--- language: - en library_name: sentence-transformers license: mit pipeline_tag: sentence-similarity tags: - feature-extraction - mteb - sentence-similarity - sentence-transformers model-index: - name: GIST-all-MiniLM-L6-v2 results: - task: type: Classification dataset: type: mteb/amazon_counterfactual name: MTEB AmazonCounterfactualClassification (en) config: en split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics: - type: accuracy value: 69.68656716417911 - type: ap value: 31.84640905923114 - type: f1 value: 63.4379647836158 - task: type: Classification dataset: type: mteb/amazon_polarity name: MTEB AmazonPolarityClassification config: default split: test revision: e2d317d38cd51312af73b3d32a06d1a08b442046 metrics: - type: accuracy value: 82.078025 - type: ap value: 77.3451894150185 - type: f1 value: 81.97258648080654 - task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (en) config: en split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics: - type: accuracy value: 38.254 - type: f1 value: 37.940387801030376 - task: type: Retrieval dataset: type: arguana name: MTEB ArguAna config: default split: test revision: None metrics: - type: map_at_1 value: 28.876 - type: map_at_10 value: 44.741 - type: map_at_100 value: 45.688 - type: map_at_1000 value: 45.695 - type: map_at_3 value: 39.829 - type: map_at_5 value: 42.646 - type: mrr_at_1 value: 30.156 - type: mrr_at_10 value: 45.196 - type: mrr_at_100 value: 46.149 - type: mrr_at_1000 value: 46.156000000000006 - type: mrr_at_3 value: 40.339000000000006 - type: mrr_at_5 value: 43.120000000000005 - type: ndcg_at_1 value: 28.876 - type: ndcg_at_10 value: 53.581 - type: ndcg_at_100 value: 57.428000000000004 - type: ndcg_at_1000 value: 57.599000000000004 - type: ndcg_at_3 value: 43.46 - type: ndcg_at_5 value: 48.501 - type: precision_at_1 value: 28.876 - type: precision_at_10 value: 8.186 - type: precision_at_100 value: 0.9820000000000001 - type: precision_at_1000 value: 0.1 - type: precision_at_3 value: 17.994 - type: precision_at_5 value: 13.229 - type: recall_at_1 value: 28.876 - type: recall_at_10 value: 81.863 - type: recall_at_100 value: 98.222 - type: recall_at_1000 value: 99.502 - type: recall_at_3 value: 53.983000000000004 - type: recall_at_5 value: 66.145 - task: type: Clustering dataset: type: mteb/arxiv-clustering-p2p name: MTEB ArxivClusteringP2P config: default split: test revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d metrics: - type: v_measure value: 44.81109445338116 - task: type: Clustering dataset: type: mteb/arxiv-clustering-s2s name: MTEB ArxivClusteringS2S config: default split: test revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 metrics: - type: v_measure value: 35.705350248894476 - task: type: Reranking dataset: type: mteb/askubuntudupquestions-reranking name: MTEB AskUbuntuDupQuestions config: default split: test revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 metrics: - type: map value: 63.13335364248881 - type: mrr value: 76.80605021325243 - task: type: STS dataset: type: mteb/biosses-sts name: MTEB BIOSSES config: default split: test revision: d3fb88f8f02e40887cd149695127462bbcf29b4a metrics: - type: cos_sim_pearson value: 83.33741812376516 - type: cos_sim_spearman value: 80.51267790947811 - type: euclidean_pearson value: 67.49002803470997 - type: euclidean_spearman value: 65.39064659674824 - type: manhattan_pearson value: 67.3390206944745 - type: manhattan_spearman value: 65.35329634810715 - task: type: Classification dataset: type: mteb/banking77 name: MTEB Banking77Classification config: default split: test revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 metrics: - type: accuracy value: 83.13636363636364 - type: f1 value: 83.10810612376775 - task: type: Clustering dataset: type: mteb/biorxiv-clustering-p2p name: MTEB BiorxivClusteringP2P config: default split: test revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 metrics: - type: v_measure value: 38.47849860204599 - task: type: Clustering dataset: type: mteb/biorxiv-clustering-s2s name: MTEB BiorxivClusteringS2S config: default split: test revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 metrics: - type: v_measure value: 31.159196233892057 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackAndroidRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 34.096 - type: map_at_10 value: 46.61 - type: map_at_100 value: 48.163 - type: map_at_1000 value: 48.272 - type: map_at_3 value: 43.03 - type: map_at_5 value: 45.036 - type: mrr_at_1 value: 42.489 - type: mrr_at_10 value: 52.83 - type: mrr_at_100 value: 53.525 - type: mrr_at_1000 value: 53.561 - type: mrr_at_3 value: 50.453 - type: mrr_at_5 value: 51.991 - type: ndcg_at_1 value: 42.489 - type: ndcg_at_10 value: 53.21900000000001 - type: ndcg_at_100 value: 58.277 - type: ndcg_at_1000 value: 59.836999999999996 - type: ndcg_at_3 value: 48.64 - type: ndcg_at_5 value: 50.800999999999995 - type: precision_at_1 value: 42.489 - type: precision_at_10 value: 10.343 - type: precision_at_100 value: 1.624 - type: precision_at_1000 value: 0.20400000000000001 - type: precision_at_3 value: 23.605 - type: precision_at_5 value: 16.881 - type: recall_at_1 value: 34.096 - type: recall_at_10 value: 65.003 - type: recall_at_100 value: 86.211 - type: recall_at_1000 value: 96.017 - type: recall_at_3 value: 51.307 - type: recall_at_5 value: 57.873 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackEnglishRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 29.482000000000003 - type: map_at_10 value: 39.793 - type: map_at_100 value: 41.028 - type: map_at_1000 value: 41.163 - type: map_at_3 value: 36.674 - type: map_at_5 value: 38.379999999999995 - type: mrr_at_1 value: 37.197 - type: mrr_at_10 value: 45.991 - type: mrr_at_100 value: 46.599000000000004 - type: mrr_at_1000 value: 46.649 - type: mrr_at_3 value: 43.662 - type: mrr_at_5 value: 45.054 - type: ndcg_at_1 value: 37.197 - type: ndcg_at_10 value: 45.73 - type: ndcg_at_100 value: 50.074 - type: ndcg_at_1000 value: 52.312000000000005 - type: ndcg_at_3 value: 41.308 - type: ndcg_at_5 value: 43.323 - type: precision_at_1 value: 37.197 - type: precision_at_10 value: 8.854 - type: precision_at_100 value: 1.411 - type: precision_at_1000 value: 0.191 - type: precision_at_3 value: 20.085 - type: precision_at_5 value: 14.42 - type: recall_at_1 value: 29.482000000000003 - type: recall_at_10 value: 56.077999999999996 - type: recall_at_100 value: 74.83800000000001 - type: recall_at_1000 value: 89.128 - type: recall_at_3 value: 42.971 - type: recall_at_5 value: 48.577 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGamingRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 38.679 - type: map_at_10 value: 50.854 - type: map_at_100 value: 51.849000000000004 - type: map_at_1000 value: 51.909000000000006 - type: map_at_3 value: 47.82 - type: map_at_5 value: 49.479 - type: mrr_at_1 value: 44.263000000000005 - type: mrr_at_10 value: 54.161 - type: mrr_at_100 value: 54.833 - type: mrr_at_1000 value: 54.86600000000001 - type: mrr_at_3 value: 51.912000000000006 - type: mrr_at_5 value: 53.201 - type: ndcg_at_1 value: 44.263000000000005 - type: ndcg_at_10 value: 56.486000000000004 - type: ndcg_at_100 value: 60.553999999999995 - type: ndcg_at_1000 value: 61.77 - type: ndcg_at_3 value: 51.456999999999994 - type: ndcg_at_5 value: 53.83 - type: precision_at_1 value: 44.263000000000005 - type: precision_at_10 value: 9.041 - type: precision_at_100 value: 1.204 - type: precision_at_1000 value: 0.135 - type: precision_at_3 value: 22.989 - type: precision_at_5 value: 15.598999999999998 - type: recall_at_1 value: 38.679 - type: recall_at_10 value: 69.77799999999999 - type: recall_at_100 value: 87.59 - type: recall_at_1000 value: 96.202 - type: recall_at_3 value: 56.351 - type: recall_at_5 value: 62.16199999999999 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGisRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 27.245 - type: map_at_10 value: 36.104 - type: map_at_100 value: 37.207 - type: map_at_1000 value: 37.288 - type: map_at_3 value: 33.427 - type: map_at_5 value: 34.866 - type: mrr_at_1 value: 29.604999999999997 - type: mrr_at_10 value: 38.346999999999994 - type: mrr_at_100 value: 39.274 - type: mrr_at_1000 value: 39.336 - type: mrr_at_3 value: 35.876000000000005 - type: mrr_at_5 value: 37.164 - type: ndcg_at_1 value: 29.604999999999997 - type: ndcg_at_10 value: 41.253 - type: ndcg_at_100 value: 46.511 - type: ndcg_at_1000 value: 48.503 - type: ndcg_at_3 value: 35.975 - type: ndcg_at_5 value: 38.35 - type: precision_at_1 value: 29.604999999999997 - type: precision_at_10 value: 6.305 - type: precision_at_100 value: 0.9440000000000001 - type: precision_at_1000 value: 0.11499999999999999 - type: precision_at_3 value: 15.179 - type: precision_at_5 value: 10.508000000000001 - type: recall_at_1 value: 27.245 - type: recall_at_10 value: 55.07300000000001 - type: recall_at_100 value: 79.036 - type: recall_at_1000 value: 93.809 - type: recall_at_3 value: 40.593 - type: recall_at_5 value: 46.318 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackMathematicaRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 15.440000000000001 - type: map_at_10 value: 23.758000000000003 - type: map_at_100 value: 25.1 - type: map_at_1000 value: 25.230000000000004 - type: map_at_3 value: 21.093 - type: map_at_5 value: 22.431 - type: mrr_at_1 value: 19.279 - type: mrr_at_10 value: 28.077 - type: mrr_at_100 value: 29.164 - type: mrr_at_1000 value: 29.237000000000002 - type: mrr_at_3 value: 25.497999999999998 - type: mrr_at_5 value: 26.76 - type: ndcg_at_1 value: 19.279 - type: ndcg_at_10 value: 29.025000000000002 - type: ndcg_at_100 value: 35.244 - type: ndcg_at_1000 value: 38.112 - type: ndcg_at_3 value: 24.079 - type: ndcg_at_5 value: 26.064999999999998 - type: precision_at_1 value: 19.279 - type: precision_at_10 value: 5.498 - type: precision_at_100 value: 0.985 - type: precision_at_1000 value: 0.136 - type: precision_at_3 value: 11.692 - type: precision_at_5 value: 8.383000000000001 - type: recall_at_1 value: 15.440000000000001 - type: recall_at_10 value: 40.855999999999995 - type: recall_at_100 value: 67.916 - type: recall_at_1000 value: 88.11 - type: recall_at_3 value: 27.387 - type: recall_at_5 value: 32.387 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackPhysicsRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 29.351 - type: map_at_10 value: 40.477999999999994 - type: map_at_100 value: 41.8 - type: map_at_1000 value: 41.926 - type: map_at_3 value: 37.246 - type: map_at_5 value: 39.206 - type: mrr_at_1 value: 36.092 - type: mrr_at_10 value: 46.319 - type: mrr_at_100 value: 47.087 - type: mrr_at_1000 value: 47.13 - type: mrr_at_3 value: 43.808 - type: mrr_at_5 value: 45.406 - type: ndcg_at_1 value: 36.092 - type: ndcg_at_10 value: 46.707 - type: ndcg_at_100 value: 52.266 - type: ndcg_at_1000 value: 54.303000000000004 - type: ndcg_at_3 value: 41.858000000000004 - type: ndcg_at_5 value: 44.407999999999994 - type: precision_at_1 value: 36.092 - type: precision_at_10 value: 8.527 - type: precision_at_100 value: 1.34 - type: precision_at_1000 value: 0.172 - type: precision_at_3 value: 20.212 - type: precision_at_5 value: 14.456 - type: recall_at_1 value: 29.351 - type: recall_at_10 value: 59.254 - type: recall_at_100 value: 83.047 - type: recall_at_1000 value: 95.911 - type: recall_at_3 value: 45.488 - type: recall_at_5 value: 52.186 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackProgrammersRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 25.601000000000003 - type: map_at_10 value: 34.589999999999996 - type: map_at_100 value: 35.917 - type: map_at_1000 value: 36.032 - type: map_at_3 value: 31.338 - type: map_at_5 value: 33.128 - type: mrr_at_1 value: 31.163999999999998 - type: mrr_at_10 value: 39.646 - type: mrr_at_100 value: 40.491 - type: mrr_at_1000 value: 40.549 - type: mrr_at_3 value: 36.91 - type: mrr_at_5 value: 38.446000000000005 - type: ndcg_at_1 value: 31.163999999999998 - type: ndcg_at_10 value: 40.321 - type: ndcg_at_100 value: 45.894 - type: ndcg_at_1000 value: 48.233 - type: ndcg_at_3 value: 