--- base_model: Snowflake/snowflake-arctic-embed-s 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-snowflake-arctic-embed-s results: - task: type: Classification dataset: name: MTEB AmazonCounterfactualClassification (en) type: mteb/amazon_counterfactual config: en split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics: - type: accuracy value: 71.17910447761193 - type: ap value: 33.15833652904991 - type: f1 value: 64.86214791591543 - task: type: Classification dataset: name: MTEB AmazonPolarityClassification type: mteb/amazon_polarity config: default split: test revision: e2d317d38cd51312af73b3d32a06d1a08b442046 metrics: - type: accuracy value: 78.750325 - type: ap value: 72.83242788470943 - type: f1 value: 78.63968044029453 - task: type: Classification dataset: name: MTEB AmazonReviewsClassification (en) type: mteb/amazon_reviews_multi config: en split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics: - type: accuracy value: 38.264 - type: f1 value: 37.140269688532825 - task: type: Retrieval dataset: name: MTEB ArguAna type: mteb/arguana config: default split: test revision: c22ab2a51041ffd869aaddef7af8d8215647e41a metrics: - type: map_at_1 value: 32.646 - type: map_at_10 value: 48.372 - type: map_at_100 value: 49.207 - type: map_at_1000 value: 49.214 - type: map_at_3 value: 43.611 - type: map_at_5 value: 46.601 - type: mrr_at_1 value: 33.144 - type: mrr_at_10 value: 48.557 - type: mrr_at_100 value: 49.385 - type: mrr_at_1000 value: 49.392 - type: mrr_at_3 value: 43.777 - type: mrr_at_5 value: 46.792 - type: ndcg_at_1 value: 32.646 - type: ndcg_at_10 value: 56.874 - type: ndcg_at_100 value: 60.307 - type: ndcg_at_1000 value: 60.465999999999994 - type: ndcg_at_3 value: 47.339999999999996 - type: ndcg_at_5 value: 52.685 - type: precision_at_1 value: 32.646 - type: precision_at_10 value: 8.378 - type: precision_at_100 value: 0.984 - type: precision_at_1000 value: 0.1 - type: precision_at_3 value: 19.393 - type: precision_at_5 value: 14.210999999999999 - type: recall_at_1 value: 32.646 - type: recall_at_10 value: 83.784 - type: recall_at_100 value: 98.43499999999999 - type: recall_at_1000 value: 99.644 - type: recall_at_3 value: 58.179 - type: recall_at_5 value: 71.053 - task: type: Clustering dataset: name: MTEB ArxivClusteringP2P type: mteb/arxiv-clustering-p2p config: default split: test revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d metrics: - type: v_measure value: 44.94353025039141 - task: type: Clustering dataset: name: MTEB ArxivClusteringS2S type: mteb/arxiv-clustering-s2s config: default split: test revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 metrics: - type: v_measure value: 35.870836103029156 - task: type: Reranking dataset: name: MTEB AskUbuntuDupQuestions type: mteb/askubuntudupquestions-reranking config: default split: test revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 metrics: - type: map value: 61.149290266979236 - type: mrr value: 73.8448093919008 - task: type: STS dataset: name: MTEB BIOSSES type: mteb/biosses-sts config: default split: test revision: d3fb88f8f02e40887cd149695127462bbcf29b4a metrics: - type: cos_sim_pearson value: 87.055571064151 - type: cos_sim_spearman value: 86.2652186235749 - type: euclidean_pearson value: 85.82039272282503 - type: euclidean_spearman value: 86.2652186235749 - type: manhattan_pearson value: 85.95825392094812 - type: manhattan_spearman value: 86.6742640885316 - task: type: Classification dataset: name: MTEB Banking77Classification type: mteb/banking77 config: default split: test revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 metrics: - type: accuracy value: 79.11688311688312 - type: f1 value: 78.28328901613885 - task: type: Clustering dataset: name: MTEB BigPatentClustering type: jinaai/big-patent-clustering config: default split: test revision: 62d5330920bca426ce9d3c76ea914f15fc83e891 metrics: - type: v_measure value: 19.147523589859325 - task: type: Clustering dataset: name: MTEB BiorxivClusteringP2P type: mteb/biorxiv-clustering-p2p config: default split: test revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 metrics: - type: v_measure value: 35.68369864124274 - task: type: Clustering dataset: name: MTEB BiorxivClusteringS2S type: mteb/biorxiv-clustering-s2s config: default split: test revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 metrics: - type: v_measure value: 30.474958792950872 - task: type: Retrieval dataset: name: MTEB CQADupstackAndroidRetrieval type: mteb/cqadupstack-android config: default split: test revision: f46a197baaae43b4f621051089b82a364682dfeb metrics: - type: map_at_1 value: 33.183 - type: map_at_10 value: 43.989 - type: map_at_100 value: 45.389 - type: map_at_1000 value: 45.517 - type: map_at_3 value: 40.275 - type: map_at_5 value: 42.306 - type: mrr_at_1 value: 40.486 - type: mrr_at_10 value: 49.62 - type: mrr_at_100 value: 50.351 - type: mrr_at_1000 value: 50.393 - type: mrr_at_3 value: 46.805 - type: mrr_at_5 value: 48.429 - type: ndcg_at_1 value: 40.486 - type: ndcg_at_10 value: 50.249 - type: ndcg_at_100 value: 55.206 - type: ndcg_at_1000 value: 57.145 - type: ndcg_at_3 value: 44.852 - type: ndcg_at_5 value: 47.355000000000004 - type: precision_at_1 value: 40.486 - type: precision_at_10 value: 9.571 - type: precision_at_100 value: 1.4949999999999999 - type: precision_at_1000 value: 0.196 - type: precision_at_3 value: 21.173000000000002 - type: precision_at_5 value: 15.622 - type: recall_at_1 value: 33.183 - type: recall_at_10 value: 62.134 - type: recall_at_100 value: 82.73 - type: recall_at_1000 value: 94.93599999999999 - type: recall_at_3 value: 46.497 - type: recall_at_5 value: 53.199 - task: type: Retrieval dataset: name: MTEB CQADupstackEnglishRetrieval type: mteb/cqadupstack-english config: default split: test revision: ad9991cb51e31e31e430383c75ffb2885547b5f0 metrics: - type: map_at_1 value: 32.862 - type: map_at_10 value: 42.439 - type: map_at_100 value: 43.736999999999995 - type: map_at_1000 value: 43.864 - type: map_at_3 value: 39.67 - type: map_at_5 value: 41.202 - type: mrr_at_1 value: 40.892 - type: mrr_at_10 