--- tags: - mteb - sentence-transformers - transformers - Qwen - sentence-similarity - llama-cpp - gguf-my-repo model-index: - name: gte-qwen1.5-7b results: - task: type: Classification dataset: name: MTEB AmazonCounterfactualClassification (en) type: mteb/amazon_counterfactual config: en split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics: - type: accuracy value: 83.16417910447761 - type: ap value: 49.37655308937739 - type: f1 value: 77.52987230462615 - task: type: Classification dataset: name: MTEB AmazonPolarityClassification type: mteb/amazon_polarity config: default split: test revision: e2d317d38cd51312af73b3d32a06d1a08b442046 metrics: - type: accuracy value: 96.6959 - type: ap value: 94.90885739242472 - type: f1 value: 96.69477648952649 - task: type: Classification dataset: name: MTEB AmazonReviewsClassification (en) type: mteb/amazon_reviews_multi config: en split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics: - type: accuracy value: 62.168 - type: f1 value: 60.411431278343755 - task: type: Retrieval dataset: name: MTEB ArguAna type: mteb/arguana config: default split: test revision: c22ab2a51041ffd869aaddef7af8d8215647e41a metrics: - type: map_at_1 value: 36.415 - type: map_at_10 value: 53.505 - type: map_at_100 value: 54.013 - type: map_at_1000 value: 54.013 - type: map_at_3 value: 48.459 - type: map_at_5 value: 51.524 - type: mrr_at_1 value: 36.842000000000006 - type: mrr_at_10 value: 53.679 - type: mrr_at_100 value: 54.17999999999999 - type: mrr_at_1000 value: 54.17999999999999 - type: mrr_at_3 value: 48.613 - type: mrr_at_5 value: 51.696 - type: ndcg_at_1 value: 36.415 - type: ndcg_at_10 value: 62.644999999999996 - type: ndcg_at_100 value: 64.60000000000001 - type: ndcg_at_1000 value: 64.60000000000001 - type: ndcg_at_3 value: 52.44799999999999 - type: ndcg_at_5 value: 57.964000000000006 - type: precision_at_1 value: 36.415 - type: precision_at_10 value: 9.161 - type: precision_at_100 value: 0.996 - type: precision_at_1000 value: 0.1 - type: precision_at_3 value: 21.337 - type: precision_at_5 value: 15.476999999999999 - type: recall_at_1 value: 36.415 - type: recall_at_10 value: 91.607 - type: recall_at_100 value: 99.644 - type: recall_at_1000 value: 99.644 - type: recall_at_3 value: 64.011 - type: recall_at_5 value: 77.383 - task: type: Clustering dataset: name: MTEB ArxivClusteringP2P type: mteb/arxiv-clustering-p2p config: default split: test revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d metrics: - type: v_measure value: 56.40183100758549 - task: type: Clustering dataset: name: MTEB ArxivClusteringS2S type: mteb/arxiv-clustering-s2s config: default split: test revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 metrics: - type: v_measure value: 51.44814171373338 - task: type: Reranking dataset: name: MTEB AskUbuntuDupQuestions type: mteb/askubuntudupquestions-reranking config: default split: test revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 metrics: - type: map value: 66.00208703259058 - type: mrr value: 78.95165545442553 - task: type: STS dataset: name: MTEB BIOSSES type: mteb/biosses-sts config: default split: test revision: d3fb88f8f02e40887cd149695127462bbcf29b4a metrics: - type: cos_sim_pearson value: 82.12591694410098 - type: cos_sim_spearman value: 81.11570369802254 - type: euclidean_pearson value: 80.91709076204458 - type: euclidean_spearman value: 81.11570369802254 - type: manhattan_pearson value: 80.71719561024605 - type: manhattan_spearman value: 81.21510355327713 - task: type: Classification dataset: name: MTEB Banking77Classification type: mteb/banking77 config: default split: test revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 metrics: - type: accuracy value: 81.67857142857142 - type: f1 value: 80.84103272994895 - task: type: Clustering dataset: name: MTEB BiorxivClusteringP2P type: mteb/biorxiv-clustering-p2p config: default split: test revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 metrics: - type: v_measure value: 49.008657468552016 - task: type: Clustering dataset: name: MTEB BiorxivClusteringS2S type: mteb/biorxiv-clustering-s2s config: default split: test revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 metrics: - type: v_measure value: 45.05901064421589 - task: type: Retrieval dataset: name: MTEB CQADupstackAndroidRetrieval type: BeIR/cqadupstack config: default split: test revision: f46a197baaae43b4f621051089b82a364682dfeb metrics: - type: map_at_1 value: 32.694 - type: map_at_10 value: 43.895 - type: map_at_100 value: 45.797 - type: map_at_1000 value: 45.922000000000004 - type: map_at_3 value: 40.141 - type: map_at_5 value: 42.077 - type: mrr_at_1 value: 40.2 - type: mrr_at_10 value: 50.11 - type: mrr_at_100 value: 51.101 - type: mrr_at_1000 value: 51.13100000000001 - type: mrr_at_3 value: 47.735 - type: mrr_at_5 value: 48.922 - type: ndcg_at_1 value: 40.2 - type: ndcg_at_10 value: 50.449999999999996 - type: ndcg_at_100 value: 56.85 - type: ndcg_at_1000 value: 58.345 - type: ndcg_at_3 value: 45.261 - type: ndcg_at_5 value: 47.298 - type: precision_at_1 value: 40.2 - type: precision_at_10 value: 9.742 - type: precision_at_100 value: 1.6480000000000001 - type: precision_at_1000 value: 0.214 - type: precision_at_3 value: 21.841 - type: precision_at_5 value: 15.68 - type: recall_at_1 value: 32.694 - type: recall_at_10 value: 62.751999999999995 - type: recall_at_100 value: 88.619 - type: recall_at_1000 value: 97.386 - type: recall_at_3 value: 47.087 - type: recall_at_5 value: 53.108999999999995 - task: type: Retrieval dataset: name: MTEB CQADupstackEnglishRetrieval type: BeIR/cqadupstack config: default split: test revision: ad9991cb51e31e31e430383c75ffb2885547b5f0 metrics: - type: map_at_1 value: 27.849 - type: map_at_10 value: 37.938 - type: map_at_100 value: 39.211 - type: map_at_1000 value: 39.333 - type: map_at_3 value: 35.314 - type: map_at_5 value: 36.666 - type: mrr_at_1 value: 34.904 - type: mrr_at_10 value: 43.869 - type: mrr_at_100 value: 44.614 - type: mrr_at_1000 value: 44.662 - type: mrr_at_3 value: 41.815000000000005 - type: mrr_at_5 value: 42.943 - type: ndcg_at_1 value: 34.904 - type: ndcg_at_10 value: 43.605 - type: ndcg_at_100 value: 48.339999999999996 - type: ndcg_at_1000 value: 50.470000000000006 - type: ndcg_at_3 value: 39.835 - type: ndcg_at_5 value: 41.364000000000004 - type: precision_at_1 value: 34.904 - type: precision_at_10 value: 8.222999999999999 - type: precision_at_100 value: 1.332 - type: precision_at_1000 value: 0.183 - type: precision_at_3 value: 19.575 - type: precision_at_5 value: 13.58 - type: recall_at_1 value: 27.849 - type: recall_at_10 value: 53.635 - type: recall_at_100 value: 73.932 - type: recall_at_1000 value: 87.29599999999999 - type: recall_at_3 value: 42.019 - type: recall_at_5 value: 46.58 - task: type: Retrieval dataset: name: MTEB CQADupstackGamingRetrieval type: BeIR/cqadupstack config: default split: test revision: 4885aa143210c98657558c04aaf3dc47cfb54340 metrics: - type: map_at_1 value: 29.182999999999996 - type: map_at_10 value: 41.233 - type: map_at_100 value: 42.52 - type: map_at_1000 value: 42.589 - type: map_at_3 value: 37.284 - type: map_at_5 value: 39.586 - type: mrr_at_1 value: 33.793 - type: mrr_at_10 value: 44.572 - type: mrr_at_100 value: 45.456 - type: mrr_at_1000 value: 45.497 - type: mrr_at_3 value: 41.275 - type: mrr_at_5 value: 43.278 - type: ndcg_at_1 value: 33.793 - type: ndcg_at_10 value: 47.823 - type: ndcg_at_100 value: 52.994 - type: ndcg_at_1000 value: 54.400000000000006 - type: ndcg_at_3 value: 40.82 - type: ndcg_at_5 value: 44.426 - type: precision_at_1 value: 33.793 - type: precision_at_10 value: 8.312999999999999 - type: precision_at_100 value: 1.191 - type: precision_at_1000 value: 0.136 - type: precision_at_3 value: 18.662 - type: precision_at_5 value: 13.668 - type: recall_at_1 value: 29.182999999999996 - type: recall_at_10 value: 64.14999999999999 - type: recall_at_100 value: 86.533 - type: recall_at_1000 value: 96.492 - type: recall_at_3 value: 45.7 - type: recall_at_5 value: 54.330999999999996 - task: type: Retrieval dataset: name: MTEB CQADupstackGisRetrieval type: BeIR/cqadupstack config: default split: test revision: 5003b3064772da1887988e05400cf3806fe491f2 metrics: - type: map_at_1 value: 24.389 - type: map_at_10 value: 33.858 - type: map_at_100 value: 35.081 - type: map_at_1000 value: 35.161 - type: map_at_3 value: 30.793 - type: map_at_5 value: 32.336 - type: mrr_at_1 value: 27.006000000000004 - type: mrr_at_10 value: 36.378 - type: mrr_at_100 value: 37.345 - type: mrr_at_1000 value: 37.405 - type: mrr_at_3 value: 33.578 - type: mrr_at_5 value: 34.991 - type: ndcg_at_1 value: 27.006000000000004 - type: ndcg_at_10 value: 39.612 - type: ndcg_at_100 value: 45.216 - type: ndcg_at_1000 value: 47.12 - type: ndcg_at_3 value: 33.566 - type: ndcg_at_5 value: 36.105 - type: precision_at_1 value: 27.006000000000004 - type: precision_at_10 value: 6.372999999999999 - type: precision_at_100 value: 0.968 - type: precision_at_1000 value: 0.11800000000000001 - type: precision_at_3 value: 14.501 - type: precision_at_5 value: 10.169 - type: recall_at_1 value: 24.389 - type: recall_at_10 value: 55.131 - type: recall_at_100 value: 80.315 - type: recall_at_1000 value: 94.284 - type: recall_at_3 value: 38.643 - type: recall_at_5 value: 44.725 - task: type: Retrieval dataset: name: MTEB CQADupstackMathematicaRetrieval type: BeIR/cqadupstack config: default split: test revision: 90fceea13679c63fe563ded68f3b6f06e50061de metrics: - type: map_at_1 value: 15.845999999999998 - type: map_at_10 value: 25.019000000000002 - type: map_at_100 value: 26.478 - type: map_at_1000 value: 26.598 - type: map_at_3 value: 21.595 - type: map_at_5 value: 23.335 - type: mrr_at_1 value: 20.274 - type: mrr_at_10 value: 29.221000000000004 - type: mrr_at_100 value: 30.354999999999997 - type: mrr_at_1000 value: 30.419 - type: mrr_at_3 value: 26.161 - type: mrr_at_5 value: 27.61 - type: ndcg_at_1 value: 20.274 - type: ndcg_at_10 value: 31.014000000000003 - type: ndcg_at_100 value: 37.699 - type: ndcg_at_1000 value: 40.363 - type: ndcg_at_3 value: 24.701999999999998 - type: ndcg_at_5 value: 27.261999999999997 - type: precision_at_1 value: 20.274 - type: precision_at_10 value: 6.219 - type: precision_at_100 value: 1.101 - type: precision_at_1000 value: 0.146 - type: precision_at_3 value: 12.231 - type: precision_at_5 value: 9.129 - type: recall_at_1 value: 15.845999999999998 - type: recall_at_10 value: 45.358 - type: recall_at_100 value: 74.232 - type: recall_at_1000 value: 92.985 - type: recall_at_3 value: 28.050000000000004 - type: recall_at_5 value: 34.588 - task: type: Retrieval dataset: name: MTEB CQADupstackPhysicsRetrieval type: BeIR/cqadupstack config: default split: test revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4 metrics: - type: map_at_1 value: 33.808 - type: map_at_10 value: 46.86 - type: map_at_100 value: 48.237 - type: map_at_1000 value: 48.331 - type: map_at_3 value: 42.784 - type: map_at_5 value: 45.015 - type: mrr_at_1 value: 41.771 - type: mrr_at_10 value: 52.35300000000001 - type: mrr_at_100 value: 53.102000000000004 - type: mrr_at_1000 value: 53.132999999999996 - type: mrr_at_3 value: 49.663000000000004 - type: mrr_at_5 value: 51.27 - type: ndcg_at_1 value: 41.771 - type: ndcg_at_10 value: 53.562 - type: ndcg_at_100 value: 58.809999999999995 - type: ndcg_at_1000 value: 60.23 - type: ndcg_at_3 value: 47.514 - type: ndcg_at_5 value: 50.358999999999995 - type: precision_at_1 value: 41.771 - type: precision_at_10 value: 10.038 - type: precision_at_100 value: 1.473 - type: precision_at_1000 value: 0.17600000000000002 - type: precision_at_3 value: 22.875 - type: precision_at_5 value: 16.477 - type: recall_at_1 value: 33.808 - type: recall_at_10 value: 67.721 - type: recall_at_100 value: 89.261 - type: recall_at_1000 value: 98.042 - type: recall_at_3 value: 50.807 - type: recall_at_5 value: 58.162000000000006 - task: type: Retrieval dataset: name: MTEB CQADupstackProgrammersRetrieval type: BeIR/cqadupstack config: default split: test revision: 6184bc1440d2dbc7612be22b50686b8826d22b32 metrics: - type: map_at_1 value: 28.105000000000004 - type: map_at_10 value: 40.354 - type: map_at_100 value: 41.921 - type: map_at_1000 value: 42.021 - type: map_at_3 value: 36.532 - type: map_at_5 value: 38.671 - type: mrr_at_1 value: 34.475 - type: mrr_at_10 value: 45.342 - type: mrr_at_100 value: 46.300000000000004 - type: mrr_at_1000 value: 46.343 - type: mrr_at_3 value: 42.637 - type: mrr_at_5 value: 44.207 - type: ndcg_at_1 value: 34.475 - type: ndcg_at_10 value: 46.945 - type: ndcg_at_100 value: 52.939 - type: ndcg_at_1000 value: 54.645999999999994 - type: ndcg_at_3 value: 41.065000000000005 - type: ndcg_at_5 value: 43.832 - type: precision_at_1 value: 34.475 - type: precision_at_10 value: 8.892999999999999 - type: precision_at_100 value: 1.377 - type: precision_at_1000 value: 0.17099999999999999 - type: precision_at_3 value: 20.091 - type: precision_at_5 value: 14.452000000000002 - type: recall_at_1 value: 28.105000000000004 - type: recall_at_10 value: 