--- base_model: jinaai/jina-embeddings-v2-base-de language: - de - en license: apache-2.0 tags: - sentence-transformers - feature-extraction - sentence-similarity - mteb - transformers - transformers.js - llama-cpp - gguf-my-repo inference: false model-index: - name: jina-embeddings-v2-base-de results: - task: type: Classification dataset: name: MTEB AmazonCounterfactualClassification (en) type: mteb/amazon_counterfactual config: en split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics: - type: accuracy value: 73.76119402985076 - type: ap value: 35.99577188521176 - type: f1 value: 67.50397431543269 - task: type: Classification dataset: name: MTEB AmazonCounterfactualClassification (de) type: mteb/amazon_counterfactual config: de split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics: - type: accuracy value: 68.9186295503212 - type: ap value: 79.73307115840507 - type: f1 value: 66.66245744831339 - task: type: Classification dataset: name: MTEB AmazonPolarityClassification type: mteb/amazon_polarity config: default split: test revision: e2d317d38cd51312af73b3d32a06d1a08b442046 metrics: - type: accuracy value: 77.52215 - type: ap value: 71.85051037177416 - type: f1 value: 77.4171096157774 - task: type: Classification dataset: name: MTEB AmazonReviewsClassification (en) type: mteb/amazon_reviews_multi config: en split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics: - type: accuracy value: 38.498 - type: f1 value: 38.058193386555956 - task: type: Classification dataset: name: MTEB AmazonReviewsClassification (de) type: mteb/amazon_reviews_multi config: de split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics: - type: accuracy value: 37.717999999999996 - type: f1 value: 37.22674371574757 - task: type: Retrieval dataset: name: MTEB ArguAna type: arguana config: default split: test revision: None metrics: - type: map_at_1 value: 25.319999999999997 - type: map_at_10 value: 40.351 - type: map_at_100 value: 41.435 - type: map_at_1000 value: 41.443000000000005 - type: map_at_3 value: 35.266 - type: map_at_5 value: 37.99 - type: mrr_at_1 value: 25.746999999999996 - type: mrr_at_10 value: 40.515 - type: mrr_at_100 value: 41.606 - type: mrr_at_1000 value: 41.614000000000004 - type: mrr_at_3 value: 35.42 - type: mrr_at_5 value: 38.112 - type: ndcg_at_1 value: 25.319999999999997 - type: ndcg_at_10 value: 49.332 - type: ndcg_at_100 value: 53.909 - type: ndcg_at_1000 value: 54.089 - type: ndcg_at_3 value: 38.705 - type: ndcg_at_5 value: 43.606 - type: precision_at_1 value: 25.319999999999997 - type: precision_at_10 value: 7.831 - type: precision_at_100 value: 0.9820000000000001 - type: precision_at_1000 value: 0.1 - type: precision_at_3 value: 16.24 - type: precision_at_5 value: 12.119 - type: recall_at_1 value: 25.319999999999997 - type: recall_at_10 value: 78.307 - type: recall_at_100 value: 98.222 - type: recall_at_1000 value: 99.57300000000001 - type: recall_at_3 value: 48.72 - type: recall_at_5 value: 60.597 - task: type: Clustering dataset: name: MTEB ArxivClusteringP2P type: mteb/arxiv-clustering-p2p config: default split: test revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d metrics: - type: v_measure value: 41.43100588255654 - task: type: Clustering dataset: name: MTEB ArxivClusteringS2S type: mteb/arxiv-clustering-s2s config: default split: test revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 metrics: - type: v_measure value: 32.08988904593667 - task: type: Reranking dataset: name: MTEB AskUbuntuDupQuestions type: mteb/askubuntudupquestions-reranking config: default split: test revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 metrics: - type: map value: 60.55514765595906 - type: mrr value: 73.51393835465858 - task: type: STS dataset: name: MTEB BIOSSES type: mteb/biosses-sts config: default split: test revision: d3fb88f8f02e40887cd149695127462bbcf29b4a metrics: - type: cos_sim_pearson value: 79.6723823121172 - type: cos_sim_spearman value: 76.90596922214986 - type: euclidean_pearson value: 77.87910737957918 - type: euclidean_spearman value: 76.66319260598262 - type: manhattan_pearson value: 77.37039493457965 - type: manhattan_spearman value: 76.09872191280964 - task: type: BitextMining dataset: name: MTEB BUCC (de-en) type: mteb/bucc-bitext-mining config: de-en split: test revision: d51519689f32196a32af33b075a01d0e7c51e252 metrics: - type: accuracy value: 98.97703549060543 - type: f1 value: 98.86569241475296 - type: precision value: 98.81002087682673 - type: recall value: 98.97703549060543 - task: type: Classification dataset: name: MTEB Banking77Classification type: mteb/banking77 config: default split: test revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 metrics: - type: accuracy value: 83.93506493506493 - type: f1 value: 83.91014949949302 - task: type: Clustering dataset: name: MTEB BiorxivClusteringP2P type: mteb/biorxiv-clustering-p2p config: default split: test revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 metrics: - type: v_measure value: 34.970675877585144 - task: type: Clustering dataset: name: MTEB BiorxivClusteringS2S type: mteb/biorxiv-clustering-s2s config: default split: test revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 metrics: - type: v_measure value: 28.779230269190954 - task: type: Clustering dataset: name: MTEB BlurbsClusteringP2P type: slvnwhrl/blurbs-clustering-p2p config: default split: test revision: a2dd5b02a77de3466a3eaa98ae586b5610314496 metrics: - type: v_measure value: 35.490175601567216 - task: type: Clustering dataset: name: MTEB BlurbsClusteringS2S type: slvnwhrl/blurbs-clustering-s2s config: default split: test revision: 9bfff9a7f8f6dc6ffc9da71c48dd48b68696471d metrics: - type: v_measure value: 16.16638280560168 - task: type: Retrieval dataset: name: MTEB CQADupstackAndroidRetrieval type: BeIR/cqadupstack config: default split: test revision: None metrics: - type: map_at_1 value: 30.830999999999996 - type: map_at_10 value: 41.355 - type: map_at_100 value: 42.791000000000004 - type: map_at_1000 value: 42.918 - type: map_at_3 value: 38.237 - type: map_at_5 value: 40.066 - type: mrr_at_1 value: 38.484 - type: mrr_at_10 value: 47.593 - type: mrr_at_100 value: 48.388 - type: mrr_at_1000 value: 48.439 - type: mrr_at_3 value: 45.279 - type: mrr_at_5 value: 46.724 - type: ndcg_at_1 value: 38.484 - type: ndcg_at_10 value: 47.27 - type: ndcg_at_100 value: 52.568000000000005 - type: ndcg_at_1000 value: 54.729000000000006 - type: ndcg_at_3 value: 43.061 - type: ndcg_at_5 value: 45.083 - type: precision_at_1 value: 38.484 - type: precision_at_10 value: 8.927 - type: precision_at_100 value: 1.425 - type: precision_at_1000 value: 0.19 - type: precision_at_3 value: 20.791999999999998 - type: precision_at_5 value: 14.85 - type: recall_at_1 value: 30.830999999999996 - type: recall_at_10 value: 57.87799999999999 - type: recall_at_100 value: 80.124 - type: recall_at_1000 value: 94.208 - type: recall_at_3 value: 45.083 - type: recall_at_5 value: 51.154999999999994 - type: map_at_1 value: 25.782 - type: map_at_10 value: 34.492 - type: map_at_100 value: 35.521 - type: map_at_1000 value: 35.638 - type: map_at_3 value: 31.735999999999997 - type: map_at_5 value: 33.339 - type: mrr_at_1 value: 32.357 - type: mrr_at_10 value: 39.965 - type: mrr_at_100 value: 40.644000000000005 - type: mrr_at_1000 value: 40.695 - type: mrr_at_3 value: 37.739 - type: mrr_at_5 value: 39.061 - type: ndcg_at_1 value: 32.357 - type: ndcg_at_10 value: 39.644 - type: ndcg_at_100 value: 43.851 - type: ndcg_at_1000 value: 46.211999999999996 - type: ndcg_at_3 value: 35.675000000000004 - type: ndcg_at_5 value: 37.564 - type: precision_at_1 value: 32.357 - type: precision_at_10 value: 7.344 - type: precision_at_100 value: 1.201 - type: precision_at_1000 value: 0.168 - type: precision_at_3 value: 17.155 - type: precision_at_5 value: 12.166 - type: recall_at_1 value: 25.782 - type: recall_at_10 value: 49.132999999999996 - type: recall_at_100 value: 67.24 - type: recall_at_1000 value: 83.045 - type: recall_at_3 value: 37.021 - type: recall_at_5 value: 42.548 - type: map_at_1 value: 35.778999999999996 - type: map_at_10 value: 47.038000000000004 - type: map_at_100 value: 48.064 - type: map_at_1000 value: 48.128 - type: map_at_3 value: 44.186 - type: map_at_5 value: 45.788000000000004 - type: mrr_at_1 value: 41.254000000000005 - type: mrr_at_10 value: 50.556999999999995 - type: mrr_at_100 value: 51.296 - type: mrr_at_1000 value: 51.331 - type: mrr_at_3 value: 48.318 - type: mrr_at_5 value: 49.619 - type: ndcg_at_1 value: 41.254000000000005 - type: ndcg_at_10 value: 52.454 - type: ndcg_at_100 value: 56.776 - type: ndcg_at_1000 value: 58.181000000000004 - type: ndcg_at_3 value: 47.713 - type: ndcg_at_5 value: 49.997 - type: precision_at_1 value: 41.254000000000005 - type: precision_at_10 value: 8.464 - type: precision_at_100 value: 1.157 - type: precision_at_1000 value: 0.133 - type: precision_at_3 value: 21.526 - type: precision_at_5 value: 14.696000000000002 - type: recall_at_1 value: 35.778999999999996 - type: recall_at_10 value: 64.85300000000001 - type: recall_at_100 value: 83.98400000000001 - type: recall_at_1000 value: 94.18299999999999 - type: recall_at_3 value: 51.929 - type: recall_at_5 value: 57.666 - type: map_at_1 value: 21.719 - type: map_at_10 value: 29.326999999999998 - type: map_at_100 value: 30.314000000000004 - type: map_at_1000 value: 30.397000000000002 - type: map_at_3 value: 27.101 - type: map_at_5 value: 28.141 - type: mrr_at_1 value: 23.503 - type: mrr_at_10 value: 31.225 - type: mrr_at_100 value: 32.096000000000004 - type: mrr_at_1000 value: 32.159 - type: mrr_at_3 value: 29.076999999999998 - type: mrr_at_5 value: 30.083 - type: ndcg_at_1 value: 23.503 - type: ndcg_at_10 value: 33.842 - type: ndcg_at_100 value: 39.038000000000004 - type: ndcg_at_1000 value: 41.214 - type: ndcg_at_3 value: 29.347 - type: ndcg_at_5 value: 31.121 - type: precision_at_1 value: 23.503 - type: precision_at_10 value: 5.266 - type: precision_at_100 value: 0.831 - type: precision_at_1000 value: 0.106 - type: precision_at_3 value: 12.504999999999999 - type: precision_at_5 value: 8.565000000000001 - type: recall_at_1 value: 21.719 - type: recall_at_10 value: 46.024 - type: recall_at_100 value: 70.78999999999999 - type: recall_at_1000 value: 87.022 - type: recall_at_3 value: 33.64 - type: recall_at_5 value: 37.992 - type: map_at_1 value: 15.601 - type: map_at_10 value: 22.054000000000002 - type: map_at_100 value: 23.177 - type: map_at_1000 value: 23.308 - type: map_at_3 value: 19.772000000000002 - type: map_at_5 value: 21.055 - type: mrr_at_1 value: 19.403000000000002 - type: mrr_at_10 value: 26.409 - type: mrr_at_100 value: 27.356 - type: mrr_at_1000 value: 27.441 - type: mrr_at_3 value: 24.108999999999998 - type: mrr_at_5 value: 25.427 - type: ndcg_at_1 value: 19.403000000000002 - type: ndcg_at_10 value: 26.474999999999998 - type: ndcg_at_100 value: 32.086 - type: ndcg_at_1000 value: 35.231 - type: ndcg_at_3 value: 22.289 - type: ndcg_at_5 value: 24.271 - type: precision_at_1 value: 19.403000000000002 - type: precision_at_10 value: 4.813 - type: precision_at_100 value: 0.8869999999999999 - type: precision_at_1000 value: 0.13 - type: precision_at_3 value: 10.531 - type: precision_at_5 value: 7.710999999999999 - type: recall_at_1 value: 15.601 - type: recall_at_10 value: 35.916 - type: recall_at_100 value: 60.8 - type: recall_at_1000 value: 83.245 - type: recall_at_3 value: 24.321 - type: recall_at_5 value: 29.372999999999998 - type: map_at_1 value: 25.522 - type: map_at_10 value: 34.854 - type: map_at_100 value: 36.269 - type: map_at_1000 value: 36.387 - type: map_at_3 value: 32.187 - type: map_at_5 value: 33.692 - type: mrr_at_1 value: 31.375999999999998 - type: mrr_at_10 value: 40.471000000000004 - type: mrr_at_100 value: 41.481 - type: mrr_at_1000 value: 41.533 - type: mrr_at_3 value: 38.274 - type: mrr_at_5 value: 39.612 - type: ndcg_at_1 value: 31.375999999999998 - type: ndcg_at_10 value: 40.298 - type: ndcg_at_100 value: 46.255 - type: ndcg_at_1000 value: 48.522 - type: ndcg_at_3 value: 36.049 - type: ndcg_at_5 value: 38.095 - type: precision_at_1 value: 31.375999999999998 - type: precision_at_10 value: 7.305000000000001 - type: precision_at_100 value: 1.201 - type: precision_at_1000 value: 0.157 - type: precision_at_3 value: 17.132 - type: precision_at_5 value: 12.107999999999999 - type: recall_at_1 value: 25.522 - type: recall_at_10 value: 50.988 - type: recall_at_100 value: 76.005 - type: recall_at_1000 value: 91.11200000000001 - type: recall_at_3 value: 38.808 - type: recall_at_5 value: 44.279 - type: map_at_1 value: 24.615000000000002 - type: map_at_10 value: 32.843 - type: map_at_100 value: 34.172999999999995 - type: map_at_1000 value: 34.286 - type: map_at_3 value: 30.125 - type: map_at_5 value: 31.495 - type: mrr_at_1 value: 30.023 - type: mrr_at_10 value: 38.106 - type: mrr_at_100 value: 39.01 - type: mrr_at_1000 value: 39.071 - type: mrr_at_3 value: 35.674 - type: mrr_at_5 value: 36.924 - type: ndcg_at_1 value: 30.023 - type: ndcg_at_10 value: 38.091 - type: ndcg_at_100 value: 43.771 - type: ndcg_at_1000 value: 46.315 - type: ndcg_at_3 value: 33.507 - type: ndcg_at_5 value: 35.304 - type: precision_at_1 value: 30.023 - type: precision_at_10 value: 6.837999999999999 - type: precision_at_100 value: 1.124 - type: precision_at_1000 value: 0.152 - type: precision_at_3 value: 15.562999999999999 - type: precision_at_5 value: 10.936 - type: recall_at_1 value: 24.615000000000002 - type: recall_at_10 value: 48.691 - type: recall_at_100 value: 72.884 - type: recall_at_1000 value: 90.387 - type: recall_at_3 value: 35.659 - type: recall_at_5 value: 40.602 - type: map_at_1 value: 23.223666666666666 - type: map_at_10 value: 31.338166666666673 - type: map_at_100 value: 32.47358333333333 - type: map_at_1000 value: 32.5955 - type: map_at_3 value: 28.84133333333333 - type: map_at_5 value: 30.20808333333333 - type: mrr_at_1 value: 27.62483333333333 - type: mrr_at_10 value: 35.385916666666674 - type: mrr_at_100 value: 36.23325 - type: mrr_at_1000 value: 36.29966666666667 - type: mrr_at_3 value: 33.16583333333333 - type: mrr_at_5 value: 34.41983333333334 - type: ndcg_at_1 value: 27.62483333333333 - type: ndcg_at_10 value: 36.222 - type: ndcg_at_100 value: 41.29491666666666 - type: ndcg_at_1000 value: 43.85508333333333 - type: ndcg_at_3 value: 31.95116666666667 - type: ndcg_at_5 value: 33.88541666666667 - type: precision_at_1 value: 27.62483333333333 - type: precision_at_10 value: 6.339916666666667 - type: precision_at_100 value: 1.0483333333333333 - type: precision_at_1000 value: 0.14608333333333334 - type: precision_at_3 value: 14.726500000000003 - type: precision_at_5 value: 10.395 - type: recall_at_1 value: 23.223666666666666 - type: recall_at_10 value: 46.778999999999996 - type: recall_at_100 value: 69.27141666666667 - type: recall_at_1000 value: 87.27383333333334 - type: recall_at_3 value: 34.678749999999994 - type: recall_at_5 value: 39.79900000000001 - type: map_at_1 value: 21.677 - type: map_at_10 value: 27.828000000000003 - type: map_at_100 value: 28.538999999999998 - type: map_at_1000 value: 28.64 - type: map_at_3 value: 26.105 - type: map_at_5 value: 27.009 - type: mrr_at_1 value: 24.387 - type: mrr_at_10 value: 30.209999999999997 - type: mrr_at_100 value: 30.953000000000003 - type: mrr_at_1000 value: 31.029 - type: mrr_at_3 value: 28.707 - type: mrr_at_5 value: 29.610999999999997 - type: ndcg_at_1 value: 24.387 - type: ndcg_at_10 value: 31.378 - type: ndcg_at_100 value: 35.249 - type: ndcg_at_1000 value: 37.923 - type: ndcg_at_3 value: 28.213 - type: ndcg_at_5 value: 29.658 - type: precision_at_1 value: 24.387 - type: precision_at_10 value: 4.8309999999999995 - type: precision_at_100 value: 0.73 - type: precision_at_1000 value: 0.104 - type: precision_at_3 value: 12.168 - type: precision_at_5 value: 8.251999999999999 - type: recall_at_1 value: 21.677 - type: recall_at_10 value: 40.069 - type: recall_at_100 value: 58.077 - type: recall_at_1000 value: 77.97 - type: recall_at_3 value: 31.03 - type: recall_at_5 value: 34.838 - type: map_at_1 value: 14.484 - type: map_at_10 value: 20.355 - type: map_at_100 value: 21.382 - type: map_at_1000 value: 21.511 - type: map_at_3 value: 18.448 - type: map_at_5 value: 19.451999999999998 - type: mrr_at_1 value: 17.584 - type: mrr_at_10 value: 23.825 - type: mrr_at_100 value: 24.704 - type: mrr_at_1000 value: 24.793000000000003 - type: mrr_at_3 value: 21.92 - type: mrr_at_5 value: 22.97 - type: ndcg_at_1 value: 17.584 - type: ndcg_at_10 value: 24.315 - type: ndcg_at_100 value: 29.354999999999997 - type: ndcg_at_1000 value: 32.641999999999996 - type: ndcg_at_3 value: 20.802 - type: ndcg_at_5 value: 22.335 - type: precision_at_1 value: 17.584 - type: precision_at_10 value: 4.443 - type: precision_at_100 value: 0.8160000000000001 - type: precision_at_1000 value: 0.128 - type: precision_at_3 value: 9.807 - type: precision_at_5 value: 7.0889999999999995 - type: recall_at_1 value: 14.484 - type: recall_at_10 value: 32.804 - type: recall_at_100 value: 55.679 - type: recall_at_1000 value: 79.63 - type: recall_at_3 value: 22.976 - type: recall_at_5 value: 26.939 - type: map_at_1 value: 22.983999999999998 - type: map_at_10 value: 30.812 - type: map_at_100 value: 31.938 - type: map_at_1000 value: 32.056000000000004 - type: map_at_3 value: 28.449999999999996 - type: map_at_5 value: 29.542 - type: mrr_at_1 value: 27.145999999999997 - type: mrr_at_10 value: 34.782999999999994 - type: mrr_at_100 value: 35.699 - type: mrr_at_1000 value: 35.768 - type: mrr_at_3 value: 32.572 - type: mrr_at_5 value: 33.607 - type: ndcg_at_1 value: 27.145999999999997 - type: ndcg_at_10 value: 35.722 - type: ndcg_at_100 value: 40.964 - type: ndcg_at_1000 value: 43.598 - type: ndcg_at_3 value: 31.379 - type: ndcg_at_5 value: 32.924 - type: precision_at_1 value: 27.145999999999997 - type: precision_at_10 value: 6.063000000000001 - type: precision_at_100 value: 0.9730000000000001 - type: precision_at_1000 value: 0.13 - type: precision_at_3 value: 14.366000000000001 - type: precision_at_5 value: 9.776 - type: recall_at_1 value: 22.983999999999998 - type: recall_at_10 value: 46.876 - type: recall_at_100 value: 69.646 - type: recall_at_1000 value: 88.305 - type: recall_at_3 value: 34.471000000000004 - type: recall_at_5 value: 38.76 - type: map_at_1 value: 23.017000000000003 - type: map_at_10 value: 31.049 - type: map_at_100 value: 32.582 - type: map_at_1000 value: 32.817 - type: map_at_3 