value: 48.61 - type: mrr_at_100 value: 49.29 - type: mrr_at_1000 value: 49.332 - type: mrr_at_3 value: 46.688 - type: mrr_at_5 value: 47.803000000000004 - type: ndcg_at_1 value: 40.892 - type: ndcg_at_10 value: 47.797 - type: ndcg_at_100 value: 52.17699999999999 - type: ndcg_at_1000 value: 54.127 - type: ndcg_at_3 value: 44.189 - type: ndcg_at_5 value: 45.821 - type: precision_at_1 value: 40.892 - type: precision_at_10 value: 8.841000000000001 - type: precision_at_100 value: 1.419 - type: precision_at_1000 value: 0.188 - type: precision_at_3 value: 21.104 - type: precision_at_5 value: 14.777000000000001 - type: recall_at_1 value: 32.862 - type: recall_at_10 value: 56.352999999999994 - type: recall_at_100 value: 74.795 - type: recall_at_1000 value: 86.957 - type: recall_at_3 value: 45.269999999999996 - type: recall_at_5 value: 50.053000000000004 - task: type: Retrieval dataset: name: MTEB CQADupstackGamingRetrieval type: mteb/cqadupstack-gaming config: default split: test revision: 4885aa143210c98657558c04aaf3dc47cfb54340 metrics: - type: map_at_1 value: 42.998999999999995 - type: map_at_10 value: 54.745 - type: map_at_100 value: 55.650999999999996 - type: map_at_1000 value: 55.703 - type: map_at_3 value: 51.67 - type: map_at_5 value: 53.503 - type: mrr_at_1 value: 49.028 - type: mrr_at_10 value: 58.172000000000004 - type: mrr_at_100 value: 58.744 - type: mrr_at_1000 value: 58.769000000000005 - type: mrr_at_3 value: 55.977 - type: mrr_at_5 value: 57.38799999999999 - type: ndcg_at_1 value: 49.028 - type: ndcg_at_10 value: 60.161 - type: ndcg_at_100 value: 63.806 - type: ndcg_at_1000 value: 64.821 - type: ndcg_at_3 value: 55.199 - type: ndcg_at_5 value: 57.830999999999996 - type: precision_at_1 value: 49.028 - type: precision_at_10 value: 9.455 - type: precision_at_100 value: 1.216 - type: precision_at_1000 value: 0.135 - type: precision_at_3 value: 24.242 - type: precision_at_5 value: 16.614 - type: recall_at_1 value: 42.998999999999995 - type: recall_at_10 value: 72.542 - type: recall_at_100 value: 88.605 - type: recall_at_1000 value: 95.676 - type: recall_at_3 value: 59.480999999999995 - type: recall_at_5 value: 65.886 - task: type: Retrieval dataset: name: MTEB CQADupstackGisRetrieval type: mteb/cqadupstack-gis config: default split: test revision: 5003b3064772da1887988e05400cf3806fe491f2 metrics: - type: map_at_1 value: 27.907 - type: map_at_10 value: 35.975 - type: map_at_100 value: 36.985 - type: map_at_1000 value: 37.063 - type: map_at_3 value: 33.467999999999996 - type: map_at_5 value: 34.749 - type: mrr_at_1 value: 30.056 - type: mrr_at_10 value: 38.047 - type: mrr_at_100 value: 38.932 - type: mrr_at_1000 value: 38.991 - type: mrr_at_3 value: 35.705999999999996 - type: mrr_at_5 value: 36.966 - type: ndcg_at_1 value: 30.056 - type: ndcg_at_10 value: 40.631 - type: ndcg_at_100 value: 45.564 - type: ndcg_at_1000 value: 47.685 - type: ndcg_at_3 value: 35.748000000000005 - type: ndcg_at_5 value: 37.921 - type: precision_at_1 value: 30.056 - type: precision_at_10 value: 6.079 - type: precision_at_100 value: 0.898 - type: precision_at_1000 value: 0.11199999999999999 - type: precision_at_3 value: 14.727 - type: precision_at_5 value: 10.056 - type: recall_at_1 value: 27.907 - type: recall_at_10 value: 52.981 - type: recall_at_100 value: 75.53999999999999 - type: recall_at_1000 value: 91.759 - type: recall_at_3 value: 39.878 - type: recall_at_5 value: 45.077 - task: type: Retrieval dataset: name: MTEB CQADupstackMathematicaRetrieval type: mteb/cqadupstack-mathematica config: default split: test revision: 90fceea13679c63fe563ded68f3b6f06e50061de metrics: - type: map_at_1 value: 16.764000000000003 - type: map_at_10 value: 24.294 - type: map_at_100 value: 25.507999999999996 - type: map_at_1000 value: 25.64 - type: map_at_3 value: 21.807000000000002 - type: map_at_5 value: 23.21 - type: mrr_at_1 value: 20.771 - type: mrr_at_10 value: 28.677000000000003 - type: mrr_at_100 value: 29.742 - type: mrr_at_1000 value: 29.816 - type: mrr_at_3 value: 26.327 - type: mrr_at_5 value: 27.639000000000003 - type: ndcg_at_1 value: 20.771 - type: ndcg_at_10 value: 29.21 - type: ndcg_at_100 value: 34.788000000000004 - type: ndcg_at_1000 value: 37.813 - type: ndcg_at_3 value: 24.632 - type: ndcg_at_5 value: 26.801000000000002 - type: precision_at_1 value: 20.771 - type: precision_at_10 value: 5.373 - type: precision_at_100 value: 0.923 - type: precision_at_1000 value: 0.133 - type: precision_at_3 value: 12.065 - type: precision_at_5 value: 8.706 - type: recall_at_1 value: 16.764000000000003 - type: recall_at_10 value: 40.072 - type: recall_at_100 value: 63.856 - type: recall_at_1000 value: 85.141 - type: recall_at_3 value: 27.308 - type: recall_at_5 value: 32.876 - task: type: Retrieval dataset: name: MTEB CQADupstackPhysicsRetrieval type: mteb/cqadupstack-physics config: default split: test revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4 metrics: - type: map_at_1 value: 31.194 - type: map_at_10 value: 40.731 - type: map_at_100 value: 42.073 - type: map_at_1000 value: 42.178 - type: map_at_3 value: 37.726 - type: map_at_5 value: 39.474 - type: mrr_at_1 value: 37.729 - type: mrr_at_10 value: 46.494 - type: mrr_at_100 value: 47.368 - type: mrr_at_1000 value: 47.407 - type: mrr_at_3 value: 44.224999999999994 - type: mrr_at_5 value: 45.582 - type: ndcg_at_1 value: 37.729 - type: ndcg_at_10 value: 46.312999999999995 - type: ndcg_at_100 value: 51.915 - type: ndcg_at_1000 value: 53.788000000000004 - type: ndcg_at_3 value: 41.695 - type: ndcg_at_5 value: 43.956 - type: precision_at_1 value: 37.729 - type: precision_at_10 value: 8.181 - type: precision_at_100 value: 1.275 - type: precision_at_1000 value: 0.16199999999999998 - type: precision_at_3 value: 19.41 - type: precision_at_5 value: 13.648 - type: recall_at_1 value: 31.194 - type: recall_at_10 value: 57.118 - type: recall_at_100 value: 80.759 - type: recall_at_1000 value: 92.779 - type: recall_at_3 value: 44.083 - type: recall_at_5 value: 50.044999999999995 - task: type: Retrieval dataset: name: MTEB CQADupstackProgrammersRetrieval type: mteb/cqadupstack-programmers config: default split: test revision: 6184bc1440d2dbc7612be22b50686b8826d22b32 metrics: - type: map_at_1 value: 28.047 - type: map_at_10 value: 37.79 - type: map_at_100 value: 39.145 - type: map_at_1000 value: 39.254 - type: map_at_3 value: 34.857 - type: map_at_5 value: 36.545 - type: mrr_at_1 value: 35.388 - type: mrr_at_10 value: 43.475 - type: mrr_at_100 value: 44.440000000000005 - type: mrr_at_1000 value: 44.494 - type: mrr_at_3 value: 41.286 - type: mrr_at_5 value: 42.673 - type: ndcg_at_1 value: 35.388 - type: ndcg_at_10 value: 43.169000000000004 - type: ndcg_at_100 value: 48.785000000000004 - type: ndcg_at_1000 value: 51.029 - type: ndcg_at_3 value: 38.801 - type: ndcg_at_5 value: 40.9 - type: precision_at_1 value: 35.388 - type: precision_at_10 value: 7.7509999999999994 - type: precision_at_100 value: 1.212 - type: precision_at_1000 value: 0.157 - type: precision_at_3 value: 18.455 - type: precision_at_5 value: 13.014000000000001 - type: recall_at_1 value: 28.047 - type: recall_at_10 value: 53.53099999999999 - type: recall_at_100 value: 77.285 - type: recall_at_1000 value: 92.575 - type: recall_at_3 value: 40.949000000000005 - type: recall_at_5 value: 46.742 - task: type: Retrieval dataset: name: MTEB CQADupstackRetrieval type: mteb/cqadupstack config: default split: test revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4 metrics: - type: map_at_1 value: 28.131999999999994 - type: map_at_10 value: 36.93333333333334 - type: map_at_100 value: 38.117250000000006 - type: map_at_1000 value: 38.23275 - type: map_at_3 value: 34.19708333333333 - type: map_at_5 value: 35.725166666666674 - type: mrr_at_1 value: 33.16116666666667 - type: mrr_at_10 value: 41.057833333333335 - type: mrr_at_100 value: 41.90033333333333 - type: mrr_at_1000 value: 41.95625 - type: mrr_at_3 value: 38.757333333333335 - type: mrr_at_5 value: 40.097333333333324 - type: ndcg_at_1 value: 33.16116666666667 - type: ndcg_at_10 value: 42.01983333333333 - type: ndcg_at_100 value: 46.99916666666667 - type: ndcg_at_1000 value: 49.21783333333334 - type: ndcg_at_3 value: 37.479916666666654 - type: ndcg_at_5 value: 39.6355 - type: precision_at_1 value: 33.16116666666667 - type: precision_at_10 value: 7.230249999999999 - type: precision_at_100 value: 1.1411666666666667 - type: precision_at_1000 value: 0.1520833333333333 - type: precision_at_3 value: 17.028166666666667 - type: precision_at_5 value: 12.046999999999999 - type: recall_at_1 value: 28.131999999999994 - type: recall_at_10 value: 52.825500000000005 - type: recall_at_100 value: 74.59608333333333 - type: recall_at_1000 value: 89.87916666666668 - type: recall_at_3 value: 40.13625 - type: recall_at_5 value: 45.699999999999996 - task: type: Retrieval dataset: name: MTEB CQADupstackStatsRetrieval type: mteb/cqadupstack-stats config: default split: test revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a metrics: - type: map_at_1 value: 24.773999999999997 - type: map_at_10 value: 31.997999999999998 - type: map_at_100 value: 32.857 - type: map_at_1000 value: 32.957 - type: map_at_3 value: 30.041 - type: map_at_5 value: 31.119000000000003 - type: mrr_at_1 value: 27.607 - type: mrr_at_10 value: 34.538000000000004 - type: mrr_at_100 value: 35.308 - type: mrr_at_1000 value: 35.375 - type: mrr_at_3 value: 32.643 - type: mrr_at_5 value: 33.755 - type: ndcg_at_1 value: 27.607 - type: ndcg_at_10 value: 36.035000000000004 - type: ndcg_at_100 value: 40.351 - type: ndcg_at_1000 value: 42.684 - type: ndcg_at_3 value: 32.414 - type: ndcg_at_5 value: 34.11 - type: precision_at_1 value: 27.607 - type: precision_at_10 value: 5.6129999999999995 - type: precision_at_100 value: 0.8370000000000001 - type: precision_at_1000 value: 0.11199999999999999 - type: precision_at_3 value: 13.957 - type: precision_at_5 value: 9.571 - type: recall_at_1 value: 24.773999999999997 - type: recall_at_10 value: 45.717 - type: recall_at_100 value: 65.499 - type: recall_at_1000 value: 82.311 - type: recall_at_3 value: 35.716 - type: recall_at_5 value: 40.007999999999996 - task: type: Retrieval dataset: name: MTEB CQADupstackTexRetrieval type: mteb/cqadupstack-tex config: default split: test revision: 46989137a86843e03a6195de44b09deda022eec7 metrics: - type: map_at_1 value: 19.227 - type: map_at_10 value: 26.649 - type: map_at_100 value: 27.711999999999996 - type: map_at_1000 value: 27.837 - type: map_at_3 value: 24.454 - type: map_at_5 value: 25.772000000000002 - type: mrr_at_1 value: 23.433999999999997 - type: mrr_at_10 value: 30.564999999999998 - type: mrr_at_100 value: 31.44 - type: mrr_at_1000 value: 31.513999999999996 - type: mrr_at_3 value: 28.435 - type: mrr_at_5 value: 29.744999999999997 - type: ndcg_at_1 value: 23.433999999999997 - type: ndcg_at_10 value: 31.104 - type: ndcg_at_100 value: 36.172 - type: ndcg_at_1000 value: 39.006 - type: ndcg_at_3 value: 27.248 - type: ndcg_at_5 value: 29.249000000000002 - type: precision_at_1 value: 23.433999999999997 - type: precision_at_10 value: 5.496 - type: precision_at_100 value: 0.9490000000000001 - type: precision_at_1000 value: 0.13699999999999998 - type: precision_at_3 value: 12.709000000000001 - type: precision_at_5 value: 9.209 - type: recall_at_1 value: 19.227 - type: recall_at_10 value: 40.492 - type: recall_at_100 value: 63.304 - type: recall_at_1000 value: 83.45 - type: recall_at_3 value: 29.713 - type: recall_at_5 value: 34.82 - task: type: Retrieval dataset: name: MTEB CQADupstackUnixRetrieval type: mteb/cqadupstack-unix config: default split: test revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53 metrics: - type: map_at_1 value: 29.199 - type: map_at_10 value: 37.617 - type: map_at_100 value: 38.746 - type: map_at_1000 value: 38.851 - type: map_at_3 value: 34.882000000000005 - type: map_at_5 value: 36.571999999999996 - type: mrr_at_1 value: 33.489000000000004 - type: mrr_at_10 value: 41.089999999999996 - type: mrr_at_100 value: 41.965 - type: mrr_at_1000 value: 42.028 - type: mrr_at_3 value: 38.666 - type: mrr_at_5 value: 40.159 - type: ndcg_at_1 value: 33.489000000000004 - type: ndcg_at_10 value: 42.487 - type: ndcg_at_100 value: 47.552 - type: ndcg_at_1000 value: 49.774 - type: ndcg_at_3 value: 37.623 - type: ndcg_at_5 value: 40.184999999999995 - type: precision_at_1 value: 33.489000000000004 - type: precision_at_10 value: 6.94 - type: precision_at_100 value: 1.0699999999999998 - type: precision_at_1000 value: 0.136 - type: precision_at_3 value: 16.667 - type: precision_at_5 value: 11.922 - type: recall_at_1 value: 29.199 - type: recall_at_10 value: 53.689 - type: recall_at_100 value: 75.374 - type: recall_at_1000 value: 90.64999999999999 - type: recall_at_3 value: 40.577999999999996 - type: recall_at_5 value: 46.909 - task: type: Retrieval dataset: name: MTEB CQADupstackWebmastersRetrieval type: mteb/cqadupstack-webmasters config: default split: test revision: 160c094312a0e1facb97e55eeddb698c0abe3571 metrics: - type: map_at_1 value: 27.206999999999997 - type: map_at_10 value: 36.146 - type: map_at_100 value: 37.759 - type: map_at_1000 value: 37.979 - type: map_at_3 value: 32.967999999999996 - type: map_at_5 value: 34.809 - type: mrr_at_1 value: 32.806000000000004 - type: mrr_at_10 value: 40.449 - type: mrr_at_100 value: 41.404999999999994 - type: mrr_at_1000 value: 41.457 - type: mrr_at_3 value: 37.614999999999995 - type: mrr_at_5 value: 39.324999999999996 - type: ndcg_at_1 value: 32.806000000000004 - type: ndcg_at_10 value: 41.911 - type: ndcg_at_100 value: 47.576 - type: ndcg_at_1000 value: 50.072 - type: ndcg_at_3 value: 36.849 - type: ndcg_at_5 value: 39.475 - type: precision_at_1 value: 32.806000000000004 - type: precision_at_10 value: 8.103 - type: precision_at_100 value: 1.557 - type: precision_at_1000 value: 0.242 - type: precision_at_3 value: 17.26 - type: precision_at_5 value: 12.885 - type: recall_at_1 value: 27.206999999999997 - type: recall_at_10 value: 52.56999999999999 - type: recall_at_100 value: 78.302 - type: recall_at_1000 value: 94.121 - type: recall_at_3 value: 38.317 - type: recall_at_5 value: 45.410000000000004 - task: type: Retrieval dataset: name: MTEB CQADupstackWordpressRetrieval type: mteb/cqadupstack-wordpress config: default split: test revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4 metrics: - type: map_at_1 value: 24.221 - type: map_at_10 value: 30.826999999999998 - type: map_at_100 value: 31.845000000000002 - type: map_at_1000 value: 31.95 - type: map_at_3 value: 28.547 - type: map_at_5 value: 29.441 - type: mrr_at_1 value: 26.247999999999998 - type: mrr_at_10 value: 32.957 - type: mrr_at_100 value: 33.819 - type: mrr_at_1000 value: 33.899 - type: mrr_at_3 value: 30.714999999999996 - type: mrr_at_5 value: 31.704 - type: ndcg_at_1 value: 26.247999999999998 - type: ndcg_at_10 value: 35.171 - type: ndcg_at_100 value: 40.098 - type: ndcg_at_1000 value: 42.67 - type: ndcg_at_3 value: 30.508999999999997 - type: ndcg_at_5 value: 32.022 - type: precision_at_1 value: 26.247999999999998 - type: precision_at_10 value: 5.36 - type: precision_at_100 value: 0.843 - type: precision_at_1000 value: 0.11499999999999999 - type: precision_at_3 value: 12.568999999999999 - type: precision_at_5 value: 8.540000000000001 - type: recall_at_1 value: 24.221 - type: recall_at_10 value: 46.707 - type: recall_at_100 value: 69.104 - type: recall_at_1000 value: 88.19500000000001 - type: recall_at_3 value: 33.845 - type: recall_at_5 value: 37.375 - task: type: Retrieval dataset: name: MTEB ClimateFEVER type: mteb/climate-fever config: default split: test revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380 metrics: - type: map_at_1 value: 13.624 - type: map_at_10 value: 22.557 - type: map_at_100 value: 24.367 - type: map_at_1000 value: 24.54 - type: map_at_3 value: 18.988 - type: map_at_5 value: 20.785999999999998 - type: mrr_at_1 value: 30.619000000000003 - type: mrr_at_10 value: 42.019 - type: mrr_at_100 value: 42.818 - type: mrr_at_1000 value: 42.856 - type: mrr_at_3 value: 38.578 - type: mrr_at_5 value: 40.669 - type: ndcg_at_1 value: 30.619000000000003 - type: ndcg_at_10 value: 31.252999999999997 - type: ndcg_at_100 value: 38.238 - type: ndcg_at_1000 value: 41.368 - type: ndcg_at_3 value: 25.843 - type: ndcg_at_5 value: 27.638 - type: precision_at_1 value: 30.619000000000003 - type: precision_at_10 value: 9.687 - type: precision_at_100 value: 1.718 - type: precision_at_1000 value: 0.22999999999999998 - type: precision_at_3 value: 18.849 - type: precision_at_5 value: 14.463000000000001 - type: recall_at_1 value: 13.624 - type: recall_at_10 value: 36.693999999999996 - type: recall_at_100 value: 60.9 - type: recall_at_1000 value: 78.46 - type: recall_at_3 value: 23.354 - type: recall_at_5 value: 28.756999999999998 - task: type: Retrieval dataset: name: MTEB DBPedia type: mteb/dbpedia config: default split: test revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659 metrics: - type: map_at_1 value: 9.077 - type: map_at_10 value: 19.813 - type: map_at_100 value: 27.822999999999997 - type: map_at_1000 value: 29.485 - type: map_at_3 value: 14.255999999999998 - type: map_at_5 value: 16.836000000000002 - type: mrr_at_1 value: 69.25 - type: mrr_at_10 value: 77.059 - type: mrr_at_100 value: 77.41 - type: mrr_at_1000 value: 77.416 - type: mrr_at_3 value: 75.625 - type: mrr_at_5 value: 76.512 - type: ndcg_at_1 value: 55.75 - type: ndcg_at_10 value: 41.587 - type: ndcg_at_100 value: 46.048 - type: ndcg_at_1000 value: 53.172 - type: ndcg_at_3 value: 46.203 - type: ndcg_at_5 value: 43.696 - type: precision_at_1 value: 69.25 - type: precision_at_10 value: 32.95 - type: precision_at_100 value: 10.555 - type: precision_at_1000 value: 2.136 - type: precision_at_3 value: 49.667 - type: precision_at_5 value: 42.5 - type: recall_at_1 value: 9.077 - type: recall_at_10 value: 25.249 - type: recall_at_100 value: 51.964 - type: recall_at_1000 value: 74.51 - type: recall_at_3 value: 15.584000000000001 - type: recall_at_5 value: 19.717000000000002 - task: type: Classification dataset: name: MTEB EmotionClassification type: mteb/emotion config: default split: test revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 metrics: - type: accuracy value: 45.769999999999996 - type: f1 