--- tags: - mteb model-index: - name: epoch_0_model results: - task: type: Classification dataset: type: mteb/amazon_counterfactual name: MTEB AmazonCounterfactualClassification (en) config: en split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics: - type: accuracy value: 77.56716417910448 - type: ap value: 40.91549063721234 - type: f1 value: 71.51708294746035 - task: type: Classification dataset: type: mteb/amazon_polarity name: MTEB AmazonPolarityClassification config: default split: test revision: e2d317d38cd51312af73b3d32a06d1a08b442046 metrics: - type: accuracy value: 89.50825 - type: ap value: 86.00556056390054 - type: f1 value: 89.48068855084334 - task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (en) config: en split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics: - type: accuracy value: 46.82399999999999 - type: f1 value: 46.272112748273315 - task: type: Retrieval dataset: type: arguana name: MTEB ArguAna config: default split: test revision: None metrics: - type: map_at_1 value: 28.592000000000002 - type: map_at_10 value: 44.37 - type: map_at_100 value: 45.355000000000004 - type: map_at_1000 value: 45.363 - type: map_at_3 value: 39.272 - type: map_at_5 value: 42.405 - type: mrr_at_1 value: 29.445 - type: mrr_at_10 value: 44.668 - type: mrr_at_100 value: 45.646 - type: mrr_at_1000 value: 45.655 - type: mrr_at_3 value: 39.545 - type: mrr_at_5 value: 42.674 - type: ndcg_at_1 value: 28.592000000000002 - type: ndcg_at_10 value: 53.230999999999995 - type: ndcg_at_100 value: 57.188 - type: ndcg_at_1000 value: 57.371 - type: ndcg_at_3 value: 42.842 - type: ndcg_at_5 value: 48.538 - type: precision_at_1 value: 28.592000000000002 - type: precision_at_10 value: 8.151 - type: precision_at_100 value: 0.9820000000000001 - type: precision_at_1000 value: 0.1 - type: precision_at_3 value: 17.733999999999998 - type: precision_at_5 value: 13.428 - type: recall_at_1 value: 28.592000000000002 - type: recall_at_10 value: 81.50800000000001 - type: recall_at_100 value: 98.222 - type: recall_at_1000 value: 99.57300000000001 - type: recall_at_3 value: 53.201 - type: recall_at_5 value: 67.14099999999999 - task: type: Clustering dataset: type: mteb/arxiv-clustering-p2p name: MTEB ArxivClusteringP2P config: default split: test revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d metrics: - type: v_measure value: 45.83975081280601 - task: type: Clustering dataset: type: mteb/arxiv-clustering-s2s name: MTEB ArxivClusteringS2S config: default split: test revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 metrics: - type: v_measure value: 36.20880276672235 - task: type: Reranking dataset: type: mteb/askubuntudupquestions-reranking name: MTEB AskUbuntuDupQuestions config: default split: test revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 metrics: - type: map value: 60.88591268158169 - type: mrr value: 75.19709361122104 - task: type: STS dataset: type: mteb/biosses-sts name: MTEB BIOSSES config: default split: test revision: d3fb88f8f02e40887cd149695127462bbcf29b4a metrics: - type: cos_sim_pearson value: 89.65453333525659 - type: cos_sim_spearman value: 86.84535232424253 - type: euclidean_pearson value: 88.44638498736246 - type: euclidean_spearman value: 86.84535232424253 - type: manhattan_pearson value: 88.73402151565195 - type: manhattan_spearman value: 87.24415659199119 - task: type: Classification dataset: type: mteb/banking77 name: MTEB Banking77Classification config: default split: test revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 metrics: - type: accuracy value: 84.7564935064935 - type: f1 value: 84.70138093263196 - task: type: Clustering dataset: type: mteb/biorxiv-clustering-p2p name: MTEB BiorxivClusteringP2P config: default split: test revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 metrics: - type: v_measure value: 38.272839537742655 - task: type: Clustering dataset: type: mteb/biorxiv-clustering-s2s name: MTEB BiorxivClusteringS2S config: default split: test revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 metrics: - type: v_measure value: 33.03251777955244 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackAndroidRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 30.319000000000003 - type: map_at_10 value: 40.161 - type: map_at_100 value: 41.557 - type: map_at_1000 value: 41.678 - type: map_at_3 value: 37.008 - type: map_at_5 value: 38.592 - type: mrr_at_1 value: 37.053000000000004 - type: mrr_at_10 value: 45.597 - type: mrr_at_100 value: 46.443 - type: mrr_at_1000 value: 46.489000000000004 - type: mrr_at_3 value: 43.085 - type: mrr_at_5 value: 44.43 - type: ndcg_at_1 value: 37.053000000000004 - type: ndcg_at_10 value: 45.948 - type: ndcg_at_100 value: 51.44800000000001 - type: ndcg_at_1000 value: 53.54 - type: ndcg_at_3 value: 41.316 - type: ndcg_at_5 value: 43.15 - type: precision_at_1 value: 37.053000000000004 - type: precision_at_10 value: 8.569 - type: precision_at_100 value: 1.425 - type: precision_at_1000 value: 0.189 - type: precision_at_3 value: 19.695 - type: precision_at_5 value: 13.763 - type: recall_at_1 value: 30.319000000000003 - type: recall_at_10 value: 57.233000000000004 - type: recall_at_100 value: 80.441 - type: recall_at_1000 value: 94.041 - type: recall_at_3 value: 43.028 - type: recall_at_5 value: 48.806 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackEnglishRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 31.022 - type: map_at_10 value: 41.305 - type: map_at_100 value: 42.576 - type: map_at_1000 value: 42.707 - type: map_at_3 value: 38.271 - type: map_at_5 value: 40.048 - type: mrr_at_1 value: 39.427 - type: mrr_at_10 value: 47.707 - type: mrr_at_100 value: 48.394 - type: mrr_at_1000 value: 48.439 - type: mrr_at_3 value: 45.552 - type: mrr_at_5 value: 46.823 - type: ndcg_at_1 value: 39.427 - type: ndcg_at_10 value: 47.121 - type: ndcg_at_100 value: 51.458999999999996 - type: ndcg_at_1000 value: 53.461000000000006 - type: ndcg_at_3 value: 43.001 - type: ndcg_at_5 value: 45.025 - type: precision_at_1 value: 39.427 - type: