--- base_model: Snowflake/snowflake-arctic-embed-m-long license: apache-2.0 pipeline_tag: sentence-similarity tags: - sentence-transformers - feature-extraction - sentence-similarity - mteb - arctic - snowflake-arctic-embed - transformers.js - llama-cpp - gguf-my-repo model-index: - name: snowflake-arctic-m-long results: - task: type: Classification dataset: name: MTEB AmazonCounterfactualClassification (en) type: mteb/amazon_counterfactual config: en split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics: - type: accuracy value: 78.4776119402985 - type: ap value: 42.34374238166049 - type: f1 value: 72.51164234732224 - task: type: Classification dataset: name: MTEB AmazonPolarityClassification type: mteb/amazon_polarity config: default split: test revision: e2d317d38cd51312af73b3d32a06d1a08b442046 metrics: - type: accuracy value: 78.7416 - type: ap value: 73.12074819362377 - type: f1 value: 78.64057339708795 - task: type: Classification dataset: name: MTEB AmazonReviewsClassification (en) type: mteb/amazon_reviews_multi config: en split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics: - type: accuracy value: 39.926 - type: f1 value: 39.35531993117573 - task: type: Retrieval dataset: name: MTEB ArguAna type: mteb/arguana config: default split: test revision: c22ab2a51041ffd869aaddef7af8d8215647e41a metrics: - type: map_at_1 value: 34.851 - type: map_at_10 value: 51.473 - type: map_at_100 value: 52.103 - type: map_at_1000 value: 52.105000000000004 - type: map_at_3 value: 46.776 - type: map_at_5 value: 49.617 - type: mrr_at_1 value: 35.491 - type: mrr_at_10 value: 51.73799999999999 - type: mrr_at_100 value: 52.37500000000001 - type: mrr_at_1000 value: 52.378 - type: mrr_at_3 value: 46.965 - type: mrr_at_5 value: 49.878 - type: ndcg_at_1 value: 34.851 - type: ndcg_at_10 value: 60.364 - type: ndcg_at_100 value: 62.888999999999996 - type: ndcg_at_1000 value: 62.946000000000005 - type: ndcg_at_3 value: 50.807 - type: ndcg_at_5 value: 55.901 - type: precision_at_1 value: 34.851 - type: precision_at_10 value: 8.855 - type: precision_at_100 value: 0.992 - type: precision_at_1000 value: 0.1 - type: precision_at_3 value: 20.839 - type: precision_at_5 value: 14.963999999999999 - type: recall_at_1 value: 34.851 - type: recall_at_10 value: 88.549 - type: recall_at_100 value: 99.21799999999999 - type: recall_at_1000 value: 99.644 - type: recall_at_3 value: 62.517999999999994 - type: recall_at_5 value: 74.822 - task: type: Clustering dataset: name: MTEB ArxivClusteringP2P type: mteb/arxiv-clustering-p2p config: default split: test revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d metrics: - type: v_measure value: 45.5554998405317 - task: type: Clustering dataset: name: MTEB ArxivClusteringS2S type: mteb/arxiv-clustering-s2s config: default split: test revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 metrics: - type: v_measure value: 35.614248811397005 - task: type: Reranking dataset: name: MTEB AskUbuntuDupQuestions type: mteb/askubuntudupquestions-reranking config: default split: test revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 metrics: - type: map value: 61.355489424753884 - type: mrr value: 75.49443784900849 - task: type: STS dataset: name: MTEB BIOSSES type: mteb/biosses-sts config: default split: test revision: d3fb88f8f02e40887cd149695127462bbcf29b4a metrics: - type: cos_sim_pearson value: 89.17311056578292 - type: cos_sim_spearman value: 88.24237210809322 - type: euclidean_pearson value: 87.3188065853646 - type: euclidean_spearman value: 88.24237210809322 - type: manhattan_pearson value: 86.89499710049658 - type: manhattan_spearman value: 87.85441146091777 - task: type: Classification dataset: name: MTEB Banking77Classification type: mteb/banking77 config: default split: test revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 metrics: - type: accuracy value: 80.26298701298703 - type: f1 value: 79.68356764080303 - task: type: Clustering dataset: name: MTEB BigPatentClustering type: jinaai/big-patent-clustering config: default split: test revision: 62d5330920bca426ce9d3c76ea914f15fc83e891 metrics: - type: v_measure value: 20.923883720813706 - task: type: Clustering dataset: name: MTEB BiorxivClusteringP2P type: mteb/biorxiv-clustering-p2p config: default split: test revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 metrics: - type: v_measure value: 36.16058801465044 - task: type: Clustering dataset: name: MTEB BiorxivClusteringS2S type: mteb/biorxiv-clustering-s2s config: default split: test revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 metrics: - type: v_measure value: 30.1402356118627 - task: type: Retrieval dataset: name: MTEB CQADupstackAndroidRetrieval type: mteb/cqadupstack-android config: default split: test revision: f46a197baaae43b4f621051089b82a364682dfeb metrics: - type: map_at_1 value: 35.612 - type: map_at_10 value: 47.117 - type: map_at_100 value: 48.711 - type: map_at_1000 value: 48.826 - type: map_at_3 value: 43.858999999999995 - type: map_at_5 value: 45.612 - type: mrr_at_1 value: 42.918 - type: mrr_at_10 value: 52.806 - type: mrr_at_100 value: 53.564 - type: mrr_at_1000 value: 53.596999999999994 - type: mrr_at_3 value: 50.453 - type: mrr_at_5 value: 51.841 - type: ndcg_at_1 value: 42.918 - type: ndcg_at_10 value: 53.291999999999994 - type: ndcg_at_100 value: 58.711999999999996 - type: ndcg_at_1000 value: 60.317 - type: ndcg_at_3 value: 48.855 - type: ndcg_at_5 value: 50.778 - type: precision_at_1 value: 42.918 - type: precision_at_10 value: 9.927999999999999 - type: precision_at_100 value: 1.592 - type: precision_at_1000 value: 0.201 - type: precision_at_3 value: 23.366999999999997 - type: precision_at_5 value: 16.366 - type: recall_at_1 value: 35.612 - type: recall_at_10 value: 64.671 - type: recall_at_100 value: 86.97 - type: recall_at_1000 value: 96.99600000000001 - type: recall_at_3 value: 51.37199999999999 - type: recall_at_5 value: 57.094 - task: type: Retrieval dataset: name: MTEB CQADupstackEnglishRetrieval type: mteb/cqadupstack-english config: default split: test revision: ad9991cb51e31e31e430383c75ffb2885547b5f0 metrics: - type: map_at_1 value: 33.742 - type: map_at_10 value: 44.49 - type: map_at_100 value: 45.781 - type: map_at_1000 value: 45.902 - type: map_at_3 value: 41.453 - type: map_at_5 value: 43.251 - type: mrr_at_1 value: 42.357 - type: mrr_at_10 value: 50.463 - type: mrr_at_100 value: 51.17 - type: mrr_at_1000 value: 51.205999999999996 - type: mrr_at_3 value: 48.397 - type: mrr_at_5 value: 49.649 - type: ndcg_at_1 value: 42.357 - type: ndcg_at_10 value: 50.175000000000004 - type: ndcg_at_100 value: 54.491 - type: ndcg_at_1000 value: 56.282 - type: ndcg_at_3 value: 46.159 - type: ndcg_at_5 value: 48.226 - type: precision_at_1 value: 42.357 - type: precision_at_10 value: 9.382 - type: precision_at_100 value: 1.473 - type: precision_at_1000 value: 0.191 - type: precision_at_3 value: 22.187 - type: precision_at_5 value: 15.758 - type: recall_at_1 value: 33.742 - type: recall_at_10 value: 59.760999999999996 - type: recall_at_100 value: 77.89500000000001 - type: recall_at_1000 value: 89.005 - type: recall_at_3 value: 47.872 - type: recall_at_5 value: 53.559 - task: type: Retrieval dataset: name: MTEB CQADupstackGamingRetrieval type: mteb/cqadupstack-gaming config: default split: test revision: 4885aa143210c98657558c04aaf3dc47cfb54340 metrics: - type: map_at_1 value: 43.883 - type: map_at_10 value: 56.464999999999996 - type: map_at_100 value: 57.394 - type: map_at_1000 value: 57.443999999999996 - type: map_at_3 value: 53.169 - type: map_at_5 value: 54.984 - type: mrr_at_1 value: 50.470000000000006 - type: mrr_at_10 value: 59.997 - type: mrr_at_100 value: 60.586 - type: mrr_at_1000 value: 60.61 - type: mrr_at_3 value: 57.837 - type: mrr_at_5 value: 59.019 - type: ndcg_at_1 value: 50.470000000000006 - type: ndcg_at_10 value: 62.134 - type: ndcg_at_100 value: 65.69500000000001 - type: ndcg_at_1000 value: 66.674 - type: ndcg_at_3 value: 56.916999999999994 - type: ndcg_at_5 value: 59.312 - type: precision_at_1 value: 50.470000000000006 - type: precision_at_10 value: 9.812 - type: precision_at_100 value: 1.25 - type: precision_at_1000 value: 0.13699999999999998 - type: precision_at_3 value: 25.119999999999997 - type: precision_at_5 value: 17.016000000000002 - type: recall_at_1 value: 43.883 - type: recall_at_10 value: 75.417 - type: recall_at_100 value: 90.545 - type: recall_at_1000 value: 97.44500000000001 - type: recall_at_3 value: 61.306000000000004 - type: recall_at_5 value: 67.244 - task: type: Retrieval dataset: name: MTEB CQADupstackGisRetrieval type: mteb/cqadupstack-gis config: default split: test revision: 5003b3064772da1887988e05400cf3806fe491f2 metrics: - type: map_at_1 value: 29.813000000000002 - type: map_at_10 value: 38.627 - type: map_at_100 value: 39.735 - type: map_at_1000 value: 39.806000000000004 - type: map_at_3 value: 36.283 - type: map_at_5 value: 37.491 - type: mrr_at_1 value: 32.316 - type: mrr_at_10 value: 40.752 - type: mrr_at_100 value: 41.699000000000005 - type: mrr_at_1000 value: 41.749 - type: mrr_at_3 value: 38.531 - type: mrr_at_5 value: 39.706 - type: ndcg_at_1 value: 32.316 - type: ndcg_at_10 value: 43.524 - type: ndcg_at_100 value: 48.648 - type: ndcg_at_1000 value: 50.405 - type: ndcg_at_3 value: 38.928000000000004 - type: ndcg_at_5 value: 40.967 - type: precision_at_1 value: 32.316 - type: precision_at_10 value: 6.451999999999999 - type: precision_at_100 value: 0.9490000000000001 - type: precision_at_1000 value: 0.11299999999999999 - type: precision_at_3 value: 16.384 - type: precision_at_5 value: 11.006 - type: recall_at_1 value: 29.813000000000002 - type: recall_at_10 value: 56.562999999999995 - type: recall_at_100 value: 79.452 - type: recall_at_1000 value: 92.715 - type: recall_at_3 value: 43.985 - type: recall_at_5 value: 49.001 - task: type: Retrieval dataset: name: MTEB CQADupstackMathematicaRetrieval type: mteb/cqadupstack-mathematica config: default split: test revision: 90fceea13679c63fe563ded68f3b6f06e50061de metrics: - type: map_at_1 value: 19.961000000000002 - type: map_at_10 value: 28.026 - type: map_at_100 value: 29.212 - type: map_at_1000 value: 29.332 - type: map_at_3 value: 25.296999999999997 - type: map_at_5 value: 26.832 - type: mrr_at_1 value: 24.627 - type: mrr_at_10 value: 33.045 - type: mrr_at_100 value: 33.944 - type: mrr_at_1000 value: 34.013 - type: mrr_at_3 value: 30.307000000000002 - type: mrr_at_5 value: 31.874000000000002 - type: ndcg_at_1 value: 24.627 - type: ndcg_at_10 value: 33.414 - type: ndcg_at_100 value: 39.061 - type: ndcg_at_1000 value: 41.795 - type: ndcg_at_3 value: 28.377000000000002 - type: ndcg_at_5 value: 30.781999999999996 - type: precision_at_1 value: 24.627 - type: precision_at_10 value: 6.02 - type: precision_at_100 value: 1.035 - type: precision_at_1000 value: 0.13899999999999998 - type: precision_at_3 value: 13.516 - type: precision_at_5 value: 9.851 - type: recall_at_1 value: 19.961000000000002 - type: recall_at_10 value: 45.174 - type: recall_at_100 value: 69.69 - type: recall_at_1000 value: 89.24600000000001 - type: recall_at_3 value: 31.062 - type: recall_at_5 value: 37.193 - task: type: Retrieval dataset: name: MTEB CQADupstackPhysicsRetrieval type: mteb/cqadupstack-physics config: default split: test revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4 metrics: - type: map_at_1 value: 32.080999999999996 - type: map_at_10 value: 42.177 - type: map_at_100 value: 43.431999999999995 - type: map_at_1000 value: 43.533 - type: map_at_3 value: 38.721 - type: map_at_5 value: 40.669 - type: mrr_at_1 value: 38.787 - type: mrr_at_10 value: 47.762 - type: mrr_at_100 value: 48.541000000000004 - type: mrr_at_1000 value: 48.581 - type: mrr_at_3 value: 45.123999999999995 - type: mrr_at_5 value: 46.639 - type: ndcg_at_1 value: 38.787 - type: ndcg_at_10 value: 48.094 - type: ndcg_at_100 value: 53.291 - type: ndcg_at_1000 value: 55.21 - type: ndcg_at_3 value: 42.721 - type: ndcg_at_5 value: 45.301 - type: precision_at_1 value: 38.787 - type: precision_at_10 value: 8.576 - type: precision_at_100 value: 1.306 - type: precision_at_1000 value: 0.164 - type: precision_at_3 value: 19.698 - type: precision_at_5 value: 14.013 - type: recall_at_1 value: 32.080999999999996 - type: recall_at_10 value: 59.948 - type: recall_at_100 value: 81.811 - type: recall_at_1000 value: 94.544 - type: recall_at_3 value: 44.903999999999996 - type: recall_at_5 value: 51.763999999999996 - task: type: Retrieval dataset: name: MTEB CQADupstackProgrammersRetrieval type: mteb/cqadupstack-programmers config: default split: test revision: 6184bc1440d2dbc7612be22b50686b8826d22b32 metrics: - type: map_at_1 value: 28.869 - type: map_at_10 value: 38.954 - type: map_at_100 value: 40.233000000000004 - type: map_at_1000 value: 40.332 - type: map_at_3 value: 35.585 - type: map_at_5 value: 37.476 - type: mrr_at_1 value: 35.959 - type: mrr_at_10 value: 44.800000000000004 - type: mrr_at_100 value: 45.609 - type: mrr_at_1000 value: 45.655 - type: mrr_at_3 value: 42.333 - type: mrr_at_5 value: 43.68 - type: ndcg_at_1 value: 35.959 - type: ndcg_at_10 value: 44.957 - type: ndcg_at_100 value: 50.275000000000006 - type: ndcg_at_1000 value: 52.29899999999999 - type: ndcg_at_3 value: 39.797 - type: ndcg_at_5 value: 42.128 - type: precision_at_1 value: 35.959 - type: precision_at_10 value: 8.185 - type: precision_at_100 value: 1.261 - type: precision_at_1000 value: 0.159 - type: precision_at_3 value: 18.988 - type: precision_at_5 value: 13.516 - type: recall_at_1 value: 28.869 - type: recall_at_10 value: 57.154 - type: recall_at_100 value: 79.764 - type: recall_at_1000 value: 93.515 - type: recall_at_3 value: 42.364000000000004 - type: recall_at_5 value: 48.756 - task: type: Retrieval dataset: name: MTEB CQADupstackRetrieval type: mteb/cqadupstack config: default split: test revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4 metrics: - type: map_at_1 value: 29.31008333333333 - type: map_at_10 value: 38.81849999999999 - type: map_at_100 value: 40.05058333333334 - type: map_at_1000 value: 40.16116666666667 - type: map_at_3 value: 35.91441666666667 - type: map_at_5 value: 37.526583333333335 - type: mrr_at_1 value: 34.60066666666667 - type: mrr_at_10 value: 43.08858333333333 - type: mrr_at_100 value: 43.927749999999996 - type: mrr_at_1000 value: 43.97866666666667 - type: mrr_at_3 value: 40.72775 - type: mrr_at_5 value: 42.067249999999994 - type: ndcg_at_1 value: 34.60066666666667 - type: ndcg_at_10 value: 44.20841666666667 - type: ndcg_at_100 value: 49.32866666666667 - type: ndcg_at_1000 value: 51.373999999999995 - type: ndcg_at_3 value: 39.452083333333334 - type: ndcg_at_5 value: 41.67 - type: precision_at_1 value: 34.60066666666667 - type: precision_at_10 value: 7.616583333333334 - type: precision_at_100 value: 1.20175 - type: precision_at_1000 value: 0.156 - type: precision_at_3 value: 17.992 - type: precision_at_5 value: 12.658416666666666 - type: recall_at_1 value: 29.31008333333333 - type: recall_at_10 value: 55.81900000000001 - type: recall_at_100 value: 78.06308333333334 - type: recall_at_1000 value: 92.10641666666668 - type: recall_at_3 value: 42.50166666666667 - type: recall_at_5 value: 48.26108333333333 - task: type: Retrieval dataset: name: MTEB CQADupstackStatsRetrieval type: mteb/cqadupstack-stats config: default split: test revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a metrics: - type: map_at_1 value: 26.773000000000003 - type: map_at_10 value: 34.13 - type: map_at_100 value: 35.113 - type: map_at_1000 value: 35.211 - type: map_at_3 value: 31.958 - type: map_at_5 value: 33.080999999999996 - type: mrr_at_1 value: 30.061 - type: mrr_at_10 value: 37.061 - type: mrr_at_100 value: 37.865 - type: mrr_at_1000 value: 37.939 - type: mrr_at_3 value: 34.995 - type: mrr_at_5 value: 36.092 - type: ndcg_at_1 value: 30.061 - type: ndcg_at_10 value: 38.391999999999996 - type: ndcg_at_100 value: 43.13 - type: ndcg_at_1000 value: 45.449 - type: ndcg_at_3 value: 34.411 - type: ndcg_at_5 value: 36.163000000000004 - type: precision_at_1 value: 30.061 - type: precision_at_10 value: 5.982 - type: precision_at_100 value: 0.911 - type: precision_at_1000 value: 0.11800000000000001 - type: precision_at_3 value: 14.673 - type: precision_at_5 value: 10.030999999999999 - type: recall_at_1 value: 26.773000000000003 - type: recall_at_10 value: 48.445 - type: recall_at_100 value: 69.741 - type: recall_at_1000 value: 86.59 - type: recall_at_3 value: 37.576 - type: recall_at_5 value: 41.948 - task: type: Retrieval dataset: name: MTEB CQADupstackTexRetrieval type: mteb/cqadupstack-tex config: default split: test revision: 46989137a86843e03a6195de44b09deda022eec7 metrics: - type: map_at_1 value: 18.556 - type: map_at_10 value: 26.340999999999998 - type: map_at_100 value: 27.560000000000002 - type: map_at_1000 value: 27.685 - type: map_at_3 value: 24.136 - type: map_at_5 value: 25.34 - type: mrr_at_1 value: 22.368 - type: mrr_at_10 value: 30.192999999999998 - type: mrr_at_100 value: 31.183 - type: mrr_at_1000 value: 31.258000000000003 - type: mrr_at_3 value: 28.223 - type: mrr_at_5 value: 29.294999999999998 - type: ndcg_at_1 value: 22.368 - type: ndcg_at_10 value: 31.029 - type: ndcg_at_100 value: 36.768 - type: ndcg_at_1000 value: 39.572 - type: ndcg_at_3 value: 27.197 - type: ndcg_at_5 value: 28.912 - type: precision_at_1 value: 22.368 - type: precision_at_10 value: 5.606 - type: precision_at_100 value: 0.9979999999999999 - type: precision_at_1000 value: 0.14100000000000001 - type: precision_at_3 value: 12.892999999999999 - type: precision_at_5 value: 9.16 - type: recall_at_1 value: 18.556 - type: recall_at_10 value: 41.087 - type: recall_at_100 value: 66.92 - type: recall_at_1000 value: 86.691 - type: recall_at_3 value: 30.415 - type: recall_at_5 value: 34.813 - task: type: Retrieval dataset: name: MTEB CQADupstackUnixRetrieval type: mteb/cqadupstack-unix config: default split: test revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53 metrics: - type: map_at_1 value: 29.953999999999997 - type: map_at_10 value: 39.633 - type: map_at_100 value: 40.923 - type: map_at_1000 value: 41.016000000000005 - type: map_at_3 value: 36.609 - type: map_at_5 value: 38.443 - type: mrr_at_1 value: 35.354 - type: mrr_at_10 value: 43.718 - type: mrr_at_100 value: 44.651999999999994 - type: mrr_at_1000 value: 44.696000000000005 - type: mrr_at_3 value: 41.154 - type: mrr_at_5 value: 42.730000000000004 - type: ndcg_at_1 value: 35.354 - type: ndcg_at_10 value: 44.933 - type: ndcg_at_100 value: 50.577000000000005 - type: ndcg_at_1000 value: 52.428 - type: ndcg_at_3 value: 39.833 - type: ndcg_at_5 value: 42.465 - type: precision_at_1 value: 35.354 - type: precision_at_10 value: 7.416 - type: precision_at_100 value: 1.157 - type: precision_at_1000 value: 0.14100000000000001 - type: precision_at_3 value: 17.817 - type: precision_at_5 value: 12.687000000000001 - type: recall_at_1 value: 29.953999999999997 - type: recall_at_10 value: 56.932 - type: recall_at_100 value: 80.93900000000001 - type: recall_at_1000 value: 93.582 - type: recall_at_3 value: 43.192 - type: recall_at_5 value: 49.757 - task: type: Retrieval dataset: name: MTEB CQADupstackWebmastersRetrieval type: mteb/cqadupstack-webmasters config: default split: test revision: 160c094312a0e1facb97e55eeddb698c0abe3571 metrics: - type: map_at_1 