--- tags: - mteb - sentence-similarity - sentence-transformers - Sentence Transformers - llama-cpp - gguf-my-repo language: - en license: mit base_model: thenlper/gte-small model-index: - name: gte-small results: - task: type: Classification dataset: name: MTEB AmazonCounterfactualClassification (en) type: mteb/amazon_counterfactual config: en split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics: - type: accuracy value: 73.22388059701493 - type: ap value: 36.09895941426988 - type: f1 value: 67.3205651539195 - task: type: Classification dataset: name: MTEB AmazonPolarityClassification type: mteb/amazon_polarity config: default split: test revision: e2d317d38cd51312af73b3d32a06d1a08b442046 metrics: - type: accuracy value: 91.81894999999999 - type: ap value: 88.5240138417305 - type: f1 value: 91.80367382706962 - task: type: Classification dataset: name: MTEB AmazonReviewsClassification (en) type: mteb/amazon_reviews_multi config: en split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics: - type: accuracy value: 48.032 - type: f1 value: 47.4490665674719 - task: type: Retrieval dataset: name: MTEB ArguAna type: arguana config: default split: test revision: None metrics: - type: map_at_1 value: 30.725 - type: map_at_10 value: 46.604 - type: map_at_100 value: 47.535 - type: map_at_1000 value: 47.538000000000004 - type: map_at_3 value: 41.833 - type: map_at_5 value: 44.61 - type: mrr_at_1 value: 31.223 - type: mrr_at_10 value: 46.794000000000004 - type: mrr_at_100 value: 47.725 - type: mrr_at_1000 value: 47.727000000000004 - type: mrr_at_3 value: 42.07 - type: mrr_at_5 value: 44.812000000000005 - type: ndcg_at_1 value: 30.725 - type: ndcg_at_10 value: 55.440999999999995 - type: ndcg_at_100 value: 59.134 - type: ndcg_at_1000 value: 59.199 - type: ndcg_at_3 value: 45.599000000000004 - type: ndcg_at_5 value: 50.637 - type: precision_at_1 value: 30.725 - type: precision_at_10 value: 8.364 - type: precision_at_100 value: 0.991 - type: precision_at_1000 value: 0.1 - type: precision_at_3 value: 18.848000000000003 - type: precision_at_5 value: 13.77 - type: recall_at_1 value: 30.725 - type: recall_at_10 value: 83.64200000000001 - type: recall_at_100 value: 99.14699999999999 - type: recall_at_1000 value: 99.644 - type: recall_at_3 value: 56.543 - type: recall_at_5 value: 68.848 - task: type: Clustering dataset: name: MTEB ArxivClusteringP2P type: mteb/arxiv-clustering-p2p config: default split: test revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d metrics: - type: v_measure value: 47.90178078197678 - task: type: Clustering dataset: name: MTEB ArxivClusteringS2S type: mteb/arxiv-clustering-s2s config: default split: test revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 metrics: - type: v_measure value: 40.25728393431922 - task: type: Reranking dataset: name: MTEB AskUbuntuDupQuestions type: mteb/askubuntudupquestions-reranking config: default split: test revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 metrics: - type: map value: 61.720297062897764 - type: mrr value: 75.24139295607439 - task: type: STS dataset: name: MTEB BIOSSES type: mteb/biosses-sts config: default split: test revision: d3fb88f8f02e40887cd149695127462bbcf29b4a metrics: - type: cos_sim_pearson value: 89.43527309184616 - type: cos_sim_spearman value: 88.17128615100206 - type: euclidean_pearson value: 87.89922623089282 - type: euclidean_spearman value: 87.96104039655451 - type: manhattan_pearson value: 87.9818290932077 - type: manhattan_spearman value: 88.00923426576885 - task: type: Classification dataset: name: MTEB Banking77Classification type: mteb/banking77 config: default split: test revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 metrics: - type: accuracy value: 84.0844155844156 - type: f1 value: 84.01485017302213 - task: type: Clustering dataset: name: MTEB BiorxivClusteringP2P type: mteb/biorxiv-clustering-p2p config: default split: test revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 metrics: - type: v_measure value: 38.36574769259432 - task: type: Clustering dataset: name: MTEB BiorxivClusteringS2S type: mteb/biorxiv-clustering-s2s config: default split: test revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 metrics: - type: v_measure value: 35.4857033165287 - task: type: Retrieval dataset: name: MTEB CQADupstackAndroidRetrieval type: BeIR/cqadupstack config: default split: test revision: None metrics: - type: map_at_1 value: 30.261 - type: map_at_10 value: 42.419000000000004 - type: map_at_100 value: 43.927 - type: map_at_1000 value: 44.055 - type: map_at_3 value: 38.597 - type: map_at_5 value: 40.701 - type: mrr_at_1 value: 36.91 - type: mrr_at_10 value: 48.02 - type: mrr_at_100 value: 48.658 - type: mrr_at_1000 value: 48.708 - type: mrr_at_3 value: 44.945 - type: mrr_at_5 value: 46.705000000000005 - type: ndcg_at_1 value: 36.91 - type: ndcg_at_10 value: 49.353 - type: ndcg_at_100 value: 54.456 - type: ndcg_at_1000 value: 56.363 - type: ndcg_at_3 value: 43.483 - type: ndcg_at_5 value: 46.150999999999996 - type: precision_at_1 value: 36.91 - type: precision_at_10 value: 9.700000000000001 - type: precision_at_100 value: 1.557 - type: precision_at_1000 value: 0.202 - type: precision_at_3 value: 21.078 - type: precision_at_5 value: 15.421999999999999 - type: recall_at_1 value: 30.261 - type: recall_at_10 value: 63.242 - type: recall_at_100 value: 84.09100000000001 - type: recall_at_1000 value: 96.143 - type: recall_at_3 value: 46.478 - type: recall_at_5 value: 53.708 - type: map_at_1 value: 31.145 - type: map_at_10 value: 40.996 - type: map_at_100 value: 42.266999999999996 - type: map_at_1000 value: 42.397 - type: map_at_3 value: 38.005 - type: map_at_5 value: 39.628 - type: mrr_at_1 value: 38.344 - type: mrr_at_10 value: 46.827000000000005 - type: mrr_at_100 value: 47.446 - type: mrr_at_1000 value: 47.489 - type: mrr_at_3 value: 44.448 - type: mrr_at_5 value: 45.747 - type: ndcg_at_1 value: 38.344 - type: ndcg_at_10 value: 46.733000000000004 - type: ndcg_at_100 value: 51.103 - type: ndcg_at_1000 value: 53.075 - type: ndcg_at_3 value: 42.366 - type: ndcg_at_5 value: 44.242 - type: precision_at_1 