precision_at_10 value: 8.994 - type: precision_at_100 value: 1.456 - type: precision_at_1000 value: 0.192 - type: precision_at_3 value: 20.913 - type: precision_at_5 value: 14.917 - type: recall_at_1 value: 31.022 - type: recall_at_10 value: 56.769999999999996 - type: recall_at_100 value: 75.154 - type: recall_at_1000 value: 87.832 - type: recall_at_3 value: 44.295 - type: recall_at_5 value: 50.041000000000004 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGamingRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 41.021 - type: map_at_10 value: 52.931 - type: map_at_100 value: 53.846000000000004 - type: map_at_1000 value: 53.905 - type: map_at_3 value: 49.952000000000005 - type: map_at_5 value: 51.566 - type: mrr_at_1 value: 46.708 - type: mrr_at_10 value: 56.467999999999996 - type: mrr_at_100 value: 57.06400000000001 - type: mrr_at_1000 value: 57.096999999999994 - type: mrr_at_3 value: 54.295 - type: mrr_at_5 value: 55.52 - type: ndcg_at_1 value: 46.708 - type: ndcg_at_10 value: 58.458 - type: ndcg_at_100 value: 62.21 - type: ndcg_at_1000 value: 63.438 - type: ndcg_at_3 value: 53.493 - type: ndcg_at_5 value: 55.824 - type: precision_at_1 value: 46.708 - type: precision_at_10 value: 9.166 - type: precision_at_100 value: 1.199 - type: precision_at_1000 value: 0.135 - type: precision_at_3 value: 23.532 - type: precision_at_5 value: 15.862000000000002 - type: recall_at_1 value: 41.021 - type: recall_at_10 value: 71.25 - type: recall_at_100 value: 87.507 - type: recall_at_1000 value: 96.206 - type: recall_at_3 value: 58.089 - type: recall_at_5 value: 63.82 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGisRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 26.413999999999998 - type: map_at_10 value: 34.404 - type: map_at_100 value: 35.359 - type: map_at_1000 value: 35.435 - type: map_at_3 value: 32.017 - type: map_at_5 value: 33.243 - type: mrr_at_1 value: 28.362 - type: mrr_at_10 value: 36.393 - type: mrr_at_100 value: 37.211 - type: mrr_at_1000 value: 37.273 - type: mrr_at_3 value: 33.992 - type: mrr_at_5 value: 35.309000000000005 - type: ndcg_at_1 value: 28.362 - type: ndcg_at_10 value: 38.964 - type: ndcg_at_100 value: 43.791000000000004 - type: ndcg_at_1000 value: 45.89 - type: ndcg_at_3 value: 34.201 - type: ndcg_at_5 value: 36.334 - type: precision_at_1 value: 28.362 - type: precision_at_10 value: 5.842 - type: precision_at_100 value: 0.868 - type: precision_at_1000 value: 0.109 - type: precision_at_3 value: 14.049 - type: precision_at_5 value: 9.695 - type: recall_at_1 value: 26.413999999999998 - type: recall_at_10 value: 51.017999999999994 - type: recall_at_100 value: 73.551 - type: recall_at_1000 value: 89.51 - type: recall_at_3 value: 38.385000000000005 - type: recall_at_5 value: 43.351 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackMathematicaRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 17.721999999999998 - type: map_at_10 value: 24.55 - type: map_at_100 value: 25.586 - type: map_at_1000 value: 25.715 - type: map_at_3 value: 22.445 - type: map_at_5 value: 23.497 - type: mrr_at_1 value: 21.642 - type: mrr_at_10 value: 28.979 - type: mrr_at_100 value: 29.898000000000003 - type: mrr_at_1000 value: 29.981 - type: mrr_at_3 value: 26.886 - type: mrr_at_5 value: 28.055999999999997 - type: ndcg_at_1 value: 21.642 - type: ndcg_at_10 value: 29.158 - type: ndcg_at_100 value: 34.352 - type: ndcg_at_1000 value: 37.456 - type: ndcg_at_3 value: 25.302000000000003 - type: ndcg_at_5 value: 26.916 - type: precision_at_1 value: 21.642 - type: precision_at_10 value: 5.274 - type: precision_at_100 value: 0.907 - type: precision_at_1000 value: 0.131 - type: precision_at_3 value: 12.148 - type: precision_at_5 value: 8.458 - type: recall_at_1 value: 17.721999999999998 - type: recall_at_10 value: 38.926 - type: recall_at_100 value: 61.698 - type: recall_at_1000 value: 83.742 - type: recall_at_3 value: 28.209 - type: recall_at_5 value: 32.462999999999994 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackPhysicsRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 28.429 - type: map_at_10 value: 38.0 - type: map_at_100 value: 39.262 - type: map_at_1000 value: 39.371 - type: map_at_3 value: 35.031 - type: map_at_5 value: 36.935 - type: mrr_at_1 value: 33.782000000000004 - type: mrr_at_10 value: 43.164 - type: mrr_at_100 value: 43.962 - type: mrr_at_1000 value: 44.012 - type: mrr_at_3 value: 40.711999999999996 - type: mrr_at_5 value: 42.32 - type: ndcg_at_1 value: 33.782000000000004 - type: ndcg_at_10 value: 43.574 - type: ndcg_at_100 value: 48.903999999999996 - type: ndcg_at_1000 value: 51.074 - type: ndcg_at_3 value: 38.858 - type: ndcg_at_5 value: 41.581 - type: precision_at_1 value: 33.782000000000004 - type: precision_at_10 value: 7.7 - type: precision_at_100 value: 1.217 - type: precision_at_1000 value: 0.157 - type: precision_at_3 value: 18.157999999999998 - type: precision_at_5 value: 13.128 - type: recall_at_1 value: 28.429 - type: recall_at_10 value: 54.63 - type: recall_at_100 value: 77.183 - type: recall_at_1000 value: 91.708 - type: recall_at_3 value: 41.81 - type: recall_at_5 value: 48.794 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackProgrammersRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 25.579 - type: map_at_10 value: 35.135 - type: map_at_100 value: 36.382999999999996 - type: map_at_1000 value: 36.482 - type: map_at_3 value: 32.25 - type: map_at_5 value: 33.873999999999995 - type: mrr_at_1 value: 31.279 - type: mrr_at_10 value: 40.261 - type: mrr_at_100 value: 41.128 - type: mrr_at_1000 value: 41.175 - type: mrr_at_3 value: 37.823 - type: mrr_at_5 value: 39.245000000000005 - type: ndcg_at_1 value: 31.279 - type: ndcg_at_10 value: 40.64 - type: ndcg_at_100 value: 46.224 - type: ndcg_at_1000 value: 48.392 - type: ndcg_at_3 value: 35.913000000000004 - type: ndcg_at_5 value: 38.086999999999996 - type: precision_at_1 value: 31.279 - type: precision_at_10 value: 7.306 - type: precision_at_100 value: 1.185 - type: precision_at_1000 value: 0.154 - type: precision_at_3 