value: 28.303 - type: map_at_5 value: 29.854000000000003 - type: mrr_at_1 value: 27.866000000000003 - type: mrr_at_10 value: 35.56 - type: mrr_at_100 value: 36.453 - type: mrr_at_1000 value: 36.519 - type: mrr_at_3 value: 32.938 - type: mrr_at_5 value: 34.391 - type: ndcg_at_1 value: 27.866000000000003 - type: ndcg_at_10 value: 36.506 - type: ndcg_at_100 value: 42.344 - type: ndcg_at_1000 value: 45.213 - type: ndcg_at_3 value: 31.805 - type: ndcg_at_5 value: 33.933 - type: precision_at_1 value: 27.866000000000003 - type: precision_at_10 value: 7.016 - type: precision_at_100 value: 1.468 - type: precision_at_1000 value: 0.23900000000000002 - type: precision_at_3 value: 14.822 - type: precision_at_5 value: 10.791 - type: recall_at_1 value: 23.017000000000003 - type: recall_at_10 value: 47.053 - type: recall_at_100 value: 73.177 - type: recall_at_1000 value: 91.47800000000001 - type: recall_at_3 value: 33.675 - type: recall_at_5 value: 39.36 - type: map_at_1 value: 16.673 - type: map_at_10 value: 24.051000000000002 - type: map_at_100 value: 24.933 - type: map_at_1000 value: 25.06 - type: map_at_3 value: 21.446 - type: map_at_5 value: 23.064 - type: mrr_at_1 value: 18.115000000000002 - type: mrr_at_10 value: 25.927 - type: mrr_at_100 value: 26.718999999999998 - type: mrr_at_1000 value: 26.817999999999998 - type: mrr_at_3 value: 23.383000000000003 - type: mrr_at_5 value: 25.008999999999997 - type: ndcg_at_1 value: 18.115000000000002 - type: ndcg_at_10 value: 28.669 - type: ndcg_at_100 value: 33.282000000000004 - type: ndcg_at_1000 value: 36.481 - type: ndcg_at_3 value: 23.574 - type: ndcg_at_5 value: 26.340000000000003 - type: precision_at_1 value: 18.115000000000002 - type: precision_at_10 value: 4.769 - type: precision_at_100 value: 0.767 - type: precision_at_1000 value: 0.116 - type: precision_at_3 value: 10.351 - type: precision_at_5 value: 7.8 - type: recall_at_1 value: 16.673 - type: recall_at_10 value: 41.063 - type: recall_at_100 value: 62.851 - type: recall_at_1000 value: 86.701 - type: recall_at_3 value: 27.532 - type: recall_at_5 value: 34.076 - task: type: Retrieval dataset: name: MTEB ClimateFEVER type: climate-fever config: default split: test revision: None metrics: - type: map_at_1 value: 8.752 - type: map_at_10 value: 15.120000000000001 - type: map_at_100 value: 16.678 - type: map_at_1000 value: 16.854 - type: map_at_3 value: 12.603 - type: map_at_5 value: 13.918 - type: mrr_at_1 value: 19.283 - type: mrr_at_10 value: 29.145 - type: mrr_at_100 value: 30.281000000000002 - type: mrr_at_1000 value: 30.339 - type: mrr_at_3 value: 26.069 - type: mrr_at_5 value: 27.864 - type: ndcg_at_1 value: 19.283 - type: ndcg_at_10 value: 21.804000000000002 - type: ndcg_at_100 value: 28.576 - type: ndcg_at_1000 value: 32.063 - type: ndcg_at_3 value: 17.511 - type: ndcg_at_5 value: 19.112000000000002 - type: precision_at_1 value: 19.283 - type: precision_at_10 value: 6.873 - type: precision_at_100 value: 1.405 - type: precision_at_1000 value: 0.20500000000000002 - type: precision_at_3 value: 13.16 - type: precision_at_5 value: 10.189 - type: recall_at_1 value: 8.752 - type: recall_at_10 value: 27.004 - type: recall_at_100 value: 50.648 - type: recall_at_1000 value: 70.458 - type: recall_at_3 value: 16.461000000000002 - type: recall_at_5 value: 20.973 - task: type: Retrieval dataset: name: MTEB DBPedia type: dbpedia-entity config: default split: test revision: None metrics: - type: map_at_1 value: 6.81 - type: map_at_10 value: 14.056 - type: map_at_100 value: 18.961 - type: map_at_1000 value: 20.169 - type: map_at_3 value: 10.496 - type: map_at_5 value: 11.952 - type: mrr_at_1 value: 53.5 - type: mrr_at_10 value: 63.479 - type: mrr_at_100 value: 63.971999999999994 - type: mrr_at_1000 value: 63.993 - type: mrr_at_3 value: 61.541999999999994 - type: mrr_at_5 value: 62.778999999999996 - type: ndcg_at_1 value: 42.25 - type: ndcg_at_10 value: 31.471 - type: ndcg_at_100 value: 35.115 - type: ndcg_at_1000 value: 42.408 - type: ndcg_at_3 value: 35.458 - type: ndcg_at_5 value: 32.973 - type: precision_at_1 value: 53.5 - type: precision_at_10 value: 24.85 - type: precision_at_100 value: 7.79 - type: precision_at_1000 value: 1.599 - type: precision_at_3 value: 38.667 - type: precision_at_5 value: 31.55 - type: recall_at_1 value: 6.81 - type: recall_at_10 value: 19.344 - type: recall_at_100 value: 40.837 - type: recall_at_1000 value: 64.661 - type: recall_at_3 value: 11.942 - type: recall_at_5 value: 14.646 - task: type: Classification dataset: name: MTEB EmotionClassification type: mteb/emotion config: default split: test revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 metrics: - type: accuracy value: 44.64499999999999 - type: f1 value: 39.39106911352714 - task: type: Retrieval dataset: name: MTEB FEVER type: fever config: default split: test revision: None metrics: - type: map_at_1 value: 48.196 - type: map_at_10 value: 61.404 - type: map_at_100 value: 61.846000000000004 - type: map_at_1000 value: 61.866 - type: map_at_3 value: 58.975 - type: map_at_5 value: 60.525 - type: mrr_at_1 value: 52.025 - type: mrr_at_10 value: 65.43299999999999 - type: mrr_at_100 value: 65.80799999999999 - type: mrr_at_1000 value: 65.818 - type: mrr_at_3 value: 63.146 - type: mrr_at_5 value: 64.64 - type: ndcg_at_1 value: 52.025 - type: ndcg_at_10 value: 67.889 - type: ndcg_at_100 value: 69.864 - type: ndcg_at_1000 value: 70.337 - type: ndcg_at_3 value: 63.315 - type: ndcg_at_5 value: 65.91799999999999 - type: precision_at_1 value: 52.025 - type: precision_at_10 value: 9.182 - type: precision_at_100 value: 1.027 - type: precision_at_1000 value: 0.108 - type: precision_at_3 value: 25.968000000000004 - type: precision_at_5 value: 17.006 - type: recall_at_1 value: 48.196 - type: recall_at_10 value: 83.885 - type: recall_at_100 value: 92.671 - type: recall_at_1000 value: 96.018 - type: recall_at_3 value: 71.59 - type: recall_at_5 value: 77.946 - task: type: Retrieval dataset: name: MTEB FiQA2018 type: fiqa config: default split: test revision: None metrics: - type: map_at_1 value: 15.193000000000001 - type: map_at_10 value: 25.168000000000003 - type: map_at_100 value: 27.017000000000003 - type: map_at_1000 value: 27.205000000000002 - type: map_at_3 value: 21.746 - type: map_at_5 value: 23.579 - type: mrr_at_1 value: 31.635999999999996 - type: mrr_at_10 value: 40.077 - type: mrr_at_100 value: 41.112 - type: mrr_at_1000 value: 41.160999999999994 - type: mrr_at_3 value: 37.937 - type: mrr_at_5 value: 39.18 - type: ndcg_at_1 value: 31.635999999999996 - type: ndcg_at_10 value: 32.298 - type: ndcg_at_100 value: 39.546 - type: ndcg_at_1000 value: 42.88 - type: ndcg_at_3 value: 29.221999999999998 - type: ndcg_at_5 value: 30.069000000000003 - type: precision_at_1 value: 31.635999999999996 - type: precision_at_10 value: 9.367 - type: precision_at_100 value: 1.645 - type: precision_at_1000 value: 0.22399999999999998 - type: precision_at_3 value: 20.01 - type: precision_at_5 value: 14.753 - type: recall_at_1 value: 15.193000000000001 - type: recall_at_10 value: 38.214999999999996 - type: recall_at_100 value: 65.95 - type: recall_at_1000 value: 85.85300000000001 - type: recall_at_3 value: 26.357000000000003 - type: recall_at_5 value: 31.319999999999997 - task: type: Retrieval dataset: name: MTEB GerDaLIR type: jinaai/ger_da_lir config: default split: test revision: None metrics: - type: map_at_1 value: 10.363 - type: map_at_10 value: 16.222 - type: map_at_100 value: 17.28 - type: map_at_1000 value: 17.380000000000003 - type: map_at_3 value: 14.054 - type: map_at_5 value: 15.203 - type: mrr_at_1 value: 11.644 - type: mrr_at_10 value: 17.625 - type: mrr_at_100 value: 18.608 - type: mrr_at_1000 value: 18.695999999999998 - type: mrr_at_3 value: 15.481 - type: mrr_at_5 value: 16.659 - type: ndcg_at_1 value: 11.628 - type: ndcg_at_10 value: 20.028000000000002 - type: ndcg_at_100 value: 25.505 - type: ndcg_at_1000 value: 28.288000000000004 - type: ndcg_at_3 value: 15.603 - type: ndcg_at_5 value: 17.642 - type: precision_at_1 value: 11.628 - type: precision_at_10 value: 3.5589999999999997 - type: precision_at_100 value: 0.664 - type: precision_at_1000 value: 0.092 - type: precision_at_3 value: 7.109999999999999 - type: precision_at_5 value: 5.401 - type: recall_at_1 value: 10.363 - type: recall_at_10 value: 30.586000000000002 - type: recall_at_100 value: 56.43 - type: recall_at_1000 value: 78.142 - type: recall_at_3 value: 18.651 - type: recall_at_5 value: 23.493 - task: type: Retrieval dataset: name: MTEB GermanDPR type: deepset/germandpr config: default split: test revision: 5129d02422a66be600ac89cd3e8531b4f97d347d metrics: - type: map_at_1 value: 60.78 - type: map_at_10 value: 73.91499999999999 - type: map_at_100 value: 74.089 - type: map_at_1000 value: 74.09400000000001 - type: map_at_3 value: 71.87 - type: map_at_5 value: 73.37700000000001 - type: mrr_at_1 value: 60.78 - type: mrr_at_10 value: 73.91499999999999 - type: mrr_at_100 value: 74.089 - type: mrr_at_1000 value: 74.09400000000001 - type: mrr_at_3 value: 71.87 - type: mrr_at_5 value: 73.37700000000001 - type: ndcg_at_1 value: 60.78 - type: ndcg_at_10 value: 79.35600000000001 - type: ndcg_at_100 value: 80.077 - type: ndcg_at_1000 value: 80.203 - type: ndcg_at_3 value: 75.393 - type: ndcg_at_5 value: 78.077 - type: precision_at_1 value: 60.78 - type: precision_at_10 value: 9.59 - type: precision_at_100 value: 0.9900000000000001 - type: precision_at_1000 value: 0.1 - type: precision_at_3 value: 28.52 - type: precision_at_5 value: 18.4 - type: recall_at_1 value: 60.78 - type: recall_at_10 value: 95.902 - type: recall_at_100 value: 99.024 - type: recall_at_1000 value: 100.0 - type: recall_at_3 value: 85.56099999999999 - type: recall_at_5 value: 92.0 - task: type: STS dataset: name: MTEB GermanSTSBenchmark type: jinaai/german-STSbenchmark config: default split: test revision: 49d9b423b996fea62b483f9ee6dfb5ec233515ca metrics: - type: cos_sim_pearson value: 88.49524420894356 - type: cos_sim_spearman value: 88.32407839427714 - type: euclidean_pearson value: 87.25098779877104 - type: euclidean_spearman value: 88.22738098593608 - type: manhattan_pearson value: 87.23872691839607 - type: manhattan_spearman value: 88.2002968380165 - task: type: Retrieval dataset: name: MTEB HotpotQA type: hotpotqa config: default split: test revision: None metrics: - type: map_at_1 value: 31.81 - type: map_at_10 value: 46.238 - type: map_at_100 value: 47.141 - type: map_at_1000 value: 47.213 - type: map_at_3 value: 43.248999999999995 - type: map_at_5 value: 45.078 - type: mrr_at_1 value: 63.619 - type: mrr_at_10 value: 71.279 - type: mrr_at_100 value: 71.648 - type: mrr_at_1000 value: 71.665 - type: mrr_at_3 value: 69.76599999999999 - type: mrr_at_5 value: 70.743 - type: ndcg_at_1 value: 63.619 - type: ndcg_at_10 value: 55.38999999999999 - type: ndcg_at_100 value: 58.80800000000001 - type: ndcg_at_1000 value: 60.331999999999994 - type: ndcg_at_3 value: 50.727 - type: ndcg_at_5 value: 53.284 - type: precision_at_1 value: 63.619 - type: precision_at_10 value: 11.668000000000001 - type: precision_at_100 value: 1.434 - type: precision_at_1000 value: 0.164 - type: precision_at_3 value: 32.001000000000005 - type: precision_at_5 value: 21.223 - type: recall_at_1 value: 31.81 - type: recall_at_10 value: 58.339 - type: recall_at_100 value: 71.708 - type: recall_at_1000 value: 81.85 - type: recall_at_3 value: 48.001 - type: recall_at_5 value: 53.059 - task: type: Classification dataset: name: MTEB ImdbClassification type: mteb/imdb config: default split: test revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 metrics: - type: accuracy value: 68.60640000000001 - type: ap value: 62.84296904042086 - type: f1 value: 68.50643633327537 - task: type: Reranking dataset: name: MTEB MIRACL type: jinaai/miracl config: default split: test revision: 8741c3b61cd36ed9ca1b3d4203543a41793239e2 metrics: - type: map value: 64.29704335389768 - type: mrr value: 72.11962197159565 - task: type: Classification dataset: name: MTEB MTOPDomainClassification (en) type: mteb/mtop_domain config: en split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics: - type: accuracy value: 89.3844049247606 - type: f1 value: 89.2124328528015 - task: type: Classification dataset: name: MTEB MTOPDomainClassification (de) type: mteb/mtop_domain config: de split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics: - type: accuracy value: 88.36855452240067 - type: f1 value: 87.35458822097442 - task: type: Classification dataset: name: MTEB MTOPIntentClassification (en) type: mteb/mtop_intent config: en split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics: - type: accuracy value: 66.48654810761514 - type: f1 value: 50.07229882504409 - task: type: Classification dataset: name: MTEB MTOPIntentClassification (de) type: mteb/mtop_intent config: de split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics: - type: accuracy value: 63.832065370526905 - type: f1 value: 46.283579383385806 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (de) type: mteb/amazon_massive_intent config: de split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 63.89038332212509 - type: f1 value: 61.86279849685129 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (en) type: mteb/amazon_massive_intent config: en split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 69.11230665770006 - type: f1 value: 67.44780095350535 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (de) type: mteb/amazon_massive_scenario config: de split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 71.25084061869536 - type: f1 value: 71.43965023016408 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (en) type: mteb/amazon_massive_scenario config: en split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 73.73907195696032 - type: f1 value: 73.69920814839061 - task: type: Clustering dataset: name: MTEB MedrxivClusteringP2P type: mteb/medrxiv-clustering-p2p config: default split: test revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 metrics: - type: v_measure value: 31.32577306498249 - task: type: Clustering dataset: name: MTEB MedrxivClusteringS2S type: mteb/medrxiv-clustering-s2s config: default split: test revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 metrics: - type: v_measure value: 28.759349326367783 - task: type: Reranking dataset: name: MTEB MindSmallReranking type: mteb/mind_small config: default split: test revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 metrics: - type: map value: 30.401342674703425 - type: mrr value: 31.384379585660987 - task: type: Retrieval dataset: name: MTEB NFCorpus type: nfcorpus config: default split: test revision: None metrics: - type: map_at_1 value: 4.855 - type: map_at_10 value: 10.01 - type: map_at_100 value: 12.461 - type: map_at_1000 value: 13.776 - type: map_at_3 value: 7.252 - type: map_at_5 value: 8.679 - type: mrr_at_1 value: 41.176 - type: mrr_at_10 value: 49.323 - type: mrr_at_100 value: 49.954 - type: mrr_at_1000 value: 49.997 - type: mrr_at_3 value: 46.904 - type: mrr_at_5 value: 48.375 - type: ndcg_at_1 value: 39.318999999999996 - type: ndcg_at_10 value: 28.607 - type: ndcg_at_100 value: 26.554 - type: ndcg_at_1000 value: 35.731 - type: ndcg_at_3 value: 32.897999999999996 - type: ndcg_at_5 value: 31.53 - type: precision_at_1 value: 41.176 - type: precision_at_10 value: 20.867 - type: precision_at_100 value: 6.796 - type: precision_at_1000 value: 1.983 - type: precision_at_3 value: 30.547 - type: precision_at_5 value: 27.245 - type: recall_at_1 value: 4.855 - type: recall_at_10 value: 14.08 - type: recall_at_100 value: 28.188000000000002 - type: recall_at_1000 value: 60.07900000000001 - type: recall_at_3 value: 7.947 - type: recall_at_5 value: 10.786 - task: type: Retrieval dataset: name: MTEB NQ type: nq config: default split: test revision: None metrics: - type: map_at_1 value: 26.906999999999996 - type: map_at_10 value: 41.147 - type: map_at_100 value: 42.269 - type: map_at_1000 value: 42.308 - type: map_at_3 value: 36.638999999999996 - type: map_at_5 value: 39.285 - type: mrr_at_1 value: 30.359 - type: mrr_at_10 value: 43.607 - type: mrr_at_100 value: 44.454 - type: mrr_at_1000 value: 44.481 - type: mrr_at_3 value: 39.644 - type: mrr_at_5 value: 42.061 - type: ndcg_at_1 value: 30.330000000000002 - type: ndcg_at_10 value: 48.899 - type: ndcg_at_100 value: 53.612 - type: ndcg_at_1000 value: 54.51200000000001 - type: ndcg_at_3 value: 40.262 - type: ndcg_at_5 value: 44.787 - type: precision_at_1 value: 30.330000000000002 - type: precision_at_10 value: 8.323 - type: precision_at_100 value: 1.0959999999999999 - type: precision_at_1000 value: 0.11800000000000001 - type: precision_at_3 value: 18.395 - type: precision_at_5 value: 13.627 - type: recall_at_1 value: 26.906999999999996 - type: recall_at_10 value: 70.215 - type: recall_at_100 value: 90.61200000000001 - type: recall_at_1000 value: 97.294 - type: recall_at_3 value: 47.784 - type: recall_at_5 value: 58.251 - task: type: PairClassification dataset: name: MTEB PawsX type: paws-x config: default split: test revision: 8a04d940a42cd40658986fdd8e3da561533a3646 metrics: - type: cos_sim_accuracy value: 60.5 - type: cos_sim_ap value: 57.606096528877494 - type: cos_sim_f1 value: 62.24240307369892 - type: cos_sim_precision value: 45.27439024390244 - type: cos_sim_recall value: 99.55307262569832 - type: dot_accuracy value: 57.699999999999996 - type: dot_ap value: 51.289351057160616 - type: dot_f1 value: 62.25953130465197 - type: dot_precision value: 45.31568228105906 - type: dot_recall value: 99.4413407821229 - type: euclidean_accuracy value: 60.45 - type: euclidean_ap value: 57.616461421424034 - type: euclidean_f1 value: 62.313697657913416 - type: euclidean_precision value: 45.657826313052524 - type: euclidean_recall value: 98.10055865921787 - type: manhattan_accuracy value: 60.3 - type: manhattan_ap value: 57.580565271667325 - type: manhattan_f1 value: 62.24240307369892 - type: manhattan_precision value: 45.27439024390244 - type: manhattan_recall value: 99.55307262569832 - type: max_accuracy value: 60.5 - type: max_ap value: 57.616461421424034 - type: max_f1 value: 62.313697657913416 - task: type: Retrieval dataset: name: MTEB QuoraRetrieval type: quora config: default split: test revision: None metrics: - type: map_at_1 value: 70.21300000000001 - type: map_at_10 value: 84.136 - type: map_at_100 value: 84.796 - type: map_at_1000 value: 84.812 - type: map_at_3 value: 81.182 - type: map_at_5 