61.253 - type: recall_at_100 value: 85.92 - type: recall_at_1000 value: 96.799 - type: recall_at_3 value: 45.094 - type: recall_at_5 value: 52.455 - task: type: Retrieval dataset: name: MTEB CQADupstackRetrieval type: BeIR/cqadupstack config: default split: test revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4 metrics: - type: map_at_1 value: 24.613833333333332 - type: map_at_10 value: 34.763 - type: map_at_100 value: 36.17066666666667 - type: map_at_1000 value: 36.2905 - type: map_at_3 value: 31.53541666666666 - type: map_at_5 value: 33.29216666666667 - type: mrr_at_1 value: 29.48725 - type: mrr_at_10 value: 38.92066666666667 - type: mrr_at_100 value: 39.88725000000001 - type: mrr_at_1000 value: 39.9435 - type: mrr_at_3 value: 36.284083333333335 - type: mrr_at_5 value: 37.73941666666667 - type: ndcg_at_1 value: 29.48725 - type: ndcg_at_10 value: 40.635083333333334 - type: ndcg_at_100 value: 46.479416666666665 - type: ndcg_at_1000 value: 48.63308333333334 - type: ndcg_at_3 value: 35.19483333333333 - type: ndcg_at_5 value: 37.68016666666667 - type: precision_at_1 value: 29.48725 - type: precision_at_10 value: 7.406499999999998 - type: precision_at_100 value: 1.2225833333333334 - type: precision_at_1000 value: 0.16108333333333336 - type: precision_at_3 value: 16.53375 - type: precision_at_5 value: 11.919416666666665 - type: recall_at_1 value: 24.613833333333332 - type: recall_at_10 value: 53.91766666666666 - type: recall_at_100 value: 79.18 - type: recall_at_1000 value: 93.85133333333333 - type: recall_at_3 value: 38.866166666666665 - type: recall_at_5 value: 45.21275000000001 - type: map_at_1 value: 12.328999999999999 - type: map_at_10 value: 20.078 - type: map_at_100 value: 21.166999999999998 - type: map_at_1000 value: 21.308 - type: map_at_3 value: 17.702 - type: map_at_5 value: 18.725 - type: mrr_at_1 value: 13.678 - type: mrr_at_10 value: 21.859 - type: mrr_at_100 value: 22.816 - type: mrr_at_1000 value: 22.926 - type: mrr_at_3 value: 19.378 - type: mrr_at_5 value: 20.385 - type: ndcg_at_1 value: 13.678 - type: ndcg_at_10 value: 24.993000000000002 - type: ndcg_at_100 value: 30.464999999999996 - type: ndcg_at_1000 value: 33.916000000000004 - type: ndcg_at_3 value: 19.966 - type: ndcg_at_5 value: 21.712999999999997 - type: precision_at_1 value: 13.678 - type: precision_at_10 value: 4.473 - type: precision_at_100 value: 0.784 - type: precision_at_1000 value: 0.116 - type: precision_at_3 value: 9.181000000000001 - type: precision_at_5 value: 6.506 - type: recall_at_1 value: 12.328999999999999 - type: recall_at_10 value: 38.592 - type: recall_at_100 value: 63.817 - type: recall_at_1000 value: 89.67500000000001 - type: recall_at_3 value: 24.726 - type: recall_at_5 value: 28.959000000000003 - task: type: Retrieval dataset: name: MTEB CQADupstackStatsRetrieval type: BeIR/cqadupstack config: default split: test revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a metrics: - type: map_at_1 value: 25.106 - type: map_at_10 value: 33.367999999999995 - type: map_at_100 value: 34.586 - type: map_at_1000 value: 34.681 - type: map_at_3 value: 31.022 - type: map_at_5 value: 32.548 - type: mrr_at_1 value: 28.374 - type: mrr_at_10 value: 36.521 - type: mrr_at_100 value: 37.55 - type: mrr_at_1000 value: 37.614999999999995 - type: mrr_at_3 value: 34.509 - type: mrr_at_5 value: 35.836 - type: ndcg_at_1 value: 28.374 - type: ndcg_at_10 value: 37.893 - type: ndcg_at_100 value: 43.694 - type: ndcg_at_1000 value: 46.001999999999995 - type: ndcg_at_3 value: 33.825 - type: ndcg_at_5 value: 36.201 - type: precision_at_1 value: 28.374 - type: precision_at_10 value: 5.966 - type: precision_at_100 value: 0.9650000000000001 - type: precision_at_1000 value: 0.124 - type: precision_at_3 value: 14.774999999999999 - type: precision_at_5 value: 10.459999999999999 - type: recall_at_1 value: 25.106 - type: recall_at_10 value: 48.607 - type: recall_at_100 value: 74.66000000000001 - type: recall_at_1000 value: 91.562 - type: recall_at_3 value: 37.669999999999995 - type: recall_at_5 value: 43.484 - task: type: Retrieval dataset: name: MTEB CQADupstackTexRetrieval type: BeIR/cqadupstack config: default split: test revision: 46989137a86843e03a6195de44b09deda022eec7 metrics: - type: map_at_1 value: 13.755 - type: map_at_10 value: 20.756 - type: map_at_100 value: 22.05 - type: map_at_1000 value: 22.201 - type: map_at_3 value: 18.243000000000002 - type: map_at_5 value: 19.512 - type: mrr_at_1 value: 16.93 - type: mrr_at_10 value: 24.276 - type: mrr_at_100 value: 25.349 - type: mrr_at_1000 value: 25.441000000000003 - type: mrr_at_3 value: 21.897 - type: mrr_at_5 value: 23.134 - type: ndcg_at_1 value: 16.93 - type: ndcg_at_10 value: 25.508999999999997 - type: ndcg_at_100 value: 31.777 - type: ndcg_at_1000 value: 35.112 - type: ndcg_at_3 value: 20.896 - type: ndcg_at_5 value: 22.857 - type: precision_at_1 value: 16.93 - type: precision_at_10 value: 4.972 - type: precision_at_100 value: 0.963 - type: precision_at_1000 value: 0.145 - type: precision_at_3 value: 10.14 - type: precision_at_5 value: 7.536 - type: recall_at_1 value: 13.755 - type: recall_at_10 value: 36.46 - type: recall_at_100 value: 64.786 - type: recall_at_1000 value: 88.287 - type: recall_at_3 value: 23.681 - type: recall_at_5 value: 28.615000000000002 - task: type: Retrieval dataset: name: MTEB CQADupstackUnixRetrieval type: BeIR/cqadupstack config: default split: test revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53 metrics: - type: map_at_1 value: 26.99 - type: map_at_10 value: 38.009 - type: map_at_100 value: 39.384 - type: map_at_1000 value: 39.481 - type: map_at_3 value: 34.593 - type: map_at_5 value: 36.449999999999996 - type: mrr_at_1 value: 31.81 - type: mrr_at_10 value: 41.943000000000005 - type: mrr_at_100 value: 42.914 - type: mrr_at_1000 value: 42.962 - type: mrr_at_3 value: 39.179 - type: mrr_at_5 value: 40.798 - type: ndcg_at_1 value: 31.81 - type: ndcg_at_10 value: 44.086 - type: ndcg_at_100 value: 50.026 - type: ndcg_at_1000 value: 51.903999999999996 - type: ndcg_at_3 value: 38.23 - type: ndcg_at_5 value: 40.926 - type: precision_at_1 value: 31.81 - type: precision_at_10 value: 7.761 - type: precision_at_100 value: 1.205 - type: precision_at_1000 value: 0.148 - type: precision_at_3 value: 17.537 - type: precision_at_5 value: 12.649 - type: recall_at_1 value: 26.99 - type: recall_at_10 value: 58.467 - type: recall_at_100 value: 83.93 - type: recall_at_1000 value: 96.452 - type: recall_at_3 value: 42.685 - type: recall_at_5 value: 49.341 - task: type: Retrieval dataset: name: MTEB CQADupstackWebmastersRetrieval type: BeIR/cqadupstack config: default split: test revision: 160c094312a0e1facb97e55eeddb698c0abe3571 metrics: - type: map_at_1 value: 25.312 - type: map_at_10 value: 35.788 - type: map_at_100 value: 37.616 - type: map_at_1000 value: 37.86 - type: map_at_3 value: 32.422000000000004 - type: map_at_5 value: 34.585 - type: mrr_at_1 value: 30.631999999999998 - type: mrr_at_10 value: 40.604 - type: mrr_at_100 value: 41.745 - type: mrr_at_1000 value: 41.788 - type: mrr_at_3 value: 37.582 - type: mrr_at_5 value: 39.499 - type: ndcg_at_1 value: 30.631999999999998 - type: ndcg_at_10 value: 42.129 - type: ndcg_at_100 value: 48.943 - type: ndcg_at_1000 value: 51.089 - type: ndcg_at_3 value: 36.658 - type: ndcg_at_5 value: 39.818999999999996 - type: precision_at_1 value: 30.631999999999998 - type: precision_at_10 value: 7.904999999999999 - type: precision_at_100 value: 1.664 - type: precision_at_1000 value: 0.256 - type: precision_at_3 value: 16.996 - type: precision_at_5 value: 12.727 - type: recall_at_1 value: 25.312 - type: recall_at_10 value: 54.886 - type: recall_at_100 value: 84.155 - type: recall_at_1000 value: 96.956 - type: recall_at_3 value: 40.232 - type: recall_at_5 value: 48.204 - task: type: Retrieval dataset: name: MTEB ClimateFEVER type: mteb/climate-fever config: default split: test revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380 metrics: - type: map_at_1 value: 19.147 - type: map_at_10 value: 33.509 - type: map_at_100 value: 35.573 - type: map_at_1000 value: 35.769 - type: map_at_3 value: 27.983999999999998 - type: map_at_5 value: 31.012 - type: mrr_at_1 value: 43.844 - type: mrr_at_10 value: 56.24 - type: mrr_at_100 value: 56.801 - type: mrr_at_1000 value: 56.826 - type: mrr_at_3 value: 53.290000000000006 - type: mrr_at_5 value: 55.13 - type: ndcg_at_1 value: 43.844 - type: ndcg_at_10 value: 43.996 - type: ndcg_at_100 value: 50.965 - type: ndcg_at_1000 value: 53.927 - type: ndcg_at_3 value: 37.263000000000005 - type: ndcg_at_5 value: 39.553 - type: precision_at_1 value: 43.844 - type: precision_at_10 value: 13.687 - type: precision_at_100 value: 2.139 - type: precision_at_1000 value: 0.269 - type: precision_at_3 value: 28.122000000000003 - type: precision_at_5 value: 21.303 - type: recall_at_1 value: 19.147 - type: recall_at_10 value: 50.449999999999996 - type: recall_at_100 value: 74.00099999999999 - type: recall_at_1000 value: 90.098 - type: recall_at_3 value: 33.343 - type: recall_at_5 value: 40.744 - task: type: Retrieval dataset: name: MTEB DBPedia type: mteb/dbpedia config: default split: test revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659 metrics: - type: map_at_1 value: 8.773 - type: map_at_10 value: 21.172 - type: map_at_100 value: 30.244 - type: map_at_1000 value: 32.127 - type: map_at_3 value: 14.510000000000002 - type: map_at_5 value: 17.483 - type: mrr_at_1 value: 68.25 - type: mrr_at_10 value: 77.33 - type: mrr_at_100 value: 77.529 - type: mrr_at_1000 value: 77.536 - type: mrr_at_3 value: 75.708 - type: mrr_at_5 value: 76.72099999999999 - type: ndcg_at_1 value: 60.0 - type: ndcg_at_10 value: 48.045 - type: ndcg_at_100 value: 51.620999999999995 - type: ndcg_at_1000 value: 58.843999999999994 - type: ndcg_at_3 value: 52.922000000000004 - type: ndcg_at_5 value: 50.27 - type: precision_at_1 value: 68.25 - type: precision_at_10 value: 37.625 - type: precision_at_100 value: 11.774999999999999 - type: precision_at_1000 value: 2.395 - type: precision_at_3 value: 55.25 - type: precision_at_5 value: 47.599999999999994 - type: recall_at_1 value: 8.773 - type: recall_at_10 value: 27.332 - type: recall_at_100 value: 55.48499999999999 - type: recall_at_1000 value: 79.886 - type: recall_at_3 value: 15.823 - type: recall_at_5 value: 20.523 - task: type: Classification dataset: name: MTEB EmotionClassification type: mteb/emotion config: default split: test revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 metrics: - type: accuracy value: 54.52999999999999 - type: f1 value: 47.396628088963645 - task: type: Retrieval dataset: name: MTEB FEVER type: mteb/fever config: default split: test revision: bea83ef9e8fb933d90a2f1d5515737465d613e12 metrics: - type: map_at_1 value: 85.397 - type: map_at_10 value: 90.917 - type: map_at_100 value: 91.109 - type: map_at_1000 value: 91.121 - type: map_at_3 value: 90.045 - type: map_at_5 value: 90.602 - type: mrr_at_1 value: 92.00399999999999 - type: mrr_at_10 value: 95.39999999999999 - type: mrr_at_100 value: 95.41 - type: mrr_at_1000 value: 95.41 - type: mrr_at_3 value: 95.165 - type: mrr_at_5 value: 95.348 - type: ndcg_at_1 value: 92.00399999999999 - type: ndcg_at_10 value: 93.345 - type: ndcg_at_100 value: 93.934 - type: ndcg_at_1000 value: 94.108 - type: ndcg_at_3 value: 92.32000000000001 - type: ndcg_at_5 value: 92.899 - type: precision_at_1 value: 92.00399999999999 - type: precision_at_10 value: 10.839 - type: precision_at_100 value: 1.1440000000000001 - type: precision_at_1000 value: 0.117 - type: precision_at_3 value: 34.298 - type: precision_at_5 value: 21.128 - type: recall_at_1 value: 85.397 - type: recall_at_10 value: 96.375 - type: recall_at_100 value: 98.518 - type: recall_at_1000 value: 99.515 - type: recall_at_3 value: 93.59100000000001 - type: recall_at_5 value: 95.134 - task: type: Retrieval dataset: name: MTEB FiQA2018 type: mteb/fiqa config: default split: test revision: 27a168819829fe9bcd655c2df245fb19452e8e06 metrics: - type: map_at_1 value: 27.36 - type: map_at_10 value: 46.847 - type: map_at_100 value: 49.259 - type: map_at_1000 value: 49.389 - type: map_at_3 value: 41.095 - type: map_at_5 value: 44.084 - type: mrr_at_1 value: 51.852 - type: mrr_at_10 value: 61.67 - type: mrr_at_100 value: 62.395999999999994 - type: mrr_at_1000 value: 62.414 - type: mrr_at_3 value: 59.465 - type: mrr_at_5 value: 60.584 - type: ndcg_at_1 value: 51.852 - type: ndcg_at_10 value: 55.311 - type: ndcg_at_100 value: 62.6 - type: ndcg_at_1000 value: 64.206 - type: ndcg_at_3 value: 51.159 - type: ndcg_at_5 value: 52.038 - type: precision_at_1 value: 51.852 - type: precision_at_10 value: 15.370000000000001 - type: precision_at_100 value: 2.282 - type: precision_at_1000 value: 0.258 - type: precision_at_3 value: 34.721999999999994 - type: precision_at_5 value: 24.846 - type: recall_at_1 value: 27.36 - type: recall_at_10 value: 63.932 - type: recall_at_100 value: 89.824 - type: recall_at_1000 value: 98.556 - type: recall_at_3 value: 47.227999999999994 - type: recall_at_5 value: 53.724000000000004 - task: type: Retrieval dataset: name: MTEB HotpotQA type: mteb/hotpotqa config: default split: test revision: ab518f4d6fcca38d87c25209f94beba119d02014 metrics: - type: map_at_1 value: 40.655 - type: map_at_10 value: 63.824999999999996 - type: map_at_100 value: 64.793 - type: map_at_1000 value: 64.848 - type: map_at_3 value: 60.221000000000004 - type: map_at_5 value: 62.474 - type: mrr_at_1 value: 81.31 - type: mrr_at_10 value: 86.509 - type: mrr_at_100 value: 86.677 - type: mrr_at_1000 value: 86.682 - type: mrr_at_3 value: 85.717 - type: mrr_at_5 value: 86.21 - type: ndcg_at_1 value: 81.31 - type: ndcg_at_10 value: 72.251 - type: ndcg_at_100 value: 75.536 - type: ndcg_at_1000 value: 76.558 - type: ndcg_at_3 value: 67.291 - type: ndcg_at_5 value: 70.045 - type: precision_at_1 value: 81.31 - type: precision_at_10 value: 15.082999999999998 - type: precision_at_100 value: 1.764 - type: precision_at_1000 value: 0.19 - type: precision_at_3 value: 42.971 - type: precision_at_5 value: 27.956999999999997 - type: recall_at_1 value: 40.655 - type: recall_at_10 value: 75.41499999999999 - type: recall_at_100 value: 88.224 - type: recall_at_1000 value: 94.943 - type: recall_at_3 value: 64.456 - type: recall_at_5 value: 69.892 - task: type: Classification dataset: name: MTEB ImdbClassification type: mteb/imdb config: default split: test revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 metrics: - type: accuracy value: 95.58120000000001 - type: ap value: 93.0407063004784 - type: f1 value: 95.57849992996822 - task: type: Retrieval dataset: name: MTEB MSMARCO type: mteb/msmarco config: default split: dev revision: c5a29a104738b98a9e76336939199e264163d4a0 metrics: - type: map_at_1 value: 22.031 - type: map_at_10 value: 34.628 - type: map_at_100 value: 35.833 - type: map_at_1000 value: 35.881 - type: map_at_3 value: 30.619000000000003 - type: map_at_5 value: 32.982 - type: mrr_at_1 value: 22.736 - type: mrr_at_10 value: 35.24 - type: mrr_at_100 value: 36.381 - type: mrr_at_1000 value: 36.424 - type: mrr_at_3 value: 31.287 - type: mrr_at_5 value: 33.617000000000004 - type: ndcg_at_1 value: 22.736 - type: ndcg_at_10 value: 41.681000000000004 - type: ndcg_at_100 value: 47.371 - type: ndcg_at_1000 value: 48.555 - type: ndcg_at_3 value: 33.553 - type: ndcg_at_5 value: 37.771 - type: precision_at_1 value: 22.736 - type: precision_at_10 value: 6.625 - type: precision_at_100 value: 0.9450000000000001 - type: precision_at_1000 value: 0.105 - type: precision_at_3 value: 14.331 - type: precision_at_5 value: 10.734 - type: recall_at_1 value: 22.031 - type: recall_at_10 value: 63.378 - type: recall_at_100 value: 89.47699999999999 - type: recall_at_1000 value: 98.48400000000001 - type: recall_at_3 value: 41.388000000000005 - type: recall_at_5 value: 51.522999999999996 - task: type: Classification dataset: name: MTEB MTOPDomainClassification (en) type: mteb/mtop_domain config: en split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics: - type: accuracy value: 95.75239398084815 - type: f1 value: 95.51228043205194 - task: type: Classification dataset: name: MTEB MTOPIntentClassification (en) type: mteb/mtop_intent config: en split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics: - type: accuracy value: 84.25900592795259 - type: f1 value: 62.14790420114562 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (en) type: mteb/amazon_massive_intent config: en split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 78.47007397444519 - type: f1 value: 76.92133583932912 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (en) type: mteb/amazon_massive_scenario config: en split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 78.19098856758575 - type: f1 value: 78.10820805879119 - task: type: Clustering dataset: name: MTEB MedrxivClusteringP2P type: mteb/medrxiv-clustering-p2p config: default split: test revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 metrics: - type: v_measure value: 44.37013684222983 - task: type: Clustering dataset: name: MTEB MedrxivClusteringS2S type: mteb/medrxiv-clustering-s2s config: default split: test revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 metrics: - type: v_measure value: 42.003012591979704 - task: type: Reranking dataset: name: MTEB MindSmallReranking type: mteb/mind_small config: default split: test revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 metrics: - type: map value: 32.70743071063257 - type: mrr value: 33.938337390083994 - task: type: Retrieval dataset: name: MTEB NFCorpus type: mteb/nfcorpus config: default split: test revision: ec0fa4fe99da2ff19ca1214b7966684033a58814 metrics: - type: map_at_1 value: 6.369 - type: map_at_10 value: 14.313 - type: map_at_100 value: 18.329 - type: map_at_1000 value: 20.017 - type: map_at_3 value: 10.257 - type: map_at_5 value: 12.264999999999999 - type: mrr_at_1 value: 49.536 - type: mrr_at_10 value: 58.464000000000006 - type: mrr_at_100 value: 59.016000000000005 - type: mrr_at_1000 value: 59.053 - type: mrr_at_3 value: 56.294999999999995 - type: mrr_at_5 value: 57.766 - type: ndcg_at_1 value: 47.678 - type: ndcg_at_10 value: 38.246 - type: ndcg_at_100 value: 35.370000000000005 - type: ndcg_at_1000 value: 44.517 - type: ndcg_at_3 value: 43.368 - type: ndcg_at_5 value: 41.892 - type: precision_at_1 value: 49.536 - type: precision_at_10 value: 28.235 - type: precision_at_100 value: 9.014999999999999 - type: precision_at_1000 value: 2.257 - type: precision_at_3 value: 40.557 - type: precision_at_5 value: 36.409000000000006 - type: recall_at_1 value: 6.369 - type: recall_at_10 value: 19.195999999999998 - type: recall_at_100 value: 37.042 - type: recall_at_1000 value: 69.203 - type: recall_at_3 value: 11.564 - type: recall_at_5 value: 15.264 - task: type: Retrieval dataset: name: MTEB NQ type: mteb/nq config: default split: test revision: b774495ed302d8c44a3a7ea25c90dbce03968f31 metrics: - type: map_at_1 value: 39.323 - type: map_at_10 value: 54.608999999999995 - type: map_at_100 value: 55.523 - type: map_at_1000 value: 55.544000000000004 - type: map_at_3 value: 50.580000000000005 - type: map_at_5 value: 53.064 - type: mrr_at_1 value: 44.263999999999996 - type: mrr_at_10 value: 57.416 - type: mrr_at_100 value: 58.037000000000006 - type: mrr_at_1000 value: 58.05200000000001 - type: mrr_at_3 value: 54.330999999999996 - type: mrr_at_5 value: 56.302 - type: ndcg_at_1 value: 44.263999999999996 - type: ndcg_at_10 value: 61.785999999999994 - type: ndcg_at_100 value: 65.40599999999999 - type: ndcg_at_1000 value: 65.859 - type: ndcg_at_3 value: 54.518 - type: ndcg_at_5 value: 58.53699999999999 - type: precision_at_1 value: 44.263999999999996 - type: precision_at_10 value: 9.652 - type: precision_at_100 value: 1.169 - type: precision_at_1000 value: 0.121 - type: precision_at_3 value: 24.15 - type: precision_at_5 value: 16.848 - type: recall_at_1 value: 39.323 - type: recall_at_10 value: 80.663 - type: recall_at_100 value: 96.072 - type: recall_at_1000 value: 99.37700000000001 - type: recall_at_3 value: 62.23 - type: recall_at_5 value: 71.379 - task: type: Retrieval dataset: name: MTEB QuoraRetrieval type: mteb/quora config: default split: test revision: None metrics: - type: map_at_1 value: 72.02499999999999 - type: map_at_10 value: 86.14500000000001 - type: map_at_100 value: 86.764 - type: map_at_1000 value: 86.776 - type: map_at_3 value: 83.249 - type: map_at_5 value: 85.083 - type: mrr_at_1 value: 82.83 - type: mrr_at_10 value: 88.70599999999999 - type: mrr_at_100 value: 88.791 - type: mrr_at_1000 value: 88.791 - type: mrr_at_3 value: 87.815 - type: mrr_at_5 value: 88.435 - type: ndcg_at_1 value: 82.84 - type: ndcg_at_10 value: 89.61200000000001 - type: ndcg_at_100 value: 90.693 - type: ndcg_at_1000 value: 90.752 - type: ndcg_at_3 value: 86.96199999999999 - type: ndcg_at_5 value: 88.454 - type: precision_at_1 value: 82.84 - type: precision_at_10 value: 13.600000000000001 - type: precision_at_100 value: 1.543 - type: precision_at_1000 value: 0.157 - type: precision_at_3 value: 38.092999999999996 - type: precision_at_5 value: 25.024 - type: recall_at_1 value: 72.02499999999999 - type: recall_at_10 value: 96.21600000000001 - type: recall_at_100 value: 99.76 - type: recall_at_1000 value: 99.996 - type: recall_at_3 value: 88.57000000000001 - type: recall_at_5 value: 92.814 - task: type: Clustering dataset: name: MTEB RedditClustering type: mteb/reddit-clustering config: default split: test revision: 24640382cdbf8abc73003fb0fa6d111a705499eb metrics: - type: v_measure value: 73.37297191949929 - task: type: Clustering dataset: name: MTEB RedditClusteringP2P type: mteb/reddit-clustering-p2p config: default split: test revision: 282350215ef01743dc01b456c7f5241fa8937f16 metrics: - type: v_measure value: 72.50752304246946 - task: type: Retrieval dataset: name: MTEB SCIDOCS type: mteb/scidocs config: default split: test revision: None metrics: - type: map_at_1 value: 6.4479999999999995 - type: map_at_10 value: 17.268 - type: map_at_100 value: 20.502000000000002 - type: map_at_1000 value: 20.904 - type: map_at_3 value: 11.951 - type: map_at_5 value: 14.494000000000002 - type: mrr_at_1 value: 31.900000000000002 - type: mrr_at_10 value: 45.084999999999994 - type: mrr_at_100 value: 46.145 - type: mrr_at_1000 value: 46.164 - type: mrr_at_3 value: 41.6 - type: mrr_at_5 value: 43.76 - type: ndcg_at_1 value: 31.900000000000002 - type: ndcg_at_10 value: 27.694000000000003 - type: ndcg_at_100 value: 39.016 - type: ndcg_at_1000 value: 44.448 - type: ndcg_at_3 value: 26.279999999999998 - type: ndcg_at_5 value: 22.93 - type: precision_at_1 value: 31.900000000000002 - type: precision_at_10 value: 14.399999999999999 - type: precision_at_100 value: 3.082 - type: precision_at_1000 value: 0.436 - type: precision_at_3 value: 24.667 - type: precision_at_5 value: 20.200000000000003 - type: recall_at_1 value: 6.4479999999999995 - type: recall_at_10 value: 29.243000000000002 - type: recall_at_100 value: 62.547 - type: recall_at_1000 value: 88.40299999999999 - type: recall_at_3 value: 14.988000000000001 - type: recall_at_5 value: 20.485 - task: type: STS dataset: name: MTEB SICK-R type: mteb/sickr-sts config: default split: test revision: a6ea5a8cab320b040a23452cc28066d9beae2cee metrics: - type: cos_sim_pearson value: 80.37839336866843 - type: cos_sim_spearman value: 79.14737320486729 - type: euclidean_pearson value: 78.74010870392799 - type: euclidean_spearman value: 79.1472505448557 - type: manhattan_pearson value: 78.76735626972086 - type: manhattan_spearman value: 79.18509055331465 - task: type: STS dataset: name: MTEB STS12 type: mteb/sts12-sts config: default split: test revision: a0d554a64d88156834ff5ae9920b964011b16384 metrics: - type: cos_sim_pearson value: 84.98947740740309 - type: cos_sim_spearman value: 76.52068694652895 - 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task: type: Retrieval dataset: name: MTEB DuRetrieval type: C-MTEB/DuRetrieval config: default split: dev revision: a1a333e290fe30b10f3f56498e3a0d911a693ced metrics: - type: map_at_1 value: 26.107999999999997 - type: map_at_10 value: 78.384 - type: map_at_100 value: 81.341 - type: map_at_1000 value: 81.384 - type: map_at_3 value: 54.462999999999994 - type: map_at_5 value: 68.607 - type: mrr_at_1 value: 88.94999999999999 - type: mrr_at_10 value: 92.31 - type: mrr_at_100 value: 92.379 - type: mrr_at_1000 value: 92.38300000000001 - type: mrr_at_3 value: 91.85799999999999 - type: mrr_at_5 value: 92.146 - type: ndcg_at_1 value: 88.94999999999999 - type: ndcg_at_10 value: 86.00999999999999 - type: ndcg_at_100 value: 89.121 - type: ndcg_at_1000 value: 89.534 - type: ndcg_at_3 value: 84.69200000000001 - type: ndcg_at_5 value: 83.678 - type: precision_at_1 value: 88.94999999999999 - type: precision_at_10 value: 41.065000000000005 - type: precision_at_100 value: 4.781 - type: precision_at_1000 value: 0.488 - type: precision_at_3 value: 75.75 - type: precision_at_5 value: 63.93 - type: recall_at_1 value: 26.107999999999997 - type: recall_at_10 value: 87.349 - type: recall_at_100 value: 97.14699999999999 - type: recall_at_1000 value: 99.287 - type: recall_at_3 value: 56.601 - type: recall_at_5 value: 73.381 - task: type: Retrieval dataset: name: MTEB EcomRetrieval type: C-MTEB/EcomRetrieval config: default split: dev revision: 687de13dc7294d6fd9be10c6945f9e8fec8166b9 metrics: - type: map_at_1 value: 50.7 - type: map_at_10 value: 61.312999999999995 - type: map_at_100 value: 61.88399999999999 - type: map_at_1000 value: 61.9 - type: map_at_3 value: 58.983 - type: map_at_5 value: 60.238 - type: mrr_at_1 value: 50.7 - type: mrr_at_10 value: 61.312999999999995 - type: mrr_at_100 value: 61.88399999999999 - type: mrr_at_1000 value: 61.9 - type: mrr_at_3 value: 58.983 - type: mrr_at_5 value: 60.238 - type: ndcg_at_1 value: 50.7 - type: ndcg_at_10 value: 66.458 - type: ndcg_at_100 value: 69.098 - type: ndcg_at_1000 value: 69.539 - type: ndcg_at_3 value: 61.637 - type: ndcg_at_5 value: 63.92099999999999 - type: precision_at_1 value: 50.7 - type: precision_at_10 value: 8.260000000000002 - type: precision_at_100 value: 0.946 - type: precision_at_1000 value: 0.098 - type: precision_at_3 value: 23.1 - type: precision_at_5 value: 14.979999999999999 - type: recall_at_1 value: 50.7 - type: recall_at_10 value: 82.6 - type: recall_at_100 value: 94.6 - type: recall_at_1000 value: 98.1 - type: recall_at_3 value: 69.3 - type: recall_at_5 value: 74.9 - task: type: Classification dataset: name: MTEB IFlyTek type: C-MTEB/IFlyTek-classification config: default split: validation revision: 421605374b29664c5fc098418fe20ada9bd55f8a metrics: - type: accuracy value: 53.76683339746056 - type: f1 value: 40.026100192683714 - task: type: Classification dataset: name: MTEB JDReview type: C-MTEB/JDReview-classification config: default split: test revision: b7c64bd89eb87f8ded463478346f76731f07bf8b metrics: - type: accuracy value: 88.19887429643526 - type: ap value: 59.02998120976959 - type: f1 value: 83.3659125921227 - task: type: STS dataset: name: MTEB LCQMC type: C-MTEB/LCQMC config: default split: test revision: 17f9b096f80380fce5ed12a9be8be7784b337daf metrics: - type: cos_sim_pearson value: 72.53955204856854 - type: cos_sim_spearman value: 76.28996886746215 - type: euclidean_pearson value: 75.31184890026394 - type: euclidean_spearman value: 76.28984471300522 - type: manhattan_pearson value: 75.36930361638623 - type: manhattan_spearman value: 76.34021995551348 - task: type: Reranking dataset: name: MTEB MMarcoReranking type: C-MTEB/Mmarco-reranking config: default split: dev revision: None metrics: - type: map value: 23.63666512532725 - type: mrr value: 22.49642857142857 - task: type: Retrieval dataset: name: MTEB MMarcoRetrieval type: C-MTEB/MMarcoRetrieval config: default split: dev revision: 539bbde593d947e2a124ba72651aafc09eb33fc2 metrics: - type: map_at_1 value: 60.645 - type: map_at_10 value: 69.733 - type: map_at_100 value: 70.11699999999999 - type: map_at_1000 value: 70.135 - type: map_at_3 value: 67.585 - type: map_at_5 value: 68.904 - type: mrr_at_1 value: 62.765 - type: mrr_at_10 value: 70.428 - type: mrr_at_100 value: 70.77 - type: mrr_at_1000 value: 70.785 - type: mrr_at_3 value: 68.498 - type: mrr_at_5 value: 69.69 - type: ndcg_at_1 value: 62.765 - type: ndcg_at_10 value: 73.83 - type: ndcg_at_100 value: 75.593 - type: ndcg_at_1000 value: 76.05199999999999 - type: ndcg_at_3 value: 69.66499999999999 - type: ndcg_at_5 value: 71.929 - type: precision_at_1 value: 62.765 - type: precision_at_10 value: 9.117 - type: precision_at_100 value: 1.0 - type: precision_at_1000 value: 0.104 - type: precision_at_3 value: 26.323 - type: precision_at_5 value: 16.971 - type: recall_at_1 value: 60.645 - type: recall_at_10 value: 85.907 - type: recall_at_100 value: 93.947 - type: recall_at_1000 value: 97.531 - type: recall_at_3 value: 74.773 - type: recall_at_5 value: 80.16799999999999 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (zh-CN) type: mteb/amazon_massive_intent config: zh-CN split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 76.25084061869536 - type: f1 value: 73.65064492827022 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (zh-CN) type: mteb/amazon_massive_scenario config: zh-CN split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 77.2595830531271 - type: f1 value: 77.15217273559321 - task: type: Retrieval dataset: name: MTEB MedicalRetrieval type: C-MTEB/MedicalRetrieval config: default split: dev revision: 2039188fb5800a9803ba5048df7b76e6fb151fc6 metrics: - type: map_at_1 value: 52.400000000000006 - type: map_at_10 value: 58.367000000000004 - type: map_at_100 value: 58.913000000000004 - type: map_at_1000 value: 58.961 - type: map_at_3 value: 56.882999999999996 - type: map_at_5 value: 57.743 - type: mrr_at_1 value: 52.400000000000006 - type: mrr_at_10 value: 58.367000000000004 - type: mrr_at_100 value: 58.913000000000004 - type: mrr_at_1000 value: 58.961 - type: mrr_at_3 value: 56.882999999999996 - type: mrr_at_5 value: 57.743 - type: ndcg_at_1 value: 52.400000000000006 - type: ndcg_at_10 value: 61.329 - type: ndcg_at_100 value: 64.264 - type: ndcg_at_1000 value: 65.669 - type: ndcg_at_3 value: 58.256 - type: ndcg_at_5 value: 59.813 - type: precision_at_1 value: 52.400000000000006 - type: precision_at_10 value: 7.07 - type: precision_at_100 value: 0.851 - type: precision_at_1000 value: 0.096 - type: precision_at_3 value: 20.732999999999997 - type: precision_at_5 value: 13.200000000000001 - type: recall_at_1 value: 52.400000000000006 - type: recall_at_10 value: 70.7 - type: recall_at_100 value: 85.1 - type: recall_at_1000 value: 96.39999999999999 - type: recall_at_3 value: 62.2 - type: recall_at_5 value: 66.0 - task: type: Classification dataset: name: MTEB MultilingualSentiment type: C-MTEB/MultilingualSentiment-classification config: default split: validation revision: 46958b007a63fdbf239b7672c25d0bea67b5ea1a metrics: - type: accuracy value: 77.42333333333333 - type: f1 value: 77.24849313989888 - task: type: PairClassification dataset: name: MTEB Ocnli type: C-MTEB/OCNLI config: default split: validation revision: 66e76a618a34d6d565d5538088562851e6daa7ec metrics: - type: cos_sim_accuracy value: 80.12994044396319 - type: cos_sim_ap value: 85.21793541189636 - type: cos_sim_f1 value: 81.91489361702128 - type: cos_sim_precision value: 75.55753791257806 - type: cos_sim_recall value: 89.44033790918691 - type: dot_accuracy value: 80.12994044396319 - type: dot_ap value: 85.22568672443236 - type: dot_f1 value: 81.91489361702128 - type: dot_precision value: 75.55753791257806 - type: dot_recall value: 89.44033790918691 - type: euclidean_accuracy value: 80.12994044396319 - type: euclidean_ap value: 85.21643342357407 - type: euclidean_f1 value: 81.8830242510699 - type: euclidean_precision value: 74.48096885813149 - type: euclidean_recall value: 90.91869060190075 - type: manhattan_accuracy value: 80.5630752571738 - type: manhattan_ap value: 85.27682975032671 - type: manhattan_f1 value: 82.03883495145631 - type: manhattan_precision value: 75.92093441150045 - type: manhattan_recall value: 89.22914466737065 - type: max_accuracy value: 80.5630752571738 - type: max_ap value: 85.27682975032671 - type: max_f1 value: 82.03883495145631 - task: type: Classification dataset: name: MTEB OnlineShopping type: C-MTEB/OnlineShopping-classification config: default split: test revision: e610f2ebd179a8fda30ae534c3878750a96db120 metrics: - type: accuracy value: 94.47999999999999 - type: ap value: 92.81177660844013 - type: f1 value: 94.47045470502114 - task: type: STS dataset: name: MTEB PAWSX type: C-MTEB/PAWSX config: default