value: 17.009 - type: precision_at_5 value: 12.123000000000001 - type: recall_at_1 value: 25.579 - type: recall_at_10 value: 52.018 - type: recall_at_100 value: 76.02799999999999 - type: recall_at_1000 value: 90.996 - type: recall_at_3 value: 38.769 - type: recall_at_5 value: 44.417 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 26.15416666666666 - type: map_at_10 value: 34.64533333333333 - type: map_at_100 value: 35.7715 - type: map_at_1000 value: 35.885333333333335 - type: map_at_3 value: 32.03941666666667 - type: map_at_5 value: 33.47041666666667 - type: mrr_at_1 value: 30.654583333333328 - type: mrr_at_10 value: 38.71783333333333 - type: mrr_at_100 value: 39.52499999999999 - type: mrr_at_1000 value: 39.584250000000004 - type: mrr_at_3 value: 36.42975 - type: mrr_at_5 value: 37.72874999999999 - type: ndcg_at_1 value: 30.654583333333328 - type: ndcg_at_10 value: 39.663583333333335 - type: ndcg_at_100 value: 44.600249999999996 - type: ndcg_at_1000 value: 46.93808333333333 - type: ndcg_at_3 value: 35.2025 - type: ndcg_at_5 value: 37.27008333333333 - type: precision_at_1 value: 30.654583333333328 - type: precision_at_10 value: 6.8140833333333335 - type: precision_at_100 value: 1.1011666666666666 - type: precision_at_1000 value: 0.14883333333333335 - type: precision_at_3 value: 15.982249999999997 - type: precision_at_5 value: 11.254916666666666 - type: recall_at_1 value: 26.15416666666666 - type: recall_at_10 value: 50.44783333333333 - type: recall_at_100 value: 72.172 - type: recall_at_1000 value: 88.49900000000001 - type: recall_at_3 value: 38.030750000000005 - type: recall_at_5 value: 43.37716666666667 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackStatsRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 24.936 - type: map_at_10 value: 31.274 - type: map_at_100 value: 32.127 - type: map_at_1000 value: 32.218999999999994 - type: map_at_3 value: 29.036 - type: map_at_5 value: 30.128 - type: mrr_at_1 value: 27.454 - type: mrr_at_10 value: 33.973 - type: mrr_at_100 value: 34.75 - type: mrr_at_1000 value: 34.821999999999996 - type: mrr_at_3 value: 31.979000000000003 - type: mrr_at_5 value: 32.975 - type: ndcg_at_1 value: 27.454 - type: ndcg_at_10 value: 35.259 - type: ndcg_at_100 value: 39.513 - type: ndcg_at_1000 value: 41.913 - type: ndcg_at_3 value: 31.184 - type: ndcg_at_5 value: 32.804 - type: precision_at_1 value: 27.454 - type: precision_at_10 value: 5.445 - type: precision_at_100 value: 0.8250000000000001 - type: precision_at_1000 value: 0.109 - type: precision_at_3 value: 12.986 - type: precision_at_5 value: 8.895999999999999 - type: recall_at_1 value: 24.936 - type: recall_at_10 value: 44.807 - type: recall_at_100 value: 64.046 - type: recall_at_1000 value: 81.959 - type: recall_at_3 value: 33.587 - type: recall_at_5 value: 37.665 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackTexRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 16.641000000000002 - type: map_at_10 value: 23.794 - type: map_at_100 value: 24.769 - type: map_at_1000 value: 24.898999999999997 - type: map_at_3 value: 21.67 - type: map_at_5 value: 22.933 - type: mrr_at_1 value: 20.061999999999998 - type: mrr_at_10 value: 27.467999999999996 - type: mrr_at_100 value: 28.303 - type: mrr_at_1000 value: 28.387 - type: mrr_at_3 value: 25.361 - type: mrr_at_5 value: 26.676 - type: ndcg_at_1 value: 20.061999999999998 - type: ndcg_at_10 value: 28.218 - type: ndcg_at_100 value: 32.988 - type: ndcg_at_1000 value: 36.083 - type: ndcg_at_3 value: 24.391 - type: ndcg_at_5 value: 26.349 - type: precision_at_1 value: 20.061999999999998 - type: precision_at_10 value: 4.997 - type: precision_at_100 value: 0.8670000000000001 - type: precision_at_1000 value: 0.131 - type: precision_at_3 value: 11.402 - type: precision_at_5 value: 8.273 - type: recall_at_1 value: 16.641000000000002 - type: recall_at_10 value: 37.925 - type: recall_at_100 value: 59.317 - type: recall_at_1000 value: 81.49499999999999 - type: recall_at_3 value: 27.381 - type: recall_at_5 value: 32.323 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackUnixRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 25.684 - type: map_at_10 value: 33.499 - type: map_at_100 value: 34.533 - type: map_at_1000 value: 34.647 - type: map_at_3 value: 30.908 - type: map_at_5 value: 32.376 - type: mrr_at_1 value: 29.757 - type: mrr_at_10 value: 37.439 - type: mrr_at_100 value: 38.239000000000004 - type: mrr_at_1000 value: 38.307 - type: mrr_at_3 value: 34.997 - type: mrr_at_5 value: 36.359 - type: ndcg_at_1 value: 29.757 - type: ndcg_at_10 value: 38.334 - type: ndcg_at_100 value: 43.171 - type: ndcg_at_1000 value: 45.775 - type: ndcg_at_3 value: 33.611999999999995 - type: ndcg_at_5 value: 35.884 - type: precision_at_1 value: 29.757 - type: precision_at_10 value: 6.361999999999999 - type: precision_at_100 value: 0.98 - type: precision_at_1000 value: 0.133 - type: precision_at_3 value: 14.988000000000001 - type: precision_at_5 value: 10.653 - type: recall_at_1 value: 25.684 - type: recall_at_10 value: 49.059000000000005 - type: recall_at_100 value: 70.339 - type: recall_at_1000 value: 88.567 - type: recall_at_3 value: 36.233 - type: recall_at_5 value: 41.974000000000004 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWebmastersRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 24.265 - type: map_at_10 value: 31.948 - type: map_at_100 value: 33.558 - type: map_at_1000 value: 33.778999999999996 - type: map_at_3 value: 29.387999999999998 - type: map_at_5 value: 30.711 - type: mrr_at_1 value: 28.854000000000003 - type: mrr_at_10 value: 36.346000000000004 - type: mrr_at_100 value: 37.273 - type: mrr_at_1000 value: 37.336000000000006 - type: mrr_at_3 value: 33.794000000000004 - type: mrr_at_5 value: 35.168 - type: ndcg_at_1 value: 28.854000000000003 - type: ndcg_at_10 value: 37.281 - type: ndcg_at_100 value: 43.125 - type: ndcg_at_1000 value: 45.9 - type: ndcg_at_3 value: 32.637 - type: ndcg_at_5 value: 34.628 - type: precision_at_1 value: 28.854000000000003 - type: precision_at_10 value: 