34.871 - type: ndcg_at_5 value: 37.302 - type: precision_at_1 value: 31.163999999999998 - type: precision_at_10 value: 7.523000000000001 - type: precision_at_100 value: 1.188 - type: precision_at_1000 value: 0.157 - type: precision_at_3 value: 16.591 - type: precision_at_5 value: 12.055 - type: recall_at_1 value: 25.601000000000003 - type: recall_at_10 value: 52.422000000000004 - type: recall_at_100 value: 76.426 - type: recall_at_1000 value: 92.142 - type: recall_at_3 value: 37.141000000000005 - type: recall_at_5 value: 43.449 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 26.267916666666668 - type: map_at_10 value: 35.758250000000004 - type: map_at_100 value: 37.0185 - type: map_at_1000 value: 37.136916666666664 - type: map_at_3 value: 32.85125 - type: map_at_5 value: 34.4165 - type: mrr_at_1 value: 31.131083333333343 - type: mrr_at_10 value: 39.95941666666667 - type: mrr_at_100 value: 40.81541666666666 - type: mrr_at_1000 value: 40.87358333333332 - type: mrr_at_3 value: 37.5175 - type: mrr_at_5 value: 38.86833333333334 - type: ndcg_at_1 value: 31.131083333333343 - type: ndcg_at_10 value: 41.26174999999999 - type: ndcg_at_100 value: 46.55975 - type: ndcg_at_1000 value: 48.80016666666666 - type: ndcg_at_3 value: 36.37566666666667 - type: ndcg_at_5 value: 38.55166666666667 - type: precision_at_1 value: 31.131083333333343 - type: precision_at_10 value: 7.315916666666666 - type: precision_at_100 value: 1.1813333333333333 - type: precision_at_1000 value: 0.15666666666666665 - type: precision_at_3 value: 16.818166666666663 - type: precision_at_5 value: 11.923 - type: recall_at_1 value: 26.267916666666668 - type: recall_at_10 value: 53.28391666666666 - type: recall_at_100 value: 76.53983333333332 - type: recall_at_1000 value: 91.93008333333334 - type: recall_at_3 value: 39.60583333333334 - type: recall_at_5 value: 45.25741666666667 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackStatsRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 23.372 - type: map_at_10 value: 30.916 - type: map_at_100 value: 31.980999999999998 - type: map_at_1000 value: 32.07 - type: map_at_3 value: 28.778 - type: map_at_5 value: 29.872 - type: mrr_at_1 value: 26.074 - type: mrr_at_10 value: 33.451 - type: mrr_at_100 value: 34.366 - type: mrr_at_1000 value: 34.424 - type: mrr_at_3 value: 31.569999999999997 - type: mrr_at_5 value: 32.467 - type: ndcg_at_1 value: 26.074 - type: ndcg_at_10 value: 35.119 - type: ndcg_at_100 value: 40.357 - type: ndcg_at_1000 value: 42.548 - type: ndcg_at_3 value: 31.281 - type: ndcg_at_5 value: 32.866 - type: precision_at_1 value: 26.074 - type: precision_at_10 value: 5.583 - type: precision_at_100 value: 0.899 - type: precision_at_1000 value: 0.116 - type: precision_at_3 value: 13.700999999999999 - type: precision_at_5 value: 9.447999999999999 - type: recall_at_1 value: 23.372 - type: recall_at_10 value: 45.396 - type: recall_at_100 value: 69.26 - type: recall_at_1000 value: 85.438 - type: recall_at_3 value: 34.373 - type: recall_at_5 value: 38.509 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackTexRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 17.483999999999998 - type: map_at_10 value: 25.191999999999997 - type: map_at_100 value: 26.432 - type: map_at_1000 value: 26.566000000000003 - type: map_at_3 value: 22.697 - type: map_at_5 value: 24.101 - type: mrr_at_1 value: 21.645 - type: mrr_at_10 value: 29.243000000000002 - type: mrr_at_100 value: 30.232 - type: mrr_at_1000 value: 30.312 - type: mrr_at_3 value: 26.967000000000002 - type: mrr_at_5 value: 28.262999999999998 - type: ndcg_at_1 value: 21.645 - type: ndcg_at_10 value: 30.087999999999997 - type: ndcg_at_100 value: 35.806 - type: ndcg_at_1000 value: 38.763 - type: ndcg_at_3 value: 25.746999999999996 - type: ndcg_at_5 value: 27.765 - type: precision_at_1 value: 21.645 - type: precision_at_10 value: 5.6129999999999995 - type: precision_at_100 value: 1.004 - type: precision_at_1000 value: 0.14400000000000002 - type: precision_at_3 value: 12.331 - type: precision_at_5 value: 9.009 - type: recall_at_1 value: 17.483999999999998 - type: recall_at_10 value: 40.723 - type: recall_at_100 value: 66.226 - type: recall_at_1000 value: 87.312 - type: recall_at_3 value: 28.481 - type: recall_at_5 value: 33.777 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackUnixRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 26.735 - type: map_at_10 value: 36.431000000000004 - type: map_at_100 value: 37.696000000000005 - type: map_at_1000 value: 37.793 - type: map_at_3 value: 33.416000000000004 - type: map_at_5 value: 34.934 - type: mrr_at_1 value: 31.25 - type: mrr_at_10 value: 40.516000000000005 - type: mrr_at_100 value: 41.392 - type: mrr_at_1000 value: 41.449000000000005 - type: mrr_at_3 value: 37.842 - type: mrr_at_5 value: 39.265 - type: ndcg_at_1 value: 31.25 - type: ndcg_at_10 value: 42.191 - type: ndcg_at_100 value: 47.683 - type: ndcg_at_1000 value: 49.815 - type: ndcg_at_3 value: 36.744 - type: ndcg_at_5 value: 39.007 - type: precision_at_1 value: 31.25 - type: precision_at_10 value: 7.276000000000001 - type: precision_at_100 value: 1.125 - type: precision_at_1000 value: 0.14100000000000001 - type: precision_at_3 value: 16.76 - type: precision_at_5 value: 11.791 - type: recall_at_1 value: 26.735 - type: recall_at_10 value: 55.444 - type: recall_at_100 value: 79.098 - type: recall_at_1000 value: 93.815 - type: recall_at_3 value: 40.623 - type: recall_at_5 value: 46.322 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWebmastersRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 26.495 - type: map_at_10 value: 35.648 - type: map_at_100 value: 37.275000000000006 - type: map_at_1000 value: 37.494 - type: map_at_3 value: 32.446999999999996 - type: map_at_5 value: 34.233000000000004 - type: mrr_at_1 value: 31.225 - type: mrr_at_10 value: 40.127 - type: mrr_at_100 value: 41.092 - type: mrr_at_1000 value: 41.148 - type: mrr_at_3 value: 37.153999999999996 - type: mrr_at_5 value: 38.873999999999995 - type: ndcg_at_1 value: 31.225 - type: ndcg_at_10 value: 41.665 - type: ndcg_at_100 value: 47.557 - type: ndcg_at_1000 value: 49.992 - type: ndcg_at_3 value: 36.114000000000004 - type: ndcg_at_5 value: 38.675 - type: precision_at_1 value: 31.225 - type: precision_at_10 value: 7.904999999999999 - type: precision_at_100 value: 1.5890000000000002 - type: precision_at_1000 value: 0.246 - type: precision_at_3 value: 16.535 - type: precision_at_5 value: 12.134 - type: recall_at_1 value: 26.495 - type: recall_at_10 value: 53.727000000000004 - type: recall_at_100 value: 79.34400000000001 - type: recall_at_1000 value: 94.35900000000001 - type: recall_at_3 value: 38.432 - type: recall_at_5 value: 45.050000000000004 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWordpressRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 21.235 - type: map_at_10 value: 28.725 - type: map_at_100 value: 29.774 - type: map_at_1000 value: 29.9 - type: map_at_3 value: 26.249 - type: map_at_5 value: 27.332 - type: mrr_at_1 value: 23.29 - type: mrr_at_10 value: 30.805 - type: mrr_at_100 value: 31.730000000000004 - type: mrr_at_1000 value: 31.822 - type: mrr_at_3 value: 28.558 - type: mrr_at_5 value: 29.529 - type: ndcg_at_1 value: 23.29 - type: ndcg_at_10 value: 33.337 - type: ndcg_at_100 value: 38.494 - type: ndcg_at_1000 value: 41.414 - type: ndcg_at_3 value: 28.433999999999997 - type: ndcg_at_5 value: 30.227999999999998 - type: precision_at_1 value: 23.29 - type: precision_at_10 value: 5.323 - type: precision_at_100 value: 0.8630000000000001 - type: precision_at_1000 value: 0.123 - type: precision_at_3 value: 12.138 - type: precision_at_5 value: 8.392 - type: recall_at_1 value: 21.235 - type: recall_at_10 value: 45.653 - type: recall_at_100 value: 69.486 - type: recall_at_1000 value: 90.91799999999999 - type: recall_at_3 value: 32.123000000000005 - type: recall_at_5 value: 36.479 - task: type: Retrieval dataset: type: climate-fever name: MTEB ClimateFEVER config: default split: test revision: None metrics: - type: map_at_1 value: 9.180000000000001 - type: map_at_10 value: 16.461000000000002 - type: map_at_100 value: 18.093999999999998 - type: map_at_1000 value: 18.297 - type: map_at_3 value: 13.475000000000001 - type: map_at_5 value: 15.02 - type: mrr_at_1 value: 21.303 - type: mrr_at_10 value: 31.755 - type: mrr_at_100 value: 32.826 - type: mrr_at_1000 value: 32.873000000000005 - type: mrr_at_3 value: 28.469 - type: mrr_at_5 value: 30.325999999999997 - type: ndcg_at_1 value: 21.303 - type: ndcg_at_10 value: 23.892 - type: ndcg_at_100 value: 30.848 - type: ndcg_at_1000 value: 34.577999999999996 - type: ndcg_at_3 value: 18.88 - type: ndcg_at_5 value: 20.683 - type: precision_at_1 value: 21.303 - type: precision_at_10 value: 7.693999999999999 - type: precision_at_100 value: 1.517 - type: precision_at_1000 value: 0.22 - type: precision_at_3 value: 14.180000000000001 - type: precision_at_5 value: 11.231 - type: recall_at_1 value: 9.180000000000001 - type: recall_at_10 value: 29.813000000000002 - type: recall_at_100 value: 54.116 - type: recall_at_1000 value: 75.248 - type: recall_at_3 value: 17.684 - type: recall_at_5 value: 22.557 - task: type: Retrieval dataset: type: dbpedia-entity name: MTEB DBPedia config: default split: test revision: None metrics: - type: map_at_1 value: 8.508000000000001 - type: map_at_10 value: 16.39 - type: map_at_100 value: 21.981 - type: map_at_1000 value: 23.253 - type: map_at_3 value: 12.465 - type: map_at_5 value: 14.194999999999999 - type: mrr_at_1 value: 60.0 - type: mrr_at_10 value: 68.499 - type: mrr_at_100 value: 69.014 - type: mrr_at_1000 value: 69.024 - type: mrr_at_3 value: 66.625 - type: mrr_at_5 value: 67.887 - type: ndcg_at_1 value: 48.5 - type: ndcg_at_10 value: 34.870000000000005 - type: ndcg_at_100 value: 38.448 - type: ndcg_at_1000 value: 45.668 - type: ndcg_at_3 value: 39.931 - type: ndcg_at_5 value: 37.007 - type: precision_at_1 value: 60.0 - type: precision_at_10 value: 26.924999999999997 - type: precision_at_100 value: 8.358 - type: precision_at_1000 value: 1.7850000000000001 - type: precision_at_3 value: 43.0 - type: precision_at_5 value: 35.449999999999996 - type: recall_at_1 value: 8.508000000000001 - type: recall_at_10 value: 21.089 - type: recall_at_100 value: 43.146 - type: recall_at_1000 value: 66.776 - type: recall_at_3 value: 13.33 - type: recall_at_5 value: 16.225 - task: type: Classification dataset: type: mteb/emotion name: MTEB EmotionClassification config: default split: test revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 metrics: - type: accuracy value: 46.735 - type: f1 value: 42.30853263256299 - task: type: Retrieval dataset: type: fever name: MTEB FEVER config: default split: test revision: None metrics: - type: map_at_1 value: 54.54 - type: map_at_10 value: 65.24600000000001 - type: map_at_100 value: 65.69 - type: map_at_1000 value: 65.71000000000001 - type: map_at_3 value: 63.234 - type: map_at_5 value: 64.455 - type: mrr_at_1 value: 58.821 - type: mrr_at_10 value: 69.616 - type: mrr_at_100 value: 69.98 - type: mrr_at_1000 value: 69.992 - type: mrr_at_3 value: 67.782 - type: mrr_at_5 value: 68.917 - type: ndcg_at_1 value: 58.821 - type: ndcg_at_10 value: 70.798 - type: ndcg_at_100 value: 72.719 - type: ndcg_at_1000 value: 73.19600000000001 - type: ndcg_at_3 value: 67.037 - type: ndcg_at_5 value: 69.048 - type: precision_at_1 value: 58.821 - type: precision_at_10 value: 9.182 - type: precision_at_100 value: 1.024 - type: precision_at_1000 value: 0.108 - type: precision_at_3 value: 26.662999999999997 - type: precision_at_5 value: 17.159 - type: recall_at_1 value: 54.54 - type: recall_at_10 value: 83.67999999999999 - type: recall_at_100 value: 92.099 - type: recall_at_1000 value: 95.532 - type: recall_at_3 value: 73.478 - type: recall_at_5 value: 78.424 - task: type: Retrieval dataset: type: fiqa name: MTEB FiQA2018 config: default split: test revision: None metrics: - type: map_at_1 value: 17.601 - type: map_at_10 value: 28.676000000000002 - type: map_at_100 value: 30.463 - type: map_at_1000 value: 30.666 - type: map_at_3 value: 24.734 - type: map_at_5 