value: 38.344 - type: precision_at_10 value: 8.822000000000001 - type: precision_at_100 value: 1.417 - type: precision_at_1000 value: 0.187 - type: precision_at_3 value: 20.403 - type: precision_at_5 value: 14.306 - type: recall_at_1 value: 31.145 - type: recall_at_10 value: 56.909 - type: recall_at_100 value: 75.274 - type: recall_at_1000 value: 87.629 - type: recall_at_3 value: 43.784 - type: recall_at_5 value: 49.338 - type: map_at_1 value: 38.83 - type: map_at_10 value: 51.553000000000004 - type: map_at_100 value: 52.581 - type: map_at_1000 value: 52.638 - type: map_at_3 value: 48.112 - type: map_at_5 value: 50.095 - type: mrr_at_1 value: 44.513999999999996 - type: mrr_at_10 value: 54.998000000000005 - type: mrr_at_100 value: 55.650999999999996 - type: mrr_at_1000 value: 55.679 - type: mrr_at_3 value: 52.602000000000004 - type: mrr_at_5 value: 53.931 - type: ndcg_at_1 value: 44.513999999999996 - type: ndcg_at_10 value: 57.67400000000001 - type: ndcg_at_100 value: 61.663999999999994 - type: ndcg_at_1000 value: 62.743 - type: ndcg_at_3 value: 51.964 - type: ndcg_at_5 value: 54.773 - type: precision_at_1 value: 44.513999999999996 - type: precision_at_10 value: 9.423 - type: precision_at_100 value: 1.2309999999999999 - type: precision_at_1000 value: 0.13699999999999998 - type: precision_at_3 value: 23.323 - type: precision_at_5 value: 16.163 - type: recall_at_1 value: 38.83 - type: recall_at_10 value: 72.327 - type: recall_at_100 value: 89.519 - type: recall_at_1000 value: 97.041 - type: recall_at_3 value: 57.206 - type: recall_at_5 value: 63.88399999999999 - type: map_at_1 value: 25.484 - type: map_at_10 value: 34.527 - type: map_at_100 value: 35.661 - type: map_at_1000 value: 35.739 - type: map_at_3 value: 32.199 - type: map_at_5 value: 33.632 - type: mrr_at_1 value: 27.458 - type: mrr_at_10 value: 36.543 - type: mrr_at_100 value: 37.482 - type: mrr_at_1000 value: 37.543 - type: mrr_at_3 value: 34.256 - type: mrr_at_5 value: 35.618 - type: ndcg_at_1 value: 27.458 - type: ndcg_at_10 value: 39.396 - type: ndcg_at_100 value: 44.742 - type: ndcg_at_1000 value: 46.708 - type: ndcg_at_3 value: 34.817 - type: ndcg_at_5 value: 37.247 - type: precision_at_1 value: 27.458 - type: precision_at_10 value: 5.976999999999999 - type: precision_at_100 value: 0.907 - type: precision_at_1000 value: 0.11100000000000002 - type: precision_at_3 value: 14.878 - type: precision_at_5 value: 10.35 - type: recall_at_1 value: 25.484 - type: recall_at_10 value: 52.317 - type: recall_at_100 value: 76.701 - type: recall_at_1000 value: 91.408 - type: recall_at_3 value: 40.043 - type: recall_at_5 value: 45.879 - type: map_at_1 value: 16.719 - type: map_at_10 value: 25.269000000000002 - type: map_at_100 value: 26.442 - type: map_at_1000 value: 26.557 - type: map_at_3 value: 22.56 - type: map_at_5 value: 24.082 - type: mrr_at_1 value: 20.896 - type: mrr_at_10 value: 29.982999999999997 - type: mrr_at_100 value: 30.895 - type: mrr_at_1000 value: 30.961 - type: mrr_at_3 value: 27.239 - type: mrr_at_5 value: 28.787000000000003 - type: ndcg_at_1 value: 20.896 - type: ndcg_at_10 value: 30.814000000000004 - type: ndcg_at_100 value: 36.418 - type: ndcg_at_1000 value: 39.182 - type: ndcg_at_3 value: 25.807999999999996 - type: ndcg_at_5 value: 28.143 - type: precision_at_1 value: 20.896 - type: precision_at_10 value: 5.821 - type: precision_at_100 value: 0.991 - type: precision_at_1000 value: 0.136 - type: precision_at_3 value: 12.562000000000001 - type: precision_at_5 value: 9.254 - type: recall_at_1 value: 16.719 - type: recall_at_10 value: 43.155 - type: recall_at_100 value: 67.831 - type: recall_at_1000 value: 87.617 - type: recall_at_3 value: 29.259 - type: recall_at_5 value: 35.260999999999996 - type: map_at_1 value: 29.398999999999997 - type: map_at_10 value: 39.876 - type: map_at_100 value: 41.205999999999996 - type: map_at_1000 value: 41.321999999999996 - type: map_at_3 value: 36.588 - type: map_at_5 value: 38.538 - type: mrr_at_1 value: 35.9 - type: mrr_at_10 value: 45.528 - type: mrr_at_100 value: 46.343 - type: mrr_at_1000 value: 46.388 - type: mrr_at_3 value: 42.862 - type: mrr_at_5 value: 44.440000000000005 - type: ndcg_at_1 value: 35.9 - type: ndcg_at_10 value: 45.987 - type: ndcg_at_100 value: 51.370000000000005 - type: ndcg_at_1000 value: 53.400000000000006 - type: ndcg_at_3 value: 40.841 - type: ndcg_at_5 value: 43.447 - type: precision_at_1 value: 35.9 - type: precision_at_10 value: 8.393 - type: precision_at_100 value: 1.283 - type: precision_at_1000 value: 0.166 - type: precision_at_3 value: 19.538 - type: precision_at_5 value: 13.975000000000001 - type: recall_at_1 value: 29.398999999999997 - type: recall_at_10 value: 58.361 - type: recall_at_100 value: 81.081 - type: recall_at_1000 value: 94.004 - type: recall_at_3 value: 43.657000000000004 - type: recall_at_5 value: 50.519999999999996 - type: map_at_1 value: 21.589 - type: map_at_10 value: 31.608999999999998 - type: map_at_100 value: 33.128 - type: map_at_1000 value: 33.247 - type: map_at_3 value: 28.671999999999997 - type: map_at_5 value: 30.233999999999998 - type: mrr_at_1 value: 26.712000000000003 - type: mrr_at_10 value: 36.713 - type: mrr_at_100 value: 37.713 - type: mrr_at_1000 value: 37.771 - type: mrr_at_3 value: 34.075 - type: mrr_at_5 value: 35.451 - type: ndcg_at_1 value: 26.712000000000003 - type: ndcg_at_10 value: 37.519999999999996 - type: ndcg_at_100 value: 43.946000000000005 - type: ndcg_at_1000 value: 46.297 - type: ndcg_at_3 value: 32.551 - type: ndcg_at_5 value: 34.660999999999994 - type: precision_at_1 value: 26.712000000000003 - type: precision_at_10 value: 7.066 - type: precision_at_100 value: 1.216 - type: precision_at_1000 value: 0.157 - type: precision_at_3 value: 15.906 - type: precision_at_5 value: 11.437999999999999 - type: recall_at_1 value: 21.589 - type: recall_at_10 value: 50.090999999999994 - type: recall_at_100 value: 77.43900000000001 - type: recall_at_1000 value: 93.35900000000001 - type: recall_at_3 value: 36.028999999999996 - type: recall_at_5 value: 41.698 - type: map_at_1 value: 25.121666666666663 - type: map_at_10 value: 34.46258333333334 - type: map_at_100 