split: test revision: 9c6a90e430ac22b5779fb019a23e820b11a8b5e1 metrics: - type: cos_sim_pearson value: 46.13154582182421 - type: cos_sim_spearman value: 50.21718723757444 - type: euclidean_pearson value: 49.41535243569054 - type: euclidean_spearman value: 50.21831909208907 - type: manhattan_pearson value: 49.50756578601167 - type: manhattan_spearman value: 50.229118655684566 - task: type: STS dataset: name: MTEB QBQTC type: C-MTEB/QBQTC config: default split: test revision: 790b0510dc52b1553e8c49f3d2afb48c0e5c48b7 metrics: - type: cos_sim_pearson value: 30.787794367421956 - type: cos_sim_spearman value: 31.81774306987836 - type: euclidean_pearson value: 29.809436608089495 - type: euclidean_spearman value: 31.817379098812165 - type: manhattan_pearson value: 30.377027186607787 - type: manhattan_spearman value: 32.42286865176827 - task: type: STS dataset: name: MTEB STS22 (zh) type: mteb/sts22-crosslingual-sts config: zh split: test revision: eea2b4fe26a775864c896887d910b76a8098ad3f metrics: - type: cos_sim_pearson value: 61.29839896616376 - type: cos_sim_spearman value: 67.36328213286453 - type: euclidean_pearson value: 64.33899267794008 - type: euclidean_spearman value: 67.36552580196211 - type: manhattan_pearson value: 65.20010308796022 - type: manhattan_spearman value: 67.50982972902 - task: type: STS dataset: name: MTEB STSB type: C-MTEB/STSB config: default split: test revision: 0cde68302b3541bb8b3c340dc0644b0b745b3dc0 metrics: - type: cos_sim_pearson value: 81.23278996774297 - type: cos_sim_spearman value: 81.369375466486 - type: euclidean_pearson value: 79.91030863727944 - type: euclidean_spearman value: 81.36824495466793 - type: manhattan_pearson value: 79.88047052896854 - type: manhattan_spearman value: 81.3369604332008 - task: type: Reranking dataset: name: MTEB T2Reranking type: C-MTEB/T2Reranking config: default split: dev revision: 76631901a18387f85eaa53e5450019b87ad58ef9 metrics: - type: map value: 68.109205221286 - type: mrr value: 78.40703619520477 - task: type: Retrieval dataset: name: MTEB T2Retrieval type: C-MTEB/T2Retrieval config: default split: dev revision: 8731a845f1bf500a4f111cf1070785c793d10e64 metrics: - type: map_at_1 value: 26.704 - type: map_at_10 value: 75.739 - type: map_at_100 value: 79.606 - type: map_at_1000 value: 79.666 - type: map_at_3 value: 52.803 - type: map_at_5 value: 65.068 - type: mrr_at_1 value: 88.48899999999999 - type: mrr_at_10 value: 91.377 - type: mrr_at_100 value: 91.474 - type: mrr_at_1000 value: 91.47800000000001 - type: mrr_at_3 value: 90.846 - type: mrr_at_5 value: 91.18 - type: ndcg_at_1 value: 88.48899999999999 - type: ndcg_at_10 value: 83.581 - type: ndcg_at_100 value: 87.502 - type: ndcg_at_1000 value: 88.1 - type: ndcg_at_3 value: 84.433 - type: ndcg_at_5 value: 83.174 - type: precision_at_1 value: 88.48899999999999 - type: precision_at_10 value: 41.857 - type: precision_at_100 value: 5.039 - type: precision_at_1000 value: 0.517 - type: precision_at_3 value: 73.938 - type: precision_at_5 value: 62.163000000000004 - type: recall_at_1 value: 26.704 - type: recall_at_10 value: 83.092 - type: recall_at_100 value: 95.659 - type: recall_at_1000 value: 98.779 - type: recall_at_3 value: 54.678000000000004 - type: recall_at_5 value: 68.843 - task: type: Classification dataset: name: MTEB TNews type: C-MTEB/TNews-classification config: default split: validation revision: 317f262bf1e6126357bbe89e875451e4b0938fe4 metrics: - type: accuracy value: 51.235 - type: f1 value: 48.14373844331604 - task: type: Clustering dataset: name: MTEB ThuNewsClusteringP2P type: C-MTEB/ThuNewsClusteringP2P config: default split: test revision: 5798586b105c0434e4f0fe5e767abe619442cf93 metrics: - type: v_measure value: 87.42930040493792 - task: type: Clustering dataset: name: MTEB ThuNewsClusteringS2S type: C-MTEB/ThuNewsClusteringS2S config: default split: test revision: 8a8b2caeda43f39e13c4bc5bea0f8a667896e10d metrics: - type: v_measure value: 87.90254094650042 - task: type: Retrieval dataset: name: MTEB VideoRetrieval type: C-MTEB/VideoRetrieval config: default split: dev revision: 58c2597a5943a2ba48f4668c3b90d796283c5639 metrics: - type: map_at_1 value: 54.900000000000006 - type: map_at_10 value: 64.92 - type: map_at_100 value: 65.424 - type: map_at_1000 value: 65.43900000000001 - type: map_at_3 value: 63.132999999999996 - type: map_at_5 value: 64.208 - type: mrr_at_1 value: 54.900000000000006 - type: mrr_at_10 value: 64.92 - type: mrr_at_100 value: 65.424 - type: mrr_at_1000 value: 65.43900000000001 - type: mrr_at_3 value: 63.132999999999996 - type: mrr_at_5 value: 64.208 - type: ndcg_at_1 value: 54.900000000000006 - type: ndcg_at_10 value: 69.41199999999999 - type: ndcg_at_100 value: 71.824 - type: ndcg_at_1000 value: 72.301 - type: ndcg_at_3 value: 65.79700000000001 - type: ndcg_at_5 value: 67.713 - type: precision_at_1 value: 54.900000000000006 - type: precision_at_10 value: 8.33 - type: precision_at_100 value: 0.9450000000000001 - type: precision_at_1000 value: 0.098 - type: precision_at_3 value: 24.5 - type: precision_at_5 value: 15.620000000000001 - type: recall_at_1 value: 54.900000000000006 - type: recall_at_10 value: 83.3 - type: recall_at_100 value: 94.5 - type: recall_at_1000 value: 98.4 - type: recall_at_3 value: 73.5 - type: recall_at_5 value: 78.10000000000001 - task: type: Classification dataset: name: MTEB Waimai type: C-MTEB/waimai-classification config: default split: test revision: 339287def212450dcaa9df8c22bf93e9980c7023 metrics: - type: accuracy value: 88.63 - type: ap value: 73.78658340897097 - type: f1 value: 87.16764294033919 --- # agier9/gte-Qwen1.5-7B-instruct-Q5_K_M-GGUF This model was converted to GGUF format from [`Alibaba-NLP/gte-Qwen1.5-7B-instruct`](https://huggingface.co/Alibaba-NLP/gte-Qwen1.5-7B-instruct) 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/Alibaba-NLP/gte-Qwen1.5-7B-instruct) for more details on the model. ## Use with llama.cpp Install llama.cpp through brew. ```bash brew install ggerganov/ggerganov/llama.cpp ``` Invoke the llama.cpp server or the CLI. CLI: ```bash llama-cli --hf-repo agier9/gte-Qwen1.5-7B-instruct-Q5_K_M-GGUF --model gte-qwen1.5-7b-instruct-q5_k_m.gguf -p "The meaning to life and the universe is" ``` Server: ```bash llama-server --hf-repo agier9/gte-Qwen1.5-7B-instruct-Q5_K_M-GGUF --model gte-qwen1.5-7b-instruct-q5_k_m.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. ``` git clone https://github.com/ggerganov/llama.cpp && \ cd llama.cpp && \ make && \ ./main -m gte-qwen1.5-7b-instruct-q5_k_m.gguf -n 128 ```