--- tags: - ts model-index: - name: new7 results: - task: type: Classification dataset: type: mteb/amazon_counterfactual name: MTEB AmazonCounterfactualClassification (en) config: en split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics: - type: accuracy value: 90.25373134328359 - type: ap value: 65.16915484773354 - type: f1 value: 86.23066728099059 - task: type: Classification dataset: type: mteb/amazon_polarity name: MTEB AmazonPolarityClassification config: default split: test revision: e2d317d38cd51312af73b3d32a06d1a08b442046 metrics: - type: accuracy value: 93.974875 - type: ap value: 91.14317344009288 - type: f1 value: 93.9685240564202 - task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (en) config: en split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics: - type: accuracy value: 55.77799999999999 - type: f1 value: 55.30626203111084 - task: type: Retrieval dataset: type: arguana name: MTEB ArguAna config: default split: test revision: None metrics: - type: map_at_1 value: 28.663 - type: map_at_10 value: 43.903 - type: map_at_100 value: 44.779 - type: map_at_1000 value: 44.799 - type: map_at_3 value: 39.486 - type: map_at_5 value: 42.199 - type: mrr_at_1 value: 28.663 - type: mrr_at_10 value: 43.903 - type: mrr_at_100 value: 44.779 - type: mrr_at_1000 value: 44.799 - type: mrr_at_3 value: 39.486 - type: mrr_at_5 value: 42.199 - type: ndcg_at_1 value: 28.663 - type: ndcg_at_10 value: 51.983999999999995 - type: ndcg_at_100 value: 55.981 - type: ndcg_at_1000 value: 56.474000000000004 - type: ndcg_at_3 value: 43.025000000000006 - type: ndcg_at_5 value: 47.916 - type: precision_at_1 value: 28.663 - type: precision_at_10 value: 7.76 - type: precision_at_100 value: 0.9570000000000001 - type: precision_at_1000 value: 0.1 - type: precision_at_3 value: 17.757 - type: precision_at_5 value: 13.03 - type: recall_at_1 value: 28.663 - type: recall_at_10 value: 77.596 - type: recall_at_100 value: 95.661 - type: recall_at_1000 value: 99.502 - type: recall_at_3 value: 53.272 - type: recall_at_5 value: 65.149 - task: type: Clustering dataset: type: mteb/arxiv-clustering-p2p name: MTEB ArxivClusteringP2P config: default split: test revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d metrics: - type: v_measure value: 41.06284026514476 - task: type: Clustering dataset: type: mteb/arxiv-clustering-s2s name: MTEB ArxivClusteringS2S config: default split: test revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 metrics: - type: v_measure value: 32.96711301401968 - task: type: Reranking dataset: type: mteb/askubuntudupquestions-reranking name: MTEB AskUbuntuDupQuestions config: default split: test revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 metrics: - type: map value: 58.05094332005456 - type: mrr value: 70.90808160752759 - task: type: STS dataset: type: mteb/biosses-sts name: MTEB BIOSSES config: default split: test revision: d3fb88f8f02e40887cd149695127462bbcf29b4a metrics: - type: cos_sim_pearson value: 93.67415724859552 - type: cos_sim_spearman value: 93.37019979249912 - type: euclidean_pearson value: 91.767368542047 - type: euclidean_spearman value: 92.75874007684216 - type: manhattan_pearson value: 91.7931347639689 - type: manhattan_spearman value: 92.94428647331738 - task: type: Classification dataset: type: mteb/banking77 name: MTEB Banking77Classification config: default split: test revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 metrics: - type: accuracy value: 91.6720779220779 - type: f1 value: 91.68597413806214 - task: type: Clustering dataset: type: mteb/biorxiv-clustering-p2p name: MTEB BiorxivClusteringP2P config: default split: test revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 metrics: - type: v_measure value: 30.160011542775695 - task: type: Clustering dataset: type: mteb/biorxiv-clustering-s2s name: MTEB BiorxivClusteringS2S config: default split: test revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 metrics: - type: v_measure value: 24.890267612946595 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackAndroidRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 22.52 - type: map_at_10 value: 31.905 - type: map_at_100 value: 33.146 - type: map_at_1000 value: 33.315 - type: map_at_3 value: 29.567 - type: map_at_5 value: 30.729 - type: mrr_at_1 value: 28.469 - type: mrr_at_10 value: 37.884 - type: mrr_at_100 value: 38.757000000000005 - type: mrr_at_1000 value: 38.827 - type: mrr_at_3 value: 36.004000000000005 - type: mrr_at_5 value: 36.927 - type: ndcg_at_1 value: 28.469 - type: ndcg_at_10 value: 37.436 - type: ndcg_at_100 value: 42.754 - type: ndcg_at_1000 value: 45.744 - type: ndcg_at_3 value: 34.121 - type: ndcg_at_5 value: 35.315000000000005 - type: precision_at_1 value: 28.469 - type: precision_at_10 value: 7.167 - type: precision_at_100 value: 1.24 - type: precision_at_1000 value: 0.184 - type: precision_at_3 value: 17.072000000000003 - type: precision_at_5 value: 11.731 - type: recall_at_1 value: 22.52 - type: recall_at_10 value: 47.61 - type: recall_at_100 value: 70.494 - type: recall_at_1000 value: 90.081 - type: recall_at_3 value: 37.012 - type: recall_at_5 value: 41.053 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackEnglishRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 22.167 - type: map_at_10 value: 29.227999999999998 - type: map_at_100 value: 30.361 - type: map_at_1000 value: 30.483 - type: map_at_3 value: 27.046 - type: map_at_5 value: 28.253 - type: mrr_at_1 value: 27.961999999999996 - type: mrr_at_10 value: 34.474 - type: mrr_at_100 value: 35.257 - type: mrr_at_1000 value: 35.312 - type: mrr_at_3 value: 32.633 - type: mrr_at_5 value: 33.7 - type: ndcg_at_1 value: 27.961999999999996 - type: ndcg_at_10 value: 33.800000000000004 - type: ndcg_at_100 value: 38.435 - type: ndcg_at_1000 value: 40.753 - type: ndcg_at_3 value: 30.584 - type: ndcg_at_5 value: 32.036 - type: precision_at_1 value: 27.961999999999996 - type: precision_at_10 value: 6.338000000000001 - type: precision_at_100 value: 