--- pipeline_tag: sentence-similarity tags: - finetuner - sentence-transformers - feature-extraction - sentence-similarity - mteb datasets: - jinaai/negation-dataset language: en license: apache-2.0 model-index: - name: jina-embedding-s-en-v2 results: - task: type: Classification dataset: type: mteb/amazon_counterfactual name: MTEB AmazonCounterfactualClassification (en) config: en split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics: - type: accuracy value: 69.70149253731343 - type: ap value: 32.22528779918184 - type: f1 value: 63.66857824618267 - task: type: Classification dataset: type: mteb/amazon_polarity name: MTEB AmazonPolarityClassification config: default split: test revision: e2d317d38cd51312af73b3d32a06d1a08b442046 metrics: - type: accuracy value: 79.55879999999999 - type: ap value: 73.97885664972738 - type: f1 value: 79.4849322624122 - task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (en) config: en split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics: - type: accuracy value: 38.69 - type: f1 value: 37.17512734389121 - task: type: Retrieval dataset: type: arguana name: MTEB ArguAna config: default split: test revision: None metrics: - type: map_at_1 value: 23.684 - type: map_at_10 value: 39.086999999999996 - type: map_at_100 value: 40.222 - type: map_at_1000 value: 40.231 - type: map_at_3 value: 34.282000000000004 - type: map_at_5 value: 36.689 - type: mrr_at_1 value: 23.826 - type: mrr_at_10 value: 39.147 - type: mrr_at_100 value: 40.282000000000004 - type: mrr_at_1000 value: 40.291 - type: mrr_at_3 value: 34.353 - type: mrr_at_5 value: 36.739 - type: ndcg_at_1 value: 23.684 - type: ndcg_at_10 value: 48.081 - type: ndcg_at_100 value: 52.902 - type: ndcg_at_1000 value: 53.111 - type: ndcg_at_3 value: 37.937 - type: ndcg_at_5 value: 42.32 - type: precision_at_1 value: 23.684 - type: precision_at_10 value: 7.703 - type: precision_at_100 value: 0.98 - type: precision_at_1000 value: 0.1 - type: precision_at_3 value: 16.192999999999998 - type: precision_at_5 value: 11.863 - type: recall_at_1 value: 23.684 - type: recall_at_10 value: 77.027 - type: recall_at_100 value: 98.009 - type: recall_at_1000 value: 99.57300000000001 - type: recall_at_3 value: 48.577999999999996 - type: recall_at_5 value: 59.317 - task: type: Clustering dataset: type: mteb/arxiv-clustering-p2p name: MTEB ArxivClusteringP2P config: default split: test revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d metrics: - type: v_measure value: 44.249612940073035 - task: type: Clustering dataset: type: mteb/arxiv-clustering-s2s name: MTEB ArxivClusteringS2S config: default split: test revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 metrics: - type: v_measure value: 35.39423011105325 - task: type: Reranking dataset: type: mteb/askubuntudupquestions-reranking name: MTEB AskUbuntuDupQuestions config: default split: test revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 metrics: - type: map value: 59.89078304869791 - type: mrr value: 73.5045948203843 - task: type: STS dataset: type: mteb/biosses-sts name: MTEB BIOSSES config: default split: test revision: d3fb88f8f02e40887cd149695127462bbcf29b4a metrics: - type: cos_sim_pearson value: 82.49373811125967 - type: cos_sim_spearman value: 81.0446177409314 - type: euclidean_pearson value: 82.1327844624042 - type: euclidean_spearman value: 81.0446177409314 - type: manhattan_pearson value: 81.88575541723692 - type: manhattan_spearman value: 81.0705219456341 - task: type: Classification dataset: type: mteb/banking77 name: MTEB Banking77Classification config: default split: test revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 metrics: - type: accuracy value: 78.27272727272728 - type: f1 value: 77.36583416688741 - task: type: Clustering dataset: type: mteb/biorxiv-clustering-p2p name: MTEB BiorxivClusteringP2P config: default split: test revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 metrics: - type: v_measure value: 36.12447585258704 - task: type: Clustering dataset: type: mteb/biorxiv-clustering-s2s name: MTEB BiorxivClusteringS2S config: default split: test revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 metrics: - type: v_measure value: 29.305990951348743 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackAndroidRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 31.458000000000002 - type: map_at_10 value: 42.132 - type: map_at_100 value: 43.47 - type: map_at_1000 value: 43.612 - type: map_at_3 value: 38.718 - type: map_at_5 value: 40.556 - type: mrr_at_1 value: 38.627 - type: mrr_at_10 value: 47.998000000000005 - type: mrr_at_100 value: 48.726 - type: mrr_at_1000 value: 48.778 - type: mrr_at_3 value: 45.255 - type: mrr_at_5 value: 46.893 - type: ndcg_at_1 value: 38.627 - type: ndcg_at_10 value: 48.229 - type: ndcg_at_100 value: 53.108999999999995 - type: ndcg_at_1000 value: 55.385 - type: ndcg_at_3 value: 43.191 - type: ndcg_at_5 value: 45.385999999999996 - type: precision_at_1 value: 38.627 - type: precision_at_10 value: 9.142 - type: precision_at_100 value: 1.462 - type: precision_at_1000 value: 0.19499999999999998 - type: precision_at_3 value: 20.552999999999997 - type: precision_at_5 value: 14.677999999999999 - type: recall_at_1 value: 31.458000000000002 - type: recall_at_10 value: 59.619 - type: recall_at_100 value: 79.953 - type: recall_at_1000 value: 94.921 - type: recall_at_3 value: 44.744 - type: recall_at_5 value: 51.010999999999996 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackEnglishRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 26.762000000000004 - type: map_at_10 value: 35.366 - type: map_at_100 value: 36.481 - type: map_at_1000 value: 36.614999999999995 - type: map_at_3 value: 33.071 - type: map_at_5 value: 34.495 - type: mrr_at_1 value: 33.312000000000005 - type: mrr_at_10 value: 40.841 - type: mrr_at_100 value: 41.54 - type: mrr_at_1000 value: 41.592 - type: mrr_at_3 value: 38.928000000000004 - type: mrr_at_5 value: 40.119 - type: ndcg_at_1 value: 33.312000000000005 - type: ndcg_at_10 value: 40.238 - type: ndcg_at_100 value: 44.647 - type: ndcg_at_1000 value: 47.010999999999996 - type: ndcg_at_3 value: 36.991 - type: ndcg_at_5 value: 38.721 - type: precision_at_1 value: 33.312000000000005 - type: precision_at_10 value: 7.4079999999999995 - type: precision_at_100 value: 1.253 - type: precision_at_1000 value: 0.17500000000000002 - type: precision_at_3 value: 17.898 - type: precision_at_5 value: 12.687999999999999 - type: recall_at_1 value: 26.762000000000004 - type: recall_at_10 value: 48.41 - type: recall_at_100 value: 67.523 - type: recall_at_1000 value: 82.91199999999999 - type: recall_at_3 value: 38.6 - type: recall_at_5 value: 43.477 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGamingRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 37.578 - type: map_at_10 value: 49.415 - type: map_at_100 value: 50.339 - type: map_at_1000 value: 50.402 - type: map_at_3 value: 46.412 - type: map_at_5 value: 48.183 - type: mrr_at_1 value: 43.072 - type: mrr_at_10 value: 52.82599999999999 - type: mrr_at_100 value: 53.456 - type: mrr_at_1000 value: 53.493 - type: mrr_at_3 value: 50.407999999999994 - type: mrr_at_5 value: 51.922000000000004 - type: ndcg_at_1 value: 43.072 - type: ndcg_at_10 value: 54.949000000000005 - type: ndcg_at_100 value: 58.744 - type: ndcg_at_1000 value: 60.150000000000006 - type: ndcg_at_3 value: 49.864000000000004 - type: ndcg_at_5 value: 52.503 - type: precision_at_1 value: 43.072 - type: precision_at_10 value: 8.734 - type: precision_at_100 value: 1.1520000000000001 - type: precision_at_1000 value: 0.132 - type: precision_at_3 value: 22.131999999999998 - type: precision_at_5 value: 15.21 - type: recall_at_1 value: 37.578 - type: recall_at_10 value: 67.918 - type: recall_at_100 value: 84.373 - type: recall_at_1000 value: 94.529 - type: recall_at_3 value: 54.457 - type: recall_at_5 value: 60.941 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGisRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 23.394000000000002 - type: map_at_10 value: 31.791000000000004 - type: map_at_100 value: 32.64 - type: map_at_1000 value: 32.727000000000004 - type: map_at_3 value: 29.557 - type: map_at_5 value: 30.858999999999998 - type: mrr_at_1 value: 25.085 - type: mrr_at_10 value: 33.721000000000004 - type: mrr_at_100 value: 34.492 - type: mrr_at_1000 value: 34.564 - type: mrr_at_3 value: 31.619999999999997 - type: mrr_at_5 value: 32.896 - type: ndcg_at_1 value: 25.085 - type: ndcg_at_10 value: 36.370000000000005 - type: ndcg_at_100 value: 40.96 - type: ndcg_at_1000 value: 43.171 - type: ndcg_at_3 value: 32.104 - type: ndcg_at_5 value: 34.300000000000004 - type: precision_at_1 value: 25.085 - type: precision_at_10 value: 5.537 - type: precision_at_100 value: 0.8340000000000001 - type: precision_at_1000 value: 0.105 - type: precision_at_3 value: 13.71 - type: precision_at_5 value: 9.514 - type: recall_at_1 value: 23.394000000000002 - type: recall_at_10 value: 48.549 - type: recall_at_100 value: 70.341 - type: recall_at_1000 value: 87.01299999999999 - type: recall_at_3 value: 36.947 - type: recall_at_5 value: 42.365 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackMathematicaRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 14.818000000000001 - type: map_at_10 value: 21.773999999999997 - type: map_at_100 value: 22.787 - type: map_at_1000 value: 22.915 - type: map_at_3 value: 19.414 - type: map_at_5 value: 20.651 - type: mrr_at_1 value: 18.657 - type: mrr_at_10 value: 25.794 - type: mrr_at_100 value: 26.695999999999998 - type: mrr_at_1000 value: 26.776 - type: mrr_at_3 value: 23.279 - type: mrr_at_5 value: 24.598 - type: ndcg_at_1 value: 18.657 - type: ndcg_at_10 value: 26.511000000000003 - type: ndcg_at_100 value: 31.447999999999997 - type: ndcg_at_1000 value: 34.71 - type: ndcg_at_3 value: 21.92 - type: ndcg_at_5 value: 23.938000000000002 - type: precision_at_1 value: 18.657 - type: precision_at_10 value: 4.9 - type: precision_at_100 value: 0.851 - type: precision_at_1000 value: 0.127 - type: precision_at_3 value: 10.488999999999999 - type: precision_at_5 value: 7.710999999999999 - type: recall_at_1 value: 14.818000000000001 - type: recall_at_10 value: 37.408 - type: recall_at_100 value: 58.81999999999999 - type: recall_at_1000 value: 82.612 - type: recall_at_3 value: 24.561 - type: recall_at_5 value: 29.685 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackPhysicsRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 26.332 - type: map_at_10 value: 35.366 - type: map_at_100 value: 36.569 - type: map_at_1000 value: 36.689 - type: map_at_3 value: 32.582 - type: map_at_5 value: 34.184 - type: mrr_at_1 value: 32.05 - type: mrr_at_10 value: 40.902 - type: mrr_at_100 value: 41.754000000000005 - type: mrr_at_1000 value: 41.811 - type: mrr_at_3 value: 38.547 - type: mrr_at_5 value: 40.019 - type: ndcg_at_1 value: 32.05 - type: ndcg_at_10 value: 40.999 - type: ndcg_at_100 value: 46.284 - type: ndcg_at_1000 value: 48.698 - type: ndcg_at_3 value: 36.39 - type: ndcg_at_5 value: 38.699 - type: precision_at_1 value: 32.05 - type: precision_at_10 value: 7.315 - type: precision_at_100 value: 1.172 - type: precision_at_1000 value: 0.156 - type: precision_at_3 value: 17.036 - type: precision_at_5 value: 12.089 - type: recall_at_1 value: 26.332 - type: recall_at_10 value: 52.410000000000004 - type: recall_at_100 value: 74.763 - type: recall_at_1000 value: 91.03 - type: recall_at_3 value: 39.527 - type: recall_at_5 value: 45.517 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackProgrammersRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 22.849 - type: map_at_10 value: 31.502000000000002 - type: map_at_100 value: 32.854 - type: map_at_1000 value: 32.975 - type: map_at_3 value: 28.997 - type: map_at_5 value: 30.508999999999997 - type: mrr_at_1 value: 28.195999999999998 - type: mrr_at_10 value: 36.719 - type: mrr_at_100 value: 37.674 - type: mrr_at_1000 value: 37.743 - type: mrr_at_3 value: 34.532000000000004 - type: mrr_at_5 value: 35.845 - type: ndcg_at_1 value: 28.195999999999998 - type: ndcg_at_10 value: 36.605 - type: ndcg_at_100 value: 42.524 - type: ndcg_at_1000 value: 45.171 - type: ndcg_at_3 value: 32.574 - type: ndcg_at_5 value: 34.617 - type: precision_at_1 value: 28.195999999999998 - type: precision_at_10 value: 6.598 - type: precision_at_100 value: 1.121 - type: precision_at_1000 value: 0.153 - type: precision_at_3 value: 15.601 - type: precision_at_5 value: 11.073 - type: recall_at_1 value: 22.849 - type: recall_at_10 value: 46.528000000000006 - type: recall_at_100 value: 72.09 - type: recall_at_1000 value: 90.398 - type: recall_at_3 value: 35.116 - type: recall_at_5 value: 40.778 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 24.319500000000005 - type: map_at_10 value: 32.530166666666666 - type: map_at_100 value: 33.61566666666667 - type: map_at_1000 value: 33.73808333333333 - type: map_at_3 value: 30.074583333333326 - type: map_at_5 value: 31.429666666666662 - type: mrr_at_1 value: 28.675916666666666 - type: mrr_at_10 value: 36.49308333333334 - type: mrr_at_100 value: 37.310583333333334 - type: mrr_at_1000 value: 37.37616666666666 - type: mrr_at_3 value: 34.283166666666666 - type: mrr_at_5 value: 35.54333333333334 - type: ndcg_at_1 value: 28.675916666666666 - type: ndcg_at_10 value: 37.403416666666665 - type: ndcg_at_100 value: 42.25783333333333 - type: ndcg_at_1000 value: 44.778333333333336 - type: ndcg_at_3 value: 33.17099999999999 - type: ndcg_at_5 value: 35.12666666666667 - type: precision_at_1 value: 28.675916666666666 - type: precision_at_10 value: 6.463083333333334 - type: precision_at_100 value: 1.0585 - type: precision_at_1000 value: 0.14633333333333332 - type: precision_at_3 value: 15.158999999999997 - type: precision_at_5 value: 10.673916666666667 - type: recall_at_1 value: 24.319500000000005 - type: recall_at_10 value: 47.9135 - type: recall_at_100 value: 69.40266666666666 - type: recall_at_1000 value: 87.12566666666666 - type: recall_at_3 value: 36.03149999999999 - type: recall_at_5 value: 41.12791666666668 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackStatsRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 22.997 - type: map_at_10 value: 28.754999999999995 - type: map_at_100 value: 29.555999999999997 - type: map_at_1000 value: 29.653000000000002 - type: map_at_3 value: 27.069 - type: map_at_5 value: 27.884999999999998 - type: mrr_at_1 value: 25.767 - type: mrr_at_10 value: 31.195 - type: mrr_at_100 value: 31.964 - type: mrr_at_1000 value: 32.039 - type: mrr_at_3 value: 29.601 - type: mrr_at_5 value: 30.345 - type: ndcg_at_1 value: 25.767 - type: ndcg_at_10 value: 32.234 - type: ndcg_at_100 value: 36.461 - type: ndcg_at_1000 value: 39.005 - type: ndcg_at_3 value: 29.052 - type: ndcg_at_5 value: 30.248 - type: precision_at_1 value: 25.767 - type: precision_at_10 value: 4.893 - type: precision_at_100 value: 0.761 - type: precision_at_1000 value: 0.105 - type: precision_at_3 value: 12.219 - type: precision_at_5 value: 8.19 - type: recall_at_1 value: 22.997 - type: recall_at_10 value: 40.652 - type: recall_at_100 value: 60.302 - type: recall_at_1000 value: 79.17999999999999 - type: recall_at_3 value: 31.680999999999997 - type: recall_at_5 value: 34.698 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackTexRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 16.3 - type: map_at_10 value: 22.581 - type: map_at_100 value: 23.517 - type: map_at_1000 value: 23.638 - type: map_at_3 value: 20.567 - type: map_at_5 value: 21.688 - type: mrr_at_1 value: 19.683 - type: mrr_at_10 value: 26.185000000000002 - type: mrr_at_100 value: 27.014 - type: mrr_at_1000 value: 27.092 - type: mrr_at_3 value: 24.145 - type: mrr_at_5 value: 25.308999999999997 - type: ndcg_at_1 value: 19.683 - type: ndcg_at_10 value: 26.699 - type: ndcg_at_100 value: 31.35 - type: ndcg_at_1000 value: 34.348 - type: ndcg_at_3 value: 23.026 - type: ndcg_at_5 value: 24.731 - type: precision_at_1 value: 19.683 - type: precision_at_10 value: 4.814 - type: precision_at_100 value: 0.836 - type: precision_at_1000 value: 0.126 - type: precision_at_3 value: 10.782 - type: precision_at_5 value: 7.825 - type: recall_at_1 value: 16.3 - type: recall_at_10 value: 35.521 - type: recall_at_100 value: 56.665 - type: recall_at_1000 value: 78.361 - type: recall_at_3 value: 25.223000000000003 - type: recall_at_5 value: 29.626 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackUnixRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 24.596999999999998 - type: map_at_10 value: 32.54 - type: map_at_100 value: 33.548 - type: map_at_1000 value: 33.661 - type: map_at_3 value: 30.134 - type: map_at_5 value: 31.468 - type: mrr_at_1 value: 28.825 - type: mrr_at_10 value: 36.495 - type: mrr_at_100 value: 37.329 - type: mrr_at_1000 value: 37.397999999999996 - type: mrr_at_3 value: 34.359 - type: mrr_at_5 value: 35.53 - type: ndcg_at_1 value: 28.825 - type: ndcg_at_10 value: 37.341 - type: ndcg_at_100 value: 42.221 - type: ndcg_at_1000 value: 44.799 - type: ndcg_at_3 value: 33.058 - type: ndcg_at_5 value: 34.961999999999996 - type: precision_at_1 value: 28.825 - type: precision_at_10 value: 6.175 - type: precision_at_100 value: 0.97 - type: precision_at_1000 value: 0.13 - type: precision_at_3 value: 14.924999999999999 - type: precision_at_5 value: 10.392 - type: recall_at_1 value: 24.596999999999998 - type: recall_at_10 value: 48.067 - type: recall_at_100 value: 69.736 - type: recall_at_1000 value: 87.855 - type: recall_at_3 value: 36.248999999999995 - type: recall_at_5 value: 41.086 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWebmastersRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 24.224999999999998 - type: map_at_10 value: 31.826 - type: map_at_100 value: 33.366 - type: map_at_1000 value: 33.6 - type: map_at_3 value: 29.353 - type: map_at_5 value: 30.736 - type: mrr_at_1 value: 28.656 - type: mrr_at_10 value: 36.092 - type: mrr_at_100 value: 37.076 - type: mrr_at_1000 value: 37.141999999999996 - type: mrr_at_3 value: 33.86 - type: mrr_at_5 value: 35.144999999999996 - type: ndcg_at_1 value: 28.656 - type: ndcg_at_10 value: 37.025999999999996 - type: ndcg_at_100 value: 42.844 - type: ndcg_at_1000 value: 45.716 - type: ndcg_at_3 value: 32.98 - type: ndcg_at_5 value: 34.922 - type: precision_at_1 value: 28.656 - type: precision_at_10 value: 6.976 - type: precision_at_100 value: 1.48 - type: precision_at_1000 value: 0.23700000000000002 - type: precision_at_3 value: 15.348999999999998 - type: precision_at_5 value: 11.028 - type: recall_at_1 value: 24.224999999999998 - type: recall_at_10 value: 46.589999999999996 - type: recall_at_100 value: 72.331 - type: recall_at_1000 value: 90.891 - type: recall_at_3 value: 34.996 - type: recall_at_5 value: 40.294000000000004 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWordpressRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 20.524 - type: map_at_10 value: 27.314 - type: map_at_100 value: 28.260999999999996 - type: map_at_1000 value: 28.37 - type: map_at_3 value: 25.020999999999997 - type: map_at_5 value: 25.942 - type: mrr_at_1 value: 22.181 - type: mrr_at_10 value: 29.149 - type: mrr_at_100 value: 30.006 - type: mrr_at_1000 value: 30.086000000000002 - type: mrr_at_3 value: 26.863999999999997 - type: mrr_at_5 value: 27.899 - type: ndcg_at_1 value: 22.181 - type: ndcg_at_10 value: 31.64 - type: ndcg_at_100 value: 36.502 - type: ndcg_at_1000 value: 39.176 - type: ndcg_at_3 value: 26.901999999999997 - type: ndcg_at_5 value: 28.493000000000002 - type: precision_at_1 value: 22.181 - type: precision_at_10 value: 5.065 - type: precision_at_100 value: 0.8099999999999999 - type: precision_at_1000 value: 0.11499999999999999 - type: precision_at_3 value: 11.214 - type: precision_at_5 value: 7.689 - type: recall_at_1 value: 20.524 - type: recall_at_10 value: 43.29 - type: recall_at_100 value: 65.935 - type: recall_at_1000 value: 85.80600000000001 - type: recall_at_3 value: 30.276999999999997 - type: recall_at_5 value: 34.056999999999995 - task: type: Retrieval dataset: type: climate-fever name: MTEB ClimateFEVER config: default split: test revision: None metrics: - type: map_at_1 value: 10.488999999999999 - type: map_at_10 value: 17.98 - type: map_at_100 value: 19.581 - type: map_at_1000 value: 19.739 - type: map_at_3 value: 15.054 - type: map_at_5 value: 16.439999999999998 - type: mrr_at_1 value: 23.192 - type: mrr_at_10 value: 33.831 - type: mrr_at_100 value: 34.833 - type: mrr_at_1000 value: 34.881 - type: mrr_at_3 value: 30.793 - type: mrr_at_5 value: 32.535 - type: ndcg_at_1 value: 23.192 - type: ndcg_at_10 value: 25.446 - type: ndcg_at_100 value: 31.948 - type: ndcg_at_1000 value: 35.028 - type: ndcg_at_3 value: 20.744 - type: ndcg_at_5 value: 22.233 - type: precision_at_1 value: 23.192 - type: precision_at_10 value: 8.026 - type: precision_at_100 value: 1.482 - type: precision_at_1000 value: 0.20500000000000002 - type: precision_at_3 value: 15.548 - type: precision_at_5 value: 11.87 - type: recall_at_1 value: 10.488999999999999 - type: recall_at_10 value: 30.865 - type: recall_at_100 value: 53.428 - type: recall_at_1000 value: 70.89 - type: recall_at_3 value: 19.245 - type: recall_at_5 value: 23.657 - task: type: Retrieval dataset: type: dbpedia-entity name: MTEB DBPedia config: default split: test revision: None metrics: - type: map_at_1 value: 7.123 - type: map_at_10 value: 14.448 - type: map_at_100 value: 19.798 - type: map_at_1000 value: 21.082 - type: map_at_3 value: 10.815 - type: map_at_5 value: 12.422 - type: mrr_at_1 value: 53.5 - type: mrr_at_10 value: 63.117999999999995 - type: mrr_at_100 value: 63.617999999999995 - type: mrr_at_1000 value: 63.63799999999999 - type: mrr_at_3 value: 60.708 - type: mrr_at_5 value: 62.171 - type: ndcg_at_1 value: 42.125 - type: ndcg_at_10 value: 31.703 - type: ndcg_at_100 value: 35.935 - type: ndcg_at_1000 value: 43.173 - type: ndcg_at_3 value: 35.498000000000005 - type: ndcg_at_5 value: 33.645 - type: precision_at_1 value: 53.5 - type: precision_at_10 value: 25.025 - type: precision_at_100 value: 8.19 - type: precision_at_1000 value: 1.806 - type: precision_at_3 value: 39.083 - type: precision_at_5 value: 33.050000000000004 - type: recall_at_1 value: 7.123 - type: recall_at_10 value: 19.581 - type: recall_at_100 value: 42.061 - type: recall_at_1000 value: 65.879 - type: recall_at_3 value: 12.026 - type: recall_at_5 value: 14.846 - task: type: Classification dataset: type: mteb/emotion name: MTEB EmotionClassification config: default split: test revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 metrics: - type: accuracy value: 41.24 - type: f1 value: 36.76174115773002 - task: type: Retrieval dataset: type: fever name: MTEB FEVER config: default split: test revision: None metrics: - type: map_at_1 value: 47.821999999999996 - type: map_at_10 value: 59.794000000000004 - type: map_at_100 value: 60.316 - type: map_at_1000 value: 60.34 - type: map_at_3 value: 57.202 - type: map_at_5 value: 58.823 - type: mrr_at_1 value: 51.485 - type: mrr_at_10 value: 63.709 - type: mrr_at_100 value: 64.144 - type: mrr_at_1000 value: 64.158 - type: mrr_at_3 value: 61.251 - type: mrr_at_5 value: 62.818 - type: ndcg_at_1 value: 51.485 - type: ndcg_at_10 value: 66.097 - type: ndcg_at_100 value: 68.37 - type: ndcg_at_1000 value: 68.916 - type: ndcg_at_3 value: 61.12800000000001 - type: ndcg_at_5 value: 63.885000000000005 - type: precision_at_1 value: 51.485 - type: precision_at_10 value: 8.956999999999999 - type: precision_at_100 value: 1.02 - type: precision_at_1000 value: 0.108 - type: precision_at_3 value: 24.807000000000002 - type: precision_at_5 value: 16.387999999999998 - type: recall_at_1 value: 47.821999999999996 - type: recall_at_10 value: 81.773 - type: recall_at_100 value: 91.731 - type: recall_at_1000 value: 95.649 - type: recall_at_3 value: 68.349 - type: recall_at_5 value: 75.093 - task: type: Retrieval dataset: type: fiqa name: MTEB FiQA2018 config: default split: test revision: None metrics: - type: map_at_1 value: 15.662999999999998 - type: map_at_10 value: 25.726 - type: map_at_100 value: 27.581 - type: map_at_1000 value: 27.772000000000002 - type: map_at_3 value: 21.859 - type: map_at_5 value: 24.058 - type: mrr_at_1 value: 30.247 - type: mrr_at_10 value: 39.581 - type: mrr_at_100 value: 40.594 - type: mrr_at_1000 value: 40.647 - type: mrr_at_3 value: 37.166 - type: mrr_at_5 value: 38.585 - type: ndcg_at_1 value: 30.247 - type: ndcg_at_10 value: 32.934999999999995 - type: ndcg_at_100 value: 40.062999999999995 - type: ndcg_at_1000 value: 43.492 - type: ndcg_at_3 value: 28.871000000000002 - type: ndcg_at_5 value: 30.492 - type: precision_at_1 value: 30.247 - type: precision_at_10 value: 9.522 - type: precision_at_100 value: 1.645 - type: precision_at_1000 value: 0.22499999999999998 - type: precision_at_3 value: 19.136 - type: precision_at_5 value: 14.753 - type: recall_at_1 value: 15.662999999999998 - type: recall_at_10 value: 39.595 - type: recall_at_100 value: 66.49199999999999 - type: recall_at_1000 value: 87.19 - type: recall_at_3 value: 26.346999999999998 - type: recall_at_5 value: 32.423 - task: type: Retrieval dataset: type: hotpotqa name: MTEB HotpotQA config: default split: test revision: None metrics: - type: map_at_1 value: 30.176 - type: map_at_10 value: 42.684 - type: map_at_100 value: 43.582 - type: map_at_1000 value: 43.668 - type: map_at_3 value: 39.964 - type: map_at_5 value: 41.589 - type: mrr_at_1 value: 60.351 - type: mrr_at_10 value: 67.669 - type: mrr_at_100 value: 68.089 - type: mrr_at_1000 value: 68.111 - type: mrr_at_3 value: 66.144 - type: mrr_at_5 value: 67.125 - type: ndcg_at_1 value: 60.351 - type: ndcg_at_10 value: 51.602000000000004 - type: ndcg_at_100 value: 55.186 - type: ndcg_at_1000 value: 56.96 - type: ndcg_at_3 value: 47.251 - type: ndcg_at_5 value: 49.584 - type: precision_at_1 value: 60.351 - type: precision_at_10 value: 10.804 - type: precision_at_100 value: 1.3639999999999999 - type: precision_at_1000 value: 0.16 - type: precision_at_3 value: 29.561 - type: precision_at_5 value: 19.581 - type: recall_at_1 value: 30.176 - type: recall_at_10 value: 54.018 - type: recall_at_100 value: 68.22399999999999 - type: recall_at_1000 value: 79.97999999999999 - type: recall_at_3 value: 44.342 - type: recall_at_5 value: 48.953 - task: type: Classification dataset: type: mteb/imdb name: MTEB ImdbClassification config: default split: test revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 metrics: - type: accuracy value: 71.28320000000001 - type: ap value: 65.20730065157146 - type: f1 value: 71.19193683354304 - task: type: Retrieval dataset: type: msmarco name: MTEB MSMARCO config: default split: dev revision: None metrics: - type: map_at_1 value: 19.686 - type: map_at_10 value: 31.189 - type: map_at_100 value: 32.368 - type: map_at_1000 value: 32.43 - type: map_at_3 value: 27.577 - type: map_at_5 value: 29.603 - type: mrr_at_1 value: 20.201 - type: mrr_at_10 value: 31.762 - type: mrr_at_100 value: 32.882 - type: mrr_at_1000 value: 32.937 - type: mrr_at_3 value: 28.177999999999997 - type: mrr_at_5 value: 30.212 - type: ndcg_at_1 value: 20.215 - type: ndcg_at_10 value: 37.730999999999995 - type: ndcg_at_100 value: 43.501 - type: ndcg_at_1000 value: 45.031 - type: ndcg_at_3 value: 30.336000000000002 - type: ndcg_at_5 value: 33.961000000000006 - type: precision_at_1 value: 20.215 - type: precision_at_10 value: 6.036 - type: precision_at_100 value: 0.895 - type: precision_at_1000 value: 0.10300000000000001 - type: precision_at_3 value: 13.028 - type: precision_at_5 value: 9.633 - type: recall_at_1 value: 19.686 - type: recall_at_10 value: 57.867999999999995 - type: recall_at_100 value: 84.758 - type: recall_at_1000 value: 96.44500000000001 - type: recall_at_3 value: 37.726 - type: recall_at_5 value: 46.415 - task: type: Classification dataset: type: mteb/mtop_domain name: MTEB MTOPDomainClassification (en) config: en split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics: - type: accuracy value: 89.76972184222525 - type: f1 value: 89.11949030406099 - task: type: Classification dataset: type: mteb/mtop_intent name: MTEB MTOPIntentClassification (en) config: en split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics: - type: accuracy value: 55.57455540355677 - type: f1 value: 39.344920096224506 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (en) config: en split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 63.772696704774724 - type: f1 value: 60.70041499812703 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (en) config: en split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 69.16274377942166 - type: f1 value: 68.06744012208019 - task: type: Clustering dataset: type: mteb/medrxiv-clustering-p2p name: MTEB MedrxivClusteringP2P config: default split: test revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 metrics: - type: v_measure value: 31.822626760555522 - task: type: Clustering dataset: type: mteb/medrxiv-clustering-s2s name: MTEB MedrxivClusteringS2S config: default split: test revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 metrics: - type: v_measure value: 27.98469036402807 - task: type: Reranking dataset: type: mteb/mind_small name: MTEB MindSmallReranking config: default split: test revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 metrics: - type: map value: 30.911144124209166 - type: mrr value: 31.950116175672292 - task: type: Retrieval dataset: type: nfcorpus name: MTEB NFCorpus config: default split: test revision: None metrics: - type: map_at_1 value: 5.157 - type: map_at_10 value: 11.086 - type: map_at_100 value: 13.927 - type: map_at_1000 value: 15.226999999999999 - type: map_at_3 value: 8.525 - type: map_at_5 value: 9.767000000000001 - type: mrr_at_1 value: 43.344 - type: mrr_at_10 value: 51.646 - type: mrr_at_100 value: 52.212 - type: mrr_at_1000 value: 52.263999999999996 - type: mrr_at_3 value: 50.052 - type: mrr_at_5 value: 51.166 - type: ndcg_at_1 value: 41.949999999999996 - type: ndcg_at_10 value: 30.552 - type: ndcg_at_100 value: 28.409000000000002 - type: ndcg_at_1000 value: 37.328 - type: ndcg_at_3 value: 37.114000000000004 - type: ndcg_at_5 value: 34.117999999999995 - type: precision_at_1 value: 43.344 - type: precision_at_10 