value: 27.85 - type: map_at_10 value: 37.68 - type: map_at_100 value: 39.295 - type: map_at_1000 value: 39.527 - type: map_at_3 value: 35.036 - type: map_at_5 value: 36.269 - type: mrr_at_1 value: 33.004 - type: mrr_at_10 value: 42.096000000000004 - type: mrr_at_100 value: 43.019 - type: mrr_at_1000 value: 43.071 - type: mrr_at_3 value: 39.987 - type: mrr_at_5 value: 40.995 - type: ndcg_at_1 value: 33.004 - type: ndcg_at_10 value: 43.461 - type: ndcg_at_100 value: 49.138 - type: ndcg_at_1000 value: 51.50900000000001 - type: ndcg_at_3 value: 39.317 - type: ndcg_at_5 value: 40.760999999999996 - type: precision_at_1 value: 33.004 - type: precision_at_10 value: 8.161999999999999 - type: precision_at_100 value: 1.583 - type: precision_at_1000 value: 0.245 - type: precision_at_3 value: 18.445 - type: precision_at_5 value: 12.885 - type: recall_at_1 value: 27.85 - type: recall_at_10 value: 54.419 - type: recall_at_100 value: 79.742 - type: recall_at_1000 value: 93.97 - type: recall_at_3 value: 42.149 - type: recall_at_5 value: 46.165 - task: type: Retrieval dataset: name: MTEB CQADupstackWordpressRetrieval type: mteb/cqadupstack-wordpress config: default split: test revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4 metrics: - type: map_at_1 value: 24.627 - type: map_at_10 value: 32.182 - type: map_at_100 value: 33.217999999999996 - type: map_at_1000 value: 33.32 - type: map_at_3 value: 28.866999999999997 - type: map_at_5 value: 30.871 - type: mrr_at_1 value: 26.987 - type: mrr_at_10 value: 34.37 - type: mrr_at_100 value: 35.301 - type: mrr_at_1000 value: 35.369 - type: mrr_at_3 value: 31.391999999999996 - type: mrr_at_5 value: 33.287 - type: ndcg_at_1 value: 26.987 - type: ndcg_at_10 value: 37.096000000000004 - type: ndcg_at_100 value: 42.158 - type: ndcg_at_1000 value: 44.548 - type: ndcg_at_3 value: 30.913 - type: ndcg_at_5 value: 34.245 - type: precision_at_1 value: 26.987 - type: precision_at_10 value: 5.878 - type: precision_at_100 value: 0.906 - type: precision_at_1000 value: 0.123 - type: precision_at_3 value: 12.815999999999999 - type: precision_at_5 value: 9.612 - type: recall_at_1 value: 24.627 - type: recall_at_10 value: 50.257 - type: recall_at_100 value: 73.288 - type: recall_at_1000 value: 90.97800000000001 - type: recall_at_3 value: 33.823 - type: recall_at_5 value: 41.839 - task: type: Retrieval dataset: name: MTEB ClimateFEVER type: mteb/climate-fever config: default split: test revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380 metrics: - type: map_at_1 value: 17.343 - type: map_at_10 value: 28.59 - type: map_at_100 value: 30.591 - type: map_at_1000 value: 30.759999999999998 - type: map_at_3 value: 24.197 - type: map_at_5 value: 26.433 - type: mrr_at_1 value: 39.609 - type: mrr_at_10 value: 51.107 - type: mrr_at_100 value: 51.87199999999999 - type: mrr_at_1000 value: 51.894 - type: mrr_at_3 value: 48.154 - type: mrr_at_5 value: 49.939 - type: ndcg_at_1 value: 39.609 - type: ndcg_at_10 value: 38.329 - type: ndcg_at_100 value: 45.573 - type: ndcg_at_1000 value: 48.405 - type: ndcg_at_3 value: 32.506 - type: ndcg_at_5 value: 34.331 - type: precision_at_1 value: 39.609 - type: precision_at_10 value: 11.668000000000001 - type: precision_at_100 value: 1.9539999999999997 - type: precision_at_1000 value: 0.249 - type: precision_at_3 value: 23.952 - type: precision_at_5 value: 17.902 - type: recall_at_1 value: 17.343 - type: recall_at_10 value: 43.704 - type: recall_at_100 value: 68.363 - type: recall_at_1000 value: 84.04599999999999 - type: recall_at_3 value: 29.028 - type: recall_at_5 value: 35.022 - task: type: Retrieval dataset: name: MTEB DBPedia type: mteb/dbpedia config: default split: test revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659 metrics: - type: map_at_1 value: 9.934999999999999 - type: map_at_10 value: 22.081 - type: map_at_100 value: 32.036 - type: map_at_1000 value: 33.803 - type: map_at_3 value: 15.687999999999999 - type: map_at_5 value: 18.357 - type: mrr_at_1 value: 70.75 - type: mrr_at_10 value: 78.506 - type: mrr_at_100 value: 78.874 - type: mrr_at_1000 value: 78.88300000000001 - type: mrr_at_3 value: 77.667 - type: mrr_at_5 value: 78.342 - type: ndcg_at_1 value: 57.25 - type: ndcg_at_10 value: 45.286 - type: ndcg_at_100 value: 50.791 - type: ndcg_at_1000 value: 58.021 - type: ndcg_at_3 value: 49.504 - type: ndcg_at_5 value: 47.03 - type: precision_at_1 value: 70.75 - type: precision_at_10 value: 36.425000000000004 - type: precision_at_100 value: 11.953 - type: precision_at_1000 value: 2.248 - type: precision_at_3 value: 53.25 - type: precision_at_5 value: 46.150000000000006 - type: recall_at_1 value: 9.934999999999999 - type: recall_at_10 value: 27.592 - type: recall_at_100 value: 58.089 - type: recall_at_1000 value: 81.025 - type: recall_at_3 value: 17.048 - type: recall_at_5 value: 20.834 - task: type: Classification dataset: name: MTEB EmotionClassification type: mteb/emotion config: default split: test revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 metrics: - type: accuracy value: 47.25999999999999 - type: f1 value: 43.83371155132253 - task: type: Retrieval dataset: name: MTEB FEVER type: mteb/fever config: default split: test revision: bea83ef9e8fb933d90a2f1d5515737465d613e12 metrics: - type: map_at_1 value: 73.68900000000001 - type: map_at_10 value: 82.878 - type: map_at_100 value: 83.084 - type: map_at_1000 value: 83.097 - type: map_at_3 value: 81.528 - type: map_at_5 value: 82.432 - type: mrr_at_1 value: 79.49300000000001 - type: mrr_at_10 value: 87.24300000000001 - type: mrr_at_100 value: 87.3 - type: mrr_at_1000 value: 87.301 - type: mrr_at_3 value: 86.359 - type: mrr_at_5 value: 87.01 - type: ndcg_at_1 value: 79.49300000000001 - type: ndcg_at_10 value: 86.894 - type: ndcg_at_100 value: 87.6 - type: ndcg_at_1000 value: 87.79299999999999 - type: ndcg_at_3 value: 84.777 - type: ndcg_at_5 value: 86.08 - type: precision_at_1 value: 79.49300000000001 - type: precision_at_10 value: 10.578 - type: precision_at_100 value: 1.117 - type: precision_at_1000 value: 0.11499999999999999 - type: precision_at_3 value: 32.592999999999996 - type: precision_at_5 value: 20.423 - type: recall_at_1 value: 73.68900000000001 - type: recall_at_10 value: 94.833 - type: recall_at_100 value: 97.554 - type: recall_at_1000 value: 98.672 - type: recall_at_3 value: 89.236 - type: recall_at_5 value: 92.461 - task: type: Retrieval dataset: name: MTEB FiQA2018 type: mteb/fiqa config: default split: test revision: 27a168819829fe9bcd655c2df245fb19452e8e06 metrics: - type: map_at_1 value: 20.59 - type: map_at_10 value: 34.089000000000006 - type: map_at_100 value: 35.796 - type: map_at_1000 value: 35.988 - type: map_at_3 value: 29.877 - type: map_at_5 value: 32.202999999999996 - type: mrr_at_1 value: 41.049 - type: mrr_at_10 value: 50.370000000000005 - type: mrr_at_100 value: 51.209 - type: mrr_at_1000 value: 51.247 - type: mrr_at_3 value: 48.122 - type: mrr_at_5 value: 49.326 - type: ndcg_at_1 value: 41.049 - type: ndcg_at_10 value: 42.163000000000004 - type: ndcg_at_100 value: 48.638999999999996 - type: ndcg_at_1000 value: 51.775000000000006 - type: ndcg_at_3 value: 38.435 - type: ndcg_at_5 value: 39.561 - type: precision_at_1 value: 41.049 - type: precision_at_10 value: 11.481 - type: precision_at_100 value: 1.8239999999999998 - type: precision_at_1000 value: 0.24 - type: precision_at_3 value: 25.257 - type: precision_at_5 value: 18.519 - type: recall_at_1 value: 20.59 - type: recall_at_10 value: 49.547999999999995 - type: recall_at_100 value: 73.676 - type: recall_at_1000 value: 92.269 - type: recall_at_3 value: 35.656 - type: recall_at_5 value: 41.455 - task: type: Retrieval dataset: name: MTEB HotpotQA type: mteb/hotpotqa config: default split: test revision: ab518f4d6fcca38d87c25209f94beba119d02014 metrics: - type: map_at_1 value: 39.932 - type: map_at_10 value: 64.184 - type: map_at_100 value: 65.06 - type: map_at_1000 value: 65.109 - type: map_at_3 value: 60.27 - type: map_at_5 value: 62.732 - type: mrr_at_1 value: 79.865 - type: mrr_at_10 value: 85.99799999999999 - type: mrr_at_100 value: 86.13 - type: mrr_at_1000 value: 86.13300000000001 - type: mrr_at_3 value: 85.136 - type: mrr_at_5 value: 85.69200000000001 - type: ndcg_at_1 value: 79.865 - type: ndcg_at_10 value: 72.756 - type: ndcg_at_100 value: 75.638 - type: ndcg_at_1000 value: 76.589 - type: ndcg_at_3 value: 67.38199999999999 - type: ndcg_at_5 value: 70.402 - type: precision_at_1 value: 79.865 - type: precision_at_10 value: 15.387999999999998 - type: precision_at_100 value: 1.7610000000000001 - type: precision_at_1000 value: 0.189 - type: precision_at_3 value: 43.394 - type: precision_at_5 value: 28.424 - type: recall_at_1 value: 39.932 - type: recall_at_10 value: 76.941 - type: recall_at_100 value: 88.062 - type: recall_at_1000 value: 94.396 - type: recall_at_3 value: 65.091 - type: recall_at_5 value: 71.06 - task: type: Classification dataset: name: MTEB ImdbClassification type: mteb/imdb config: default split: test revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 metrics: - type: accuracy value: 71.7904 - type: ap value: 65.82899456730257 - type: f1 value: 71.56611877410202 - task: type: Retrieval dataset: name: MTEB MSMARCO type: mteb/msmarco config: default split: dev revision: c5a29a104738b98a9e76336939199e264163d4a0 metrics: - type: map_at_1 value: 21.931 - type: map_at_10 value: 34.849999999999994 - type: map_at_100 value: 36.033 - type: map_at_1000 value: 36.08 - type: map_at_3 value: 30.842000000000002 - type: map_at_5 value: 33.229 - type: mrr_at_1 value: 22.55 - type: mrr_at_10 value: 35.436 - type: mrr_at_100 value: 36.563 - type: mrr_at_1000 value: 36.604 - type: mrr_at_3 value: 31.507 - type: mrr_at_5 value: 33.851 - type: ndcg_at_1 value: 22.55 - type: ndcg_at_10 value: 41.969 - type: ndcg_at_100 value: 47.576 - type: ndcg_at_1000 value: 48.731 - type: ndcg_at_3 value: 33.894000000000005 - type: ndcg_at_5 value: 38.133 - type: precision_at_1 value: 22.55 - type: precision_at_10 value: 6.660000000000001 - type: precision_at_100 value: 0.946 - type: precision_at_1000 value: 0.104 - type: precision_at_3 value: 14.532 - type: precision_at_5 value: 10.865 - type: recall_at_1 value: 21.931 - type: recall_at_10 value: 63.841 - type: recall_at_100 value: 89.47699999999999 - type: recall_at_1000 value: 98.259 - type: recall_at_3 value: 42.063 - type: recall_at_5 value: 52.21 - task: type: Classification dataset: name: MTEB MTOPDomainClassification (en) type: mteb/mtop_domain config: en split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics: - type: accuracy value: 93.03921568627452 - type: f1 value: 92.56400672314416 - task: type: Classification dataset: name: MTEB MTOPIntentClassification (en) type: mteb/mtop_intent config: en split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics: - type: accuracy value: 63.515731874145 - type: f1 value: 44.922310875523216 - task: type: Classification dataset: name: MTEB MasakhaNEWSClassification (eng) type: masakhane/masakhanews config: eng split: test revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 metrics: - type: accuracy value: 77.57383966244727 - type: f1 value: 76.55222378218293 - task: type: Clustering dataset: name: MTEB MasakhaNEWSClusteringP2P (eng) type: masakhane/masakhanews config: eng split: test revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 metrics: - type: v_measure value: 62.74836240280833 - type: v_measure value: 24.414348715238184 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (en) type: mteb/amazon_massive_intent config: en split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 66.54673839946201 - type: f1 value: 64.61004101532164 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (en) type: mteb/amazon_massive_scenario config: en split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 73.11365164761264 - type: f1 value: 72.01684013680978 - task: type: Clustering dataset: name: MTEB MedrxivClusteringP2P type: mteb/medrxiv-clustering-p2p config: default split: test revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 metrics: - type: v_measure value: 31.123671999617297 - task: type: Clustering dataset: name: MTEB MedrxivClusteringS2S type: mteb/medrxiv-clustering-s2s config: default split: test revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 metrics: - type: v_measure value: 26.72684341430875 - task: type: Reranking dataset: name: MTEB MindSmallReranking type: mteb/mind_small config: default split: test revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 metrics: - type: map value: 29.910228061734816 - type: mrr value: 30.835255982532477 - task: type: Retrieval dataset: name: MTEB NFCorpus type: mteb/nfcorpus config: default split: test revision: ec0fa4fe99da2ff19ca1214b7966684033a58814 metrics: - type: map_at_1 value: 5.6770000000000005 - type: map_at_10 value: 13.15 - type: map_at_100 value: 16.205 - type: map_at_1000 value: 17.580000000000002 - type: map_at_3 value: 9.651 - type: map_at_5 value: 11.142000000000001 - type: mrr_at_1 value: 47.678 - type: mrr_at_10 value: 56.257000000000005 - type: mrr_at_100 value: 56.708000000000006 - type: mrr_at_1000 value: 56.751 - type: mrr_at_3 value: 54.128 - type: mrr_at_5 value: 55.181000000000004 - type: ndcg_at_1 value: 45.511 - type: ndcg_at_10 value: 35.867 - type: ndcg_at_100 value: 31.566 - type: ndcg_at_1000 value: 40.077 - type: ndcg_at_3 value: 41.9 - type: ndcg_at_5 value: 39.367999999999995 - type: precision_at_1 value: 47.678 - type: precision_at_10 value: 26.842 - type: precision_at_100 value: 7.991 - type: precision_at_1000 value: 2.0469999999999997 - type: precision_at_3 value: 39.938 - type: precision_at_5 value: 34.613 - type: recall_at_1 value: 5.6770000000000005 - type: recall_at_10 value: 17.119999999999997 - type: recall_at_100 value: 30.828 - type: recall_at_1000 value: 62.082 - type: recall_at_3 value: 10.456 - type: recall_at_5 value: 12.903999999999998 - task: type: Retrieval dataset: name: MTEB NQ type: mteb/nq config: default split: test revision: b774495ed302d8c44a3a7ea25c90dbce03968f31 metrics: - type: map_at_1 value: 39.021 - type: map_at_10 value: 54.976 - type: map_at_100 value: 55.793000000000006 - type: map_at_1000 value: 55.811 - type: map_at_3 value: 50.759 - type: map_at_5 value: 53.429 - type: mrr_at_1 value: 43.308 - type: mrr_at_10 value: 57.118 - type: mrr_at_100 value: 57.69499999999999 - type: mrr_at_1000 value: 57.704 - type: mrr_at_3 value: 53.848 - type: mrr_at_5 value: 55.915000000000006 - type: ndcg_at_1 value: 43.308 - type: ndcg_at_10 value: 62.33800000000001 - type: ndcg_at_100 value: 65.61099999999999 - type: ndcg_at_1000 value: 65.995 - type: ndcg_at_3 value: 54.723 - type: ndcg_at_5 value: 59.026 - type: precision_at_1 value: 43.308 - type: precision_at_10 value: 9.803 - type: precision_at_100 value: 1.167 - type: precision_at_1000 value: 0.121 - type: precision_at_3 value: 24.334 - type: precision_at_5 value: 17.144000000000002 - type: recall_at_1 value: 39.021 - type: recall_at_10 value: 82.37299999999999 - type: recall_at_100 value: 96.21499999999999 - type: recall_at_1000 value: 99.02499999999999 - type: recall_at_3 value: 63.031000000000006 - type: recall_at_5 value: 72.856 - task: type: Classification dataset: name: MTEB NewsClassification type: ag_news config: default split: test revision: eb185aade064a813bc0b7f42de02595523103ca4 metrics: - type: accuracy value: 78.03289473684211 - type: f1 value: 77.89323745730803 - task: type: PairClassification dataset: name: MTEB OpusparcusPC (en) type: GEM/opusparcus config: en split: test revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a metrics: - type: cos_sim_accuracy value: 99.89816700610999 - type: cos_sim_ap value: 100.0 - type: cos_sim_f1 value: 99.9490575649516 - type: cos_sim_precision value: 100.0 - type: cos_sim_recall value: 99.89816700610999 - type: dot_accuracy value: 99.89816700610999 - type: dot_ap value: 100.0 - type: dot_f1 value: 99.9490575649516 - type: dot_precision value: 100.0 - type: dot_recall value: 99.89816700610999 - type: euclidean_accuracy value: 99.89816700610999 - type: euclidean_ap value: 100.0 - type: euclidean_f1 value: 99.9490575649516 - type: euclidean_precision value: 100.0 - type: euclidean_recall value: 99.89816700610999 - type: manhattan_accuracy value: 99.89816700610999 - type: manhattan_ap value: 100.0 - type: manhattan_f1 value: 99.9490575649516 - type: manhattan_precision value: 100.0 - type: manhattan_recall value: 99.89816700610999 - type: max_accuracy value: 99.89816700610999 - type: max_ap value: 100.0 - type: max_f1 value: 99.9490575649516 - task: type: PairClassification dataset: name: MTEB PawsX (en) type: paws-x config: en split: test revision: 8a04d940a42cd40658986fdd8e3da561533a3646 metrics: - type: cos_sim_accuracy value: 61.75000000000001 - type: cos_sim_ap value: 59.578879568280385 - type: cos_sim_f1 value: 62.50861474844934 - type: cos_sim_precision value: 45.46365914786967 - type: cos_sim_recall value: 100.0 - type: dot_accuracy value: 61.75000000000001 - type: dot_ap value: 59.57893088951573 - type: dot_f1 value: 62.50861474844934 - type: dot_precision value: 45.46365914786967 - type: dot_recall value: 100.0 - type: euclidean_accuracy value: 61.75000000000001 - type: euclidean_ap value: 59.578755624671686 - type: euclidean_f1 value: 62.50861474844934 - type: euclidean_precision value: 45.46365914786967 - type: euclidean_recall value: 100.0 - type: manhattan_accuracy value: 61.75000000000001 - type: manhattan_ap value: 59.58504334461159 - type: manhattan_f1 value: 62.50861474844934 - type: manhattan_precision value: 45.46365914786967 - type: manhattan_recall value: 100.0 - type: max_accuracy value: 61.75000000000001 - type: max_ap value: 59.58504334461159 - type: max_f1 value: 62.50861474844934 - task: type: Retrieval dataset: name: MTEB QuoraRetrieval type: mteb/quora config: default split: test revision: e4e08e0b7dbe3c8700f0daef558ff32256715259 metrics: - type: map_at_1 value: 70.186 - type: map_at_10 value: 83.875 - type: map_at_100 value: 84.514 - type: map_at_1000 value: 84.53500000000001 - type: map_at_3 value: 80.926 - type: map_at_5 value: 82.797 - type: mrr_at_1 value: 80.82000000000001 - type: mrr_at_10 value: 87.068 - type: mrr_at_100 value: 87.178 - type: mrr_at_1000 value: 87.18 - type: mrr_at_3 value: 86.055 - type: mrr_at_5 value: 86.763 - type: ndcg_at_1 value: 80.84 - type: ndcg_at_10 value: 87.723 - type: ndcg_at_100 value: 88.98700000000001 - type: ndcg_at_1000 value: 89.13499999999999 - type: ndcg_at_3 value: 84.821 - type: ndcg_at_5 value: 86.441 - type: precision_at_1 value: 80.84 - type: precision_at_10 value: 13.270000000000001 - type: precision_at_100 value: 1.516 - type: precision_at_1000 value: 0.156 - type: precision_at_3 value: 37.013 - type: precision_at_5 value: 24.37 - type: recall_at_1 value: 70.186 - type: recall_at_10 value: 94.948 - type: recall_at_100 value: 99.223 - type: recall_at_1000 value: 99.932 - type: recall_at_3 value: 86.57000000000001 - type: recall_at_5 value: 91.157 - task: type: Clustering dataset: name: MTEB RedditClustering type: mteb/reddit-clustering config: default split: test revision: 24640382cdbf8abc73003fb0fa6d111a705499eb metrics: - type: v_measure value: 50.24198927949519 - task: type: Clustering dataset: name: MTEB RedditClusteringP2P type: mteb/reddit-clustering-p2p