value: 27.026 - type: mrr_at_1 value: 34.259 - type: mrr_at_10 value: 43.613 - type: mrr_at_100 value: 44.535000000000004 - type: mrr_at_1000 value: 44.583 - type: mrr_at_3 value: 41.307 - type: mrr_at_5 value: 42.626 - type: ndcg_at_1 value: 34.259 - type: ndcg_at_10 value: 36.097 - type: ndcg_at_100 value: 43.039 - type: ndcg_at_1000 value: 46.498 - type: ndcg_at_3 value: 32.244 - type: ndcg_at_5 value: 33.711999999999996 - type: precision_at_1 value: 34.259 - type: precision_at_10 value: 10.030999999999999 - type: precision_at_100 value: 1.7239999999999998 - type: precision_at_1000 value: 0.234 - type: precision_at_3 value: 21.193 - type: precision_at_5 value: 15.956999999999999 - type: recall_at_1 value: 17.601 - type: recall_at_10 value: 42.807 - type: recall_at_100 value: 68.571 - type: recall_at_1000 value: 89.237 - type: recall_at_3 value: 29.301 - type: recall_at_5 value: 35.528999999999996 - task: type: Retrieval dataset: type: hotpotqa name: MTEB HotpotQA config: default split: test revision: None metrics: - type: map_at_1 value: 31.182 - type: map_at_10 value: 42.631 - type: map_at_100 value: 43.577 - type: map_at_1000 value: 43.661 - type: map_at_3 value: 40.06 - type: map_at_5 value: 41.591 - type: mrr_at_1 value: 62.363 - type: mrr_at_10 value: 69.047 - type: mrr_at_100 value: 69.46 - type: mrr_at_1000 value: 69.48100000000001 - type: mrr_at_3 value: 67.574 - type: mrr_at_5 value: 68.487 - type: ndcg_at_1 value: 62.363 - type: ndcg_at_10 value: 51.629999999999995 - type: ndcg_at_100 value: 55.301 - type: ndcg_at_1000 value: 57.071000000000005 - type: ndcg_at_3 value: 47.496 - type: ndcg_at_5 value: 49.687 - type: precision_at_1 value: 62.363 - type: precision_at_10 value: 10.628 - type: precision_at_100 value: 1.352 - type: precision_at_1000 value: 0.159 - type: precision_at_3 value: 29.296 - type: precision_at_5 value: 19.309 - type: recall_at_1 value: 31.182 - type: recall_at_10 value: 53.14 - type: recall_at_100 value: 67.596 - type: recall_at_1000 value: 79.372 - type: recall_at_3 value: 43.943 - type: recall_at_5 value: 48.271 - task: type: Classification dataset: type: mteb/imdb name: MTEB ImdbClassification config: default split: test revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 metrics: - type: accuracy value: 71.55319999999999 - type: ap value: 65.44170899953346 - type: f1 value: 71.33420141354401 - task: type: Retrieval dataset: type: msmarco name: MTEB MSMARCO config: default split: dev revision: None metrics: - type: map_at_1 value: 18.89 - type: map_at_10 value: 30.076999999999998 - type: map_at_100 value: 31.281 - type: map_at_1000 value: 31.341 - type: map_at_3 value: 26.391 - type: map_at_5 value: 28.557 - type: mrr_at_1 value: 19.312 - type: mrr_at_10 value: 30.566 - type: mrr_at_100 value: 31.728 - type: mrr_at_1000 value: 31.781 - type: mrr_at_3 value: 26.901000000000003 - type: mrr_at_5 value: 29.072 - type: ndcg_at_1 value: 19.326999999999998 - type: ndcg_at_10 value: 36.516999999999996 - type: ndcg_at_100 value: 42.458 - type: ndcg_at_1000 value: 43.99 - type: ndcg_at_3 value: 29.005 - type: ndcg_at_5 value: 32.889 - type: precision_at_1 value: 19.326999999999998 - type: precision_at_10 value: 5.868 - type: precision_at_100 value: 0.8880000000000001 - type: precision_at_1000 value: 0.10200000000000001 - type: precision_at_3 value: 12.388 - type: precision_at_5 value: 9.401 - type: recall_at_1 value: 18.89 - type: recall_at_10 value: 56.442 - type: recall_at_100 value: 84.16 - type: recall_at_1000 value: 95.97099999999999 - type: recall_at_3 value: 36.077999999999996 - type: recall_at_5 value: 45.395 - task: type: Classification dataset: type: mteb/mtop_domain name: MTEB MTOPDomainClassification (en) config: en split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics: - type: accuracy value: 93.69585043319653 - type: f1 value: 93.27706251110098 - task: type: Classification dataset: type: mteb/mtop_intent name: MTEB MTOPIntentClassification (en) config: en split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics: - type: accuracy value: 74.62836297309622 - type: f1 value: 56.21163652384411 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (en) config: en split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 71.37861466039006 - type: f1 value: 69.85338860172736 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (en) config: en split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 75.58170813718897 - type: f1 value: 75.77358464349743 - task: type: Clustering dataset: type: mteb/medrxiv-clustering-p2p name: MTEB MedrxivClusteringP2P config: default split: test revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 metrics: - type: v_measure value: 33.29659845527655 - task: type: Clustering dataset: type: mteb/medrxiv-clustering-s2s name: MTEB MedrxivClusteringS2S config: default split: test revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 metrics: - type: v_measure value: 29.97507851301835 - task: type: Reranking dataset: type: mteb/mind_small name: MTEB MindSmallReranking config: default split: test revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 metrics: - type: map value: 31.158968289313076 - type: mrr value: 32.27027446726339 - task: type: Retrieval dataset: type: nfcorpus name: MTEB NFCorpus config: default split: test revision: None metrics: - type: map_at_1 value: 5.021 - type: map_at_10 value: 11.346 - type: map_at_100 value: 14.457 - type: map_at_1000 value: 15.875 - type: map_at_3 value: 8.376999999999999 - type: map_at_5 value: 9.793000000000001 - type: mrr_at_1 value: 43.344 - type: mrr_at_10 value: 51.266 - type: mrr_at_100 value: 51.871 - type: mrr_at_1000 value: 51.915 - type: mrr_at_3 value: 49.174 - type: mrr_at_5 value: 50.475 - type: ndcg_at_1 value: 41.331 - type: ndcg_at_10 value: 31.257 - type: ndcg_at_100 value: 29.264000000000003 - type: ndcg_at_1000 value: 38.024 - type: ndcg_at_3 value: 36.643 - type: ndcg_at_5 value: 34.808 - type: precision_at_1 value: 43.034 - type: precision_at_10 value: 22.972 - type: precision_at_100 value: 