value: 41.64144711933962 - task: type: Retrieval dataset: name: MTEB FEVER type: mteb/fever config: default split: test revision: bea83ef9e8fb933d90a2f1d5515737465d613e12 metrics: - type: map_at_1 value: 67.098 - type: map_at_10 value: 77.69800000000001 - type: map_at_100 value: 77.947 - type: map_at_1000 value: 77.961 - type: map_at_3 value: 76.278 - type: map_at_5 value: 77.217 - type: mrr_at_1 value: 72.532 - type: mrr_at_10 value: 82.41199999999999 - type: mrr_at_100 value: 82.527 - type: mrr_at_1000 value: 82.529 - type: mrr_at_3 value: 81.313 - type: mrr_at_5 value: 82.069 - type: ndcg_at_1 value: 72.532 - type: ndcg_at_10 value: 82.488 - type: ndcg_at_100 value: 83.382 - type: ndcg_at_1000 value: 83.622 - type: ndcg_at_3 value: 80.101 - type: ndcg_at_5 value: 81.52199999999999 - type: precision_at_1 value: 72.532 - type: precision_at_10 value: 10.203 - type: precision_at_100 value: 1.082 - type: precision_at_1000 value: 0.11199999999999999 - type: precision_at_3 value: 31.308000000000003 - type: precision_at_5 value: 19.652 - type: recall_at_1 value: 67.098 - type: recall_at_10 value: 92.511 - type: recall_at_100 value: 96.06099999999999 - type: recall_at_1000 value: 97.548 - type: recall_at_3 value: 86.105 - type: recall_at_5 value: 89.661 - task: type: Retrieval dataset: name: MTEB FiQA2018 type: mteb/fiqa config: default split: test revision: 27a168819829fe9bcd655c2df245fb19452e8e06 metrics: - type: map_at_1 value: 18.681 - type: map_at_10 value: 31.739 - type: map_at_100 value: 33.503 - type: map_at_1000 value: 33.69 - type: map_at_3 value: 27.604 - type: map_at_5 value: 29.993 - type: mrr_at_1 value: 37.5 - type: mrr_at_10 value: 46.933 - type: mrr_at_100 value: 47.771 - type: mrr_at_1000 value: 47.805 - type: mrr_at_3 value: 44.239 - type: mrr_at_5 value: 45.766 - type: ndcg_at_1 value: 37.5 - type: ndcg_at_10 value: 39.682 - type: ndcg_at_100 value: 46.127 - type: ndcg_at_1000 value: 48.994 - type: ndcg_at_3 value: 35.655 - type: ndcg_at_5 value: 37.036 - type: precision_at_1 value: 37.5 - type: precision_at_10 value: 11.08 - type: precision_at_100 value: 1.765 - type: precision_at_1000 value: 0.22999999999999998 - type: precision_at_3 value: 23.919999999999998 - type: precision_at_5 value: 17.809 - type: recall_at_1 value: 18.681 - type: recall_at_10 value: 47.548 - type: recall_at_100 value: 71.407 - type: recall_at_1000 value: 87.805 - type: recall_at_3 value: 32.979 - type: recall_at_5 value: 39.192 - task: type: Retrieval dataset: name: MTEB HotpotQA type: mteb/hotpotqa config: default split: test revision: ab518f4d6fcca38d87c25209f94beba119d02014 metrics: - type: map_at_1 value: 38.257999999999996 - type: map_at_10 value: 57.605 - type: map_at_100 value: 58.50300000000001 - type: map_at_1000 value: 58.568 - type: map_at_3 value: 54.172 - type: map_at_5 value: 56.323 - type: mrr_at_1 value: 76.51599999999999 - type: mrr_at_10 value: 82.584 - type: mrr_at_100 value: 82.78 - type: mrr_at_1000 value: 82.787 - type: mrr_at_3 value: 81.501 - type: mrr_at_5 value: 82.185 - type: ndcg_at_1 value: 76.51599999999999 - type: ndcg_at_10 value: 66.593 - type: ndcg_at_100 value: 69.699 - type: ndcg_at_1000 value: 70.953 - type: ndcg_at_3 value: 61.673 - type: ndcg_at_5 value: 64.42 - type: precision_at_1 value: 76.51599999999999 - type: precision_at_10 value: 13.857 - type: precision_at_100 value: 1.628 - type: precision_at_1000 value: 0.179 - type: precision_at_3 value: 38.956 - type: precision_at_5 value: 25.541999999999998 - type: recall_at_1 value: 38.257999999999996 - type: recall_at_10 value: 69.284 - type: recall_at_100 value: 81.391 - type: recall_at_1000 value: 89.689 - type: recall_at_3 value: 58.433 - type: recall_at_5 value: 63.856 - task: type: Classification dataset: name: MTEB ImdbClassification type: mteb/imdb config: default split: test revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 metrics: - type: accuracy value: 69.48679999999999 - type: ap value: 63.97638838971138 - type: f1 value: 69.22731638841675 - task: type: Retrieval dataset: name: MTEB MSMARCO type: mteb/msmarco config: default split: dev revision: c5a29a104738b98a9e76336939199e264163d4a0 metrics: - type: map_at_1 value: 20.916999999999998 - type: map_at_10 value: 32.929 - type: map_at_100 value: 34.1 - type: map_at_1000 value: 34.152 - type: map_at_3 value: 29.065 - type: map_at_5 value: 31.287 - type: mrr_at_1 value: 21.562 - type: mrr_at_10 value: 33.533 - type: mrr_at_100 value: 34.644000000000005 - type: mrr_at_1000 value: 34.69 - type: mrr_at_3 value: 29.735 - type: mrr_at_5 value: 31.928 - type: ndcg_at_1 value: 21.562 - type: ndcg_at_10 value: 39.788000000000004 - type: ndcg_at_100 value: 45.434999999999995 - type: ndcg_at_1000 value: 46.75 - type: ndcg_at_3 value: 31.942999999999998 - type: ndcg_at_5 value: 35.888 - type: precision_at_1 value: 21.562 - type: precision_at_10 value: 6.348 - type: precision_at_100 value: 0.918 - type: precision_at_1000 value: 0.10300000000000001 - type: precision_at_3 value: 13.682 - type: precision_at_5 value: 10.189 - type: recall_at_1 value: 20.916999999999998 - type: recall_at_10 value: 60.926 - type: recall_at_100 value: 87.03800000000001 - type: recall_at_1000 value: 97.085 - type: recall_at_3 value: 39.637 - type: recall_at_5 value: 49.069 - task: type: Classification dataset: name: MTEB MTOPDomainClassification (en) type: mteb/mtop_domain config: en split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics: - type: accuracy value: 90.93935248518011 - type: f1 value: 90.56439321844506 - task: type: Classification dataset: name: MTEB MTOPIntentClassification (en) type: mteb/mtop_intent config: en split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics: - type: accuracy value: 58.62517099863203 - type: f1 value: 40.69925681703197 - task: type: Classification dataset: name: MTEB MasakhaNEWSClassification (eng) type: masakhane/masakhanews config: eng split: test revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 metrics: - type: accuracy value: 76.29746835443039 - type: f1 value: 75.31702672039506 - task: type: Clustering dataset: name: MTEB MasakhaNEWSClusteringP2P (eng) type: masakhane/masakhanews config: eng split: test revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60 metrics: - type: v_measure value: 43.05495067062023 - type: v_measure value: 19.625272848173843 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (en) type: mteb/amazon_massive_intent config: en split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 64.76126429051781 - type: f1 value: 62.60284261265268 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (en) type: mteb/amazon_massive_scenario config: en split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 70.05043712172159 - type: f1 value: 69.08340521169049 - task: type: Clustering dataset: name: MTEB MedrxivClusteringP2P type: mteb/medrxiv-clustering-p2p config: default split: test revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 metrics: - type: v_measure value: 30.78969229005989 - task: type: Clustering dataset: name: MTEB MedrxivClusteringS2S type: mteb/medrxiv-clustering-s2s config: default split: test revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 metrics: - type: v_measure value: 27.954325178520335 - task: type: Reranking dataset: name: MTEB MindSmallReranking type: mteb/mind_small config: default split: test revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 metrics: - type: map value: 30.601827413968596 - type: mrr value: 31.515372019474196 - task: type: Retrieval dataset: name: MTEB NFCorpus type: mteb/nfcorpus config: default split: test revision: ec0fa4fe99da2ff19ca1214b7966684033a58814 metrics: - type: map_at_1 value: 5.4559999999999995 - type: map_at_10 value: 12.039 - type: map_at_100 value: 14.804999999999998 - type: map_at_1000 value: 16.081 - type: map_at_3 value: 8.996 - type: map_at_5 value: 10.357 - type: mrr_at_1 value: 45.82 - type: mrr_at_10 value: 53.583999999999996 - type: mrr_at_100 value: 54.330999999999996 - type: mrr_at_1000 value: 54.366 - type: mrr_at_3 value: 52.166999999999994 - type: mrr_at_5 value: 52.971999999999994 - type: ndcg_at_1 value: 44.427 - type: ndcg_at_10 value: 32.536 - type: ndcg_at_100 value: 29.410999999999998 - type: ndcg_at_1000 value: 38.012 - type: ndcg_at_3 value: 38.674 - type: ndcg_at_5 value: 36.107 - type: precision_at_1 value: 45.82 - type: precision_at_10 value: 23.591 - type: precision_at_100 value: 7.35 - type: precision_at_1000 value: 1.9769999999999999 - type: precision_at_3 value: 36.016999999999996 - type: precision_at_5 value: 30.959999999999997 - type: recall_at_1 value: 5.4559999999999995 - type: recall_at_10 value: 15.387 - type: recall_at_100 value: 28.754999999999995 - type: recall_at_1000 value: 59.787 - type: recall_at_3 value: 10.137 - type: recall_at_5 value: 12.200999999999999 - task: type: Retrieval dataset: name: MTEB NQ type: mteb/nq config: default split: test revision: b774495ed302d8c44a3a7ea25c90dbce03968f31 metrics: - type: map_at_1 value: 32.609 - type: map_at_10 value: 48.522 - type: map_at_100 value: 49.468 - type: map_at_1000 value: 49.497 - type: map_at_3 value: 44.327 - type: map_at_5 value: 46.937 - type: mrr_at_1 value: 36.616 - type: mrr_at_10 value: 50.943000000000005 - type: mrr_at_100 value: 51.626000000000005 - type: mrr_at_1000 value: 51.647 - type: mrr_at_3 value: 47.532999999999994 - type: mrr_at_5 value: 49.714000000000006 - type: ndcg_at_1 value: 36.586999999999996 - type: ndcg_at_10 value: 56.19499999999999 - type: ndcg_at_100 value: 60.014 - type: ndcg_at_1000 value: 60.707 - type: ndcg_at_3 value: 48.486000000000004 - type: ndcg_at_5 value: 52.791999999999994 - type: precision_at_1 value: 36.586999999999996 - type: precision_at_10 value: 9.139999999999999 - type: precision_at_100 value: 1.129 - type: precision_at_1000 value: 0.11900000000000001 - type: precision_at_3 value: 22.171 - type: precision_at_5 value: 15.787999999999998 - type: recall_at_1 value: 32.609 - type: recall_at_10 value: 77.011 - type: recall_at_100 value: 93.202 - type: recall_at_1000 value: 98.344 - type: recall_at_3 value: 57.286 - type: recall_at_5 value: 67.181 - task: type: Classification dataset: name: MTEB NewsClassification type: ag_news config: default split: test revision: eb185aade064a813bc0b7f42de02595523103ca4 metrics: - type: accuracy value: 77.4421052631579 - type: f1 value: 77.23976860913628 - 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 - type: cos_sim_f1 value: 99.9490575649516 - type: cos_sim_precision value: 100 - type: cos_sim_recall value: 99.89816700610999 - type: dot_accuracy value: 99.89816700610999 - type: dot_ap value: 100 - type: dot_f1 value: 99.9490575649516 - type: dot_precision value: 100 - type: dot_recall value: 99.89816700610999 - type: euclidean_accuracy value: 99.89816700610999 - type: euclidean_ap value: 100 - type: euclidean_f1 value: 99.9490575649516 - type: euclidean_precision value: 100 - type: euclidean_recall value: 99.89816700610999 - type: manhattan_accuracy value: 99.89816700610999 - type: manhattan_ap value: 100 - type: manhattan_f1 value: 99.9490575649516 - type: manhattan_precision value: 100 - type: manhattan_recall value: 99.89816700610999 - type: max_accuracy value: 99.89816700610999 - type: max_ap value: 100 - 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: 61.25000000000001 - type: cos_sim_ap value: 59.23166242799505 - type: cos_sim_f1 value: 62.53016201309893 - type: cos_sim_precision value: 45.486459378134406 - type: cos_sim_recall value: 100 - type: dot_accuracy value: 61.25000000000001 - type: dot_ap value: 59.23109306756652 - type: dot_f1 value: 62.53016201309893 - type: dot_precision value: 45.486459378134406 - type: dot_recall value: 100 - type: euclidean_accuracy value: 61.25000000000001 - type: euclidean_ap value: 59.23166242799505 - type: euclidean_f1 value: 62.53016201309893 - type: euclidean_precision value: 45.486459378134406 - type: euclidean_recall value: 100 - type: manhattan_accuracy value: 61.25000000000001 - type: manhattan_ap value: 59.23015114712089 - type: manhattan_f1 value: 62.50861474844934 - type: manhattan_precision value: 45.46365914786967 - type: manhattan_recall value: 