value: 35.710499999999996 - type: map_at_1000 value: 35.82691666666666 - type: map_at_3 value: 31.563249999999996 - type: map_at_5 value: 33.189750000000004 - type: mrr_at_1 value: 29.66441666666667 - type: mrr_at_10 value: 38.5455 - type: mrr_at_100 value: 39.39566666666667 - type: mrr_at_1000 value: 39.45325 - type: mrr_at_3 value: 36.003333333333345 - type: mrr_at_5 value: 37.440916666666666 - type: ndcg_at_1 value: 29.66441666666667 - type: ndcg_at_10 value: 39.978416666666675 - type: ndcg_at_100 value: 45.278666666666666 - type: ndcg_at_1000 value: 47.52275 - type: ndcg_at_3 value: 35.00058333333334 - type: ndcg_at_5 value: 37.34908333333333 - type: precision_at_1 value: 29.66441666666667 - type: precision_at_10 value: 7.094500000000001 - type: precision_at_100 value: 1.1523333333333332 - type: precision_at_1000 value: 0.15358333333333332 - type: precision_at_3 value: 16.184166666666663 - type: precision_at_5 value: 11.6005 - type: recall_at_1 value: 25.121666666666663 - type: recall_at_10 value: 52.23975000000001 - type: recall_at_100 value: 75.48408333333333 - type: recall_at_1000 value: 90.95316666666668 - type: recall_at_3 value: 38.38458333333333 - type: recall_at_5 value: 44.39933333333333 - type: map_at_1 value: 23.569000000000003 - type: map_at_10 value: 30.389 - type: map_at_100 value: 31.396 - type: map_at_1000 value: 31.493 - type: map_at_3 value: 28.276 - type: map_at_5 value: 29.459000000000003 - type: mrr_at_1 value: 26.534000000000002 - type: mrr_at_10 value: 33.217999999999996 - type: mrr_at_100 value: 34.054 - type: mrr_at_1000 value: 34.12 - type: mrr_at_3 value: 31.058000000000003 - type: mrr_at_5 value: 32.330999999999996 - type: ndcg_at_1 value: 26.534000000000002 - type: ndcg_at_10 value: 34.608 - type: ndcg_at_100 value: 39.391999999999996 - type: ndcg_at_1000 value: 41.837999999999994 - type: ndcg_at_3 value: 30.564999999999998 - type: ndcg_at_5 value: 32.509 - type: precision_at_1 value: 26.534000000000002 - type: precision_at_10 value: 5.414 - type: precision_at_100 value: 0.847 - type: precision_at_1000 value: 0.11399999999999999 - type: precision_at_3 value: 12.986 - type: precision_at_5 value: 9.202 - type: recall_at_1 value: 23.569000000000003 - type: recall_at_10 value: 44.896 - type: recall_at_100 value: 66.476 - type: recall_at_1000 value: 84.548 - type: recall_at_3 value: 33.79 - type: recall_at_5 value: 38.512 - type: map_at_1 value: 16.36 - type: map_at_10 value: 23.57 - type: map_at_100 value: 24.698999999999998 - type: map_at_1000 value: 24.834999999999997 - type: map_at_3 value: 21.093 - type: map_at_5 value: 22.418 - type: mrr_at_1 value: 19.718 - type: mrr_at_10 value: 27.139999999999997 - type: mrr_at_100 value: 28.097 - type: mrr_at_1000 value: 28.177999999999997 - type: mrr_at_3 value: 24.805 - type: mrr_at_5 value: 26.121 - type: ndcg_at_1 value: 19.718 - type: ndcg_at_10 value: 28.238999999999997 - type: ndcg_at_100 value: 33.663 - type: ndcg_at_1000 value: 36.763 - type: ndcg_at_3 value: 23.747 - type: ndcg_at_5 value: 25.796000000000003 - type: precision_at_1 value: 19.718 - type: precision_at_10 value: 5.282 - type: precision_at_100 value: 0.9390000000000001 - type: precision_at_1000 value: 0.13899999999999998 - type: precision_at_3 value: 11.264000000000001 - type: precision_at_5 value: 8.341 - type: recall_at_1 value: 16.36 - type: recall_at_10 value: 38.669 - type: recall_at_100 value: 63.184 - type: recall_at_1000 value: 85.33800000000001 - type: recall_at_3 value: 26.214 - type: recall_at_5 value: 31.423000000000002 - type: map_at_1 value: 25.618999999999996 - type: map_at_10 value: 34.361999999999995 - type: map_at_100 value: 35.534 - type: map_at_1000 value: 35.634 - type: map_at_3 value: 31.402 - type: map_at_5 value: 32.815 - type: mrr_at_1 value: 30.037000000000003 - type: mrr_at_10 value: 38.284 - type: mrr_at_100 value: 39.141999999999996 - type: mrr_at_1000 value: 39.2 - type: mrr_at_3 value: 35.603 - type: mrr_at_5 value: 36.867 - type: ndcg_at_1 value: 30.037000000000003 - type: ndcg_at_10 value: 39.87 - type: ndcg_at_100 value: 45.243 - type: ndcg_at_1000 value: 47.507 - type: ndcg_at_3 value: 34.371 - type: ndcg_at_5 value: 36.521 - type: precision_at_1 value: 30.037000000000003 - type: precision_at_10 value: 6.819 - type: precision_at_100 value: 1.0699999999999998 - type: precision_at_1000 value: 0.13699999999999998 - type: precision_at_3 value: 15.392 - type: precision_at_5 value: 10.821 - type: recall_at_1 value: 25.618999999999996 - type: recall_at_10 value: 52.869 - type: recall_at_100 value: 76.395 - type: recall_at_1000 value: 92.19500000000001 - type: recall_at_3 value: 37.943 - type: recall_at_5 value: 43.342999999999996 - type: map_at_1 value: 23.283 - type: map_at_10 value: 32.155 - type: map_at_100 value: 33.724 - type: map_at_1000 value: 33.939 - type: map_at_3 value: 29.018 - type: map_at_5 value: 30.864000000000004 - type: mrr_at_1 value: 28.063 - type: mrr_at_10 value: 36.632 - type: mrr_at_100 value: 37.606 - type: mrr_at_1000 value: 37.671 - type: mrr_at_3 value: 33.992 - type: mrr_at_5 value: 35.613 - type: ndcg_at_1 value: 28.063 - type: ndcg_at_10 value: 38.024 - type: ndcg_at_100 value: 44.292 - type: ndcg_at_1000 value: 46.818 - type: ndcg_at_3 value: 32.965 - type: ndcg_at_5 value: 35.562 - type: precision_at_1 value: 28.063 - type: precision_at_10 value: 7.352 - type: precision_at_100 value: 1.514 - type: precision_at_1000 value: 0.23800000000000002 - type: precision_at_3 value: 15.481 - type: precision_at_5 value: 11.542 - type: recall_at_1 value: 23.283 - type: recall_at_10 value: 49.756 - type: recall_at_100 value: 78.05 - type: recall_at_1000 value: 93.854 - type: recall_at_3 value: 35.408 - type: recall_at_5 value: 42.187000000000005 - type: map_at_1 value: 19.201999999999998 - type: map_at_10 value: 26.826 - type: map_at_100 value: 27.961000000000002 - type: map_at_1000 value: 28.066999999999997 - type: map_at_3 value: 24.237000000000002 - type: map_at_5 value: 25.811 - type: mrr_at_1 value: 20.887 - type: mrr_at_10 value: 28.660000000000004 - type: mrr_at_100 value: 29.660999999999998 - type: mrr_at_1000 value: 