--- pipeline_tag: sentence-similarity tags: - sentence-transformers - feature-extraction - sentence-similarity - mteb model-index: - name: Dmeta-embedding results: - task: type: STS dataset: type: C-MTEB/AFQMC name: MTEB AFQMC config: default split: validation revision: None metrics: - type: cos_sim_pearson value: 65.60825224706932 - type: cos_sim_spearman value: 71.12862586297193 - type: euclidean_pearson value: 70.18130275750404 - type: euclidean_spearman value: 71.12862586297193 - type: manhattan_pearson value: 70.14470398075396 - type: manhattan_spearman value: 71.05226975911737 - task: type: STS dataset: type: C-MTEB/ATEC name: MTEB ATEC config: default split: test revision: None metrics: - type: cos_sim_pearson value: 65.52386345655479 - type: cos_sim_spearman value: 64.64245253181382 - type: euclidean_pearson value: 73.20157662981914 - type: euclidean_spearman value: 64.64245253178956 - type: manhattan_pearson value: 73.22837571756348 - type: manhattan_spearman value: 64.62632334391418 - task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (zh) config: zh split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics: - type: accuracy value: 44.925999999999995 - type: f1 value: 42.82555191308971 - task: type: STS dataset: type: C-MTEB/BQ name: MTEB BQ config: default split: test revision: None metrics: - type: cos_sim_pearson value: 71.35236446393156 - type: cos_sim_spearman value: 72.29629643702184 - type: euclidean_pearson value: 70.94570179874498 - type: euclidean_spearman value: 72.29629297226953 - type: manhattan_pearson value: 70.84463025501125 - type: manhattan_spearman value: 72.24527021975821 - task: type: Clustering dataset: type: C-MTEB/CLSClusteringP2P name: MTEB CLSClusteringP2P config: default split: test revision: None metrics: - type: v_measure value: 40.24232916894152 - task: type: Clustering dataset: type: C-MTEB/CLSClusteringS2S name: MTEB CLSClusteringS2S config: default split: test revision: None metrics: - type: v_measure value: 39.167806226929706 - task: type: Reranking dataset: type: C-MTEB/CMedQAv1-reranking name: MTEB CMedQAv1 config: default split: test revision: None metrics: - type: map value: 88.48837920106357 - type: mrr value: 90.36861111111111 - task: type: Reranking dataset: type: C-MTEB/CMedQAv2-reranking name: MTEB CMedQAv2 config: default split: test revision: None metrics: - type: map value: 89.17878171657071 - type: mrr value: 91.35805555555555 - task: type: Retrieval dataset: type: C-MTEB/CmedqaRetrieval name: MTEB CmedqaRetrieval config: default split: dev revision: None metrics: - type: map_at_1 value: 25.751 - type: map_at_10 value: 38.946 - type: map_at_100 value: 40.855000000000004 - type: map_at_1000 value: 40.953 - type: map_at_3 value: 34.533 - type: map_at_5 value: 36.905 - type: mrr_at_1 value: 39.235 - type: mrr_at_10 value: 47.713 - type: mrr_at_100 value: 48.71 - type: mrr_at_1000 value: 48.747 - type: mrr_at_3 value: 45.086 - type: mrr_at_5 value: 46.498 - type: ndcg_at_1 value: 39.235 - type: ndcg_at_10 value: 45.831 - type: ndcg_at_100 value: 53.162 - type: ndcg_at_1000 value: 54.800000000000004 - type: ndcg_at_3 value: 40.188 - type: ndcg_at_5 value: 42.387 - type: precision_at_1 value: 39.235 - type: precision_at_10 value: 10.273 - type: precision_at_100 value: 1.627 - type: precision_at_1000 value: 0.183 - type: precision_at_3 value: 22.772000000000002 - type: precision_at_5 value: 16.524 - type: recall_at_1 value: 25.751 - type: recall_at_10 value: 57.411 - type: recall_at_100 value: 87.44 - type: recall_at_1000 value: 98.386 - type: recall_at_3 value: 40.416000000000004 - type: recall_at_5 value: 47.238 - task: type: PairClassification dataset: type: C-MTEB/CMNLI name: MTEB Cmnli config: default split: validation revision: None metrics: - type: cos_sim_accuracy value: 83.59591100420926 - type: cos_sim_ap value: 90.65538153970263 - type: cos_sim_f1 value: 84.76466651795673 - type: cos_sim_precision value: 81.04073363190446 - type: cos_sim_recall