6.957000000000001 - type: precision_at_100 value: 1.455 - type: precision_at_1000 value: 0.231 - type: precision_at_3 value: 14.954 - type: precision_at_5 value: 10.751 - type: recall_at_1 value: 24.265 - type: recall_at_10 value: 47.709 - type: recall_at_100 value: 72.894 - type: recall_at_1000 value: 90.545 - type: recall_at_3 value: 34.618 - type: recall_at_5 value: 39.793 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWordpressRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 21.818 - type: map_at_10 value: 28.743000000000002 - type: map_at_100 value: 29.702 - type: map_at_1000 value: 29.787000000000003 - type: map_at_3 value: 26.497 - type: map_at_5 value: 27.742 - type: mrr_at_1 value: 23.474999999999998 - type: mrr_at_10 value: 30.819000000000003 - type: mrr_at_100 value: 31.635 - type: mrr_at_1000 value: 31.692999999999998 - type: mrr_at_3 value: 28.681 - type: mrr_at_5 value: 29.864 - type: ndcg_at_1 value: 23.474999999999998 - type: ndcg_at_10 value: 33.007999999999996 - type: ndcg_at_100 value: 38.018 - type: ndcg_at_1000 value: 40.335 - type: ndcg_at_3 value: 28.522 - type: ndcg_at_5 value: 30.659 - type: precision_at_1 value: 23.474999999999998 - type: precision_at_10 value: 5.157 - type: precision_at_100 value: 0.83 - type: precision_at_1000 value: 0.11499999999999999 - type: precision_at_3 value: 11.953 - type: precision_at_5 value: 8.540000000000001 - type: recall_at_1 value: 21.818 - type: recall_at_10 value: 44.029 - type: recall_at_100 value: 67.906 - type: recall_at_1000 value: 85.387 - type: recall_at_3 value: 31.965 - type: recall_at_5 value: 37.079 - task: type: Retrieval dataset: type: climate-fever name: MTEB ClimateFEVER config: default split: test revision: None metrics: - type: map_at_1 value: 17.615 - type: map_at_10 value: 30.302 - type: map_at_100 value: 32.382 - type: map_at_1000 value: 32.573 - type: map_at_3 value: 25.689 - type: map_at_5 value: 28.137 - type: mrr_at_1 value: 40.847 - type: mrr_at_10 value: 53.577 - type: mrr_at_100 value: 54.19199999999999 - type: mrr_at_1000 value: 54.217999999999996 - type: mrr_at_3 value: 50.684 - type: mrr_at_5 value: 52.349000000000004 - type: ndcg_at_1 value: 40.847 - type: ndcg_at_10 value: 40.497 - type: ndcg_at_100 value: 47.575 - type: ndcg_at_1000 value: 50.663000000000004 - type: ndcg_at_3 value: 34.650999999999996 - type: ndcg_at_5 value: 36.503 - type: precision_at_1 value: 40.847 - type: precision_at_10 value: 12.469 - type: precision_at_100 value: 2.012 - type: precision_at_1000 value: 0.259 - type: precision_at_3 value: 26.124000000000002 - type: precision_at_5 value: 19.518 - type: recall_at_1 value: 17.615 - type: recall_at_10 value: 46.163 - type: recall_at_100 value: 69.985 - type: recall_at_1000 value: 87.033 - type: recall_at_3 value: 31.041999999999998 - type: recall_at_5 value: 37.419999999999995 - task: type: Retrieval dataset: type: dbpedia-entity name: MTEB DBPedia config: default split: test revision: None metrics: - type: map_at_1 value: 8.616999999999999 - type: map_at_10 value: 20.591 - type: map_at_100 value: 29.738 - type: map_at_1000 value: 31.403 - type: map_at_3 value: 14.549999999999999 - type: map_at_5 value: 17.071 - type: mrr_at_1 value: 71.25 - type: mrr_at_10 value: 77.86699999999999 - type: mrr_at_100 value: 78.154 - type: mrr_at_1000 value: 78.159 - type: mrr_at_3 value: 76.333 - type: mrr_at_5 value: 77.146 - type: ndcg_at_1 value: 59.875 - type: ndcg_at_10 value: 45.233000000000004 - type: ndcg_at_100 value: 49.395 - type: ndcg_at_1000 value: 56.352000000000004 - type: ndcg_at_3 value: 50.171 - type: ndcg_at_5 value: 47.3 - type: precision_at_1 value: 71.25 - type: precision_at_10 value: 35.9 - type: precision_at_100 value: 11.733 - type: precision_at_1000 value: 2.111 - type: precision_at_3 value: 52.917 - type: precision_at_5 value: 45.25 - type: recall_at_1 value: 8.616999999999999 - type: recall_at_10 value: 26.571 - type: recall_at_100 value: 55.289 - type: recall_at_1000 value: 77.66300000000001 - type: recall_at_3 value: 15.823 - type: recall_at_5 value: 19.921 - task: type: Classification dataset: type: mteb/emotion name: MTEB EmotionClassification config: default split: test revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 metrics: - type: accuracy value: 48.584999999999994 - type: f1 value: 43.715445937798705 - task: type: Retrieval dataset: type: fever name: MTEB FEVER config: default split: test revision: None metrics: - type: map_at_1 value: 72.175 - type: map_at_10 value: 81.659 - type: map_at_100 value: 81.918 - type: map_at_1000 value: 81.931 - type: map_at_3 value: 80.304 - type: map_at_5 value: 81.21199999999999 - type: mrr_at_1 value: 77.333 - type: mrr_at_10 value: 85.26 - type: mrr_at_100 value: 85.37400000000001 - type: mrr_at_1000 value: 85.37599999999999 - type: mrr_at_3 value: 84.378 - type: mrr_at_5 value: 85.001 - type: ndcg_at_1 value: 77.333 - type: ndcg_at_10 value: 85.533 - type: ndcg_at_100 value: 86.483 - type: ndcg_at_1000 value: 86.721 - type: ndcg_at_3 value: 83.434 - type: ndcg_at_5 value: 84.71 - type: precision_at_1 value: 77.333 - type: precision_at_10 value: 10.485999999999999 - type: precision_at_100 value: 1.121 - type: precision_at_1000 value: 0.116 - type: precision_at_3 value: 32.198 - type: precision_at_5 value: 20.222 - type: recall_at_1 value: 72.175 - type: recall_at_10 value: 93.633 - type: recall_at_100 value: 97.42699999999999 - type: recall_at_1000 value: 98.94 - type: recall_at_3 value: 88.07199999999999 - type: recall_at_5 value: 91.223 - task: type: Retrieval dataset: type: fiqa name: MTEB FiQA2018 config: default split: test revision: None metrics: - type: map_at_1 value: 19.287000000000003 - type: map_at_10 value: 31.136000000000003 - type: map_at_100 value: 32.827 - type: map_at_1000 value: 33.011 - type: map_at_3 value: 27.150999999999996 - type: map_at_5 value: 29.459999999999997 - type: mrr_at_1 value: 37.963 - type: mrr_at_10 value: 46.449 - type: mrr_at_100 value: 47.353 - type: mrr_at_1000 value: 47.39 - type: mrr_at_3 value: 44.11 - type: mrr_at_5 value: 45.391 - type: ndcg_at_1 value: 37.963 - type: ndcg_at_10 value: 38.644 - type: ndcg_at_100 value: 44.923 - type: ndcg_at_1000 value: 48.059000000000005 - type: ndcg_at_3 value: 35.141 - type: ndcg_at_5 value: 36.335 - type: precision_at_1 value: 37.963 - type: precision_at_10 value: 10.494 - type: precision_at_100 value: 1.691 - type: precision_at_1000 value: 0.22699999999999998 - type: precision_at_3 value: 23.405 - type: precision_at_5 value: 17.16 - type: recall_at_1 value: 19.287000000000003 - type: recall_at_10 value: 45.558 - type: recall_at_100 value: 68.508 - type: recall_at_1000 value: 87.10900000000001 - type: recall_at_3 value: 31.991000000000003 - type: recall_at_5 value: 38.044 - task: type: Retrieval dataset: type: hotpotqa name: MTEB HotpotQA config: default split: test revision: None metrics: - type: map_at_1 value: 40.088 - type: map_at_10 value: 66.891 - type: map_at_100 value: 67.697 - type: map_at_1000 value: 67.75 - type: map_at_3 value: 63.517999999999994 - type: map_at_5 value: 65.667 - type: mrr_at_1 value: 80.176 - type: mrr_at_10 value: 85.662 - type: mrr_at_100 value: 85.827 - type: mrr_at_1000 value: 85.833 - type: mrr_at_3 value: 84.80799999999999 - type: mrr_at_5 value: 85.349 - type: ndcg_at_1 value: 80.176 - type: ndcg_at_10 value: 74.349 - type: ndcg_at_100 value: 77.10000000000001 - type: ndcg_at_1000 value: 78.084 - type: ndcg_at_3 value: 69.647 - type: ndcg_at_5 value: 72.312 - type: precision_at_1 value: 80.176 - type: precision_at_10 value: 15.629999999999999 - type: precision_at_100 value: 1.7760000000000002 - type: precision_at_1000 value: 0.191 - type: precision_at_3 value: 45.186 - type: precision_at_5 value: 29.215000000000003 - type: recall_at_1 value: 40.088 - type: recall_at_10 value: 78.14999999999999 - type: recall_at_100 value: 88.818 - type: recall_at_1000 value: 95.273 - type: recall_at_3 value: 67.779 - type: recall_at_5 value: 73.038 - task: type: Classification dataset: type: mteb/imdb name: MTEB ImdbClassification config: default split: test revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 metrics: - type: accuracy value: 83.81960000000002 - type: ap value: 78.83196561301477 - type: f1 value: 83.75970806716482 - task: type: Retrieval dataset: type: msmarco name: MTEB MSMARCO config: default split: dev revision: None metrics: - type: map_at_1 value: 23.318 - type: map_at_10 value: 35.988 - type: map_at_100 value: 37.172 - type: map_at_1000 value: 37.217 - type: map_at_3 value: 32.193 - type: map_at_5 value: 34.467 - type: mrr_at_1 value: 23.982999999999997 - type: mrr_at_10 value: 36.588 - type: mrr_at_100 value: 37.714999999999996 - type: mrr_at_1000 value: 37.754 - type: mrr_at_3 value: 32.844 - type: mrr_at_5 value: 35.106 - type: ndcg_at_1 value: 23.982999999999997 - type: ndcg_at_10 value: 42.870000000000005 - type: ndcg_at_100 value: 48.433 - type: ndcg_at_1000 value: 49.559 - type: ndcg_at_3 value: 35.211 - type: ndcg_at_5 value: 39.273 - type: precision_at_1 value: 23.982999999999997 - type: precision_at_10 value: 6.678000000000001 - type: precision_at_100 value: 0.9440000000000001 - type: precision_at_1000 value: 0.104 - type: precision_at_3 value: 14.981 - type: precision_at_5 value: 11.046 - type: recall_at_1 value: 23.318 - type: recall_at_10 value: 63.934999999999995 - type: recall_at_100 value: 89.335 - type: recall_at_1000 value: 97.966 - type: recall_at_3 value: 43.283 - type: recall_at_5 value: 53.041000000000004 - task: type: Classification dataset: type: mteb/mtop_domain name: MTEB MTOPDomainClassification (en) config: en split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics: - type: accuracy value: 93.57045143638851 - type: f1 value: 93.27721271351861 - task: type: Classification dataset: type: mteb/mtop_intent name: MTEB MTOPIntentClassification (en) config: en split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics: - type: accuracy value: 75.33971728226174 - type: f1 value: 57.738940854439825 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (en) config: en split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 73.05985205110962 - type: f1 value: 71.13355537275797 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (en) config: en split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 77.38063214525891 - type: f1 value: 77.50780716460197 - task: type: Clustering dataset: type: mteb/medrxiv-clustering-p2p name: MTEB MedrxivClusteringP2P config: default split: test revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 metrics: - type: v_measure value: 32.74942819235406 - task: type: Clustering dataset: type: mteb/medrxiv-clustering-s2s name: MTEB MedrxivClusteringS2S config: default split: test revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 metrics: - type: v_measure value: 30.696610712314364 - task: type: Reranking dataset: type: mteb/mind_small name: MTEB MindSmallReranking config: default split: test revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 metrics: - type: map value: 28.7236836309487 - type: mrr value: 29.45527326120238 - task: type: Retrieval dataset: type: nfcorpus name: MTEB NFCorpus config: default split: test revision: None metrics: - type: map_at_1 value: 5.838 - type: map_at_10 value: 13.492999999999999 - type: map_at_100 value: 16.598 - type: map_at_1000 value: 17.937 - type: map_at_3 value: 10.119 - type: map_at_5 value: 11.666 - type: mrr_at_1 value: 45.201 - type: mrr_at_10 value: 54.391 - type: mrr_at_100 value: 54.913000000000004 - type: mrr_at_1000 value: 54.952 - type: mrr_at_3 value: 52.012 - type: mrr_at_5 value: 53.715 - type: ndcg_at_1 value: 43.498 - type: ndcg_at_10 value: 35.631 - type: ndcg_at_100 value: 31.522 - type: ndcg_at_1000 value: 39.967000000000006 - type: ndcg_at_3 value: 41.258 - type: ndcg_at_5 value: 39.007 - type: precision_at_1 value: 44.891999999999996 - type: precision_at_10 value: 26.409 - type: precision_at_100 value: 7.799 - type: precision_at_1000 value: 2.044 - type: precision_at_3 value: 39.216 - type: precision_at_5 