value: 22.198 - type: precision_at_100 value: 7.234999999999999 - type: precision_at_1000 value: 2.013 - type: precision_at_3 value: 34.675 - type: precision_at_5 value: 29.04 - type: recall_at_1 value: 5.157 - type: recall_at_10 value: 13.999 - type: recall_at_100 value: 28.796 - type: recall_at_1000 value: 60.84 - type: recall_at_3 value: 9.603 - type: recall_at_5 value: 11.638 - task: type: Retrieval dataset: type: nq name: MTEB NQ config: default split: test revision: None metrics: - type: map_at_1 value: 33.024 - type: map_at_10 value: 47.229 - type: map_at_100 value: 48.195 - type: map_at_1000 value: 48.229 - type: map_at_3 value: 43.356 - type: map_at_5 value: 45.857 - type: mrr_at_1 value: 36.848 - type: mrr_at_10 value: 49.801 - type: mrr_at_100 value: 50.532999999999994 - type: mrr_at_1000 value: 50.556 - type: mrr_at_3 value: 46.605999999999995 - type: mrr_at_5 value: 48.735 - type: ndcg_at_1 value: 36.848 - type: ndcg_at_10 value: 54.202 - type: ndcg_at_100 value: 58.436 - type: ndcg_at_1000 value: 59.252 - type: ndcg_at_3 value: 47.082 - type: ndcg_at_5 value: 51.254 - type: precision_at_1 value: 36.848 - type: precision_at_10 value: 8.636000000000001 - type: precision_at_100 value: 1.105 - type: precision_at_1000 value: 0.11800000000000001 - type: precision_at_3 value: 21.08 - type: precision_at_5 value: 15.07 - type: recall_at_1 value: 33.024 - type: recall_at_10 value: 72.699 - type: recall_at_100 value: 91.387 - type: recall_at_1000 value: 97.482 - type: recall_at_3 value: 54.604 - type: recall_at_5 value: 64.224 - task: type: Retrieval dataset: type: quora name: MTEB QuoraRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 69.742 - type: map_at_10 value: 83.43 - type: map_at_100 value: 84.09400000000001 - type: map_at_1000 value: 84.113 - type: map_at_3 value: 80.464 - type: map_at_5 value: 82.356 - type: mrr_at_1 value: 80.31 - type: mrr_at_10 value: 86.629 - type: mrr_at_100 value: 86.753 - type: mrr_at_1000 value: 86.75399999999999 - type: mrr_at_3 value: 85.59 - type: mrr_at_5 value: 86.346 - type: ndcg_at_1 value: 80.28999999999999 - type: ndcg_at_10 value: 87.323 - type: ndcg_at_100 value: 88.682 - type: ndcg_at_1000 value: 88.812 - type: ndcg_at_3 value: 84.373 - type: ndcg_at_5 value: 86.065 - type: precision_at_1 value: 80.28999999999999 - type: precision_at_10 value: 13.239999999999998 - type: precision_at_100 value: 1.521 - type: precision_at_1000 value: 0.156 - type: precision_at_3 value: 36.827 - type: precision_at_5 value: 24.272 - type: recall_at_1 value: 69.742 - type: recall_at_10 value: 94.645 - type: recall_at_100 value: 99.375 - type: recall_at_1000 value: 99.97200000000001 - type: recall_at_3 value: 86.18400000000001 - type: recall_at_5 value: 90.958 - task: type: Clustering dataset: type: mteb/reddit-clustering name: MTEB RedditClustering config: default split: test revision: 24640382cdbf8abc73003fb0fa6d111a705499eb metrics: - type: v_measure value: 50.52987829115787 - task: type: Clustering dataset: type: mteb/reddit-clustering-p2p name: MTEB RedditClusteringP2P config: default split: test revision: 282350215ef01743dc01b456c7f5241fa8937f16 metrics: - type: v_measure value: 56.73289360025561 - task: type: Retrieval dataset: type: scidocs name: MTEB SCIDOCS config: default split: test revision: None metrics: - type: map_at_1 value: 4.473 - type: map_at_10 value: 10.953 - type: map_at_100 value: 12.842 - type: map_at_1000 value: 13.122 - type: map_at_3 value: 7.863 - type: map_at_5 value: 9.376 - type: mrr_at_1 value: 22.0 - type: mrr_at_10 value: 32.639 - type: mrr_at_100 value: 33.658 - type: mrr_at_1000 value: 33.727000000000004 - type: mrr_at_3 value: 29.232999999999997 - type: mrr_at_5 value: 31.373 - type: ndcg_at_1 value: 22.0 - type: ndcg_at_10 value: 18.736 - type: ndcg_at_100 value: 26.209 - type: ndcg_at_1000 value: 31.427 - type: ndcg_at_3 value: 17.740000000000002 - type: ndcg_at_5 value: 15.625 - type: precision_at_1 value: 22.0 - type: precision_at_10 value: 9.700000000000001 - type: precision_at_100 value: 2.052 - type: precision_at_1000 value: 0.331 - type: precision_at_3 value: 16.533 - type: precision_at_5 value: 13.74 - type: recall_at_1 value: 4.473 - type: recall_at_10 value: 19.627 - type: recall_at_100 value: 41.63 - type: recall_at_1000 value: 67.173 - type: recall_at_3 value: 10.067 - type: recall_at_5 value: 13.927 - task: type: STS dataset: type: mteb/sickr-sts name: MTEB SICK-R config: default split: test revision: a6ea5a8cab320b040a23452cc28066d9beae2cee metrics: - type: cos_sim_pearson value: 83.27314719076216 - type: cos_sim_spearman value: 76.39295628838427 - type: euclidean_pearson value: 80.38849931283136 - type: euclidean_spearman value: 76.39295685543406 - type: manhattan_pearson value: 80.28382869912794 - type: manhattan_spearman value: 76.28362123227473 - task: type: STS dataset: type: mteb/sts12-sts name: MTEB STS12 config: default split: test revision: a0d554a64d88156834ff5ae9920b964011b16384 metrics: - type: cos_sim_pearson value: 82.36858074786585 - type: cos_sim_spearman value: 72.81528838052759 - type: euclidean_pearson value: 78.83576324502302 - type: euclidean_spearman value: 72.8152880167174 - type: manhattan_pearson value: 78.81284819385367 - type: manhattan_spearman value: 72.76091465928633 - task: type: STS dataset: type: mteb/sts13-sts name: MTEB STS13 config: default split: test revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca metrics: - type: cos_sim_pearson value: 81.08132718998489 - type: cos_sim_spearman value: 82.00988939015869 - type: euclidean_pearson value: 81.02243847451692 - type: euclidean_spearman value: 82.00992010206836 - type: manhattan_pearson value: 80.97749306075134 - type: manhattan_spearman value: 81.97800195109437 - task: type: STS dataset: type: mteb/sts14-sts name: MTEB STS14 config: default split: test revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 metrics: - type: cos_sim_pearson value: 80.83442047735284 - type: cos_sim_spearman value: 77.50930325127395 - type: euclidean_pearson value: 79.34941050260747 - type: euclidean_spearman value: 77.50930324686452 - type: manhattan_pearson value: 79.28081079289419 - type: manhattan_spearman value: 77.42311420628891 - task: type: STS dataset: type: mteb/sts15-sts name: MTEB STS15 config: default split: test revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 metrics: - type: cos_sim_pearson value: 85.70132781546333 - type: cos_sim_spearman value: 86.58415907086527 - type: euclidean_pearson value: 85.63892869817083 - type: euclidean_spearman value: 86.58415907086527 - type: manhattan_pearson value: 85.56054168116064 - type: manhattan_spearman value: 86.50292824173809 - task: type: STS dataset: type: mteb/sts16-sts name: MTEB STS16 config: default split: test revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 metrics: - type: cos_sim_pearson value: 81.48780971731246 - type: cos_sim_spearman value: 82.79818891852887 - type: euclidean_pearson value: 81.93990926192305 - type: euclidean_spearman value: 82.79818891852887 - type: manhattan_pearson value: 81.97538189750966 - type: manhattan_spearman value: 82.88761825524075 - task: type: STS dataset: type: mteb/sts17-crosslingual-sts name: MTEB STS17 (en-en) config: en-en split: test revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics: - type: cos_sim_pearson value: 88.4989925729811 - type: cos_sim_spearman value: 88.47370962620529 - type: euclidean_pearson value: 88.2312980339956 - type: euclidean_spearman value: 88.47370962620529 - type: manhattan_pearson value: 88.15570940509707 - type: manhattan_spearman value: 88.36900000569275 - 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: 63.90740805015967 - type: cos_sim_spearman value: 63.968359064784444 - type: euclidean_pearson value: 64.67928113832794 - type: euclidean_spearman value: 63.968359064784444 - type: manhattan_pearson value: 63.92597430517486 - type: manhattan_spearman value: 63.31372007361158 - task: type: STS dataset: type: mteb/stsbenchmark-sts name: MTEB STSBenchmark config: default split: test revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 metrics: - type: cos_sim_pearson value: 82.56902991447632 - type: cos_sim_spearman value: 83.16262853325924 - type: euclidean_pearson value: 83.47693312869555 - type: euclidean_spearman value: 83.16266829656969 - type: manhattan_pearson value: 83.51067558632968 - type: manhattan_spearman value: 83.25136388306153 - task: type: Reranking dataset: type: mteb/scidocs-reranking name: MTEB SciDocsRR config: default split: test revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab metrics: - type: map value: 80.1518040851234 - type: mrr value: 94.49083052024228 - task: type: Retrieval dataset: type: scifact name: MTEB SciFact config: default split: test revision: None metrics: - type: map_at_1 value: 50.661 - type: map_at_10 value: 59.816 - type: map_at_100 value: 60.412 - type: map_at_1000 value: 60.446999999999996 - type: map_at_3 value: 56.567 - type: map_at_5 value: 58.45 - type: mrr_at_1 value: 53.667 - type: mrr_at_10 value: 61.342 - type: mrr_at_100 value: 61.8 - type: mrr_at_1000 value: 61.836 - type: mrr_at_3 value: 59.111000000000004 - type: mrr_at_5 value: 60.411 - type: ndcg_at_1 value: 53.667 - type: ndcg_at_10 value: 64.488 - type: ndcg_at_100 value: 67.291 - type: ndcg_at_1000 value: 68.338 - type: ndcg_at_3 value: 59.101000000000006 - type: ndcg_at_5 value: 61.812999999999995 - type: precision_at_1 value: 53.667 - type: precision_at_10 value: 8.799999999999999 - type: precision_at_100 value: 1.0330000000000001 - type: precision_at_1000 value: 0.11199999999999999 - type: precision_at_3 value: 23.0 - type: precision_at_5 value: 15.6 - type: recall_at_1 value: 50.661 - type: recall_at_10 value: 77.422 - type: recall_at_100 value: 90.667 - type: recall_at_1000 value: 99.0 - type: recall_at_3 value: 63.144 - type: recall_at_5 value: 69.817 - task: type: PairClassification dataset: type: mteb/sprintduplicatequestions-pairclassification name: MTEB SprintDuplicateQuestions config: default split: test revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 metrics: - type: cos_sim_accuracy value: 99.81287128712871 - type: cos_sim_ap value: 94.91998708151321 - type: cos_sim_f1 value: 90.36206017338093 - type: cos_sim_precision value: 92.19562955254943 - type: cos_sim_recall value: 88.6 - type: dot_accuracy value: 99.81287128712871 - type: dot_ap value: 94.91998708151321 - type: dot_f1 value: 90.36206017338093 - type: dot_precision value: 92.19562955254943 - type: dot_recall value: 88.6 - type: euclidean_accuracy value: 99.81287128712871 - type: euclidean_ap value: 94.9199944407842 - type: euclidean_f1 value: 90.36206017338093 - type: euclidean_precision value: 92.19562955254943 - type: euclidean_recall value: 88.6 - type: manhattan_accuracy value: 99.8108910891089 - type: manhattan_ap value: 94.83783896670839 - type: manhattan_f1 value: 90.27989821882952 - type: manhattan_precision value: 91.91709844559585 - type: manhattan_recall value: 88.7 - type: max_accuracy value: 99.81287128712871 - type: max_ap value: 94.9199944407842 - type: max_f1 value: 90.36206017338093 - task: type: Clustering dataset: type: mteb/stackexchange-clustering name: MTEB StackExchangeClustering config: default split: test revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 metrics: - type: v_measure value: 56.165546412944714 - task: type: Clustering dataset: type: mteb/stackexchange-clustering-p2p name: MTEB StackExchangeClusteringP2P config: default split: test revision: 815ca46b2622cec33ccafc3735d572c266efdb44 metrics: - type: v_measure value: 34.19894321136813 - task: type: Reranking dataset: type: mteb/stackoverflowdupquestions-reranking name: MTEB StackOverflowDupQuestions config: default split: test revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 metrics: - type: map value: 50.02944308369115 - type: mrr value: 50.63055714710127 - task: type: Summarization dataset: type: mteb/summeval name: MTEB SummEval config: default split: test revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c metrics: - type: cos_sim_pearson