value: 88.84732288987608 - type: dot_accuracy value: 83.59591100420926 - type: dot_ap value: 90.64355541781003 - type: dot_f1 value: 84.76466651795673 - type: dot_precision value: 81.04073363190446 - type: dot_recall value: 88.84732288987608 - type: euclidean_accuracy value: 83.59591100420926 - type: euclidean_ap value: 90.6547878194287 - type: euclidean_f1 value: 84.76466651795673 - type: euclidean_precision value: 81.04073363190446 - type: euclidean_recall value: 88.84732288987608 - type: manhattan_accuracy value: 83.51172579675286 - type: manhattan_ap value: 90.59941589844144 - type: manhattan_f1 value: 84.51827242524917 - type: manhattan_precision value: 80.28613507258574 - type: manhattan_recall value: 89.22141688099134 - type: max_accuracy value: 83.59591100420926 - type: max_ap value: 90.65538153970263 - type: max_f1 value: 84.76466651795673 - task: type: Retrieval dataset: type: C-MTEB/CovidRetrieval name: MTEB CovidRetrieval config: default split: dev revision: None metrics: - type: map_at_1 value: 63.251000000000005 - type: map_at_10 value: 72.442 - type: map_at_100 value: 72.79299999999999 - type: map_at_1000 value: 72.80499999999999 - type: map_at_3 value: 70.293 - type: map_at_5 value: 71.571 - type: mrr_at_1 value: 63.541000000000004 - type: mrr_at_10 value: 72.502 - type: mrr_at_100 value: 72.846 - type: mrr_at_1000 value: 72.858 - type: mrr_at_3 value: 70.39 - type: mrr_at_5 value: 71.654 - type: ndcg_at_1 value: 63.541000000000004 - type: ndcg_at_10 value: 76.774 - type: ndcg_at_100 value: 78.389 - type: ndcg_at_1000 value: 78.678 - type: ndcg_at_3 value: 72.47 - type: ndcg_at_5 value: 74.748 - type: precision_at_1 value: 63.541000000000004 - type: precision_at_10 value: 9.115 - type: precision_at_100 value: 0.9860000000000001 - type: precision_at_1000 value: 0.101 - type: precision_at_3 value: 26.379 - type: precision_at_5 value: 16.965 - type: recall_at_1 value: 63.251000000000005 - type: recall_at_10 value: 90.253 - type: recall_at_100 value: 97.576 - type: recall_at_1000 value: 99.789 - type: recall_at_3 value: 78.635 - type: recall_at_5 value: 84.141 - task: type: Retrieval dataset: type: C-MTEB/DuRetrieval name: MTEB DuRetrieval config: default split: dev revision: None metrics: - type: map_at_1 value: 23.597 - type: map_at_10 value: 72.411 - type: map_at_100 value: 75.58500000000001 - type: map_at_1000 value: 75.64800000000001 - type: map_at_3 value: 49.61 - type: map_at_5 value: 62.527 - type: mrr_at_1 value: 84.65 - type: mrr_at_10 value: 89.43900000000001 - type: mrr_at_100 value: 89.525 - type: mrr_at_1000 value: 89.529 - type: mrr_at_3 value: 89.0 - type: mrr_at_5 value: 89.297 - type: ndcg_at_1 value: 84.65 - type: ndcg_at_10 value: 81.47 - type: ndcg_at_100 value: 85.198 - type: ndcg_at_1000 value: 85.828 - type: ndcg_at_3 value: 79.809 - type: ndcg_at_5 value: 78.55 - type: precision_at_1 value: 84.65 - type: precision_at_10 value: 39.595 - type: precision_at_100 value: 4.707 - type: precision_at_1000 value: 0.485 - type: precision_at_3 value: 71.61699999999999 - type: precision_at_5 value: 60.45 - type: recall_at_1 value: 23.597 - type: recall_at_10 value: 83.34 - type: recall_at_100 value: 95.19800000000001 - type: recall_at_1000 value: 98.509 - type: recall_at_3 value: 52.744 - type: recall_at_5 value: 68.411 - task: type: Retrieval dataset: type: C-MTEB/EcomRetrieval name: MTEB EcomRetrieval config: default split: dev revision: None metrics: - type: map_at_1 value: 53.1 - type: map_at_10 value: 63.359 - type: map_at_100 value: 63.9 - type: map_at_1000 value: 63.909000000000006 - type: map_at_3 value: 60.95 - type: map_at_5 value: 62.305 - type: mrr_at_1 value: 53.1 - type: mrr_at_10 value: 63.359 - type: mrr_at_100 value: 63.9 - type: mrr_at_1000 value: 63.909000000000006 - type: mrr_at_3 value: 60.95 - type: mrr_at_5 value: 62.305 - type: ndcg_at_1 value: 53.1 - type: ndcg_at_10 value: 68.418 - type: ndcg_at_100 value: 70.88499999999999 - type: ndcg_at_1000 value: 71.135 - type: ndcg_at_3 value: 63.50599999999999 - type: ndcg_at_5 value: 65.92 - type: precision_at_1 value: 53.1 - type: precision_at_10 value: 8.43 - type: precision_at_100 value: 0.955 - type: precision_at_1000 value: 0.098 - type: precision_at_3 value: 23.633000000000003 - type: precision_at_5 value: 15.340000000000002 - type: recall_at_1 value: 53.1 - type: recall_at_10 value: 84.3 - type: recall_at_100 value: 95.5 - type: recall_at_1000 value: 97.5 - type: recall_at_3 value: 70.89999999999999 - type: recall_at_5 value: 76.7 - task: type: Classification dataset: type: C-MTEB/IFlyTek-classification name: MTEB IFlyTek config: default split: validation revision: None metrics: - type: accuracy value: 48.303193535975375 - type: f1 value: 35.96559358693866 - task: type: Classification dataset: type: C-MTEB/JDReview-classification name: MTEB JDReview config: default split: test revision: None metrics: - type: accuracy value: 85.06566604127579 - type: ap value: 52.0596483757231 - type: f1 value: 79.5196835127668 - task: type: STS dataset: type: C-MTEB/LCQMC name: MTEB LCQMC config: default split: test revision: None metrics: - type: cos_sim_pearson value: 74.48499423626059 - type: cos_sim_spearman value: 78.75806756061169 - type: euclidean_pearson value: 78.47917601852879 - type: euclidean_spearman value: 78.75807199272622 - type: manhattan_pearson value: 78.40207586289772 - type: manhattan_spearman value: 78.6911776964119 - task: type: Reranking dataset: type: C-MTEB/Mmarco-reranking name: MTEB MMarcoReranking config: default split: dev revision: None metrics: - type: map value: 24.75987466552363 - type: mrr value: 23.40515873015873 - task: type: Retrieval dataset: type: C-MTEB/MMarcoRetrieval name: MTEB MMarcoRetrieval config: default split: dev revision: None metrics: - type: map_at_1 value: 58.026999999999994 - type: map_at_10 value: 67.50699999999999 - type: map_at_100 value: 67.946 - type: map_at_1000 value: 67.96600000000001 - type: map_at_3 value: 65.503 - type: map_at_5 value: 66.649 - type: mrr_at_1 value: 60.20100000000001 - type: mrr_at_10 value: 68.271 - type: mrr_at_100 value: 68.664 - type: mrr_at_1000 value: 68.682 - type: mrr_at_3 value: 66.47800000000001 - type: mrr_at_5 value: 67.499 - type: ndcg_at_1 value: 60.20100000000001 - type: ndcg_at_10 value: 71.697 - type: ndcg_at_100 value: 73.736 - type: ndcg_at_1000 value: 74.259 - type: ndcg_at_3 value: 67.768 - type: ndcg_at_5 value: 69.72 - type: precision_at_1 value: 60.20100000000001 - type: precision_at_10 value: 8.927999999999999 - type: precision_at_100 value: 0.9950000000000001 - type: precision_at_1000 value: 0.104 - type: precision_at_3 value: 25.883 - type: precision_at_5 value: 16.55 - type: recall_at_1 value: 58.026999999999994 - type: recall_at_10 value: 83.966 - type: recall_at_100 value: 93.313 - type: recall_at_1000 value: 97.426 - type: recall_at_3 value: 73.342 - type: recall_at_5 value: 77.997 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (zh-CN) config: zh-CN split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 71.1600537995965 - type: f1 value: 68.8126216609964 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (zh-CN) config: zh-CN split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 73.54068594485541 - type: f1 value: 73.46845879869848 - task: type: Retrieval dataset: type: C-MTEB/MedicalRetrieval name: MTEB MedicalRetrieval config: default split: dev revision: None metrics: - type: map_at_1 value: 54.900000000000006 - type: map_at_10 value: 61.363 - type: map_at_100 value: 61.924 - type: map_at_1000 value: 61.967000000000006 - type: map_at_3 value: 59.767 - type: map_at_5 value: 60.802 - type: mrr_at_1 value: 55.1 - type: mrr_at_10 value: 61.454 - type: mrr_at_100 value: 62.016000000000005 - type: mrr_at_1000 value: 62.059 - type: mrr_at_3 value: 59.882999999999996 - type: mrr_at_5 value: 60.893 - type: ndcg_at_1 value: 54.900000000000006 - type: ndcg_at_10 value: 64.423 - type: ndcg_at_100 value: 67.35900000000001 - type: ndcg_at_1000 value: 68.512 - type: ndcg_at_3 value: 61.224000000000004 - type: ndcg_at_5 value: 63.083 - type: precision_at_1 value: 54.900000000000006 - type: precision_at_10 value: 7.3999999999999995 - type: precision_at_100 value: 0.882 - type: precision_at_1000 value: 0.097 - type: precision_at_3 value: 21.8 - type: precision_at_5 value: 13.98 - type: recall_at_1 value: 54.900000000000006 - type: recall_at_10 value: 74.0 - type: recall_at_100 value: 88.2 - type: recall_at_1000 value: 97.3 - type: recall_at_3 value: 65.4 - type: recall_at_5 value: 69.89999999999999 - task: type: Classification dataset: type: C-MTEB/MultilingualSentiment-classification name: MTEB MultilingualSentiment config: default split: validation revision: None metrics: - type: accuracy value: 75.15666666666667 - type: f1 value: 74.8306375354435 - task: type: PairClassification dataset: type: C-MTEB/OCNLI name: MTEB Ocnli config: default split: validation revision: None metrics: - type: cos_sim_accuracy value: 83.10774228478614 - type: cos_sim_ap value: 87.17679348388666 - type: cos_sim_f1 value: 84.59302325581395 - type: cos_sim_precision value: 78.15577439570276 - type: cos_sim_recall value: 92.18585005279832 - type: dot_accuracy value: 83.10774228478614 - type: dot_ap value: 87.17679348388666 - type: dot_f1 value: 84.59302325581395 - type: dot_precision value: 78.15577439570276 - type: dot_recall value: 92.18585005279832 - type: euclidean_accuracy value: 83.10774228478614 - type: euclidean_ap value: 87.17679348388666 - type: euclidean_f1 value: 84.59302325581395 - type: euclidean_precision value: 78.15577439570276 - type: euclidean_recall value: 92.18585005279832 - type: manhattan_accuracy value: 82.67460747157553 - type: manhattan_ap value: 86.94296334435238 - type: manhattan_f1 value: 84.32327166504382 - type: manhattan_precision value: 78.22944896115628 - type: manhattan_recall value: 91.4466737064414 - type: max_accuracy value: 83.10774228478614 - type: max_ap value: 87.17679348388666 - type: max_f1 value: 84.59302325581395 - task: type: Classification dataset: type: C-MTEB/OnlineShopping-classification name: MTEB OnlineShopping config: default split: test revision: None metrics: - type: accuracy value: 93.24999999999999 - type: ap value: 90.98617641063584 - type: f1 value: 93.23447883650289 - task: type: STS dataset: type: C-MTEB/PAWSX name: MTEB PAWSX config: default split: test revision: None metrics: - type: cos_sim_pearson value: 41.071417937737856 - type: cos_sim_spearman value: 45.049199344455424 - type: euclidean_pearson value: 44.913450096830786 - type: euclidean_spearman value: 45.05733424275291 - type: manhattan_pearson value: 44.881623825912065 - type: manhattan_spearman value: 44.989923561416596 - task: type: STS dataset: type: C-MTEB/QBQTC name: MTEB QBQTC config: default split: test revision: None metrics: - type: cos_sim_pearson value: 41.38238052689359 - type: cos_sim_spearman value: 42.61949690594399 - type: euclidean_pearson value: 40.61261500356766 - type: euclidean_spearman value: 42.619626605620724 - type: manhattan_pearson value: 40.8886109204474 - type: manhattan_spearman value: 42.75791523010463 - task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (zh) config: zh split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics: - type: cos_sim_pearson value: 62.10977863727196 - type: cos_sim_spearman value: 63.843727112473225 - type: euclidean_pearson value: 63.25133487817196 - type: euclidean_spearman value: 63.843727112473225 - type: manhattan_pearson value: 63.58749018644103 - type: manhattan_spearman value: 63.83820575456674 - task: type: STS dataset: type: C-MTEB/STSB name: MTEB STSB config: default split: test revision: None metrics: - type: cos_sim_pearson value: 79.30616496720054 - type: cos_sim_spearman value: 80.767935782436 - type: euclidean_pearson value: 80.4160642670106 - type: euclidean_spearman value: 80.76820284024356 - type: manhattan_pearson value: 80.27318714580251 - type: manhattan_spearman