value: 34.056 - type: recall_at_1 value: 5.838 - type: recall_at_10 value: 17.314 - type: recall_at_100 value: 30.653000000000002 - type: recall_at_1000 value: 61.092 - type: recall_at_3 value: 11.299 - type: recall_at_5 value: 13.689000000000002 - task: type: Retrieval dataset: type: nq name: MTEB NQ config: default split: test revision: None metrics: - type: map_at_1 value: 37.08 - type: map_at_10 value: 52.493 - type: map_at_100 value: 53.39699999999999 - type: map_at_1000 value: 53.422000000000004 - type: map_at_3 value: 48.504000000000005 - type: map_at_5 value: 50.878 - type: mrr_at_1 value: 41.425 - type: mrr_at_10 value: 55.001999999999995 - type: mrr_at_100 value: 55.665 - type: mrr_at_1000 value: 55.681999999999995 - type: mrr_at_3 value: 51.873000000000005 - type: mrr_at_5 value: 53.801 - type: ndcg_at_1 value: 41.396 - type: ndcg_at_10 value: 59.77400000000001 - type: ndcg_at_100 value: 63.476 - type: ndcg_at_1000 value: 64.011 - type: ndcg_at_3 value: 52.504 - type: ndcg_at_5 value: 56.379000000000005 - type: precision_at_1 value: 41.396 - type: precision_at_10 value: 9.429 - type: precision_at_100 value: 1.1520000000000001 - type: precision_at_1000 value: 0.12 - type: precision_at_3 value: 23.445 - type: precision_at_5 value: 16.333000000000002 - type: recall_at_1 value: 37.08 - type: recall_at_10 value: 79.22 - type: recall_at_100 value: 95.013 - type: recall_at_1000 value: 98.921 - type: recall_at_3 value: 60.702 - type: recall_at_5 value: 69.539 - task: type: Retrieval dataset: type: quora name: MTEB QuoraRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 70.218 - type: map_at_10 value: 83.871 - type: map_at_100 value: 84.494 - type: map_at_1000 value: 84.514 - type: map_at_3 value: 80.95 - type: map_at_5 value: 82.783 - type: mrr_at_1 value: 80.9 - type: mrr_at_10 value: 87.176 - type: mrr_at_100 value: 87.283 - type: mrr_at_1000 value: 87.28399999999999 - type: mrr_at_3 value: 86.173 - type: mrr_at_5 value: 86.872 - type: ndcg_at_1 value: 80.92 - type: ndcg_at_10 value: 87.76899999999999 - type: ndcg_at_100 value: 89.017 - type: ndcg_at_1000 value: 89.154 - type: ndcg_at_3 value: 84.87 - type: ndcg_at_5 value: 86.469 - type: precision_at_1 value: 80.92 - type: precision_at_10 value: 13.272 - type: precision_at_100 value: 1.5150000000000001 - type: precision_at_1000 value: 0.156 - type: precision_at_3 value: 37.03 - type: precision_at_5 value: 24.336 - type: recall_at_1 value: 70.218 - type: recall_at_10 value: 95.027 - type: recall_at_100 value: 99.29599999999999 - type: recall_at_1000 value: 99.936 - type: recall_at_3 value: 86.64 - type: recall_at_5 value: 91.23 - task: type: Clustering dataset: type: mteb/reddit-clustering name: MTEB RedditClustering config: default split: test revision: 24640382cdbf8abc73003fb0fa6d111a705499eb metrics: - type: v_measure value: 56.98075987853009 - task: type: Clustering dataset: type: mteb/reddit-clustering-p2p name: MTEB RedditClusteringP2P config: default split: test revision: 282350215ef01743dc01b456c7f5241fa8937f16 metrics: - type: v_measure value: 62.50448653901921 - task: type: Retrieval dataset: type: scidocs name: MTEB SCIDOCS config: default split: test revision: None metrics: - type: map_at_1 value: 4.303 - type: map_at_10 value: 10.918999999999999 - type: map_at_100 value: 12.709999999999999 - type: map_at_1000 value: 12.985 - type: map_at_3 value: 7.924 - type: map_at_5 value: 9.299 - type: mrr_at_1 value: 21.2 - type: mrr_at_10 value: 31.732 - type: mrr_at_100 value: 32.716 - type: mrr_at_1000 value: 32.775999999999996 - type: mrr_at_3 value: 28.549999999999997 - type: mrr_at_5 value: 30.064999999999998 - type: ndcg_at_1 value: 21.2 - type: ndcg_at_10 value: 18.576999999999998 - type: ndcg_at_100 value: 25.648 - type: ndcg_at_1000 value: 30.733 - type: ndcg_at_3 value: 17.718999999999998 - type: ndcg_at_5 value: 15.123000000000001 - type: precision_at_1 value: 21.2 - type: precision_at_10 value: 9.71 - type: precision_at_100 value: 1.992 - type: precision_at_1000 value: 0.322 - type: precision_at_3 value: 16.7 - type: precision_at_5 value: 13.18 - type: recall_at_1 value: 4.303 - type: recall_at_10 value: 19.688 - type: recall_at_100 value: 40.453 - type: recall_at_1000 value: 65.348 - type: recall_at_3 value: 10.148 - type: recall_at_5 value: 13.347999999999999 - task: type: STS dataset: type: mteb/sickr-sts name: MTEB SICK-R config: default split: test revision: a6ea5a8cab320b040a23452cc28066d9beae2cee metrics: - type: cos_sim_pearson value: 82.1158093156676 - type: cos_sim_spearman value: 78.04442753931265 - type: euclidean_pearson value: 79.96880352884281 - type: euclidean_spearman value: 78.04442519916647 - type: manhattan_pearson value: 79.95975401430859 - type: manhattan_spearman value: 78.03343142853139 - task: type: STS dataset: type: mteb/sts12-sts name: MTEB STS12 config: default split: test revision: a0d554a64d88156834ff5ae9920b964011b16384 metrics: - type: cos_sim_pearson value: 83.79721434783521 - type: cos_sim_spearman value: 78.25975096999896 - type: euclidean_pearson value: 79.1424902310369 - type: euclidean_spearman value: 78.25975658297341 - type: manhattan_pearson value: 79.18358724961024 - type: manhattan_spearman value: 78.25842688776181 - task: type: STS dataset: type: mteb/sts13-sts name: MTEB STS13 config: default split: test revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca metrics: - type: cos_sim_pearson value: 83.01380419796578 - type: cos_sim_spearman value: 84.25947132331721 - type: euclidean_pearson value: 83.60092535471402 - type: euclidean_spearman value: 84.25947132331721 - type: manhattan_pearson value: 83.58567994241997 - type: manhattan_spearman value: 84.26967070369717 - task: type: STS dataset: type: mteb/sts14-sts name: MTEB STS14 config: default split: test revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 metrics: - type: cos_sim_pearson value: 81.21721151989871 - type: cos_sim_spearman value: 80.54270694465328 - type: euclidean_pearson value: 80.59816986031214 - type: euclidean_spearman value: 