1.127 - type: precision_at_1000 value: 0.159 - type: precision_at_3 value: 14.649999999999999 - type: precision_at_5 value: 10.408000000000001 - type: recall_at_1 value: 22.167 - type: recall_at_10 value: 41.735 - type: recall_at_100 value: 61.612 - type: recall_at_1000 value: 77.046 - type: recall_at_3 value: 31.985000000000003 - type: recall_at_5 value: 36.216 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGamingRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 28.88 - type: map_at_10 value: 39.483000000000004 - type: map_at_100 value: 40.65 - type: map_at_1000 value: 40.727000000000004 - type: map_at_3 value: 36.095 - type: map_at_5 value: 38.138 - type: mrr_at_1 value: 33.292 - type: mrr_at_10 value: 42.655 - type: mrr_at_100 value: 43.505 - type: mrr_at_1000 value: 43.555 - type: mrr_at_3 value: 39.634 - type: mrr_at_5 value: 41.589999999999996 - type: ndcg_at_1 value: 33.292 - type: ndcg_at_10 value: 45.216 - type: ndcg_at_100 value: 50.029999999999994 - type: ndcg_at_1000 value: 51.795 - type: ndcg_at_3 value: 39.184000000000005 - type: ndcg_at_5 value: 42.416 - type: precision_at_1 value: 33.292 - type: precision_at_10 value: 7.661 - type: precision_at_100 value: 1.089 - type: precision_at_1000 value: 0.129 - type: precision_at_3 value: 17.701 - type: precision_at_5 value: 12.878 - type: recall_at_1 value: 28.88 - type: recall_at_10 value: 59.148 - type: recall_at_100 value: 80.10300000000001 - type: recall_at_1000 value: 92.938 - type: recall_at_3 value: 43.262 - type: recall_at_5 value: 51.05800000000001 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGisRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 17.732 - type: map_at_10 value: 24.104999999999997 - type: map_at_100 value: 25.085 - type: map_at_1000 value: 25.180000000000003 - type: map_at_3 value: 21.826999999999998 - type: map_at_5 value: 22.988 - type: mrr_at_1 value: 19.209 - type: mrr_at_10 value: 25.528000000000002 - type: mrr_at_100 value: 26.477 - type: mrr_at_1000 value: 26.56 - type: mrr_at_3 value: 23.315 - type: mrr_at_5 value: 24.427 - type: ndcg_at_1 value: 19.209 - type: ndcg_at_10 value: 28.055000000000003 - type: ndcg_at_100 value: 33.357 - type: ndcg_at_1000 value: 35.996 - type: ndcg_at_3 value: 23.526 - type: ndcg_at_5 value: 25.471 - type: precision_at_1 value: 19.209 - type: precision_at_10 value: 4.463 - type: precision_at_100 value: 0.756 - type: precision_at_1000 value: 0.10200000000000001 - type: precision_at_3 value: 9.981 - type: precision_at_5 value: 7.119000000000001 - type: recall_at_1 value: 17.732 - type: recall_at_10 value: 39.086999999999996 - type: recall_at_100 value: 64.264 - type: recall_at_1000 value: 84.589 - type: recall_at_3 value: 26.668999999999997 - type: recall_at_5 value: 31.361 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackMathematicaRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 10.99 - type: map_at_10 value: 16.661 - type: map_at_100 value: 17.763 - type: map_at_1000 value: 17.892 - type: map_at_3 value: 14.813 - type: map_at_5 value: 15.678 - type: mrr_at_1 value: 13.930000000000001 - type: mrr_at_10 value: 20.25 - type: mrr_at_100 value: 21.233 - type: mrr_at_1000 value: 21.325 - type: mrr_at_3 value: 18.262999999999998 - type: mrr_at_5 value: 19.177 - type: ndcg_at_1 value: 13.930000000000001 - type: ndcg_at_10 value: 20.558 - type: ndcg_at_100 value: 26.137 - type: ndcg_at_1000 value: 29.54 - type: ndcg_at_3 value: 17.015 - type: ndcg_at_5 value: 18.314 - type: precision_at_1 value: 13.930000000000001 - type: precision_at_10 value: 3.9050000000000002 - type: precision_at_100 value: 0.782 - type: precision_at_1000 value: 0.121 - type: precision_at_3 value: 8.333 - type: precision_at_5 value: 5.92 - type: recall_at_1 value: 10.99 - type: recall_at_10 value: 29.156 - type: recall_at_100 value: 54.06100000000001 - type: recall_at_1000 value: 78.69699999999999 - type: recall_at_3 value: 19.11 - type: recall_at_5 value: 22.609 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackPhysicsRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 21.351 - type: map_at_10 value: 29.961 - type: map_at_100 value: 31.214 - type: map_at_1000 value: 31.349 - type: map_at_3 value: 27.283 - type: map_at_5 value: 28.851 - type: mrr_at_1 value: 25.602000000000004 - type: mrr_at_10 value: 34.554 - type: mrr_at_100 value: 35.423 - type: mrr_at_1000 value: 35.492000000000004 - type: mrr_at_3 value: 31.97 - type: mrr_at_5 value: 33.399 - type: ndcg_at_1 value: 25.602000000000004 - type: ndcg_at_10 value: 35.339999999999996 - type: ndcg_at_100 value: 40.89 - type: ndcg_at_1000 value: 43.732 - type: ndcg_at_3 value: 30.657 - type: ndcg_at_5 value: 32.945 - type: precision_at_1 value: 25.602000000000004 - type: precision_at_10 value: 6.574000000000001 - type: precision_at_100 value: 1.095 - type: precision_at_1000 value: 0.153 - type: precision_at_3 value: 14.629 - type: precision_at_5 value: 10.645 - type: recall_at_1 value: 21.351 - type: recall_at_10 value: 46.754 - type: recall_at_100 value: 70.247 - type: recall_at_1000 value: 89.653 - type: recall_at_3 value: 33.894000000000005 - type: recall_at_5 value: 39.667 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackProgrammersRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 17.052999999999997 - type: map_at_10 value: 24.291999999999998 - type: map_at_100 value: 25.348 - type: map_at_1000 value: 25.487 - type: map_at_3 value: 21.922 - type: map_at_5 value: 23.256 - type: mrr_at_1 value: 20.776 - type: mrr_at_10 value: 28.17 - type: mrr_at_100 value: 28.99 - type: mrr_at_1000 value: 29.082 - type: mrr_at_3 value: 25.951 - type: mrr_at_5 value: 27.241 - type: ndcg_at_1 value: 20.776 - type: ndcg_at_10 value: 28.909000000000002 - type: ndcg_at_100 value: 33.917 - type: ndcg_at_1000 value: 37.173 - type: ndcg_at_3 value: 24.769 - type: ndcg_at_5 value: 26.698 - type: precision_at_1 value: 20.776 - type: precision_at_10 value: 5.445 - type: precision_at_100 value: 0.943 - type: precision_at_1000 value: 