value: 80.61030164164964 - task: type: Reranking dataset: type: C-MTEB/T2Reranking name: MTEB T2Reranking config: default split: dev revision: None metrics: - type: map value: 66.26242871142425 - type: mrr value: 76.20689863623174 - task: type: Retrieval dataset: type: C-MTEB/T2Retrieval name: MTEB T2Retrieval config: default split: dev revision: None metrics: - type: map_at_1 value: 26.240999999999996 - type: map_at_10 value: 73.009 - type: map_at_100 value: 76.893 - type: map_at_1000 value: 76.973 - type: map_at_3 value: 51.339 - type: map_at_5 value: 63.003 - type: mrr_at_1 value: 87.458 - type: mrr_at_10 value: 90.44 - type: mrr_at_100 value: 90.558 - type: mrr_at_1000 value: 90.562 - type: mrr_at_3 value: 89.89 - type: mrr_at_5 value: 90.231 - type: ndcg_at_1 value: 87.458 - type: ndcg_at_10 value: 81.325 - type: ndcg_at_100 value: 85.61999999999999 - type: ndcg_at_1000 value: 86.394 - type: ndcg_at_3 value: 82.796 - type: ndcg_at_5 value: 81.219 - type: precision_at_1 value: 87.458 - type: precision_at_10 value: 40.534 - type: precision_at_100 value: 4.96 - type: precision_at_1000 value: 0.514 - type: precision_at_3 value: 72.444 - type: precision_at_5 value: 60.601000000000006 - type: recall_at_1 value: 26.240999999999996 - type: recall_at_10 value: 80.42 - type: recall_at_100 value: 94.118 - type: recall_at_1000 value: 98.02199999999999 - type: recall_at_3 value: 53.174 - type: recall_at_5 value: 66.739 - task: type: Classification dataset: type: C-MTEB/TNews-classification name: MTEB TNews config: default split: validation revision: None metrics: - type: accuracy value: 52.40899999999999 - type: f1 value: 50.68532128056062 - task: type: Clustering dataset: type: C-MTEB/ThuNewsClusteringP2P name: MTEB ThuNewsClusteringP2P config: default split: test revision: None metrics: - type: v_measure value: 65.57616085176686 - task: type: Clustering dataset: type: C-MTEB/ThuNewsClusteringS2S name: MTEB ThuNewsClusteringS2S config: default split: test revision: None metrics: - type: v_measure value: 58.844999922904925 - task: type: Retrieval dataset: type: C-MTEB/VideoRetrieval name: MTEB VideoRetrieval config: default split: dev revision: None metrics: - type: map_at_1 value: 58.4 - type: map_at_10 value: 68.64 - type: map_at_100 value: 69.062 - type: map_at_1000 value: 69.073 - type: map_at_3 value: 66.567 - type: map_at_5 value: 67.89699999999999 - type: mrr_at_1 value: 58.4 - type: mrr_at_10 value: 68.64 - type: mrr_at_100 value: 69.062 - type: mrr_at_1000 value: 69.073 - type: mrr_at_3 value: 66.567 - type: mrr_at_5 value: 67.89699999999999 - type: ndcg_at_1 value: 58.4 - type: ndcg_at_10 value: 73.30600000000001 - type: ndcg_at_100 value: 75.276 - type: ndcg_at_1000 value: 75.553 - type: ndcg_at_3 value: 69.126 - type: ndcg_at_5 value: 71.519 - type: precision_at_1 value: 58.4 - type: precision_at_10 value: 8.780000000000001 - type: precision_at_100 value: 0.968 - type: precision_at_1000 value: 0.099 - type: precision_at_3 value: 25.5 - type: precision_at_5 value: 16.46 - type: recall_at_1 value: 58.4 - type: recall_at_10 value: 87.8 - type: recall_at_100 value: 96.8 - type: recall_at_1000 value: 99.0 - type: recall_at_3 value: 76.5 - type: recall_at_5 value: 82.3 - task: type: Classification dataset: type: C-MTEB/waimai-classification name: MTEB Waimai config: default split: test revision: None metrics: - type: accuracy value: 86.21000000000001 - type: ap value: 69.17460264576461 - type: f1 value: 84.68032984659226 --- # Dmeta-embedding ## Usage (Sentence-Transformers) Using this model becomes easy when you have [sentence-transformers](https://www.SBERT.net) installed: ``` pip install -U sentence-transformers ``` Then you can use the model like this: ```python from sentence_transformers import SentenceTransformer sentences = ["This is an example sentence", "Each sentence is converted"] model = SentenceTransformer('{MODEL_NAME}') embeddings = model.encode(sentences) print(embeddings) ``` ## Citing & Authors