100 - type: max_accuracy value: 61.25000000000001 - type: max_ap value: 59.23166242799505 - type: max_f1 value: 62.53016201309893 - task: type: Retrieval dataset: name: MTEB QuoraRetrieval type: mteb/quora config: default split: test revision: e4e08e0b7dbe3c8700f0daef558ff32256715259 metrics: - type: map_at_1 value: 69.919 - type: map_at_10 value: 83.636 - type: map_at_100 value: 84.27 - type: map_at_1000 value: 84.289 - type: map_at_3 value: 80.744 - type: map_at_5 value: 82.509 - type: mrr_at_1 value: 80.52 - type: mrr_at_10 value: 86.751 - type: mrr_at_100 value: 86.875 - type: mrr_at_1000 value: 86.876 - type: mrr_at_3 value: 85.798 - type: mrr_at_5 value: 86.414 - type: ndcg_at_1 value: 80.53 - type: ndcg_at_10 value: 87.465 - type: ndcg_at_100 value: 88.762 - type: ndcg_at_1000 value: 88.90599999999999 - type: ndcg_at_3 value: 84.634 - type: ndcg_at_5 value: 86.09400000000001 - type: precision_at_1 value: 80.53 - type: precision_at_10 value: 13.263 - type: precision_at_100 value: 1.517 - type: precision_at_1000 value: 0.156 - type: precision_at_3 value: 36.973 - type: precision_at_5 value: 24.25 - type: recall_at_1 value: 69.919 - type: recall_at_10 value: 94.742 - type: recall_at_100 value: 99.221 - type: recall_at_1000 value: 99.917 - type: recall_at_3 value: 86.506 - type: recall_at_5 value: 90.736 - task: type: Clustering dataset: name: MTEB RedditClustering type: mteb/reddit-clustering config: default split: test revision: 24640382cdbf8abc73003fb0fa6d111a705499eb metrics: - type: v_measure value: 50.47309147963901 - task: type: Clustering dataset: name: MTEB RedditClusteringP2P type: mteb/reddit-clustering-p2p config: default split: test revision: 385e3cb46b4cfa89021f56c4380204149d0efe33 metrics: - type: v_measure value: 60.53779561923047 - task: type: Retrieval dataset: name: MTEB SCIDOCS type: mteb/scidocs config: default split: test revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88 metrics: - type: map_at_1 value: 4.843 - type: map_at_10 value: 11.664 - type: map_at_100 value: 13.499 - type: map_at_1000 value: 13.771 - type: map_at_3 value: 8.602 - type: map_at_5 value: 10.164 - type: mrr_at_1 value: 23.9 - 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type: cos_sim_pearson value: 68.91106612960657 - type: cos_sim_spearman value: 69.48524490302286 - type: euclidean_pearson value: 70.51347841618035 - type: euclidean_spearman value: 69.48524490302286 - type: manhattan_pearson value: 70.31770181334245 - type: manhattan_spearman value: 69.12494700138238 - task: type: STS dataset: name: MTEB STSBenchmark type: mteb/stsbenchmark-sts config: default split: test revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 metrics: - type: cos_sim_pearson value: 81.54104342761988 - type: cos_sim_spearman value: 81.18789220331483 - type: euclidean_pearson value: 81.5895544590969 - type: euclidean_spearman value: 81.18789220331483 - type: manhattan_pearson value: 81.4738562449809 - type: manhattan_spearman value: 81.06565101416024 - 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: 81.54104346197056 - type: cos_sim_spearman value: 81.18789220331483 - type: euclidean_pearson value: 81.58955451690102 - type: euclidean_spearman value: 81.18789220331483 - type: manhattan_pearson value: 81.47385630064072 - type: manhattan_spearman value: 81.06565101416024 - task: type: Reranking dataset: name: MTEB SciDocsRR type: mteb/scidocs-reranking config: default split: test revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab metrics: - type: map value: 79.34107964300796 - type: mrr value: 94.01917889662987 - task: type: Retrieval dataset: name: MTEB SciFact type: mteb/scifact config: default split: test revision: 0228b52cf27578f30900b9e5271d331663a030d7 metrics: - type: map_at_1 value: 55.928 - type: map_at_10 value: 65.443 - type: map_at_100 value: 66.067 - type: map_at_1000 value: 66.091 - type: map_at_3 value: 62.629999999999995 - type: map_at_5 value: 64.35 - type: mrr_at_1 value: 59 - type: mrr_at_10 value: 66.845 - type: mrr_at_100 value: 67.31899999999999 - type: mrr_at_1000 value: 67.342 - 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type: v_measure value: 60.69855369728728 - task: type: Clustering dataset: name: MTEB StackExchangeClusteringP2P type: mteb/stackexchange-clustering-p2p config: default split: test revision: 815ca46b2622cec33ccafc3735d572c266efdb44 metrics: - type: v_measure value: 33.98191834367251 - task: type: Reranking dataset: name: MTEB StackOverflowDupQuestions type: mteb/stackoverflowdupquestions-reranking config: default split: test revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 metrics: - type: map value: 50.156163330429614 - type: mrr value: 50.90145148968678 - task: type: Summarization dataset: name: MTEB SummEval type: mteb/summeval config: default split: test revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c metrics: - type: cos_sim_pearson value: 31.16938079808134 - type: cos_sim_spearman value: 31.74655874538245 - type: dot_pearson value: 31.169380299671705 - type: dot_spearman value: 31.74655874538245 - task: type: Retrieval dataset: name: MTEB TRECCOVID type: mteb/trec-covid config: default split: test revision: bb9466bac8153a0349341eb1b22e06409e78ef4e metrics: - type: map_at_1 value: 0.252 - type: map_at_10 value: 2.009 - type: map_at_100 value: 11.611 - type: map_at_1000 value: 27.811999999999998 - type: map_at_3 value: 0.685 - type: map_at_5 value: 1.08 - type: mrr_at_1 value: 94 - type: mrr_at_10 value: 97 - type: mrr_at_100 value: 97 - type: mrr_at_1000 value: 97 - type: mrr_at_3 value: 97 - type: mrr_at_5 value: 97 - type: ndcg_at_1 value: 88 - type: ndcg_at_10 value: 81.388 - type: ndcg_at_100 value: 60.629 - type: ndcg_at_1000 value: 52.38 - type: ndcg_at_3 value: 86.827 - type: ndcg_at_5 value: 84.597 - type: precision_at_1 value: 94 - type: precision_at_10 value: 85.8 - type: precision_at_100 value: 62.419999999999995 - type: precision_at_1000 value: 23.31 - type: precision_at_3 value: 90.667 - type: precision_at_5 value: 88.4 - type: recall_at_1 value: 0.252 - type: recall_at_10 value: 2.164 - type: recall_at_100 value: 14.613999999999999 - type: recall_at_1000 value: 48.730000000000004 - type: recall_at_3 value: 0.7020000000000001 - type: recall_at_5 value: 1.122 - task: type: Retrieval dataset: name: MTEB Touche2020 type: mteb/touche2020 config: default split: test revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f metrics: - type: map_at_1 value: 3.476 - type: map_at_10 value: 13.442000000000002 - type: map_at_100 value: 20.618 - type: map_at_1000 value: 22.175 - type: map_at_3 value: 6.968000000000001 - type: map_at_5 value: 9.214 - type: mrr_at_1 value: 44.897999999999996 - type: mrr_at_10 value: 56.77100000000001 - type: mrr_at_100 value: 57.226 - type: mrr_at_1000 value: 57.226 - type: mrr_at_3 value: 52.381 - type: mrr_at_5 value: 54.523999999999994 - type: ndcg_at_1 value: 42.857 - type: ndcg_at_10 value: 32.507999999999996 - type: ndcg_at_100 value: 43.614000000000004 - type: ndcg_at_1000 value: 53.82 - type: ndcg_at_3 value: 36.818 - type: ndcg_at_5 value: 33.346 - type: precision_at_1 value: 44.897999999999996 - type: precision_at_10 value: 28.571 - type: precision_at_100 value: 8.652999999999999 - type: precision_at_1000 value: 1.5709999999999997 - type: precision_at_3 value: 38.095 - type: precision_at_5 value: 32.245000000000005 - type: recall_at_1 value: 3.476 - type: recall_at_10 value: 20.827 - type: recall_at_100 value: 53.04299999999999 - type: recall_at_1000 value: 84.221 - type: recall_at_3 value: 8.200000000000001 - type: recall_at_5 value: 11.651 - task: type: Classification dataset: name: MTEB ToxicConversationsClassification type: mteb/toxic_conversations_50k config: default split: test revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de metrics: - type: accuracy value: 61.96360000000001 - type: ap value: 11.256160324436445 - type: f1 value: 48.07712827691349 - task: type: Classification dataset: name: MTEB TweetSentimentExtractionClassification type: mteb/tweet_sentiment_extraction config: default split: test revision: d604517c81ca91fe16a244d1248fc021f9ecee7a metrics: - type: accuracy value: 58.90492359932088 - type: f1 value: 59.12542417513503 - task: type: Clustering dataset: name: MTEB TwentyNewsgroupsClustering type: mteb/twentynewsgroups-clustering config: default split: test revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 metrics: - type: v_measure value: 38.284935353315355 - task: type: PairClassification dataset: name: MTEB TwitterSemEval2015 type: mteb/twittersemeval2015-pairclassification config: default split: test revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 metrics: - type: cos_sim_accuracy value: 83.4714192048638 - type: cos_sim_ap value: 65.77588263185375 - type: cos_sim_f1 value: 62.459508098380326 - type: cos_sim_precision value: 57.27172717271727 - type: cos_sim_recall value: 68.68073878627968 - type: dot_accuracy value: 83.4714192048638 - type: dot_ap value: 65.77588818364636 - type: dot_f1 value: 62.459508098380326 - type: dot_precision value: 57.27172717271727 - type: dot_recall value: 68.68073878627968 - type: euclidean_accuracy value: 83.4714192048638 - type: euclidean_ap value: 65.77587693431595 - type: euclidean_f1 value: 62.459508098380326 - type: euclidean_precision value: 57.27172717271727 - type: euclidean_recall value: 68.68073878627968 - type: manhattan_accuracy value: 83.47737974608094 - type: manhattan_ap value: 65.65957745829654 - type: manhattan_f1 value: 62.22760290556902 - type: manhattan_precision value: 57.494407158836694 - type: manhattan_recall value: 67.81002638522428 - type: max_accuracy value: 83.47737974608094 - type: max_ap value: 65.77588818364636 - type: max_f1 value: 62.459508098380326 - task: type: PairClassification dataset: name: MTEB TwitterURLCorpus type: mteb/twitterurlcorpus-pairclassification config: default split: test revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf metrics: - type: cos_sim_accuracy value: 88.64244964489463 - type: cos_sim_ap value: 85.154122301394 - type: cos_sim_f1 value: 77.45617911327146 - type: cos_sim_precision value: 74.23066064370413 - type: cos_sim_recall value: 80.97474591931014 - type: dot_accuracy value: 88.64244964489463 - type: dot_ap value: 85.15411965587543 - type: dot_f1 value: 77.45617911327146 - type: dot_precision value: 74.23066064370413 - type: dot_recall value: 80.97474591931014 - type: euclidean_accuracy value: 88.64244964489463 - type: euclidean_ap value: 85.15414684113986 - type: euclidean_f1 value: 77.45617911327146 - type: euclidean_precision value: 74.23066064370413 - type: euclidean_recall value: 80.97474591931014 - type: manhattan_accuracy value: 88.57841425078588 - type: manhattan_ap value: 85.12472268567576 - type: manhattan_f1 value: 77.39497339937627 - type: manhattan_precision value: 73.92584285413892 - type: manhattan_recall value: 81.20572836464429 - type: max_accuracy value: 88.64244964489463 - type: max_ap value: 85.15414684113986 - type: max_f1 value: 77.45617911327146 - task: type: Clustering dataset: name: MTEB WikiCitiesClustering type: jinaai/cities_wiki_clustering config: default split: test revision: ddc9ee9242fa65332597f70e967ecc38b9d734fa metrics: - type: v_measure value: 79.58576208710117 --- # yishan-wang/snowflake-arctic-embed-s-Q8_0-GGUF This model was converted to GGUF format from [`Snowflake/snowflake-arctic-embed-s`](https://huggingface.co/Snowflake/snowflake-arctic-embed-s) 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-s) 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 yishan-wang/snowflake-arctic-embed-s-Q8_0-GGUF --hf-file snowflake-arctic-embed-s-q8_0.gguf -p "The meaning to life and the universe is" ``` ### Server: ```bash llama-server --hf-repo yishan-wang/snowflake-arctic-embed-s-Q8_0-GGUF --hf-file snowflake-arctic-embed-s-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 yishan-wang/snowflake-arctic-embed-s-Q8_0-GGUF --hf-file snowflake-arctic-embed-s-q8_0.gguf -p "The meaning to life and the universe is" ``` or ``` ./llama-server --hf-repo yishan-wang/snowflake-arctic-embed-s-Q8_0-GGUF --hf-file snowflake-arctic-embed-s-q8_0.gguf -c 2048 ```