29.731 - type: mrr_at_3 value: 26.155 - type: mrr_at_5 value: 27.68 - type: ndcg_at_1 value: 20.887 - type: ndcg_at_10 value: 31.523 - type: ndcg_at_100 value: 37.055 - type: ndcg_at_1000 value: 39.579 - type: ndcg_at_3 value: 26.529000000000003 - type: ndcg_at_5 value: 29.137 - type: precision_at_1 value: 20.887 - type: precision_at_10 value: 5.065 - type: precision_at_100 value: 0.856 - type: precision_at_1000 value: 0.11900000000000001 - type: precision_at_3 value: 11.399 - type: precision_at_5 value: 8.392 - type: recall_at_1 value: 19.201999999999998 - type: recall_at_10 value: 44.285000000000004 - type: recall_at_100 value: 69.768 - type: recall_at_1000 value: 88.302 - type: recall_at_3 value: 30.804 - type: recall_at_5 value: 37.039 - task: type: Retrieval dataset: name: MTEB ClimateFEVER type: climate-fever config: default split: test revision: None metrics: - type: map_at_1 value: 11.244 - type: map_at_10 value: 18.956 - type: map_at_100 value: 20.674 - type: map_at_1000 value: 20.863 - type: map_at_3 value: 15.923000000000002 - type: map_at_5 value: 17.518 - type: mrr_at_1 value: 25.080999999999996 - type: mrr_at_10 value: 35.94 - type: mrr_at_100 value: 36.969 - type: mrr_at_1000 value: 37.013 - type: mrr_at_3 value: 32.617000000000004 - type: mrr_at_5 value: 34.682 - type: ndcg_at_1 value: 25.080999999999996 - type: ndcg_at_10 value: 26.539 - type: ndcg_at_100 value: 33.601 - type: ndcg_at_1000 value: 37.203 - type: ndcg_at_3 value: 21.695999999999998 - type: ndcg_at_5 value: 23.567 - type: precision_at_1 value: 25.080999999999996 - type: precision_at_10 value: 8.143 - type: precision_at_100 value: 1.5650000000000002 - type: precision_at_1000 value: 0.22300000000000003 - type: precision_at_3 value: 15.983 - type: precision_at_5 value: 12.417 - type: recall_at_1 value: 11.244 - type: recall_at_10 value: 31.457 - type: recall_at_100 value: 55.92 - type: recall_at_1000 value: 76.372 - type: recall_at_3 value: 19.784 - type: recall_at_5 value: 24.857000000000003 - task: type: Retrieval dataset: name: MTEB DBPedia type: dbpedia-entity config: default split: test revision: None metrics: - type: map_at_1 value: 8.595 - type: map_at_10 value: 18.75 - type: map_at_100 value: 26.354 - type: map_at_1000 value: 27.912 - type: map_at_3 value: 13.794 - type: map_at_5 value: 16.021 - type: mrr_at_1 value: 65.75 - type: mrr_at_10 value: 73.837 - type: mrr_at_100 value: 74.22800000000001 - type: mrr_at_1000 value: 74.234 - type: mrr_at_3 value: 72.5 - type: mrr_at_5 value: 73.387 - type: ndcg_at_1 value: 52.625 - type: ndcg_at_10 value: 39.101 - type: ndcg_at_100 value: 43.836000000000006 - type: ndcg_at_1000 value: 51.086 - type: ndcg_at_3 value: 44.229 - type: ndcg_at_5 value: 41.555 - type: precision_at_1 value: 65.75 - type: precision_at_10 value: 30.45 - type: precision_at_100 value: 9.81 - type: precision_at_1000 value: 2.045 - type: precision_at_3 value: 48.667 - type: precision_at_5 value: 40.8 - type: recall_at_1 value: 8.595 - type: recall_at_10 value: 24.201 - type: recall_at_100 value: 50.096 - type: recall_at_1000 value: 72.677 - type: recall_at_3 value: 15.212 - type: recall_at_5 value: 18.745 - task: type: Classification dataset: name: MTEB EmotionClassification type: mteb/emotion config: default split: test revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 metrics: - type: accuracy value: 46.565 - type: f1 value: 41.49914329345582 - task: type: Retrieval dataset: name: MTEB FEVER type: fever config: default split: test revision: None metrics: - type: map_at_1 value: 66.60000000000001 - type: map_at_10 value: 76.838 - type: map_at_100 value: 77.076 - type: map_at_1000 value: 77.09 - type: map_at_3 value: 75.545 - type: map_at_5 value: 76.39 - type: mrr_at_1 value: 71.707 - type: mrr_at_10 value: 81.514 - type: mrr_at_100 value: 81.64099999999999 - type: mrr_at_1000 value: 81.645 - type: mrr_at_3 value: 80.428 - type: mrr_at_5 value: 81.159 - type: ndcg_at_1 value: 71.707 - type: ndcg_at_10 value: 81.545 - type: ndcg_at_100 value: 82.477 - type: ndcg_at_1000 value: 82.73899999999999 - type: ndcg_at_3 value: 79.292 - type: ndcg_at_5 value: 80.599 - type: precision_at_1 value: 71.707 - type: precision_at_10 value: 10.035 - type: precision_at_100 value: 1.068 - type: precision_at_1000 value: 0.11100000000000002 - type: precision_at_3 value: 30.918 - type: precision_at_5 value: 19.328 - type: recall_at_1 value: 66.60000000000001 - type: recall_at_10 value: 91.353 - type: recall_at_100 value: 95.21 - type: recall_at_1000 value: 96.89999999999999 - type: recall_at_3 value: 85.188 - type: recall_at_5 value: 88.52 - task: type: Retrieval dataset: name: MTEB FiQA2018 type: fiqa config: default split: test revision: None metrics: - type: map_at_1 value: 19.338 - type: map_at_10 value: 31.752000000000002 - type: map_at_100 value: 33.516 - type: map_at_1000 value: 33.694 - type: map_at_3 value: 27.716 - type: map_at_5 value: 29.67 - type: mrr_at_1 value: 38.117000000000004 - type: mrr_at_10 value: 47.323 - type: mrr_at_100 value: 48.13 - type: mrr_at_1000 value: 48.161 - type: mrr_at_3 value: 45.062000000000005 - type: mrr_at_5 value: 46.358 - type: ndcg_at_1 value: 38.117000000000004 - type: ndcg_at_10 value: 39.353 - type: ndcg_at_100 value: 46.044000000000004 - type: ndcg_at_1000 value: 49.083 - type: ndcg_at_3 value: 35.891 - type: ndcg_at_5 value: 36.661 - type: precision_at_1 value: 38.117000000000004 - type: precision_at_10 value: 11.187999999999999 - type: precision_at_100 value: 1.802 - type: precision_at_1000 value: 0.234 - type: precision_at_3 value: 24.126 - type: precision_at_5 value: 17.562 - type: recall_at_1 value: 19.338 - type: recall_at_10 value: 45.735 - type: recall_at_100 value: 71.281 - type: recall_at_1000 value: 89.537 - type: recall_at_3 value: 32.525 - type: recall_at_5 value: 37.671 - task: type: Retrieval dataset: name: MTEB HotpotQA type: hotpotqa config: default split: test revision: None metrics: - type: map_at_1 value: 36.995 - type: map_at_10 value: 55.032000000000004 - type: map_at_100 value: 55.86 - type: map_at_1000 value: 55.932 - type: map_at_3 value: 52.125 - type: map_at_5 value: 