80.54271664913747 - type: manhattan_pearson value: 80.5726582983618 - type: manhattan_spearman value: 80.5337273819897 - task: type: STS dataset: type: mteb/sts15-sts name: MTEB STS15 config: default split: test revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 metrics: - type: cos_sim_pearson value: 85.37279580582026 - type: cos_sim_spearman value: 86.49650639126628 - type: euclidean_pearson value: 86.16280095909306 - type: euclidean_spearman value: 86.49650639126628 - type: manhattan_pearson value: 86.10906620664134 - type: manhattan_spearman value: 86.43874476942065 - task: type: STS dataset: type: mteb/sts16-sts name: MTEB STS16 config: default split: test revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 metrics: - type: cos_sim_pearson value: 83.25909618059293 - type: cos_sim_spearman value: 85.13586725576114 - type: euclidean_pearson value: 84.23420740305912 - type: euclidean_spearman value: 85.13586725576114 - type: manhattan_pearson value: 84.31272025462884 - type: manhattan_spearman value: 85.21734270533285 - 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: 86.36016115914764 - type: cos_sim_spearman value: 86.50087120712864 - type: euclidean_pearson value: 87.43563849261436 - type: euclidean_spearman value: 86.50087120712864 - type: manhattan_pearson value: 87.3340358043399 - type: manhattan_spearman value: 86.48887803473512 - task: type: STS dataset: type: mteb/sts22-crosslingual-sts name: MTEB STS22 (en) config: en split: test revision: eea2b4fe26a775864c896887d910b76a8098ad3f metrics: - type: cos_sim_pearson value: 65.4382473357056 - type: cos_sim_spearman value: 65.02380140355883 - type: euclidean_pearson value: 66.29732592598693 - type: euclidean_spearman value: 65.02380140355883 - type: manhattan_pearson value: 66.60136092354136 - type: manhattan_spearman value: 65.21766397453412 - task: type: STS dataset: type: mteb/stsbenchmark-sts name: MTEB STSBenchmark config: default split: test revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 metrics: - type: cos_sim_pearson value: 84.10229648323359 - type: cos_sim_spearman value: 84.81137203891447 - type: euclidean_pearson value: 84.30614386139715 - type: euclidean_spearman value: 84.81137203891447 - type: manhattan_pearson value: 84.34828274644255 - type: manhattan_spearman value: 84.8268824733233 - task: type: Reranking dataset: type: mteb/scidocs-reranking name: MTEB SciDocsRR config: default split: test revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab metrics: - type: map value: 81.0838765555117 - type: mrr value: 94.65012928248223 - task: type: Retrieval dataset: type: scifact name: MTEB SciFact config: default split: test revision: None metrics: - type: map_at_1 value: 57.760999999999996 - type: map_at_10 value: 67.12 - type: map_at_100 value: 67.69 - type: map_at_1000 value: 67.716 - type: map_at_3 value: 64.846 - type: map_at_5 value: 66.148 - type: mrr_at_1 value: 60.667 - type: mrr_at_10 value: 68.497 - type: mrr_at_100 value: 68.92200000000001 - type: mrr_at_1000 value: 68.944 - type: mrr_at_3 value: 66.889 - type: mrr_at_5 value: 67.839 - type: ndcg_at_1 value: 60.667 - type: ndcg_at_10 value: 71.429 - type: ndcg_at_100 value: 73.821 - type: ndcg_at_1000 value: 74.524 - type: ndcg_at_3 value: 67.57600000000001 - type: ndcg_at_5 value: 69.44500000000001 - type: precision_at_1 value: 60.667 - type: precision_at_10 value: 9.333 - type: precision_at_100 value: 1.0630000000000002 - type: precision_at_1000 value: 0.11199999999999999 - type: precision_at_3 value: 26.333000000000002 - type: precision_at_5 value: 17.133000000000003 - type: recall_at_1 value: 57.760999999999996 - type: recall_at_10 value: 83.122 - type: recall_at_100 value: 93.767 - type: recall_at_1000 value: 99.333 - type: recall_at_3 value: 72.64399999999999 - type: recall_at_5 value: 77.378 - task: type: PairClassification dataset: type: mteb/sprintduplicatequestions-pairclassification name: MTEB SprintDuplicateQuestions config: default split: test revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 metrics: - type: cos_sim_accuracy value: 99.8108910891089 - type: cos_sim_ap value: 95.09566660724403 - type: cos_sim_f1 value: 90.20408163265306 - type: cos_sim_precision value: 92.08333333333333 - type: cos_sim_recall value: 88.4 - type: dot_accuracy value: 99.8108910891089 - type: dot_ap value: 95.09566660724403 - type: dot_f1 value: 90.20408163265306 - type: dot_precision value: 92.08333333333333 - type: dot_recall value: 88.4 - type: euclidean_accuracy value: 99.8108910891089 - type: euclidean_ap value: 95.09566660724404 - type: euclidean_f1 value: 90.20408163265306 - type: euclidean_precision value: 92.08333333333333 - type: euclidean_recall value: 88.4 - type: manhattan_accuracy value: 99.8108910891089 - type: manhattan_ap value: 95.05229326105041 - type: manhattan_f1 value: 90.30948756976154 - type: manhattan_precision value: 91.65808444902163 - type: manhattan_recall value: 89.0 - type: max_accuracy value: 99.8108910891089 - type: max_ap value: 95.09566660724404 - type: max_f1 value: 90.30948756976154 - task: type: Clustering dataset: type: mteb/stackexchange-clustering name: MTEB StackExchangeClustering config: default split: test revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 metrics: - type: v_measure value: 63.716387449356304 - task: type: Clustering dataset: type: mteb/stackexchange-clustering-p2p name: MTEB StackExchangeClusteringP2P config: default split: test revision: 815ca46b2622cec33ccafc3735d572c266efdb44 metrics: - type: v_measure value: 33.57171985530598 - task: type: Reranking dataset: type: mteb/stackoverflowdupquestions-reranking name: MTEB StackOverflowDupQuestions config: default split: test revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 metrics: - type: map value: 50.31022782714341 - type: mrr value: 51.005100903997956 - task: type: Summarization dataset: type: mteb/summeval name: MTEB SummEval config: default split: test revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c metrics: - type: cos_sim_pearson