_f1 value: 78.5863394982604 license: apache-2.0 language: - en base_model: - answerdotai/ModernBERT-base --- # ModernBERT-Embed-Unsupervised `modernbert-embed-unsupervised` is the unsupervised checkpoint trained with the [contrastors](https://github.com/nomic-ai/contrastors) library for 1 epoch over the 235M weakly-supervised contrastive pairs curated in [Nomic Embed](https://arxiv.org/abs/2402.01613). We suggest using [moderbert-embed](https://huggingface.co/nomic-ai/modernbert-embed) for embedding tasks. ## Performance The modernbert-unsupervised model performs similarly to the `nomic-embed-text-v1_unsup` model | Model | Average (56) | Classification (12) | Clustering (11) | Pair Classification (3) | Reranking (4) | Retrieval (15) | STS (10) | Overall | |-------|--------------|--------------------:|-----------------|------------------------|---------------|----------------|-----------|----------| | nomic-embed-text-v1_unsup | 59.9 | 71.2 | 42.5 | 83.7 | 55.0 | 48.0 | 80.8 | 30.7 | | modernbert-embed-unsupervised | 60.03 | 72.11 | 44.34 | 82.78 | 55.0 | 47.05 | 80.33 | 31.2 |