config: default split: test revision: 385e3cb46b4cfa89021f56c4380204149d0efe33 metrics: - type: v_measure value: 61.452073078765544 - task: type: Retrieval dataset: name: MTEB SCIDOCS type: mteb/scidocs config: default split: test revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88 metrics: - type: map_at_1 value: 4.972 - type: map_at_10 value: 12.314 - type: map_at_100 value: 14.333000000000002 - type: map_at_1000 value: 14.628 - type: map_at_3 value: 8.972 - 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type: euclidean_pearson value: 79.4830436509311 - type: euclidean_spearman value: 79.82293444619499 - type: manhattan_pearson value: 79.49785594799296 - type: manhattan_spearman value: 79.8280390479434 - task: type: STS dataset: name: MTEB STS14 type: mteb/sts14-sts config: default split: test revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 metrics: - type: cos_sim_pearson value: 76.36839628231121 - type: cos_sim_spearman value: 73.63809739428072 - type: euclidean_pearson value: 74.93718121215906 - type: euclidean_spearman value: 73.63810227650436 - type: manhattan_pearson value: 74.8737197659424 - type: manhattan_spearman value: 73.57534688126572 - task: type: STS dataset: name: MTEB STS15 type: mteb/sts15-sts config: default split: test revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 metrics: - type: cos_sim_pearson value: 82.67482138157656 - type: cos_sim_spearman value: 83.23485786963107 - type: euclidean_pearson value: 82.50847772197369 - type: euclidean_spearman value: 83.23485786963107 - 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task: type: STS dataset: name: MTEB STS22 (en) type: mteb/sts22-crosslingual-sts config: en split: test revision: eea2b4fe26a775864c896887d910b76a8098ad3f metrics: - type: cos_sim_pearson value: 68.34450491529164 - type: cos_sim_spearman value: 68.79451793414492 - type: euclidean_pearson value: 68.75619738499324 - type: euclidean_spearman value: 68.79451793414492 - type: manhattan_pearson value: 68.75256119543882 - type: manhattan_spearman value: 68.81836416978547 - task: type: STS dataset: name: MTEB STSBenchmark type: mteb/stsbenchmark-sts config: default split: test revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 metrics: - type: cos_sim_pearson value: 77.95580414975612 - type: cos_sim_spearman value: 77.89671867168987 - type: euclidean_pearson value: 77.61352097720862 - type: euclidean_spearman value: 77.89671867168987 - type: manhattan_pearson value: 77.65282228135632 - type: manhattan_spearman value: 77.91730533156762 - task: type: STS dataset: name: MTEB STSBenchmarkMultilingualSTS (en) type: PhilipMay/stsb_multi_mt config: en split: test revision: 93d57ef91790589e3ce9c365164337a8a78b7632 metrics: - type: cos_sim_pearson value: 77.95580421496413 - type: cos_sim_spearman value: 77.89671867168987 - type: euclidean_pearson value: 77.61352107168794 - type: euclidean_spearman value: 77.89671867168987 - type: manhattan_pearson value: 77.65282237231794 - type: manhattan_spearman value: 77.91730533156762 - task: type: Reranking dataset: name: MTEB SciDocsRR type: mteb/scidocs-reranking config: default split: test revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab metrics: - type: map value: 79.22928110092924 - type: mrr value: 94.46700902583257 - task: type: Retrieval dataset: name: MTEB SciFact type: mteb/scifact config: default split: test revision: 0228b52cf27578f30900b9e5271d331663a030d7 metrics: - type: map_at_1 value: 56.011 - type: map_at_10 value: 65.544 - type: map_at_100 value: 66.034 - type: map_at_1000 value: 66.065 - type: map_at_3 value: 63.077000000000005 - type: map_at_5 value: 64.354 - type: mrr_at_1 value: 59.0 - type: mrr_at_10 value: 66.74900000000001 - type: mrr_at_100 value: 67.176 - type: mrr_at_1000 value: 67.203 - type: mrr_at_3 value: 65.056 - type: mrr_at_5 value: 65.956 - type: ndcg_at_1 value: 59.0 - type: ndcg_at_10 value: 69.95599999999999 - type: ndcg_at_100 value: 72.27 - type: ndcg_at_1000 value: 73.066 - type: ndcg_at_3 value: 65.837 - type: ndcg_at_5 value: 67.633 - type: precision_at_1 value: 59.0 - type: precision_at_10 value: 9.333 - type: precision_at_100 value: 1.053 - type: precision_at_1000 value: 0.11199999999999999 - type: precision_at_3 value: 26.0 - type: precision_at_5 value: 16.866999999999997 - type: recall_at_1 value: 56.011 - type: recall_at_10 value: 82.133 - type: recall_at_100 value: 92.767 - type: recall_at_1000 value: 99.0 - type: recall_at_3 value: 70.95 - type: recall_at_5 value: 75.556 - task: type: PairClassification dataset: name: MTEB SprintDuplicateQuestions type: mteb/sprintduplicatequestions-pairclassification config: default split: test revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 metrics: - type: cos_sim_accuracy value: 99.81584158415842 - 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type: v_measure value: 62.63494511649264 - task: type: Clustering dataset: name: MTEB StackExchangeClusteringP2P type: mteb/stackexchange-clustering-p2p config: default split: test revision: 815ca46b2622cec33ccafc3735d572c266efdb44 metrics: - type: v_measure value: 37.165838327685755 - task: type: Reranking dataset: name: MTEB StackOverflowDupQuestions type: mteb/stackoverflowdupquestions-reranking config: default split: test revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 metrics: - type: map value: 51.384873075208084 - type: mrr value: 52.196439181733304 - task: type: Summarization dataset: name: MTEB SummEval type: mteb/summeval config: default split: test revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c metrics: - type: cos_sim_pearson value: 32.13690355567596 - type: cos_sim_spearman value: 31.38349778638125 - type: dot_pearson value: 32.13689596691593 - type: dot_spearman value: 31.38349778638125 - task: type: Retrieval dataset: name: MTEB TRECCOVID type: mteb/trec-covid config: default split: test revision: bb9466bac8153a0349341eb1b22e06409e78ef4e metrics: - type: map_at_1 value: 0.26 - type: map_at_10 value: 2.08 - type: map_at_100 value: 12.598 - type: map_at_1000 value: 30.119 - type: map_at_3 value: 0.701 - type: map_at_5 value: 1.11 - type: mrr_at_1 value: 96.0 - type: mrr_at_10 value: 97.167 - type: mrr_at_100 value: 97.167 - type: mrr_at_1000 value: 97.167 - type: mrr_at_3 value: 96.667 - type: mrr_at_5 value: 97.167 - type: ndcg_at_1 value: 91.0 - type: ndcg_at_10 value: 81.69800000000001 - type: ndcg_at_100 value: 62.9 - type: ndcg_at_1000 