53.884 - type: mrr_at_1 value: 73.991 - type: mrr_at_10 value: 80.096 - type: mrr_at_100 value: 80.32000000000001 - type: mrr_at_1000 value: 80.331 - type: mrr_at_3 value: 79.037 - type: mrr_at_5 value: 79.719 - type: ndcg_at_1 value: 73.991 - type: ndcg_at_10 value: 63.786 - type: ndcg_at_100 value: 66.78 - type: ndcg_at_1000 value: 68.255 - type: ndcg_at_3 value: 59.501000000000005 - type: ndcg_at_5 value: 61.82299999999999 - type: precision_at_1 value: 73.991 - type: precision_at_10 value: 13.157 - type: precision_at_100 value: 1.552 - type: precision_at_1000 value: 0.17500000000000002 - type: precision_at_3 value: 37.519999999999996 - type: precision_at_5 value: 24.351 - type: recall_at_1 value: 36.995 - type: recall_at_10 value: 65.78699999999999 - type: recall_at_100 value: 77.583 - type: recall_at_1000 value: 87.421 - type: recall_at_3 value: 56.279999999999994 - type: recall_at_5 value: 60.878 - task: type: Classification dataset: name: MTEB ImdbClassification type: mteb/imdb config: default split: test revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 metrics: - type: accuracy value: 86.80239999999999 - type: ap value: 81.97305141128378 - type: f1 value: 86.76976305549273 - task: type: Retrieval dataset: name: MTEB MSMARCO type: msmarco config: default split: dev revision: None metrics: - type: map_at_1 value: 21.166 - type: map_at_10 value: 33.396 - type: map_at_100 value: 34.588 - type: map_at_1000 value: 34.637 - type: map_at_3 value: 29.509999999999998 - type: map_at_5 value: 31.719 - type: mrr_at_1 value: 21.762 - type: mrr_at_10 value: 33.969 - type: mrr_at_100 value: 35.099000000000004 - type: mrr_at_1000 value: 35.141 - type: mrr_at_3 value: 30.148000000000003 - type: mrr_at_5 value: 32.324000000000005 - type: ndcg_at_1 value: 21.776999999999997 - type: ndcg_at_10 value: 40.306999999999995 - type: ndcg_at_100 value: 46.068 - type: ndcg_at_1000 value: 47.3 - type: ndcg_at_3 value: 32.416 - type: ndcg_at_5 value: 36.345 - type: precision_at_1 value: 21.776999999999997 - type: precision_at_10 value: 6.433 - type: precision_at_100 value: 0.932 - type: precision_at_1000 value: 0.104 - type: precision_at_3 value: 13.897 - type: precision_at_5 value: 10.324 - type: recall_at_1 value: 21.166 - type: recall_at_10 value: 61.587 - type: recall_at_100 value: 88.251 - type: recall_at_1000 value: 97.727 - type: recall_at_3 value: 40.196 - type: recall_at_5 value: 49.611 - task: type: Classification dataset: name: MTEB MTOPDomainClassification (en) type: mteb/mtop_domain config: en split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics: - type: accuracy value: 93.04605563155496 - type: f1 value: 92.78007303978372 - task: type: Classification dataset: name: MTEB MTOPIntentClassification (en) type: mteb/mtop_intent config: en split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics: - type: accuracy value: 69.65116279069767 - type: f1 value: 52.75775172527262 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (en) type: mteb/amazon_massive_intent config: en split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 70.34633490248822 - type: f1 value: 68.15345065392562 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (en) type: mteb/amazon_massive_scenario config: en split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 75.63887020847343 - type: f1 value: 76.08074680233685 - task: type: Clustering dataset: name: MTEB MedrxivClusteringP2P type: mteb/medrxiv-clustering-p2p config: default split: test revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 metrics: - type: v_measure value: 33.77933406071333 - task: type: Clustering dataset: name: MTEB MedrxivClusteringS2S type: mteb/medrxiv-clustering-s2s config: default split: test revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 metrics: - type: v_measure value: 32.06504927238196 - task: type: Reranking dataset: name: MTEB MindSmallReranking type: mteb/mind_small config: default split: test revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 metrics: - type: map value: 32.20682480490871 - type: mrr value: 33.41462721527003 - task: type: Retrieval dataset: name: MTEB NFCorpus type: nfcorpus config: default split: test revision: None metrics: - type: map_at_1 value: 5.548 - type: map_at_10 value: 13.086999999999998 - type: map_at_100 value: 16.698 - type: map_at_1000 value: 18.151999999999997 - type: map_at_3 value: 9.576 - type: map_at_5 value: 11.175 - type: mrr_at_1 value: 44.272 - type: mrr_at_10 value: 53.635999999999996 - type: mrr_at_100 value: 54.228 - type: mrr_at_1000 value: 54.26499999999999 - type: mrr_at_3 value: 51.754 - type: mrr_at_5 value: 53.086 - type: ndcg_at_1 value: 42.724000000000004 - type: ndcg_at_10 value: 34.769 - type: ndcg_at_100 value: 32.283 - type: ndcg_at_1000 value: 40.843 - type: ndcg_at_3 value: 39.852 - type: ndcg_at_5 value: 37.858999999999995 - type: precision_at_1 value: 44.272 - type: precision_at_10 value: 26.068 - type: precision_at_100 value: 8.328000000000001 - type: precision_at_1000 value: 2.1 - type: precision_at_3 value: 37.874 - type: precision_at_5 value: 33.065 - type: recall_at_1 value: 5.548 - type: recall_at_10 value: 16.936999999999998 - type: recall_at_100 value: 33.72 - type: recall_at_1000 value: 64.348 - type: recall_at_3 value: 10.764999999999999 - type: recall_at_5 value: 13.361 - task: type: Retrieval dataset: name: MTEB NQ type: nq config: default split: test revision: None metrics: - type: map_at_1 value: 28.008 - type: map_at_10 value: 42.675000000000004 - type: map_at_100 value: 43.85 - type: map_at_1000 value: 43.884 - type: map_at_3 value: 38.286 - type: map_at_5 value: 40.78 - type: mrr_at_1 value: 31.518 - type: mrr_at_10 value: 45.015 - type: mrr_at_100 value: 45.924 - type: mrr_at_1000 value: 45.946999999999996 - type: mrr_at_3 value: 41.348 - type: mrr_at_5 value: 43.428 - type: ndcg_at_1 value: 31.489 - type: ndcg_at_10 value: 50.285999999999994 - type: ndcg_at_100 value: 55.291999999999994 - type: ndcg_at_1000 value: 56.05 - type: ndcg_at_3 value: 41.976 - type: ndcg_at_5 value: 46.103 - type: precision_at_1 value: 31.489 - type: precision_at_10 value: 8.456 - type: precision_at_100 value: 1.125 - type: precision_at_1000 value: 0.12 - type: precision_at_3 value: 19.09 - type: precision_at_5 value: 13.841000000000001 - type: recall_at_1 value: 28.008 - type: recall_at_10 value: 71.21499999999999 - type: recall_at_100 value: 92.99 - type: recall_at_1000 value: 98.578 - type: recall_at_3 value: 49.604 - type: recall_at_5 value: 59.094 - task: type: Retrieval dataset: name: MTEB QuoraRetrieval type: quora config: default split: test revision: None metrics: - type: map_at_1 value: 70.351 - type: map_at_10 value: 84.163 - type: map_at_100 value: 84.785 - type: map_at_1000 value: 84.801 - type: map_at_3 value: 81.16 - type: map_at_5 value: 83.031 - type: mrr_at_1 value: 80.96 - type: mrr_at_10 value: 87.241 - type: mrr_at_100 value: 87.346 - type: mrr_at_1000 value: 87.347 - type: mrr_at_3 value: 86.25699999999999 - type: mrr_at_5 value: 86.907 - type: ndcg_at_1 value: 80.97 - type: ndcg_at_10 value: 88.017 - type: ndcg_at_100 value: 89.241 - type: ndcg_at_1000 value: 89.34299999999999 - type: ndcg_at_3 value: 85.053 - type: ndcg_at_5 value: 86.663 - type: precision_at_1 value: 80.97 - type: precision_at_10 value: 13.358 - type: precision_at_100 value: 1.525 - type: precision_at_1000 value: 0.157 - type: precision_at_3 value: 37.143 - type: precision_at_5 value: 24.451999999999998 - type: recall_at_1 value: 70.351 - type: recall_at_10 value: 95.39800000000001 - type: recall_at_100 value: 99.55199999999999 - type: recall_at_1000 value: 99.978 - type: recall_at_3 value: 86.913 - type: recall_at_5 value: 91.448 - task: type: Clustering dataset: name: MTEB RedditClustering type: mteb/reddit-clustering config: default split: test revision: 24640382cdbf8abc73003fb0fa6d111a705499eb metrics: - type: v_measure value: 55.62406719814139 - task: type: Clustering dataset: name: MTEB RedditClusteringP2P type: mteb/reddit-clustering-p2p config: default split: test revision: 282350215ef01743dc01b456c7f5241fa8937f16 metrics: - type: v_measure value: 61.386700035141736 - task: type: Retrieval dataset: name: MTEB SCIDOCS type: scidocs config: default split: test revision: None metrics: - type: map_at_1 value: 4.618 - type: map_at_10 value: 12.920000000000002 - type: map_at_100 value: 15.304 - type: map_at_1000 value: 15.656999999999998 - type: map_at_3 value: 9.187 - type: map_at_5 value: 10.937 - type: mrr_at_1 value: 22.8 - type: mrr_at_10 value: 35.13 - type: mrr_at_100 value: 36.239 - type: mrr_at_1000 value: 36.291000000000004 - type: mrr_at_3 value: 31.917 - type: mrr_at_5 value: 33.787 - type: ndcg_at_1 value: 22.8 - type: ndcg_at_10 value: 21.382 - type: ndcg_at_100 value: 30.257 - type: ndcg_at_1000 value: 36.001 - type: ndcg_at_3 value: 20.43 - type: ndcg_at_5 value: 17.622 - type: precision_at_1 value: 22.8 - type: precision_at_10 value: 11.26 - type: precision_at_100 value: 2.405 - type: precision_at_1000 value: 0.377 - type: precision_at_3 value: 19.633 - type: precision_at_5 value: 15.68 - type: recall_at_1 value: 4.618 - type: recall_at_10 value: 22.811999999999998 - type: recall_at_100 value: 48.787000000000006 - type: recall_at_1000 value: 76.63799999999999 - type: recall_at_3 value: 11.952 - type: recall_at_5 value: 15.892000000000001 - task: type: STS dataset: name: MTEB SICK-R type: mteb/sickr-sts config: default split: test revision: a6ea5a8cab320b040a23452cc28066d9beae2cee metrics: - type: cos_sim_pearson value: 84.01529458252244 - type: cos_sim_spearman value: 77.92985224770254 - type: euclidean_pearson value: 81.04251429422487 - type: euclidean_spearman value: 77.92838490549133 - type: manhattan_pearson value: 80.95892251458979 - type: manhattan_spearman value: 77.81028089705941 - task: type: STS dataset: name: MTEB STS12 type: mteb/sts12-sts config: default split: test revision: a0d554a64d88156834ff5ae9920b964011b16384 metrics: - type: cos_sim_pearson value: 83.97885282534388 - type: cos_sim_spearman value: 75.1221970851712 - type: euclidean_pearson value: 80.34455956720097 - type: euclidean_spearman value: 74.5894274239938 - type: manhattan_pearson value: 80.38999766325465 - type: manhattan_spearman value: 74.68524557166975 - task: type: STS dataset: name: MTEB STS13 type: mteb/sts13-sts config: default split: test revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca metrics: - type: cos_sim_pearson value: 82.95746064915672 - type: cos_sim_spearman value: 85.08683458043946 - type: euclidean_pearson value: 84.56699492836385 - type: euclidean_spearman value: 85.66089116133713 - type: manhattan_pearson value: 84.47553323458541 - type: manhattan_spearman value: 85.56142206781472 - task: type: STS dataset: name: MTEB STS14 type: mteb/sts14-sts config: default split: test revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 metrics: - type: cos_sim_pearson value: 82.71377893595067 - type: cos_sim_spearman value: 81.03453291428589 - type: euclidean_pearson value: 82.57136298308613 - type: euclidean_spearman value: 81.15839961890875 - type: manhattan_pearson value: 82.55157879373837 - type: manhattan_spearman value: 81.1540163767054 - task: type: STS dataset: name: MTEB STS15 type: mteb/sts15-sts config: default split: test revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 metrics: - type: cos_sim_pearson value: 86.64197832372373 - type: cos_sim_spearman value: 88.31966852492485 - type: euclidean_pearson value: 87.98692129976983 - type: euclidean_spearman value: 88.6247340837856 - type: manhattan_pearson value: 87.90437827826412 - type: manhattan_spearman value: 88.56278787131457 - task: type: STS dataset: name: MTEB STS16 type: mteb/sts16-sts config: default split: test revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 metrics: - type: cos_sim_pearson value: 81.84159950146693 - type: cos_sim_spearman value: 83.90678384140168 - type: euclidean_pearson value: 83.19005018860221 - type: euclidean_spearman value: 84.16260415876295 - type: manhattan_pearson value: 83.05030612994494 - type: manhattan_spearman value: 83.99605629718336 - task: type: STS dataset: name: MTEB STS17 (en-en) type: mteb/sts17-crosslingual-sts config: en-en split: test revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics: - type: cos_sim_pearson value: 87.49935350176666 - type: cos_sim_spearman value: 87.59086606735383 - type: euclidean_pearson value: 88.06537181129983 - type: euclidean_spearman value: 87.6687448086014 - type: manhattan_pearson value: 87.96599131972935 - type: manhattan_spearman value: 87.63295748969642 - task: type: STS dataset: name: MTEB STS22 (en) type: mteb/sts22-crosslingual-sts config: en split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics: - type: cos_sim_pearson value: 67.68232799482763 - type: cos_sim_spearman value: 67.99930378085793 - type: euclidean_pearson value: 68.50275360001696 - type: euclidean_spearman value: 67.81588179309259 - type: manhattan_pearson value: 68.5892154749763 - type: manhattan_spearman value: 67.84357259640682 - task: type: STS dataset: name: MTEB STSBenchmark type: mteb/stsbenchmark-sts config: default split: test revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 metrics: - type: cos_sim_pearson value: 84.37049618406554 - type: cos_sim_spearman value: 85.57014313159492 - type: euclidean_pearson value: 85.57469513908282 - type: euclidean_spearman value: 85.661948135258 - type: manhattan_pearson value: 85.36866831229028 - type: manhattan_spearman value: 85.5043455368843 - task: type: Reranking dataset: name: MTEB SciDocsRR type: mteb/scidocs-reranking config: default split: test revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab metrics: - type: map value: 84.83259065376154 - type: mrr value: 95.58455433455433 - task: type: Retrieval dataset: name: MTEB SciFact type: scifact config: default split: test revision: None metrics: - type: map_at_1 value: 58.817 - type: map_at_10 value: 68.459 - type: map_at_100 value: 68.951 - type: map_at_1000 value: 68.979 - type: map_at_3 value: 65.791 - type: map_at_5 value: 67.583 - type: mrr_at_1 value: 61.667 - type: mrr_at_10 value: 69.368 - type: mrr_at_100 value: 69.721 - type: mrr_at_1000 value: 69.744 - type: mrr_at_3 value: 67.278 - type: mrr_at_5 value: 68.611 - type: ndcg_at_1 value: 61.667 - type: ndcg_at_10 value: 72.70100000000001 - type: ndcg_at_100 value: 74.928 - type: ndcg_at_1000 value: 75.553 - type: ndcg_at_3 value: 68.203 - type: ndcg_at_5 value: 70.804 - type: precision_at_1 value: 61.667 - type: precision_at_10 value: 9.533 - type: precision_at_100 value: 1.077 - type: precision_at_1000 value: 0.11299999999999999 - type: precision_at_3 value: 26.444000000000003 - type: precision_at_5 value: 17.599999999999998 - type: recall_at_1 value: 58.817 - type: recall_at_10 value: 84.789 - type: recall_at_100 value: 95.0 - type: recall_at_1000 value: 99.667 - type: recall_at_3 value: 72.8 - type: recall_at_5 value: 79.294 - task: type: PairClassification dataset: name: MTEB SprintDuplicateQuestions type: mteb/sprintduplicatequestions-pairclassification config: default split: test revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 metrics: - type: cos_sim_accuracy value: 99.8108910891089 - type: cos_sim_ap value: 95.5743678558349 - type: cos_sim_f1 value: 90.43133366385722 - type: cos_sim_precision value: 89.67551622418878 - type: cos_sim_recall value: 91.2 - type: dot_accuracy value: 99.75841584158415 - type: dot_ap value: 94.00786363627253 - type: dot_f1 value: 87.51910341314316 - type: dot_precision value: 89.20041536863967 - type: dot_recall value: 85.9 - type: euclidean_accuracy value: 99.81485148514851 - type: euclidean_ap value: 95.4752113136905 - type: euclidean_f1 value: 90.44334975369456 - type: euclidean_precision value: 89.126213592233 - type: euclidean_recall value: 91.8 - type: manhattan_accuracy value: 99.81584158415842 - type: manhattan_ap value: 95.5163172682464 - type: manhattan_f1 value: 90.51987767584097 - type: manhattan_precision value: 92.3076923076923 - type: manhattan_recall value: 88.8 - type: max_accuracy value: 99.81584158415842 - type: max_ap value: 95.5743678558349 - type: max_f1 value: 90.51987767584097 - task: type: Clustering dataset: name: MTEB StackExchangeClustering type: mteb/stackexchange-clustering config: default split: test revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 metrics: - type: v_measure value: 62.63235986949449 - task: type: Clustering dataset: name: MTEB StackExchangeClusteringP2P type: mteb/stackexchange-clustering-p2p config: default split: test revision: 815ca46b2622cec33ccafc3735d572c266efdb44 metrics: - type: v_measure value: 36.334795589585575 - task: type: Reranking dataset: name: MTEB StackOverflowDupQuestions type: mteb/stackoverflowdupquestions-reranking config: default split: test revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 metrics: - type: map value: 52.02955214518782 - type: mrr value: 52.8004838298956 - task: type: Summarization dataset: name: MTEB SummEval type: mteb/summeval config: default split: test revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c metrics: - type: cos_sim_pearson value: 30.63769566275453 - type: cos_sim_spearman value: 30.422379185989335 - type: dot_pearson value: 26.88493071882256 - type: dot_spearman value: 26.505249740971305 - task: type: Retrieval dataset: name: MTEB TRECCOVID type: trec-covid config: default split: test revision: None metrics: - type: map_at_1 value: 0.21 - type: map_at_10 value: 1.654 - type: map_at_100 value: 10.095 - type: map_at_1000 value: 25.808999999999997 - type: map_at_3 value: 0.594 - type: map_at_5 value: 0.9289999999999999 - type: mrr_at_1 value: 78.0 - type: mrr_at_10 value: 87.019 - type: mrr_at_100 value: 87.019 - type: mrr_at_1000 value: 87.019 - type: mrr_at_3 value: 86.333 - type: mrr_at_5 value: 86.733 - type: ndcg_at_1 value: 73.0 - type: ndcg_at_10 value: 66.52900000000001 - type: ndcg_at_100 value: 53.433 - type: ndcg_at_1000 value: 51.324000000000005 - type: ndcg_at_3 value: 72.02199999999999 - type: ndcg_at_5 value: 69.696 - type: precision_at_1 value: 78.0 - type: precision_at_10 value: 70.39999999999999 - type: precision_at_100 value: 55.46 - type: precision_at_1000 value: 22.758 - type: precision_at_3 value: 76.667 - type: precision_at_5 value: 74.0 - type: recall_at_1 value: 0.21 - type: recall_at_10 value: 