value: 30.55380844566254 - type: cos_sim_spearman value: 30.694665194755576 - type: dot_pearson value: 30.553807051946595 - type: dot_spearman value: 30.694665194755576 - task: type: Retrieval dataset: type: trec-covid name: MTEB TRECCOVID config: default split: test revision: None metrics: - type: map_at_1 value: 0.231 - type: map_at_10 value: 2.097 - type: map_at_100 value: 11.899999999999999 - type: map_at_1000 value: 27.965 - type: map_at_3 value: 0.7040000000000001 - type: map_at_5 value: 1.13 - type: mrr_at_1 value: 88.0 - type: mrr_at_10 value: 94.0 - type: mrr_at_100 value: 94.0 - type: mrr_at_1000 value: 94.0 - type: mrr_at_3 value: 94.0 - type: mrr_at_5 value: 94.0 - type: ndcg_at_1 value: 82.0 - type: ndcg_at_10 value: 79.72 - type: ndcg_at_100 value: 60.731 - type: ndcg_at_1000 value: 52.528 - type: ndcg_at_3 value: 84.776 - type: ndcg_at_5 value: 83.977 - type: precision_at_1 value: 88.0 - type: precision_at_10 value: 84.8 - type: precision_at_100 value: 62.46000000000001 - type: precision_at_1000 value: 23.336000000000002 - type: precision_at_3 value: 91.333 - type: precision_at_5 value: 89.60000000000001 - type: recall_at_1 value: 0.231 - type: recall_at_10 value: 2.242 - type: recall_at_100 value: 14.629 - type: recall_at_1000 value: 48.937999999999995 - type: recall_at_3 value: 0.733 - type: recall_at_5 value: 1.187 - task: type: Retrieval dataset: type: webis-touche2020 name: MTEB Touche2020 config: default split: test revision: None metrics: - type: map_at_1 value: 2.326 - type: map_at_10 value: 11.613 - type: map_at_100 value: 17.999000000000002 - type: map_at_1000 value: 19.579 - type: map_at_3 value: 5.5280000000000005 - type: map_at_5 value: 8.235000000000001 - type: mrr_at_1 value: 28.571 - type: mrr_at_10 value: 47.865 - type: mrr_at_100 value: 48.638999999999996 - type: mrr_at_1000 value: 48.638999999999996 - type: mrr_at_3 value: 42.516999999999996 - type: mrr_at_5 value: 46.293 - type: ndcg_at_1 value: 25.509999999999998 - type: ndcg_at_10 value: 28.663 - type: ndcg_at_100 value: 39.208 - type: ndcg_at_1000 value: 50.32 - type: ndcg_at_3 value: 28.636 - type: ndcg_at_5 value: 28.819 - type: precision_at_1 value: 28.571 - type: precision_at_10 value: 27.143 - type: precision_at_100 value: 8.082 - type: precision_at_1000 value: 1.543 - type: precision_at_3 value: 31.293 - type: precision_at_5 value: 31.019999999999996 - type: recall_at_1 value: 2.326 - type: recall_at_10 value: 19.12 - type: recall_at_100 value: 49.721 - type: recall_at_1000 value: 83.123 - type: recall_at_3 value: 6.783 - type: recall_at_5 value: 11.472999999999999 - task: type: Classification dataset: type: mteb/toxic_conversations_50k name: MTEB ToxicConversationsClassification config: default split: test revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c metrics: - type: accuracy value: 70.39139999999999 - type: ap value: 14.323066144268354 - type: f1 value: 54.37688697193885 - task: type: Classification dataset: type: mteb/tweet_sentiment_extraction name: MTEB TweetSentimentExtractionClassification config: default split: test revision: d604517c81ca91fe16a244d1248fc021f9ecee7a metrics: - type: accuracy value: 59.81890209394454 - type: f1 value: 60.116654203584496 - task: type: Clustering dataset: type: mteb/twentynewsgroups-clustering name: MTEB TwentyNewsgroupsClustering config: default split: test revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 metrics: - type: v_measure value: 49.5398447532487 - task: type: PairClassification dataset: type: mteb/twittersemeval2015-pairclassification name: MTEB TwitterSemEval2015 config: default split: test revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 metrics: - type: cos_sim_accuracy value: 85.62317458425225 - type: cos_sim_ap value: 72.58795996654061 - type: cos_sim_f1 value: 66.74816625916871 - type: cos_sim_precision value: 62.1867881548975 - type: cos_sim_recall value: 72.0316622691293 - type: dot_accuracy value: 85.62317458425225 - type: dot_ap value: 72.58796057492127 - type: dot_f1 value: 66.74816625916871 - type: dot_precision value: 62.1867881548975 - type: dot_recall value: 72.0316622691293 - type: euclidean_accuracy value: 85.62317458425225 - type: euclidean_ap value: 72.58798058258095 - type: euclidean_f1 value: 66.74816625916871 - type: euclidean_precision value: 62.1867881548975 - type: euclidean_recall value: 72.0316622691293 - type: manhattan_accuracy value: 85.5754902545151 - type: manhattan_ap value: 72.5765018516196 - type: manhattan_f1 value: 66.70611906734524 - type: manhattan_precision value: 60.485082635758744 - type: manhattan_recall value: 74.35356200527704 - type: max_accuracy value: 85.62317458425225 - type: max_ap value: 72.58798058258095 - type: max_f1 value: 66.74816625916871 - task: type: PairClassification dataset: type: mteb/twitterurlcorpus-pairclassification name: MTEB TwitterURLCorpus config: default split: test revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf metrics: - type: cos_sim_accuracy value: 89.03830480847596 - type: cos_sim_ap value: 86.09219791618496 - type: cos_sim_f1 value: 78.19673991150107 - type: cos_sim_precision value: 76.84531331301568 - type: cos_sim_recall value: 79.59655066214968 - type: dot_accuracy value: 89.03830480847596 - type: dot_ap value: 86.09219596898019 - type: dot_f1 value: 78.19673991150107 - type: dot_precision value: 76.84531331301568 - type: dot_recall value: 79.59655066214968 - type: euclidean_accuracy value: 89.03830480847596 - type: euclidean_ap value: 86.09219836933755 - type: euclidean_f1 value: 78.19673991150107 - type: euclidean_precision value: 76.84531331301568 - type: euclidean_recall value: 79.59655066214968 - type: manhattan_accuracy value: 89.04024527496411 - type: manhattan_ap value: 86.07752622427454 - type: manhattan_f1 value: 78.17774911808216 - type: manhattan_precision value: 77.04672897196262 - type: manhattan_recall value: 79.3424699722821 - type: max_accuracy value: 89.04024527496411 - type: max_ap value: 86.09219836933755 - type: max_f1 value: 78.19673991150107 ---