0.13899999999999998 - type: precision_at_3 value: 11.985999999999999 - type: precision_at_5 value: 8.699 - type: recall_at_1 value: 17.052999999999997 - type: recall_at_10 value: 38.922000000000004 - type: recall_at_100 value: 60.624 - type: recall_at_1000 value: 83.83 - type: recall_at_3 value: 27.35 - type: recall_at_5 value: 32.513999999999996 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 17.981 - type: map_at_10 value: 24.99583333333333 - type: map_at_100 value: 26.054083333333335 - type: map_at_1000 value: 26.180916666666672 - type: map_at_3 value: 22.802666666666667 - type: map_at_5 value: 24.00508333333333 - type: mrr_at_1 value: 21.373916666666666 - type: mrr_at_10 value: 28.53433333333333 - type: mrr_at_100 value: 29.404000000000003 - type: mrr_at_1000 value: 29.481999999999996 - type: mrr_at_3 value: 26.462999999999997 - type: mrr_at_5 value: 27.596083333333333 - type: ndcg_at_1 value: 21.373916666666666 - type: ndcg_at_10 value: 29.40908333333333 - type: ndcg_at_100 value: 34.43266666666666 - type: ndcg_at_1000 value: 37.334916666666665 - type: ndcg_at_3 value: 25.518250000000002 - type: ndcg_at_5 value: 27.286916666666666 - type: precision_at_1 value: 21.373916666666666 - type: precision_at_10 value: 5.265666666666667 - type: precision_at_100 value: 0.9175833333333334 - type: precision_at_1000 value: 0.13533333333333336 - type: precision_at_3 value: 11.92425 - type: precision_at_5 value: 8.532250000000001 - type: recall_at_1 value: 17.981 - type: recall_at_10 value: 39.14641666666667 - type: recall_at_100 value: 61.65433333333334 - type: recall_at_1000 value: 82.39216666666665 - type: recall_at_3 value: 28.15266666666667 - type: recall_at_5 value: 32.795 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackStatsRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 16.834 - type: map_at_10 value: 22.046 - type: map_at_100 value: 22.954 - type: map_at_1000 value: 23.051 - type: map_at_3 value: 20.602999999999998 - type: map_at_5 value: 21.387999999999998 - type: mrr_at_1 value: 19.172 - type: mrr_at_10 value: 24.558 - type: mrr_at_100 value: 25.439 - type: mrr_at_1000 value: 25.509999999999998 - type: mrr_at_3 value: 23.185 - type: mrr_at_5 value: 23.852 - type: ndcg_at_1 value: 19.172 - type: ndcg_at_10 value: 25.189 - type: ndcg_at_100 value: 29.918 - type: ndcg_at_1000 value: 32.677 - type: ndcg_at_3 value: 22.496 - type: ndcg_at_5 value: 23.677 - type: precision_at_1 value: 19.172 - type: precision_at_10 value: 3.834 - type: precision_at_100 value: 0.679 - type: precision_at_1000 value: 0.1 - type: precision_at_3 value: 9.611 - type: precision_at_5 value: 6.4719999999999995 - type: recall_at_1 value: 16.834 - type: recall_at_10 value: 32.554 - type: recall_at_100 value: 54.416 - type: recall_at_1000 value: 75.334 - type: recall_at_3 value: 25.057000000000002 - type: recall_at_5 value: 28.155 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackTexRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 10.778 - type: map_at_10 value: 15.885 - type: map_at_100 value: 16.716 - type: map_at_1000 value: 16.838 - type: map_at_3 value: 14.283999999999999 - type: map_at_5 value: 15.067 - type: mrr_at_1 value: 13.421 - type: mrr_at_10 value: 19.022 - type: mrr_at_100 value: 19.819 - type: mrr_at_1000 value: 19.912 - type: mrr_at_3 value: 17.366 - type: mrr_at_5 value: 18.18 - type: ndcg_at_1 value: 13.421 - type: ndcg_at_10 value: 19.375 - type: ndcg_at_100 value: 23.733999999999998 - type: ndcg_at_1000 value: 26.878 - type: ndcg_at_3 value: 16.383 - type: ndcg_at_5 value: 17.53 - type: precision_at_1 value: 13.421 - type: precision_at_10 value: 3.637 - type: precision_at_100 value: 0.681 - type: precision_at_1000 value: 0.11100000000000002 - type: precision_at_3 value: 7.983 - type: precision_at_5 value: 5.671 - type: recall_at_1 value: 10.778 - type: recall_at_10 value: 26.985999999999997 - type: recall_at_100 value: 47.143 - type: recall_at_1000 value: 69.842 - type: recall_at_3 value: 18.289 - type: recall_at_5 value: 21.459 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackUnixRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 17.077 - type: map_at_10 value: 23.31 - type: map_at_100 value: 24.351 - type: map_at_1000 value: 24.471 - type: map_at_3 value: 21.272 - type: map_at_5 value: 22.320999999999998 - type: mrr_at_1 value: 19.683 - type: mrr_at_10 value: 26.44 - type: mrr_at_100 value: 27.395000000000003 - type: mrr_at_1000 value: 27.479 - type: mrr_at_3 value: 24.549000000000003 - type: mrr_at_5 value: 25.477 - type: ndcg_at_1 value: 19.683 - type: ndcg_at_10 value: 27.33 - type: ndcg_at_100 value: 32.595 - type: ndcg_at_1000 value: 35.671 - type: ndcg_at_3 value: 23.536 - type: ndcg_at_5 value: 25.09 - type: precision_at_1 value: 19.683 - type: precision_at_10 value: 4.711 - type: precision_at_100 value: 0.84 - type: precision_at_1000 value: 0.121 - type: precision_at_3 value: 10.697 - type: precision_at_5 value: 7.5 - type: recall_at_1 value: 17.077 - type: recall_at_10 value: 36.532 - type: recall_at_100 value: 59.955999999999996 - type: recall_at_1000 value: 82.536 - type: recall_at_3 value: 25.982 - type: recall_at_5 value: 29.965999999999998 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWebmastersRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 17.137 - type: map_at_10 value: 23.889 - type: map_at_100 value: 25.089 - type: map_at_1000 value: 25.284000000000002 - type: map_at_3 value: 21.844 - type: map_at_5 value: 23.185 - type: mrr_at_1 value: 20.552999999999997 - type: mrr_at_10 value: 27.996 - type: mrr_at_100 value: 28.921000000000003 - type: mrr_at_1000 value: 28.999999999999996 - type: mrr_at_3 value: 25.955000000000002 - type: mrr_at_5 value: 27.269 - type: ndcg_at_1 value: 20.552999999999997 - type: ndcg_at_10 value: 28.555000000000003 - type: ndcg_at_100 value: 34.035 - type: ndcg_at_1000 value: 37.466 - type: ndcg_at_3 value: 25.105 - type: ndcg_at_5 value: 27.13 - type: precision_at_1 value: 20.552999999999997 - type: precision_at_10 value: 5.534 - type: precision_at_100 value: 1.117 - type: precision_at_1000 value: 0.20400000000000001 - type: precision_at_3 value: 12.253 - type: precision_at_5 value: 9.17 - type: recall_at_1 value: 17.137 - type: recall_at_10 value: 37.527 - type: recall_at_100 value: 62.905 - type: recall_at_1000 value: 85.839 - type: recall_at_3 value: 27.262999999999998 - type: recall_at_5 value: 32.735 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWordpressRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 13.253 - type: map_at_10 value: 19.185 - type: map_at_100 value: 19.972 - type: map_at_1000 value: 20.094 - type: map_at_3 value: 17.076 - type: map_at_5 value: 18.207 - type: mrr_at_1 value: 14.418000000000001 - type: mrr_at_10 value: 20.881 - type: mrr_at_100 value: 21.632 - type: mrr_at_1000 value: 21.73 - type: mrr_at_3 value: 18.731 - type: mrr_at_5 value: 19.914 - type: ndcg_at_1 value: 14.418000000000001 - type: ndcg_at_10 value: 23.146 - type: ndcg_at_100 value: 27.389999999999997 - type: ndcg_at_1000 value: 30.593999999999998 - type: ndcg_at_3 value: 18.843 - type: ndcg_at_5 value: 20.821 - type: precision_at_1 value: 14.418000000000001 - type: precision_at_10 value: 3.9190000000000005 - type: precision_at_100 value: 0.662 - type: precision_at_1000 value: 0.101 - type: precision_at_3 value: 8.195 - type: precision_at_5 value: 6.174 - type: recall_at_1 value: 13.253 - type: recall_at_10 value: 33.745999999999995 - type: recall_at_100 value: 54.027 - type: recall_at_1000 value: 78.321 - type: recall_at_3 value: 21.959 - type: recall_at_5 value: 26.747 - task: type: Retrieval dataset: type: climate-fever name: MTEB ClimateFEVER config: default split: test revision: None metrics: - type: ndcg_at_1 value: 9.446 - type: ndcg_at_3 value: 8.708 - type: ndcg_at_5 value: 9.583 - type: ndcg_at_10 value: 11.324 - type: ndcg_at_100 value: 16.563 - type: ndcg_at_1000 value: 20.402 - type: map_at_1 value: 4.407 - type: map_at_3 value: 6.283999999999999 - type: map_at_5 value: 6.888 - type: map_at_10 value: 7.545 - type: map_at_100 value: 8.502 - type: map_at_1000 value: 8.677 - type: recall_at_1 value: 4.407 - type: recall_at_3 value: 8.341999999999999 - type: recall_at_5 value: 10.609 - type: recall_at_10 value: 14.572 - type: recall_at_100 value: 33.802 - type: recall_at_1000 value: 56.13 - type: precision_at_1 value: 9.446 - type: precision_at_3 value: 6.3839999999999995 - type: precision_at_5 value: 5.029 - type: precision_at_10 value: 3.655 - type: precision_at_100 value: 0.9169999999999999 - type: precision_at_1000 value: 0.159 - type: mrr_at_1 value: 9.446 - type: mrr_at_3 value: 12.975 - type: mrr_at_5 value: 14.102 - type: mrr_at_10 value: 15.223999999999998 - type: mrr_at_100 value: 16.378 - type: mrr_at_1000 value: 16.469 - task: type: Retrieval dataset: type: dbpedia-entity name: MTEB DBPedia config: default split: test revision: None metrics: - type: map_at_1 value: 4.3839999999999995 - type: map_at_10 value: 8.92 - type: map_at_100 value: 12.509999999999998 - type: map_at_1000 value: 13.555 - type: map_at_3 value: 6.508 - type: map_at_5 value: 7.521 - type: mrr_at_1 value: 38.0 - type: mrr_at_10 value: 47.796 - type: mrr_at_100 value: 48.554 - type: mrr_at_1000 value: 48.579 - type: mrr_at_3 value: 44.708 - type: mrr_at_5 value: 46.521 - type: ndcg_at_1 value: 29.125 - type: ndcg_at_10 value: 22.126 - type: ndcg_at_100 value: 26.369999999999997 - type: ndcg_at_1000 value: 33.604 - type: ndcg_at_3 value: 24.102999999999998 - type: ndcg_at_5 value: 22.926 - type: precision_at_1 value: 38.0 - type: precision_at_10 value: 18.2 - type: precision_at_100 value: 6.208 - type: precision_at_1000 value: 1.3679999999999999 - type: precision_at_3 value: 26.5 - type: precision_at_5 value: 22.900000000000002 - type: recall_at_1 value: 4.3839999999999995 - type: recall_at_10 value: 13.520999999999999 - type: recall_at_100 value: 33.053 - type: recall_at_1000 value: 56.516 - type: recall_at_3 value: 7.515 - type: recall_at_5 value: 9.775 - task: type: Classification dataset: type: mteb/emotion name: MTEB EmotionClassification config: default split: test revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 metrics: - type: accuracy value: 90.38999999999999 - type: f1 value: 87.12778738994012 - task: type: Retrieval dataset: type: fever name: MTEB FEVER config: default split: test revision: None metrics: - type: map_at_1 value: 70.132 - type: map_at_10 value: 79.527 - type: map_at_100 value: 79.81200000000001 - type: map_at_1000 value: 79.828 - type: map_at_3 value: 78.191 - type: map_at_5 value: 79.092 - type: mrr_at_1 value: 75.563 - type: mrr_at_10 value: 83.80199999999999 - type: mrr_at_100 value: 83.93 - type: mrr_at_1000 value: 83.933 - type: mrr_at_3 value: 82.818 - type: mrr_at_5 value: 83.505 - type: ndcg_at_1 value: 75.563 - type: ndcg_at_10 value: 83.692 - type: ndcg_at_100 value: 84.706 - type: ndcg_at_1000 value: 85.001 - type: ndcg_at_3 value: 81.51 - type: ndcg_at_5 value: 82.832 - type: precision_at_1 value: 75.563 - type: precision_at_10 value: 10.245 - type: precision_at_100 value: 1.0959999999999999 - type: precision_at_1000 value: 0.11399999999999999 - type: precision_at_3 value: 31.518 - type: precision_at_5 value: 19.772000000000002 - type: recall_at_1 value: 70.132 - type: recall_at_10 value: 92.204 - type: recall_at_100 value: 96.261 - type: recall_at_1000 value: 98.17399999999999 - type: recall_at_3 value: 86.288 - type: recall_at_5 value: 89.63799999999999 - task: type: Retrieval dataset: type: fiqa name: MTEB FiQA2018 config: default split: test revision: None metrics: - type: map_at_1 value: 7.688000000000001 - type: map_at_10 value: 13.839000000000002 - type: map_at_100 value: 15.082999999999998 - type: map_at_1000 value: 15.276 - type: map_at_3 value: 11.662 - type: map_at_5 value: 12.827 - type: mrr_at_1 value: 15.741 - type: mrr_at_10 value: 23.304 - type: mrr_at_100 value: 24.239 - type: mrr_at_1000 value: 24.319 - type: mrr_at_3 value: 20.962 - type: mrr_at_5 value: 22.243 - type: ndcg_at_1 value: 15.741 - type: ndcg_at_10 value: 18.914 - type: ndcg_at_100 value: 24.742 - type: ndcg_at_1000 value: 28.938000000000002 - type: ndcg_at_3 value: 16.181 - type: ndcg_at_5 value: 17.078 - type: precision_at_1 value: 15.741 - type: precision_at_10 value: 5.7410000000000005 - type: precision_at_100 value: 1.168 - type: precision_at_1000 value: 0.19 - type: precision_at_3 value: 11.368 - type: precision_at_5 value: 8.735 - type: recall_at_1 value: 7.688000000000001 - type: recall_at_10 value: 24.442 - type: recall_at_100 value: 47.288999999999994 - type: recall_at_1000 value: 73.49900000000001 - type: recall_at_3 value: 15.15 - type: recall_at_5 value: 18.858 - task: type: Retrieval dataset: type: hotpotqa name: MTEB HotpotQA config: default split: test revision: None metrics: - type: map_at_1 value: 40.412 - type: map_at_10 value: 66.376 - type: map_at_100 value: 67.217 - type: map_at_1000 value: 67.271 - type: map_at_3 value: 62.741 - type: map_at_5 value: 65.069 - type: mrr_at_1 value: 80.824 - type: mrr_at_10 value: 86.53 - type: mrr_at_100 value: 86.67399999999999 - type: mrr_at_1000 value: 86.678 - type: mrr_at_3 value: 85.676 - type: mrr_at_5 value: 86.256 - type: ndcg_at_1 value: 80.824 - type: ndcg_at_10 value: 74.332 - type: ndcg_at_100 value: 77.154 - type: ndcg_at_1000 value: 78.12400000000001 - type: ndcg_at_3 value: 69.353 - type: ndcg_at_5 value: 72.234 - type: precision_at_1 value: 80.824 - type: precision_at_10 value: 15.652 - type: precision_at_100 value: 1.7840000000000003 - type: precision_at_1000 value: 0.191 - type: precision_at_3 value: 44.911 - type: precision_at_5 value: 29.221000000000004 - type: recall_at_1 value: 40.412 - type: recall_at_10 value: 78.25800000000001 - type: recall_at_100 value: 89.196 - type: recall_at_1000 value: 95.544 - type: recall_at_3 value: 67.367 - type: recall_at_5 value: 73.05199999999999 - task: type: Classification dataset: type: mteb/imdb name: MTEB ImdbClassification config: default split: test revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 metrics: - type: accuracy value: 88.8228 - type: ap value: 84.52103126779862 - type: f1 value: 88.797782219813 - task: type: Retrieval dataset: type: msmarco name: MTEB MSMARCO config: default split: dev revision: None metrics: - type: map_at_1 value: 8.461 - type: map_at_10 value: 14.979999999999999 - type: map_at_100 value: 16.032 - type: map_at_1000 value: 16.128 - type: map_at_3 value: 12.64 - type: map_at_5 value: 13.914000000000001 - type: mrr_at_1 value: 8.681999999999999 - type: mrr_at_10 value: 15.341 - type: mrr_at_100 value: 16.377 - type: mrr_at_1000 value: 16.469 - type: mrr_at_3 value: 12.963 - type: mrr_at_5 value: 14.262 - type: ndcg_at_1 value: 8.681999999999999 - type: ndcg_at_10 value: 19.045 - type: ndcg_at_100 value: 24.735 - type: ndcg_at_1000 value: 27.556000000000004 - type: ndcg_at_3 value: 14.154 - type: ndcg_at_5 value: 16.448 - type: precision_at_1 value: 8.681999999999999 - type: precision_at_10 value: 3.292 - type: precision_at_100 value: 0.623 - type: precision_at_1000 value: 0.087 - type: precision_at_3 value: 6.275 - type: precision_at_5 value: 4.92 - type: recall_at_1 value: 8.461 - type: recall_at_10 value: 31.729000000000003 - type: recall_at_100 value: 59.367000000000004 - type: recall_at_1000 value: 81.86 - type: recall_at_3 value: 18.234 - type: recall_at_5 value: 23.74 - task: type: Classification dataset: type: mteb/mtop_domain name: MTEB MTOPDomainClassification (en) config: en split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics: - type: accuracy value: 98.1623347013224 - type: f1 value: 97.95934123221338 - task: type: Classification dataset: type: mteb/mtop_intent name: MTEB MTOPIntentClassification (en) config: en split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics: - type: accuracy value: 93.0141358869129 - type: f1 value: 77.42161481798763 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (en) config: en split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 77.20242098184264 - type: f1 value: 73.64580701123289 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (en) config: en split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 88.38264963012777 - type: f1 value: 87.6445935642575 - task: type: Clustering dataset: type: mteb/medrxiv-clustering-p2p name: MTEB MedrxivClusteringP2P config: default split: test revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 metrics: - type: v_measure value: 28.982276213044095 - task: type: Clustering dataset: type: mteb/medrxiv-clustering-s2s name: MTEB MedrxivClusteringS2S config: default split: test revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 metrics: - type: v_measure value: 26.08731318128303 - task: type: Reranking dataset: type: mteb/mind_small name: MTEB MindSmallReranking config: default split: test revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 metrics: - type: map value: 29.680164236394784 - type: mrr value: 30.60242075910688 - task: type: Retrieval dataset: type: nfcorpus name: MTEB NFCorpus config: default split: test revision: None metrics: - type: map_at_1 value: 4.35 - type: map_at_10 value: 10.03 - type: map_at_100 value: 12.61 - type: map_at_1000 value: 13.916999999999998 - type: map_at_3 value: 7.428 - type: map_at_5 value: 8.625 - type: mrr_at_1 value: 39.009 - type: mrr_at_10 value: 47.63 - type: mrr_at_100 value: 48.259 - type: mrr_at_1000 value: 48.302 - type: mrr_at_3 value: 45.408 - type: mrr_at_5 value: 46.971000000000004 - type: ndcg_at_1 value: 36.997 - type: ndcg_at_10 value: 28.781000000000002 - type: ndcg_at_100 value: 26.644000000000002 - type: ndcg_at_1000 value: 35.812 - type: ndcg_at_3 value: 34.056 - type: ndcg_at_5 value: 31.804 - type: precision_at_1 value: 38.080000000000005 - type: precision_at_10 value: 20.96 - type: precision_at_100 value: 6.808 - type: precision_at_1000 value: 1.991 - type: precision_at_3 value: 32.095 - type: precision_at_5 value: 27.43 - type: recall_at_1 value: 4.35 - type: recall_at_10 value: 14.396 - type: recall_at_100 value: 28.126 - type: recall_at_1000 value: 60.785 - type: recall_at_3 value: 9.001000000000001 - type: recall_at_5 value: 11.197 - task: type: Retrieval dataset: type: nq name: MTEB NQ config: default split: test revision: None metrics: - type: map_at_1 value: 9.408 - type: map_at_10 value: 17.247 - type: map_at_100 value: 18.578 - type: map_at_1000 value: 18.683 - type: map_at_3 value: 14.424999999999999 - type: map_at_5 value: 15.967999999999998 - type: mrr_at_1 value: 10.718 - type: mrr_at_10 value: 18.974 - type: mrr_at_100 value: 20.153 - type: mrr_at_1000 value: 20.238 - type: mrr_at_3 value: 16.087 - type: mrr_at_5 value: 17.685000000000002 - type: ndcg_at_1 value: 10.718 - type: ndcg_at_10 value: 22.313 - type: ndcg_at_100 value: 28.810999999999996 - type: ndcg_at_1000 value: 31.495 - type: ndcg_at_3 value: 16.487 - type: ndcg_at_5 value: 19.252 - type: precision_at_1 value: 10.718 - type: precision_at_10 value: 4.256 - type: precision_at_100 value: 0.7979999999999999 - type: precision_at_1000 value: 0.105 - type: precision_at_3 value: 7.976 - type: precision_at_5 value: 6.3149999999999995 - type: recall_at_1 value: 9.408 - type: recall_at_10 value: 36.364999999999995 - type: recall_at_100 value: 66.16499999999999 - type: recall_at_1000 value: 86.47399999999999 - type: recall_at_3 value: 20.829 - type: recall_at_5 value: 27.296 - task: type: Retrieval dataset: type: quora name: MTEB QuoraRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 65.499 - type: map_at_10 value: 78.432 - type: map_at_100 value: 79.169 - type: map_at_1000 value: 79.199 - type: map_at_3 value: 75.476 - type: map_at_5 value: 77.28399999999999 - type: mrr_at_1 value: 75.55 - type: mrr_at_10 value: 82.16499999999999 - type: mrr_at_100 value: 82.37 - type: mrr_at_1000 value: 82.375 - type: mrr_at_3 value: 80.925 - type: mrr_at_5 value: 81.748 - type: ndcg_at_1 value: 75.58 - type: ndcg_at_10 value: 82.663 - type: ndcg_at_100 value: 84.526 - type: ndcg_at_1000 value: 84.843 - type: ndcg_at_3 value: 79.38300000000001 - type: ndcg_at_5 value: 81.133 - type: precision_at_1 value: 75.58 - type: precision_at_10 value: 12.562000000000001 - type: precision_at_100 value: 1.48 - type: precision_at_1000 value: 0.155 - type: precision_at_3 value: 34.583000000000006 - type: precision_at_5 value: 22.858 - type: recall_at_1 value: 65.499 - type: recall_at_10 value: 90.71000000000001 - type: recall_at_100 value: 97.717 - type: recall_at_1000 value: 99.551 - type: recall_at_3 value: 81.273 - type: recall_at_5 value: 86.172 - task: type: Clustering dataset: type: mteb/reddit-clustering name: MTEB RedditClustering config: default split: test revision: 24640382cdbf8abc73003fb0fa6d111a705499eb metrics: - type: v_measure value: 43.28689524907211 - task: type: Clustering dataset: type: mteb/reddit-clustering-p2p name: MTEB RedditClusteringP2P config: default split: test revision: 282350215ef01743dc01b456c7f5241fa8937f16 metrics: - type: v_measure value: 54.41734813535957 - task: type: Retrieval dataset: type: scidocs name: MTEB SCIDOCS config: default split: test revision: None metrics: - type: map_at_1 value: 3.305 - type: map_at_10 value: 8.502 - type: map_at_100 value: 10.288 - type: map_at_1000 value: 10.599 - type: map_at_3 value: 6.146 - type: map_at_5 value: 7.207 - type: mrr_at_1 value: 16.400000000000002 - type: mrr_at_10 value: 26.054 - type: mrr_at_100 value: 27.319 - type: mrr_at_1000 value: 27.400000000000002 - type: mrr_at_3 value: 22.967000000000002 - type: mrr_at_5 value: 24.542 - type: ndcg_at_1 value: 16.400000000000002 - type: ndcg_at_10 value: 14.943000000000001 - type: ndcg_at_100 value: 22.596 - type: ndcg_at_1000 value: 28.345 - type: ndcg_at_3 value: 14.011000000000001 - type: ndcg_at_5 value: 12.065 - type: precision_at_1 value: 16.400000000000002 - type: precision_at_10 value: 7.93 - type: precision_at_100 value: 1.902 - type: precision_at_1000 value: 0.328 - type: precision_at_3 value: 13.233 - type: precision_at_5 value: 10.620000000000001 - type: recall_at_1 value: 3.305 - type: recall_at_10 value: 16.07 - type: recall_at_100 value: 38.592999999999996 - type: recall_at_1000 value: 66.678 - type: recall_at_3 value: 8.025 - type: recall_at_5 value: 10.743 - task: type: STS dataset: type: mteb/sickr-sts name: MTEB SICK-R config: default split: test revision: a6ea5a8cab320b040a23452cc28066d9beae2cee metrics: - type: cos_sim_pearson value: 94.03602783680165 - type: cos_sim_spearman value: 91.93466287712853 - type: euclidean_pearson value: 91.5804659261222 - type: euclidean_spearman value: 91.84239224991634 - type: manhattan_pearson value: 91.57789872896991 - type: manhattan_spearman value: 91.82031929038708 - task: type: STS dataset: type: mteb/sts12-sts name: MTEB STS12 config: default split: test revision: a0d554a64d88156834ff5ae9920b964011b16384 metrics: - type: cos_sim_pearson value: 97.2530615783017 - type: cos_sim_spearman value: 95.61025838976805 - type: euclidean_pearson value: 95.41071037458771 - type: euclidean_spearman value: 95.6207550803838 - type: manhattan_pearson value: 95.39723545188045 - type: manhattan_spearman value: 95.61540593501014 - task: type: STS dataset: type: mteb/sts13-sts name: MTEB STS13 config: default split: test revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca metrics: - type: cos_sim_pearson value: 95.27491458980685 - type: cos_sim_spearman value: 95.1521844663505 - type: euclidean_pearson value: 94.63883752108002 - type: euclidean_spearman value: 94.85954995945424 - type: manhattan_pearson value: 94.59749433419627 - type: manhattan_spearman value: 94.80626857571967 - task: type: STS dataset: type: mteb/sts14-sts name: MTEB STS14 config: default split: test revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 metrics: - type: cos_sim_pearson value: 97.10518525877228 - type: cos_sim_spearman value: 96.85836209648471 - type: euclidean_pearson value: 95.8019730340664 - type: euclidean_spearman value: 96.78892865690494 - type: manhattan_pearson value: 95.79265816494754 - type: manhattan_spearman value: 96.7712534155723 - task: type: STS dataset: type: mteb/sts15-sts name: MTEB STS15 config: default split: test revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 metrics: - type: cos_sim_pearson value: 96.66550105336606 - type: cos_sim_spearman value: 96.73134982392861 - type: euclidean_pearson value: 95.50375963201927 - type: euclidean_spearman value: 96.46785996403956 - type: manhattan_pearson value: 95.47555707089327 - type: manhattan_spearman value: 96.40825860300748 - task: type: STS dataset: type: mteb/sts16-sts name: MTEB STS16 config: default split: test revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 metrics: - type: cos_sim_pearson value: 96.07365154052914 - type: cos_sim_spearman value: 96.1720485037732 - type: euclidean_pearson value: 95.58880196128803 - type: euclidean_spearman value: 96.02102007396296 - type: manhattan_pearson value: 95.60295336628664 - type: manhattan_spearman value: 96.03461694944212 - 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: 96.14907313714893 - type: cos_sim_spearman value: 96.14822520805113 - type: euclidean_pearson value: 95.62140726773103 - type: euclidean_spearman value: 96.01818385482282 - type: manhattan_pearson value: 95.60795162280982 - type: manhattan_spearman value: 96.00703635484169 - task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (en) config: en split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics: - type: cos_sim_pearson value: 66.35513203366195 - type: cos_sim_spearman value: 64.92002333937089 - type: euclidean_pearson value: 67.06304516009153 - type: euclidean_spearman value: 65.3504536039936 - type: manhattan_pearson value: 67.22016756598737 - type: manhattan_spearman value: 65.64455991383844 - task: type: STS dataset: type: mteb/stsbenchmark-sts name: MTEB STSBenchmark config: default split: test revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 metrics: - type: cos_sim_pearson value: 96.59372149477922 - type: cos_sim_spearman value: 96.97247348665515 - type: euclidean_pearson value: 95.64890160850817 - type: euclidean_spearman value: 96.84619618958573 - type: manhattan_pearson value: 95.65581449537562 - type: manhattan_spearman value: 96.853383309355 - task: type: Reranking dataset: type: mteb/scidocs-reranking name: MTEB SciDocsRR config: default split: test revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab metrics: - type: map value: 79.9991957697061 - type: mrr value: 93.85864317236866 - task: type: Retrieval dataset: type: scifact name: MTEB SciFact config: default split: test revision: None metrics: - type: map_at_1 value: 42.25 - type: map_at_10 value: 51.257 - type: map_at_100 value: 52.261 - type: map_at_1000 value: 52.309000000000005 - type: map_at_3 value: 48.759 - type: map_at_5 value: 50.413 - type: mrr_at_1 value: 44.0 - type: mrr_at_10 value: 52.367 - type: mrr_at_100 value: 53.181999999999995 - type: mrr_at_1000 value: 53.223 - type: mrr_at_3 value: 50.222 - type: mrr_at_5 value: 51.656 - type: ndcg_at_1 value: 44.0 - type: ndcg_at_10 value: 55.672 - type: ndcg_at_100 value: 59.779 - type: ndcg_at_1000 value: 61.114999999999995 - type: ndcg_at_3 value: 51.136 - type: ndcg_at_5 value: 53.822 - type: precision_at_1 value: 44.0 - type: precision_at_10 value: 7.6 - type: precision_at_100 value: 0.9730000000000001 - type: precision_at_1000 value: 0.109 - type: precision_at_3 value: 20.111 - type: precision_at_5 value: 13.733 - type: recall_at_1 value: 42.25 - type: recall_at_10 value: 67.989 - type: recall_at_100 value: 85.56700000000001 - type: recall_at_1000 value: 96.267 - type: recall_at_3 value: 56.27799999999999 - type: recall_at_5 value: 62.678 - task: type: PairClassification dataset: type: mteb/sprintduplicatequestions-pairclassification name: MTEB SprintDuplicateQuestions config: default split: test revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 metrics: - type: cos_sim_accuracy value: 99.75346534653465 - type: cos_sim_ap value: 92.92934020206276 - type: cos_sim_f1 value: 87.37373737373737 - type: cos_sim_precision value: 88.26530612244898 - type: cos_sim_recall value: 86.5 - type: dot_accuracy value: 99.7 - type: dot_ap value: 90.30253078505329 - type: dot_f1 value: 84.55696202531644 - type: dot_precision value: 85.64102564102564 - type: dot_recall value: 83.5 - type: euclidean_accuracy value: 99.75742574257426 - type: euclidean_ap value: 92.97542565802068 - type: euclidean_f1 value: 87.48083801737351 - type: euclidean_precision value: 89.44618599791013 - type: euclidean_recall value: 85.6 - type: manhattan_accuracy value: 99.75643564356436 - type: manhattan_ap value: 92.92733519229752 - type: manhattan_f1 value: 87.41044012282498 - type: manhattan_precision value: 89.51781970649894 - type: manhattan_recall value: 85.39999999999999 - type: max_accuracy value: 99.75742574257426 - type: max_ap value: 92.97542565802068 - type: max_f1 value: 87.48083801737351 - task: type: Clustering dataset: type: mteb/stackexchange-clustering name: MTEB StackExchangeClustering config: default split: test revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 metrics: - type: v_measure value: 46.968629347107225 - task: type: Clustering dataset: type: mteb/stackexchange-clustering-p2p name: MTEB StackExchangeClusteringP2P config: default split: test revision: 815ca46b2622cec33ccafc3735d572c266efdb44 metrics: - type: v_measure value: 31.76101811464947 - task: type: Reranking dataset: type: mteb/stackoverflowdupquestions-reranking name: MTEB StackOverflowDupQuestions config: default split: test revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 metrics: - type: map value: 47.838618465936364 - type: mrr value: 48.51134772090654 - task: type: Summarization dataset: type: mteb/summeval name: MTEB SummEval config: default split: test revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c metrics: - type: cos_sim_pearson value: 30.101149949190837 - type: cos_sim_spearman value: 30.99886288816569 - type: dot_pearson value: 28.905040829977978 - type: dot_spearman value: 28.101690957830428 - task: type: Retrieval dataset: type: trec-covid name: MTEB TRECCOVID config: default split: test revision: None metrics: - type: map_at_1 value: 0.129 - type: map_at_10 value: 0.6930000000000001 - type: map_at_100 value: 2.408 - type: map_at_1000 value: 4.731 - type: map_at_3 value: 0.314 - type: map_at_5 value: 0.43 - type: mrr_at_1 value: 44.0 - type: mrr_at_10 value: 55.132999999999996 - type: mrr_at_100 value: 56.455 - type: mrr_at_1000 value: 56.474000000000004 - type: mrr_at_3 value: 53.333 - type: mrr_at_5 value: 55.132999999999996 - type: ndcg_at_1 value: 40.0 - type: ndcg_at_10 value: 33.283 - type: ndcg_at_100 value: 18.892 - type: ndcg_at_1000 value: 17.457 - type: ndcg_at_3 value: 39.073 - type: ndcg_at_5 value: 35.609 - type: precision_at_1 value: 44.0 - type: precision_at_10 value: 33.800000000000004 - type: precision_at_100 value: 17.44 - type: precision_at_1000 value: 7.04 - type: precision_at_3 value: 40.666999999999994 - type: precision_at_5 value: 36.4 - type: recall_at_1 value: 0.129 - type: recall_at_10 value: 0.91 - type: recall_at_100 value: 4.449 - type: recall_at_1000 value: 16.091 - type: recall_at_3 value: 0.349 - type: recall_at_5 value: 0.518 - task: type: Retrieval dataset: type: webis-touche2020 name: MTEB Touche2020 config: default split: test revision: None metrics: - type: map_at_1 value: 1.189 - type: map_at_10 value: 5.196 - type: map_at_100 value: 8.984 - type: map_at_1000 value: 10.333 - type: map_at_3 value: 2.513 - type: map_at_5 value: 3.8089999999999997 - type: mrr_at_1 value: 14.285999999999998 - type: mrr_at_10 value: 26.295 - type: mrr_at_100 value: 28.285 - type: mrr_at_1000 value: 28.303 - type: mrr_at_3 value: 22.109 - type: mrr_at_5 value: 24.864 - type: ndcg_at_1 value: 12.245000000000001 - type: ndcg_at_10 value: 13.196 - type: ndcg_at_100 value: 24.189 - type: ndcg_at_1000 value: 36.015 - type: ndcg_at_3 value: 12.153 - type: ndcg_at_5 value: 13.459999999999999 - type: precision_at_1 value: 14.285999999999998 - type: precision_at_10 value: 12.653 - type: precision_at_100 value: 5.673 - type: precision_at_1000 value: 1.32 - type: precision_at_3 value: 12.925 - type: precision_at_5 value: 15.101999999999999 - type: recall_at_1 value: 1.189 - type: recall_at_10 value: 9.478 - type: recall_at_100 value: 36.076 - type: recall_at_1000 value: 71.88900000000001 - type: recall_at_3 value: 3.1710000000000003 - type: recall_at_5 value: 5.944 - task: type: Classification dataset: type: mteb/toxic_conversations_50k name: MTEB ToxicConversationsClassification config: default split: test revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c metrics: - type: accuracy value: 81.1632 - type: ap value: 21.801031224655016 - type: f1 value: 63.93057804886679 - task: type: Classification dataset: type: mteb/tweet_sentiment_extraction name: MTEB TweetSentimentExtractionClassification config: default split: test revision: d604517c81ca91fe16a244d1248fc021f9ecee7a metrics: - type: accuracy value: 68.15789473684211 - type: f1 value: 68.55744497973521 - task: type: Clustering dataset: type: mteb/twentynewsgroups-clustering name: MTEB TwentyNewsgroupsClustering config: default split: test revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 metrics: - type: v_measure value: 53.77313771942972 - task: type: PairClassification dataset: type: mteb/twittersemeval2015-pairclassification name: MTEB TwitterSemEval2015 config: default split: test revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 metrics: - type: cos_sim_accuracy value: 85.79603027954938 - type: cos_sim_ap value: 73.19931192854375 - type: cos_sim_f1 value: 66.7699457784663 - type: cos_sim_precision value: 65.3690596562184 - type: cos_sim_recall value: 68.23218997361478 - type: dot_accuracy value: 84.72313286046374 - type: dot_ap value: 69.84066382008972 - type: dot_f1 value: 64.42618869803336 - type: dot_precision value: 60.98020735155514 - type: dot_recall value: 68.28496042216359 - type: euclidean_accuracy value: 85.81391190320082 - type: euclidean_ap value: 73.4051677083228 - type: euclidean_f1 value: 67.35092864125122 - type: euclidean_precision value: 62.721893491124256 - type: euclidean_recall value: 72.71767810026385 - type: manhattan_accuracy value: 85.81391190320082 - type: manhattan_ap value: 73.33759860950396 - type: manhattan_f1 value: 67.32576589771757 - type: manhattan_precision value: 62.63910969793323 - type: manhattan_recall value: 72.77044854881267 - type: max_accuracy value: 85.81391190320082 - type: max_ap value: 73.4051677083228 - type: max_f1 value: 67.35092864125122 - task: type: PairClassification dataset: type: mteb/twitterurlcorpus-pairclassification name: MTEB TwitterURLCorpus config: default split: test revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf metrics: - type: cos_sim_accuracy value: 88.17479722125199 - type: cos_sim_ap value: 84.37486145048878 - type: cos_sim_f1 value: 76.65294717365856 - type: cos_sim_precision value: 75.21304186735827 - type: cos_sim_recall value: 78.14906067138897 - type: dot_accuracy value: 87.72460899600264 - type: dot_ap value: 83.01188676406672 - type: dot_f1 value: 75.8810775054206 - type: dot_precision value: 72.58665541728186 - type: dot_recall value: 79.48875885432707 - type: euclidean_accuracy value: 88.16315442232313 - type: euclidean_ap value: 84.32021529803454 - type: euclidean_f1 value: 76.60147856804691 - type: euclidean_precision value: 72.67638725727316 - type: euclidean_recall value: 80.97474591931014 - type: manhattan_accuracy value: 88.19226141964528 - type: manhattan_ap value: 84.30111334073442 - type: manhattan_f1 value: 76.48944401459048 - type: manhattan_precision value: 73.34134105843285 - type: manhattan_recall value: 79.91992608561749 - type: max_accuracy value: 88.19226141964528 - type: max_ap value: 84.37486145048878 - type: max_f1 value: 76.65294717365856 ---