value: 31.3377433394579 - type: cos_sim_spearman value: 30.877807383527983 - type: dot_pearson value: 31.337752376327405 - type: dot_spearman value: 30.877807383527983 - task: type: Retrieval dataset: type: trec-covid name: MTEB TRECCOVID config: default split: test revision: None metrics: - type: map_at_1 value: 0.20500000000000002 - type: map_at_10 value: 1.6099999999999999 - type: map_at_100 value: 8.635 - type: map_at_1000 value: 20.419999999999998 - type: map_at_3 value: 0.59 - type: map_at_5 value: 0.9249999999999999 - type: mrr_at_1 value: 80.0 - type: mrr_at_10 value: 88.452 - type: mrr_at_100 value: 88.452 - type: mrr_at_1000 value: 88.452 - type: mrr_at_3 value: 87.667 - type: mrr_at_5 value: 88.167 - type: ndcg_at_1 value: 77.0 - type: ndcg_at_10 value: 67.079 - type: ndcg_at_100 value: 49.937 - type: ndcg_at_1000 value: 44.031 - type: ndcg_at_3 value: 73.123 - type: ndcg_at_5 value: 70.435 - type: precision_at_1 value: 80.0 - type: precision_at_10 value: 70.39999999999999 - type: precision_at_100 value: 51.25999999999999 - type: precision_at_1000 value: 19.698 - type: precision_at_3 value: 78.0 - type: precision_at_5 value: 75.2 - type: recall_at_1 value: 0.20500000000000002 - type: recall_at_10 value: 1.8399999999999999 - type: recall_at_100 value: 11.971 - type: recall_at_1000 value: 41.042 - type: recall_at_3 value: 0.632 - type: recall_at_5 value: 1.008 - task: type: Retrieval dataset: type: webis-touche2020 name: MTEB Touche2020 config: default split: test revision: None metrics: - type: map_at_1 value: 1.183 - type: map_at_10 value: 9.58 - type: map_at_100 value: 16.27 - type: map_at_1000 value: 17.977999999999998 - type: map_at_3 value: 4.521 - type: map_at_5 value: 6.567 - type: mrr_at_1 value: 12.245000000000001 - type: mrr_at_10 value: 33.486 - type: mrr_at_100 value: 34.989 - type: mrr_at_1000 value: 34.989 - type: mrr_at_3 value: 28.231 - type: mrr_at_5 value: 31.701 - type: ndcg_at_1 value: 9.184000000000001 - type: ndcg_at_10 value: 22.133 - type: ndcg_at_100 value: 36.882 - type: ndcg_at_1000 value: 48.487 - type: ndcg_at_3 value: 18.971 - type: ndcg_at_5 value: 20.107 - type: precision_at_1 value: 12.245000000000001 - type: precision_at_10 value: 21.837 - type: precision_at_100 value: 8.265 - type: precision_at_1000 value: 1.606 - type: precision_at_3 value: 22.448999999999998 - type: precision_at_5 value: 23.265 - type: recall_at_1 value: 1.183 - type: recall_at_10 value: 17.01 - type: recall_at_100 value: 51.666000000000004 - type: recall_at_1000 value: 87.56 - type: recall_at_3 value: 6.0280000000000005 - type: recall_at_5 value: 9.937999999999999 - task: type: Classification dataset: type: mteb/toxic_conversations_50k name: MTEB ToxicConversationsClassification config: default split: test revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c metrics: - type: accuracy value: 70.6812 - type: ap value: 13.776718216594006 - type: f1 value: 54.14269849375851 - task: type: Classification dataset: type: mteb/tweet_sentiment_extraction name: MTEB TweetSentimentExtractionClassification config: default split: test revision: d604517c81ca91fe16a244d1248fc021f9ecee7a metrics: - type: accuracy value: 57.3372948500283 - type: f1 value: 57.39381291375 - task: type: Clustering dataset: type: mteb/twentynewsgroups-clustering name: MTEB TwentyNewsgroupsClustering config: default split: test revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 metrics: - type: v_measure value: 41.49681931876514 - task: type: PairClassification dataset: type: mteb/twittersemeval2015-pairclassification name: MTEB TwitterSemEval2015 config: default split: test revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 metrics: - type: cos_sim_accuracy value: 84.65756690707516 - type: cos_sim_ap value: 70.06190309300052 - type: cos_sim_f1 value: 65.49254432311848 - type: cos_sim_precision value: 59.00148085466469 - type: cos_sim_recall value: 73.58839050131925 - type: dot_accuracy value: 84.65756690707516 - type: dot_ap value: 70.06187157356817 - type: dot_f1 value: 65.49254432311848 - type: dot_precision value: 59.00148085466469 - type: dot_recall value: 73.58839050131925 - type: euclidean_accuracy value: 84.65756690707516 - type: euclidean_ap value: 70.06190439203068 - type: euclidean_f1 value: 65.49254432311848 - type: euclidean_precision value: 59.00148085466469 - type: euclidean_recall value: 73.58839050131925 - type: manhattan_accuracy value: 84.58604041246946 - type: manhattan_ap value: 69.93103436414437 - type: manhattan_f1 value: 65.48780487804878 - type: manhattan_precision value: 60.8843537414966 - type: manhattan_recall value: 70.84432717678101 - type: max_accuracy value: 84.65756690707516 - type: max_ap value: 70.06190439203068 - type: max_f1 value: 65.49254432311848 - task: type: PairClassification dataset: type: mteb/twitterurlcorpus-pairclassification name: MTEB TwitterURLCorpus config: default split: test revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf metrics: - type: cos_sim_accuracy value: 88.78410369852912 - type: cos_sim_ap value: 85.45825760499459 - type: cos_sim_f1 value: 77.73455035163849 - type: cos_sim_precision value: 75.5966239813737 - type: cos_sim_recall value: 79.9969202340622 - type: dot_accuracy value: 88.78410369852912 - type: dot_ap value: 85.45825790635979 - type: dot_f1 value: 77.73455035163849 - type: dot_precision value: 75.5966239813737 - type: dot_recall value: 79.9969202340622 - type: euclidean_accuracy value: 88.78410369852912 - type: euclidean_ap value: 85.45826341243391 - type: euclidean_f1 value: 77.73455035163849 - type: euclidean_precision value: 75.5966239813737 - type: euclidean_recall value: 79.9969202340622 - type: manhattan_accuracy value: 88.7026041060271 - type: manhattan_ap value: 85.43182830781821 - type: manhattan_f1 value: 77.61487303506651 - type: manhattan_precision value: 76.20955773226477 - type: manhattan_recall value: 79.07299045272559 - type: max_accuracy value: 88.78410369852912 - type: max_ap value: 85.45826341243391 - type: max_f1 value: 77.73455035163849 ---