value: 55.245999999999995 - type: ndcg_at_3 value: 86.397 - type: ndcg_at_5 value: 84.286 - type: precision_at_1 value: 96.0 - type: precision_at_10 value: 87.0 - type: precision_at_100 value: 64.86 - type: precision_at_1000 value: 24.512 - type: precision_at_3 value: 90.667 - type: precision_at_5 value: 88.8 - type: recall_at_1 value: 0.26 - type: recall_at_10 value: 2.238 - type: recall_at_100 value: 15.488 - type: recall_at_1000 value: 51.6 - type: recall_at_3 value: 0.716 - type: recall_at_5 value: 1.151 - task: type: Retrieval dataset: name: MTEB Touche2020 type: mteb/touche2020 config: default split: test revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f metrics: - type: map_at_1 value: 3.376 - type: map_at_10 value: 13.142000000000001 - type: map_at_100 value: 19.763 - type: map_at_1000 value: 21.319 - type: map_at_3 value: 6.805999999999999 - type: map_at_5 value: 8.952 - type: mrr_at_1 value: 46.939 - type: mrr_at_10 value: 61.082 - type: mrr_at_100 value: 61.45 - type: mrr_at_1000 value: 61.468999999999994 - type: mrr_at_3 value: 57.483 - type: mrr_at_5 value: 59.931999999999995 - type: ndcg_at_1 value: 44.897999999999996 - type: ndcg_at_10 value: 32.35 - type: ndcg_at_100 value: 42.719 - type: ndcg_at_1000 value: 53.30200000000001 - type: ndcg_at_3 value: 37.724999999999994 - type: ndcg_at_5 value: 34.79 - type: precision_at_1 value: 46.939 - type: precision_at_10 value: 28.366999999999997 - type: precision_at_100 value: 8.429 - type: precision_at_1000 value: 1.557 - type: precision_at_3 value: 38.095 - type: precision_at_5 value: 33.469 - type: recall_at_1 value: 3.376 - type: recall_at_10 value: 20.164 - type: recall_at_100 value: 50.668 - type: recall_at_1000 value: 83.159 - type: recall_at_3 value: 8.155 - type: recall_at_5 value: 11.872 - task: type: Classification dataset: name: MTEB ToxicConversationsClassification type: mteb/toxic_conversations_50k config: default split: test revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de metrics: - type: accuracy value: 66.739 - type: ap value: 12.17931839228834 - type: f1 value: 51.05383188624636 - task: type: Classification dataset: name: MTEB TweetSentimentExtractionClassification type: mteb/tweet_sentiment_extraction config: default split: test revision: d604517c81ca91fe16a244d1248fc021f9ecee7a metrics: - type: accuracy value: 56.72891907187323 - type: f1 value: 56.997614557150946 - task: type: Clustering dataset: name: MTEB TwentyNewsgroupsClustering type: mteb/twentynewsgroups-clustering config: default split: test revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 metrics: - type: v_measure value: 39.825318429345224 - task: type: PairClassification dataset: name: MTEB TwitterSemEval2015 type: mteb/twittersemeval2015-pairclassification config: default split: test revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 metrics: - type: cos_sim_accuracy value: 83.65619598259522 - type: cos_sim_ap value: 66.17412885183877 - type: cos_sim_f1 value: 63.09125656951745 - type: cos_sim_precision value: 57.63858577040594 - type: cos_sim_recall value: 69.68337730870712 - type: dot_accuracy value: 83.65619598259522 - type: dot_ap value: 66.17413621964548 - type: dot_f1 value: 63.09125656951745 - type: dot_precision value: 57.63858577040594 - type: dot_recall value: 69.68337730870712 - type: euclidean_accuracy value: 83.65619598259522 - type: euclidean_ap value: 66.17412836413126 - type: euclidean_f1 value: 63.09125656951745 - type: euclidean_precision value: 57.63858577040594 - type: euclidean_recall value: 69.68337730870712 - type: manhattan_accuracy value: 83.5548667819038 - type: manhattan_ap value: 66.07998834521334 - type: manhattan_f1 value: 62.96433419721092 - type: manhattan_precision value: 59.14676559239509 - type: manhattan_recall value: 67.30870712401055 - type: max_accuracy value: 83.65619598259522 - type: max_ap value: 66.17413621964548 - type: max_f1 value: 63.09125656951745 - task: type: PairClassification dataset: name: MTEB TwitterURLCorpus type: mteb/twitterurlcorpus-pairclassification config: default split: test revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf metrics: - type: cos_sim_accuracy value: 88.55706911941631 - type: cos_sim_ap value: 85.20971331546805 - type: cos_sim_f1 value: 77.28446050593702 - type: cos_sim_precision value: 74.16135881104033 - type: cos_sim_recall value: 80.6821681552202 - type: dot_accuracy value: 88.55706911941631 - type: dot_ap value: 85.2097154112633 - type: dot_f1 value: 77.28446050593702 - type: dot_precision value: 74.16135881104033 - type: dot_recall value: 80.6821681552202 - type: euclidean_accuracy value: 88.55706911941631 - type: euclidean_ap value: 85.20971719214488 - type: euclidean_f1 value: 77.28446050593702 - type: euclidean_precision value: 74.16135881104033 - type: euclidean_recall value: 80.6821681552202 - type: manhattan_accuracy value: 88.52020025614158 - type: manhattan_ap value: 85.17569799117058 - type: manhattan_f1 value: 77.27157773040933 - type: manhattan_precision value: 72.79286638077734 - type: manhattan_recall value: 82.33754234678165 - type: max_accuracy value: 88.55706911941631 - type: max_ap value: 85.20971719214488 - type: max_f1 value: 77.28446050593702 - task: type: Clustering dataset: name: MTEB WikiCitiesClustering type: jinaai/cities_wiki_clustering config: default split: test revision: ddc9ee9242fa65332597f70e967ecc38b9d734fa metrics: - type: v_measure value: 85.63474850264893 --- # yixuan-chia/snowflake-arctic-embed-m-long-Q8_0-GGUF This model was converted to GGUF format from [`Snowflake/snowflake-arctic-embed-m-long`](https://huggingface.co/Snowflake/snowflake-arctic-embed-m-long) 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/Snowflake/snowflake-arctic-embed-m-long) 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 yixuan-chia/snowflake-arctic-embed-m-long-Q8_0-GGUF --hf-file snowflake-arctic-embed-m-long-q8_0.gguf -p "The meaning to life and the universe is" ``` ### Server: ```bash llama-server --hf-repo yixuan-chia/snowflake-arctic-embed-m-long-Q8_0-GGUF --hf-file snowflake-arctic-embed-m-long-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 yixuan-chia/snowflake-arctic-embed-m-long-Q8_0-GGUF --hf-file snowflake-arctic-embed-m-long-q8_0.gguf -p "The meaning to life and the universe is" ``` or ``` ./llama-server --hf-repo yixuan-chia/snowflake-arctic-embed-m-long-Q8_0-GGUF --hf-file snowflake-arctic-embed-m-long-q8_0.gguf -c 2048 ```