1.8849999999999998 - type: recall_at_100 value: 13.801 - type: recall_at_1000 value: 49.649 - type: recall_at_3 value: 0.632 - type: recall_at_5 value: 1.009 - task: type: Retrieval dataset: name: MTEB Touche2020 type: webis-touche2020 config: default split: test revision: None metrics: - type: map_at_1 value: 1.797 - type: map_at_10 value: 9.01 - type: map_at_100 value: 14.682 - type: map_at_1000 value: 16.336000000000002 - type: map_at_3 value: 4.546 - type: map_at_5 value: 5.9270000000000005 - type: mrr_at_1 value: 24.490000000000002 - type: mrr_at_10 value: 41.156 - type: mrr_at_100 value: 42.392 - type: mrr_at_1000 value: 42.408 - type: mrr_at_3 value: 38.775999999999996 - type: mrr_at_5 value: 40.102 - type: ndcg_at_1 value: 21.429000000000002 - type: ndcg_at_10 value: 22.222 - type: ndcg_at_100 value: 34.405 - type: ndcg_at_1000 value: 46.599000000000004 - type: ndcg_at_3 value: 25.261 - type: ndcg_at_5 value: 22.695999999999998 - type: precision_at_1 value: 24.490000000000002 - type: precision_at_10 value: 19.796 - type: precision_at_100 value: 7.306 - type: precision_at_1000 value: 1.5350000000000001 - type: precision_at_3 value: 27.211000000000002 - type: precision_at_5 value: 22.857 - type: recall_at_1 value: 1.797 - type: recall_at_10 value: 15.706000000000001 - type: recall_at_100 value: 46.412 - type: recall_at_1000 value: 83.159 - type: recall_at_3 value: 6.1370000000000005 - type: recall_at_5 value: 8.599 - task: type: Classification dataset: name: MTEB ToxicConversationsClassification type: mteb/toxic_conversations_50k config: default split: test revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c metrics: - type: accuracy value: 70.3302 - type: ap value: 14.169121204575601 - type: f1 value: 54.229345975274235 - task: type: Classification dataset: name: MTEB TweetSentimentExtractionClassification type: mteb/tweet_sentiment_extraction config: default split: test revision: d604517c81ca91fe16a244d1248fc021f9ecee7a metrics: - type: accuracy value: 58.22297679683077 - type: f1 value: 58.62984908377875 - task: type: Clustering dataset: name: MTEB TwentyNewsgroupsClustering type: mteb/twentynewsgroups-clustering config: default split: test revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 metrics: - type: v_measure value: 49.952922428464255 - task: type: PairClassification dataset: name: MTEB TwitterSemEval2015 type: mteb/twittersemeval2015-pairclassification config: default split: test revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 metrics: - type: cos_sim_accuracy value: 84.68140907194373 - type: cos_sim_ap value: 70.12180123666836 - type: cos_sim_f1 value: 65.77501791258658 - type: cos_sim_precision value: 60.07853403141361 - type: cos_sim_recall value: 72.66490765171504 - type: dot_accuracy value: 81.92167848840674 - type: dot_ap value: 60.49837581423469 - type: dot_f1 value: 58.44186046511628 - type: dot_precision value: 52.24532224532224 - type: dot_recall value: 66.3060686015831 - type: euclidean_accuracy value: 84.73505394289802 - type: euclidean_ap value: 70.3278904593286 - type: euclidean_f1 value: 65.98851124940161 - type: euclidean_precision value: 60.38107752956636 - type: euclidean_recall value: 72.74406332453826 - type: manhattan_accuracy value: 84.73505394289802 - type: manhattan_ap value: 70.00737738537337 - type: manhattan_f1 value: 65.80150784822642 - type: manhattan_precision value: 61.892583120204606 - type: manhattan_recall value: 70.23746701846966 - type: max_accuracy value: 84.73505394289802 - type: max_ap value: 70.3278904593286 - type: max_f1 value: 65.98851124940161 - task: type: PairClassification dataset: name: MTEB TwitterURLCorpus type: mteb/twitterurlcorpus-pairclassification config: default split: test revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf metrics: - type: cos_sim_accuracy value: 88.44258159661582 - type: cos_sim_ap value: 84.91926704880888 - type: cos_sim_f1 value: 77.07651086632926 - type: cos_sim_precision value: 74.5894554883319 - type: cos_sim_recall value: 79.73514012935017 - type: dot_accuracy value: 85.88116583226608 - type: dot_ap value: 78.9753854779923 - type: dot_f1 value: 72.17757637979255 - type: dot_precision value: 66.80647486729143 - type: dot_recall value: 78.48783492454572 - type: euclidean_accuracy value: 88.5299025885823 - type: euclidean_ap value: 85.08006075642194 - type: euclidean_f1 value: 77.29637336504163 - type: euclidean_precision value: 74.69836253950014 - type: euclidean_recall value: 80.08161379735141 - type: manhattan_accuracy value: 88.55124771995187 - type: manhattan_ap value: 85.00941529932851 - type: manhattan_f1 value: 77.33100233100232 - type: manhattan_precision value: 73.37572573956317 - type: manhattan_recall value: 81.73698798891284 - type: max_accuracy value: 88.55124771995187 - type: max_ap value: 85.08006075642194 - type: max_f1 value: 77.33100233100232 --- # ggml-org/gte-small-Q8_0-GGUF This model was converted to GGUF format from [`thenlper/gte-small`](https://huggingface.co/thenlper/gte-small) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space. Refer to the [original model card](https://huggingface.co/thenlper/gte-small) for more details on the model. ## Use with llama.cpp Install llama.cpp through brew (works on Mac and Linux) ```bash brew install llama.cpp ``` Invoke the llama.cpp server or the CLI. ### CLI: ```bash llama-cli --hf-repo ggml-org/gte-small-Q8_0-GGUF --hf-file gte-small-q8_0.gguf -p "The meaning to life and the universe is" ``` ### Server: ```bash llama-server --hf-repo ggml-org/gte-small-Q8_0-GGUF --hf-file gte-small-q8_0.gguf -c 2048 ``` Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well. Step 1: Clone llama.cpp from GitHub. ``` git clone https://github.com/ggerganov/llama.cpp ``` Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux). ``` cd llama.cpp && LLAMA_CURL=1 make ``` Step 3: Run inference through the main binary. ``` ./llama-cli --hf-repo ggml-org/gte-small-Q8_0-GGUF --hf-file gte-small-q8_0.gguf -p "The meaning to life and the universe is" ``` or ``` ./llama-server --hf-repo ggml-org/gte-small-Q8_0-GGUF --hf-file gte-small-q8_0.gguf -c 2048 ```