7.576 - type: precision_at_1000 value: 2.0629999999999997 - type: precision_at_3 value: 34.572 - type: precision_at_5 value: 30.341 - type: recall_at_1 value: 5.021 - type: recall_at_10 value: 15.197 - type: recall_at_100 value: 30.874000000000002 - type: recall_at_1000 value: 61.934 - type: recall_at_3 value: 9.467 - type: recall_at_5 value: 11.904 - task: type: Retrieval dataset: type: nq name: MTEB NQ config: default split: test revision: None metrics: - type: map_at_1 value: 24.468999999999998 - type: map_at_10 value: 38.885999999999996 - type: map_at_100 value: 40.154 - type: map_at_1000 value: 40.195 - type: map_at_3 value: 34.565 - type: map_at_5 value: 37.069 - type: mrr_at_1 value: 27.578000000000003 - type: mrr_at_10 value: 41.079 - type: mrr_at_100 value: 42.081 - type: mrr_at_1000 value: 42.109 - type: mrr_at_3 value: 37.278 - type: mrr_at_5 value: 39.585 - type: ndcg_at_1 value: 27.549 - type: ndcg_at_10 value: 46.506 - type: ndcg_at_100 value: 51.92400000000001 - type: ndcg_at_1000 value: 52.833 - type: ndcg_at_3 value: 38.214999999999996 - type: ndcg_at_5 value: 42.498000000000005 - type: precision_at_1 value: 27.549 - type: precision_at_10 value: 8.019 - type: precision_at_100 value: 1.103 - type: precision_at_1000 value: 0.11900000000000001 - type: precision_at_3 value: 17.806 - type: precision_at_5 value: 13.100000000000001 - type: recall_at_1 value: 24.468999999999998 - type: recall_at_10 value: 67.632 - type: recall_at_100 value: 91.169 - type: recall_at_1000 value: 97.851 - type: recall_at_3 value: 46.043 - type: recall_at_5 value: 55.962999999999994 - task: type: Retrieval dataset: type: quora name: MTEB QuoraRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 70.44 - type: map_at_10 value: 84.209 - type: map_at_100 value: 84.868 - type: map_at_1000 value: 84.884 - type: map_at_3 value: 81.192 - type: map_at_5 value: 83.06099999999999 - type: mrr_at_1 value: 81.12 - type: mrr_at_10 value: 87.30499999999999 - type: mrr_at_100 value: 87.413 - type: mrr_at_1000 value: 87.414 - type: mrr_at_3 value: 86.337 - type: mrr_at_5 value: 86.985 - type: ndcg_at_1 value: 81.15 - type: ndcg_at_10 value: 88.032 - type: ndcg_at_100 value: 89.292 - type: ndcg_at_1000 value: 89.393 - type: ndcg_at_3 value: 85.098 - type: ndcg_at_5 value: 86.691 - type: precision_at_1 value: 81.15 - type: precision_at_10 value: 13.395999999999999 - type: precision_at_100 value: 1.5310000000000001 - type: precision_at_1000 value: 0.157 - type: precision_at_3 value: 37.16 - type: precision_at_5 value: 24.458 - type: recall_at_1 value: 70.44 - type: recall_at_10 value: 95.204 - type: recall_at_100 value: 99.506 - type: recall_at_1000 value: 99.978 - type: recall_at_3 value: 86.83999999999999 - type: recall_at_5 value: 91.328 - task: type: Clustering dataset: type: mteb/reddit-clustering name: MTEB RedditClustering config: default split: test revision: 24640382cdbf8abc73003fb0fa6d111a705499eb metrics: - type: v_measure value: 44.091918771223966 - task: type: Clustering dataset: type: mteb/reddit-clustering-p2p name: MTEB RedditClusteringP2P config: default split: test revision: 282350215ef01743dc01b456c7f5241fa8937f16 metrics: - type: v_measure value: 49.3850718319815 - task: type: Retrieval dataset: type: scidocs name: MTEB SCIDOCS config: default split: test revision: None metrics: - type: map_at_1 value: 5.108 - type: map_at_10 value: 12.878 - type: map_at_100 value: 15.398 - type: map_at_1000 value: 15.762 - type: map_at_3 value: 9.028 - type: map_at_5 value: 10.886 - type: mrr_at_1 value: 25.2 - type: mrr_at_10 value: 36.051 - type: mrr_at_100 value: 37.198 - type: mrr_at_1000 value: 37.254 - type: mrr_at_3 value: 32.483000000000004 - type: mrr_at_5 value: 34.583000000000006 - type: ndcg_at_1 value: 25.2 - type: ndcg_at_10 value: 21.436 - type: ndcg_at_100 value: 30.758000000000003 - type: ndcg_at_1000 value: 36.774 - type: ndcg_at_3 value: 19.977 - type: ndcg_at_5 value: 17.634 - type: precision_at_1 value: 25.2 - type: precision_at_10 value: 11.16 - type: precision_at_100 value: 2.46 - type: precision_at_1000 value: 0.38999999999999996 - type: precision_at_3 value: 18.4 - type: precision_at_5 value: 15.440000000000001 - type: recall_at_1 value: 5.108 - type: recall_at_10 value: 22.615 - type: recall_at_100 value: 49.838 - type: recall_at_1000 value: 79.12700000000001 - type: recall_at_3 value: 11.203000000000001 - type: recall_at_5 value: 15.638 - task: type: STS dataset: type: mteb/sickr-sts name: MTEB SICK-R config: default split: test revision: a6ea5a8cab320b040a23452cc28066d9beae2cee metrics: - type: cos_sim_pearson value: 84.87907802108278 - type: cos_sim_spearman value: 78.47745630820519 - type: euclidean_pearson value: 81.24598854050433 - type: euclidean_spearman value: 76.49536405466311 - type: manhattan_pearson value: 81.2143517198192 - type: manhattan_spearman value: 76.41735187637899 - task: type: STS dataset: type: mteb/sts12-sts name: MTEB STS12 config: default split: test revision: a0d554a64d88156834ff5ae9920b964011b16384 metrics: - type: cos_sim_pearson value: 84.72222146895906 - type: cos_sim_spearman value: 75.78345138703104 - type: euclidean_pearson value: 81.35072741369821 - type: euclidean_spearman value: 71.44372390021385 - type: manhattan_pearson value: 81.42777992212991 - type: manhattan_spearman value: 71.50748732911025 - task: type: STS dataset: type: mteb/sts13-sts name: MTEB STS13 config: default split: test revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca metrics: - type: cos_sim_pearson value: 82.46314178714782 - type: cos_sim_spearman value: 83.30487501773337 - type: euclidean_pearson value: 81.97496753880277 - type: euclidean_spearman value: 83.26569157819903 - type: manhattan_pearson value: 81.95087299528338 - type: manhattan_spearman value: 83.25657383286989 - task: type: STS dataset: type: mteb/sts14-sts name: MTEB STS14 config: default split: test revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 metrics: - type: cos_sim_pearson value: 82.38192118423038 - type: cos_sim_spearman value: 78.40410104736917 - type: euclidean_pearson value: 79.48941144435967 - type: euclidean_spearman value: 76.87243228899331 - type: manhattan_pearson value: 79.37383745954276 - type: manhattan_spearman value: 76.81624170740595 - task: type: STS dataset: type: mteb/sts15-sts name: MTEB STS15 config: default split: test revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 metrics: - type: cos_sim_pearson value: 84.89499997364136 - type: cos_sim_spearman value: 86.49722400765071 - type: euclidean_pearson value: 80.83327622391033 - type: euclidean_spearman value: 81.77906221038033 - type: manhattan_pearson value: 80.68927444298423 - type: manhattan_spearman value: 81.67585996918764 - task: type: STS dataset: type: mteb/sts16-sts name: MTEB STS16 config: default split: test revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 metrics: - type: cos_sim_pearson value: 80.85434430333662 - type: cos_sim_spearman value: 82.32641704038703 - type: euclidean_pearson value: 78.92319495883405 - type: euclidean_spearman value: 80.06748121443441 - type: manhattan_pearson value: 78.68188267117745 - type: manhattan_spearman value: 79.72019793896195 - 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: 87.0896689258414 - type: cos_sim_spearman value: 87.31114069713735 - type: euclidean_pearson value: 83.93671908621272 - type: euclidean_spearman value: 82.83918654090873 - type: manhattan_pearson value: 83.5943550673816 - type: manhattan_spearman value: 82.47327946394148 - 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: 66.4799391480602 - type: cos_sim_spearman value: 66.59141182659532 - type: euclidean_pearson value: 45.85714541149068 - type: euclidean_spearman value: 61.605252732946404 - type: manhattan_pearson value: 46.69415667711241 - type: manhattan_spearman value: 61.38490967409539 - task: type: STS dataset: type: mteb/stsbenchmark-sts name: MTEB STSBenchmark config: default split: test revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 metrics: - type: cos_sim_pearson value: 82.22064334651283 - type: cos_sim_spearman value: 84.23556405551305 - type: euclidean_pearson value: 80.64484589022672 - type: euclidean_spearman value: 80.27585966983669 - type: manhattan_pearson value: 80.44248540454653 - type: manhattan_spearman value: 80.06071452831723 - task: type: Reranking dataset: type: mteb/scidocs-reranking name: MTEB SciDocsRR config: default split: test revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab metrics: - type: map value: 86.82632940766443 - type: mrr value: 96.27367186190715 - task: type: Retrieval dataset: type: scifact name: MTEB SciFact config: default split: test revision: None metrics: - type: map_at_1 value: 48.443999999999996 - type: map_at_10 value: 58.309 - type: map_at_100 value: 59.116 - type: map_at_1000 value: 59.155 - type: map_at_3 value: 55.598000000000006 - type: map_at_5 value: 57.550999999999995 - type: mrr_at_1 value: 50.666999999999994 - type: mrr_at_10 value: 59.099000000000004 - type: mrr_at_100 value: 59.843 - type: mrr_at_1000 value: 59.879000000000005 - type: mrr_at_3 value: 57.167 - type: mrr_at_5 value: 58.5 - type: ndcg_at_1 value: 50.666999999999994 - type: ndcg_at_10 value: 62.483999999999995 - type: ndcg_at_100 value: 66.131 - type: ndcg_at_1000 value: 67.17 - type: ndcg_at_3 value: 58.07299999999999 - type: ndcg_at_5 value: 60.87200000000001 - type: precision_at_1 value: 50.666999999999994 - type: precision_at_10 value: 8.4 - type: precision_at_100 value: 1.0330000000000001 - type: precision_at_1000 value: 0.11199999999999999 - type: precision_at_3 value: 22.889 - type: precision_at_5 value: 15.467 - type: recall_at_1 value: 48.443999999999996 - type: recall_at_10 value: 74.26700000000001 - type: recall_at_100 value: 90.5 - type: recall_at_1000 value: 98.667 - type: recall_at_3 value: 63.039 - type: recall_at_5 value: 69.706 - task: type: PairClassification dataset: type: mteb/sprintduplicatequestions-pairclassification name: MTEB SprintDuplicateQuestions config: default split: test revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 metrics: - type: cos_sim_accuracy value: 99.76336633663367 - type: cos_sim_ap value: 94.05677361006421 - type: cos_sim_f1 value: 87.85894206549118 - type: cos_sim_precision value: 88.52791878172589 - type: cos_sim_recall value: 87.2 - type: dot_accuracy value: 99.06732673267327 - type: dot_ap value: 25.234902506145275 - type: dot_f1 value: 31.687715269804816 - type: dot_precision value: 37.19676549865229 - type: dot_recall value: 27.6 - type: euclidean_accuracy value: 99.73861386138614 - type: euclidean_ap value: 92.39504711224613 - type: euclidean_f1 value: 86.40576725025747 - type: euclidean_precision value: 89.06581740976645 - type: euclidean_recall value: 83.89999999999999 - type: manhattan_accuracy value: 99.74455445544554 - type: manhattan_ap value: 92.5050066340186 - type: manhattan_f1 value: 86.67355371900827 - type: manhattan_precision value: 89.63675213675214 - type: manhattan_recall value: 83.89999999999999 - type: max_accuracy value: 99.76336633663367 - type: max_ap value: 94.05677361006421 - type: max_f1 value: 87.85894206549118 - task: type: Clustering dataset: type: mteb/stackexchange-clustering name: MTEB StackExchangeClustering config: default split: test revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 metrics: - type: v_measure value: 52.66315650755836 - task: type: Clustering dataset: type: mteb/stackexchange-clustering-p2p name: MTEB StackExchangeClusteringP2P config: default split: test revision: 815ca46b2622cec33ccafc3735d572c266efdb44 metrics: - type: v_measure value: 32.36019149648443 - task: type: Reranking dataset: type: mteb/stackoverflowdupquestions-reranking name: MTEB StackOverflowDupQuestions config: default split: test revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 metrics: - type: map value: 50.10933600138655 - type: mrr value: 50.84273671589848 - task: type: Summarization dataset: type: mteb/summeval name: MTEB SummEval config: default split: test revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c metrics: - type: cos_sim_pearson value: 30.342194052503917 - type: cos_sim_spearman value: 30.74326118928312 - type: dot_pearson value: 12.329727800033176 - type: dot_spearman value: 14.54557726626662 - task: type: Retrieval dataset: type: trec-covid name: MTEB TRECCOVID config: default split: test revision: None metrics: - type: map_at_1 value: 0.173 - type: map_at_10 value: 1.1320000000000001 - type: map_at_100 value: 5.885 - type: map_at_1000 value: 14.762 - type: map_at_3 value: 0.443 - type: map_at_5 value: 0.66 - type: mrr_at_1 value: 66.0 - type: mrr_at_10 value: 76.34100000000001 - type: mrr_at_100 value: 76.37 - type: mrr_at_1000 value: 76.376 - type: mrr_at_3 value: 74.667 - type: mrr_at_5 value: 74.667 - type: ndcg_at_1 value: 59.0 - type: ndcg_at_10 value: 50.047 - type: ndcg_at_100 value: 37.744 - type: ndcg_at_1000 value: 35.903 - type: ndcg_at_3 value: 55.95 - type: ndcg_at_5 value: 53.379 - type: precision_at_1 value: 66.0 - type: precision_at_10 value: 53.0 - type: precision_at_100 value: 38.78 - type: precision_at_1000 value: 16.24 - type: precision_at_3 value: 60.0 - type: precision_at_5 value: 56.39999999999999 - type: recall_at_1 value: 0.173 - type: recall_at_10 value: 1.379 - type: recall_at_100 value: 9.196 - type: recall_at_1000 value: 34.488 - type: recall_at_3 value: 0.475 - type: recall_at_5 value: 0.738 - task: type: Retrieval dataset: type: webis-touche2020 name: MTEB Touche2020 config: default split: test revision: None metrics: - type: map_at_1 value: 2.1260000000000003 - type: map_at_10 value: 7.216 - type: map_at_100 value: 12.732 - type: map_at_1000 value: 14.158999999999999 - type: map_at_3 value: 3.9530000000000003 - type: map_at_5 value: 5.252 - type: mrr_at_1 value: 24.490000000000002 - type: mrr_at_10 value: 36.949 - type: mrr_at_100 value: 38.0 - type: mrr_at_1000 value: 38.0 - type: mrr_at_3 value: 31.973000000000003 - type: mrr_at_5 value: 34.32 - type: ndcg_at_1 value: 19.387999999999998 - type: ndcg_at_10 value: 17.918 - type: ndcg_at_100 value: 30.558999999999997 - type: ndcg_at_1000 value: 42.028 - type: ndcg_at_3 value: 17.202 - type: ndcg_at_5 value: 17.788 - type: precision_at_1 value: 24.490000000000002 - type: precision_at_10 value: 17.347 - type: precision_at_100 value: 6.918 - type: precision_at_1000 value: 1.4569999999999999 - type: precision_at_3 value: 19.728 - type: precision_at_5 value: 19.592000000000002 - type: recall_at_1 value: 2.1260000000000003 - type: recall_at_10 value: 12.897 - type: recall_at_100 value: 42.632999999999996 - type: recall_at_1000 value: 77.783 - type: recall_at_3 value: 4.836 - type: recall_at_5 value: 7.331 - task: type: Classification dataset: type: mteb/toxic_conversations_50k name: MTEB ToxicConversationsClassification config: default split: test revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c metrics: - type: accuracy value: 70.9516 - type: ap value: 14.148097836321893 - type: f1 value: 54.52189833022899 - task: type: Classification dataset: type: mteb/tweet_sentiment_extraction name: MTEB TweetSentimentExtractionClassification config: default split: test revision: d604517c81ca91fe16a244d1248fc021f9ecee7a metrics: - type: accuracy value: 58.33899264289756 - type: f1 value: 58.684516042056565 - task: type: Clustering dataset: type: mteb/twentynewsgroups-clustering name: MTEB TwentyNewsgroupsClustering config: default split: test revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 metrics: - type: v_measure value: 41.45569187892743 - task: type: PairClassification dataset: type: mteb/twittersemeval2015-pairclassification name: MTEB TwitterSemEval2015 config: default split: test revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 metrics: - type: cos_sim_accuracy value: 85.05692316862371 - type: cos_sim_ap value: 70.54785019750204 - type: cos_sim_f1 value: 65.99060103883255 - type: cos_sim_precision value: 62.10428305400373 - type: cos_sim_recall value: 70.3957783641161 - type: dot_accuracy value: 77.82678667222984 - type: dot_ap value: 32.73452779849359 - type: dot_f1 value: 38.1269911832259 - type: dot_precision value: 26.5066446893994 - type: dot_recall value: 67.8891820580475 - type: euclidean_accuracy value: 84.62180365977231 - type: euclidean_ap value: 68.57434108453688 - type: euclidean_f1 value: 65.23069391751316 - type: euclidean_precision value: 60.83086053412463 - type: euclidean_recall value: 70.31662269129288 - type: manhattan_accuracy value: 84.57411933003517 - type: manhattan_ap value: 68.3530821550187 - type: manhattan_f1 value: 64.74820143884892 - type: manhattan_precision value: 61.09550561797753 - type: manhattan_recall value: 68.86543535620054 - type: max_accuracy value: 85.05692316862371 - type: max_ap value: 70.54785019750204 - type: max_f1 value: 65.99060103883255 - task: type: PairClassification dataset: type: mteb/twitterurlcorpus-pairclassification name: MTEB TwitterURLCorpus config: default split: test revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf metrics: - type: cos_sim_accuracy value: 88.77440136608841 - type: cos_sim_ap value: 85.6224854550336 - type: cos_sim_f1 value: 77.76333865518139 - type: cos_sim_precision value: 75.09501613481535 - type: cos_sim_recall value: 80.6282722513089 - type: dot_accuracy value: 79.73570846431483 - type: dot_ap value: 59.509855217305315 - type: dot_f1 value: 57.20318336852364 - type: dot_precision value: 49.474630555711634 - type: dot_recall value: 67.79334770557438 - type: euclidean_accuracy value: 87.06096945705748 - type: euclidean_ap value: 81.65241378370953 - type: euclidean_f1 value: 73.29885784441386 - type: euclidean_precision value: 70.91642070405298 - type: euclidean_recall value: 75.8469356328919 - type: manhattan_accuracy value: 86.973648465091 - type: manhattan_ap value: 81.57560533116907 - type: manhattan_f1 value: 73.2408287397833 - type: manhattan_precision value: 72.33611173687767 - type: manhattan_recall value: 74.16846319679703 - type: max_accuracy value: 88.77440136608841 - type: max_ap value: 85.6224854550336 - type: max_f1 value: 77.76333865518139 ---