value: 83.027 - type: mrr_at_1 value: 80.91000000000001 - type: mrr_at_10 value: 87.155 - type: mrr_at_100 value: 87.27000000000001 - type: mrr_at_1000 value: 87.271 - type: mrr_at_3 value: 86.158 - type: mrr_at_5 value: 86.828 - type: ndcg_at_1 value: 80.88 - type: ndcg_at_10 value: 87.926 - type: ndcg_at_100 value: 89.223 - type: ndcg_at_1000 value: 89.321 - type: ndcg_at_3 value: 85.036 - type: ndcg_at_5 value: 86.614 - type: precision_at_1 value: 80.88 - type: precision_at_10 value: 13.350000000000001 - type: precision_at_100 value: 1.5310000000000001 - type: precision_at_1000 value: 0.157 - type: precision_at_3 value: 37.173 - type: precision_at_5 value: 24.476 - type: recall_at_1 value: 70.21300000000001 - type: recall_at_10 value: 95.12 - type: recall_at_100 value: 99.535 - type: recall_at_1000 value: 99.977 - type: recall_at_3 value: 86.833 - type: recall_at_5 value: 91.26100000000001 - task: type: Clustering dataset: name: MTEB RedditClustering type: mteb/reddit-clustering config: default split: test revision: 24640382cdbf8abc73003fb0fa6d111a705499eb metrics: - type: v_measure value: 47.754688783184875 - task: type: Clustering dataset: name: MTEB RedditClusteringP2P type: mteb/reddit-clustering-p2p config: default split: test revision: 282350215ef01743dc01b456c7f5241fa8937f16 metrics: - type: v_measure value: 54.875736374329364 - task: type: Retrieval dataset: name: MTEB SCIDOCS type: scidocs config: default split: test revision: None metrics: - type: map_at_1 value: 3.773 - type: map_at_10 value: 9.447 - type: map_at_100 value: 11.1 - type: map_at_1000 value: 11.37 - type: map_at_3 value: 6.787 - type: map_at_5 value: 8.077 - type: mrr_at_1 value: 18.5 - type: mrr_at_10 value: 28.227000000000004 - type: mrr_at_100 value: 29.445 - type: mrr_at_1000 value: 29.515 - type: mrr_at_3 value: 25.2 - type: mrr_at_5 value: 27.055 - type: ndcg_at_1 value: 18.5 - type: ndcg_at_10 value: 16.29 - type: ndcg_at_100 value: 23.250999999999998 - type: ndcg_at_1000 value: 28.445999999999998 - type: ndcg_at_3 value: 15.376000000000001 - type: ndcg_at_5 value: 13.528 - type: precision_at_1 value: 18.5 - type: precision_at_10 value: 8.51 - type: precision_at_100 value: 1.855 - type: precision_at_1000 value: 0.311 - type: precision_at_3 value: 14.533 - type: precision_at_5 value: 12.0 - type: recall_at_1 value: 3.773 - type: recall_at_10 value: 17.282 - type: recall_at_100 value: 37.645 - type: recall_at_1000 value: 63.138000000000005 - type: recall_at_3 value: 8.853 - type: recall_at_5 value: 12.168 - task: type: STS dataset: name: MTEB SICK-R type: mteb/sickr-sts config: default split: test revision: a6ea5a8cab320b040a23452cc28066d9beae2cee metrics: - type: cos_sim_pearson value: 85.32789517976525 - type: cos_sim_spearman value: 80.32750384145629 - type: euclidean_pearson value: 81.5025131452508 - type: euclidean_spearman value: 80.24797115147175 - 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task: type: STS dataset: name: MTEB STS14 type: mteb/sts14-sts config: default split: test revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 metrics: - type: cos_sim_pearson value: 85.39810909161844 - type: cos_sim_spearman value: 82.98595295546008 - type: euclidean_pearson value: 84.04681129969951 - type: euclidean_spearman value: 82.98197460689866 - type: manhattan_pearson value: 83.9918798171185 - type: manhattan_spearman value: 82.91148131768082 - task: type: STS dataset: name: MTEB STS15 type: mteb/sts15-sts config: default split: test revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 metrics: - type: cos_sim_pearson value: 88.02072712147692 - type: cos_sim_spearman value: 88.78821332623012 - type: euclidean_pearson value: 88.12132045572747 - type: euclidean_spearman value: 88.74273451067364 - type: manhattan_pearson value: 88.05431550059166 - type: manhattan_spearman value: 88.67610233020723 - task: type: STS dataset: name: MTEB STS16 type: mteb/sts16-sts config: default split: test revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 metrics: - type: cos_sim_pearson value: 82.96134704624787 - type: cos_sim_spearman value: 84.44062976314666 - type: euclidean_pearson value: 84.03642536310323 - type: euclidean_spearman value: 84.4535014579785 - type: manhattan_pearson value: 83.92874228901483 - type: manhattan_spearman value: 84.33634314951631 - task: type: STS dataset: name: MTEB STS17 (en-de) type: mteb/sts17-crosslingual-sts config: en-de split: test revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics: - type: cos_sim_pearson value: 87.3154168064887 - type: cos_sim_spearman value: 86.72393652571682 - type: euclidean_pearson value: 86.04193246174164 - type: euclidean_spearman value: 86.30482896608093 - type: manhattan_pearson value: 85.95524084651859 - type: manhattan_spearman value: 86.06031431994282 - task: type: STS dataset: name: MTEB STS17 (en-en) type: mteb/sts17-crosslingual-sts config: en-en split: test revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics: - type: cos_sim_pearson value: 89.91079682750804 - 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type: ndcg_at_100 value: 64.513 - type: ndcg_at_1000 value: 65.62400000000001 - type: ndcg_at_3 value: 56.186 - type: ndcg_at_5 value: 58.692 - type: precision_at_1 value: 50.666999999999994 - type: precision_at_10 value: 8.200000000000001 - type: precision_at_100 value: 1.023 - type: precision_at_1000 value: 0.11199999999999999 - type: precision_at_3 value: 21.889 - type: precision_at_5 value: 14.866999999999999 - type: recall_at_1 value: 47.760999999999996 - type: recall_at_10 value: 72.006 - type: recall_at_100 value: 89.767 - type: recall_at_1000 value: 98.833 - type: recall_at_3 value: 60.211000000000006 - type: recall_at_5 value: 66.3 - task: type: PairClassification dataset: name: MTEB SprintDuplicateQuestions type: mteb/sprintduplicatequestions-pairclassification config: default split: test revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 metrics: - type: cos_sim_accuracy value: 99.79009900990098 - type: cos_sim_ap value: 94.86690691995835 - type: cos_sim_f1 value: 89.37875751503007 - type: cos_sim_precision value: 89.5582329317269 - type: cos_sim_recall value: 89.2 - type: dot_accuracy value: 99.76336633663367 - type: dot_ap value: 94.26453740761586 - type: dot_f1 value: 88.00783162016641 - type: dot_precision value: 86.19367209971237 - type: dot_recall value: 89.9 - type: euclidean_accuracy value: 99.7940594059406 - type: euclidean_ap value: 94.85459757524379 - type: euclidean_f1 value: 89.62779156327544 - type: euclidean_precision value: 88.96551724137932 - type: euclidean_recall value: 90.3 - type: manhattan_accuracy value: 99.79009900990098 - type: manhattan_ap value: 94.76971336654465 - type: manhattan_f1 value: 89.35323383084577 - type: manhattan_precision value: 88.91089108910892 - type: manhattan_recall value: 89.8 - type: max_accuracy value: 99.7940594059406 - type: max_ap value: 94.86690691995835 - type: max_f1 value: 89.62779156327544 - task: type: Clustering dataset: name: MTEB StackExchangeClustering type: mteb/stackexchange-clustering config: default split: test revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 metrics: - type: v_measure value: 55.38197670064987 - task: type: Clustering dataset: name: MTEB StackExchangeClusteringP2P type: mteb/stackexchange-clustering-p2p config: default split: test revision: 815ca46b2622cec33ccafc3735d572c266efdb44 metrics: - type: v_measure value: 33.08330158937971 - task: type: Reranking dataset: name: MTEB StackOverflowDupQuestions type: mteb/stackoverflowdupquestions-reranking config: default split: test revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 metrics: - type: map value: 49.50367079063226 - type: mrr value: 50.30444943128768 - task: type: Summarization dataset: name: MTEB SummEval type: mteb/summeval config: default split: test revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c metrics: - type: cos_sim_pearson value: 30.37739520909561 - type: cos_sim_spearman value: 31.548500943973913 - type: dot_pearson value: 29.983610104303 - type: dot_spearman value: 29.90185869098618 - task: type: Retrieval dataset: name: MTEB TRECCOVID type: trec-covid config: default split: test revision: None metrics: - type: map_at_1 value: 0.198 - type: map_at_10 value: 1.5810000000000002 - type: map_at_100 value: 9.064 - type: map_at_1000 value: 22.161 - type: map_at_3 value: 0.536 - type: map_at_5 value: 0.8370000000000001 - type: mrr_at_1 value: 80.0 - type: mrr_at_10 value: 86.75 - type: mrr_at_100 value: 86.799 - type: mrr_at_1000 value: 86.799 - type: mrr_at_3 value: 85.0 - type: mrr_at_5 value: 86.5 - type: ndcg_at_1 value: 73.0 - type: ndcg_at_10 value: 65.122 - type: ndcg_at_100 value: 51.853 - type: ndcg_at_1000 value: 47.275 - type: ndcg_at_3 value: 66.274 - type: ndcg_at_5 value: 64.826 - type: precision_at_1 value: 80.0 - type: precision_at_10 value: 70.19999999999999 - type: precision_at_100 value: 53.480000000000004 - type: precision_at_1000 value: 20.946 - type: precision_at_3 value: 71.333 - type: precision_at_5 value: 70.0 - type: recall_at_1 value: 0.198 - type: recall_at_10 value: 1.884 - type: recall_at_100 value: 12.57 - type: recall_at_1000 value: 44.208999999999996 - type: recall_at_3 value: 0.5890000000000001 - type: recall_at_5 value: 0.95 - task: type: Clustering dataset: name: MTEB TenKGnadClusteringP2P type: slvnwhrl/tenkgnad-clustering-p2p config: default split: test revision: 5c59e41555244b7e45c9a6be2d720ab4bafae558 metrics: - type: v_measure value: 42.84199261133083 - task: type: Clustering dataset: name: MTEB TenKGnadClusteringS2S type: slvnwhrl/tenkgnad-clustering-s2s config: default split: test revision: 6cddbe003f12b9b140aec477b583ac4191f01786 metrics: - type: v_measure value: 23.689557114798838 - task: type: Retrieval dataset: name: MTEB Touche2020 type: webis-touche2020 config: default split: test revision: None metrics: - type: map_at_1 value: 1.941 - type: map_at_10 value: 8.222 - type: map_at_100 value: 14.277999999999999 - type: map_at_1000 value: 15.790000000000001 - type: map_at_3 value: 4.4670000000000005 - type: map_at_5 value: 5.762 - type: mrr_at_1 value: 24.490000000000002 - type: mrr_at_10 value: 38.784 - type: mrr_at_100 value: 39.724 - type: mrr_at_1000 value: 39.724 - type: mrr_at_3 value: 33.333 - type: mrr_at_5 value: 37.415 - type: ndcg_at_1 value: 22.448999999999998 - type: ndcg_at_10 value: 21.026 - type: ndcg_at_100 value: 33.721000000000004 - type: ndcg_at_1000 value: 45.045 - type: ndcg_at_3 value: 20.053 - type: ndcg_at_5 value: 20.09 - type: precision_at_1 value: 24.490000000000002 - type: precision_at_10 value: 19.796 - type: precision_at_100 value: 7.469 - type: precision_at_1000 value: 1.48 - type: precision_at_3 value: 21.769 - type: precision_at_5 value: 21.224 - type: recall_at_1 value: 1.941 - type: recall_at_10 value: 14.915999999999999 - type: recall_at_100 value: 46.155 - type: recall_at_1000 value: 80.664 - type: recall_at_3 value: 5.629 - type: recall_at_5 value: 8.437 - task: type: Classification dataset: name: MTEB ToxicConversationsClassification type: mteb/toxic_conversations_50k config: default split: test revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c metrics: - type: accuracy value: 69.64800000000001 - type: ap value: 12.914826731261094 - type: f1 value: 53.05213503422915 - task: type: Classification dataset: name: MTEB TweetSentimentExtractionClassification type: mteb/tweet_sentiment_extraction config: default split: test revision: d604517c81ca91fe16a244d1248fc021f9ecee7a metrics: - type: accuracy value: 60.427277872099594 - type: f1 value: 60.78292007556828 - task: type: Clustering dataset: name: MTEB TwentyNewsgroupsClustering type: mteb/twentynewsgroups-clustering config: default split: test revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 metrics: - type: v_measure value: 40.48134168406559 - task: type: PairClassification dataset: name: MTEB TwitterSemEval2015 type: mteb/twittersemeval2015-pairclassification config: default split: test revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 metrics: - type: cos_sim_accuracy value: 84.79465935506944 - type: cos_sim_ap value: 70.24589055290592 - type: cos_sim_f1 value: 65.0994575045208 - type: cos_sim_precision value: 63.76518218623482 - type: cos_sim_recall value: 66.49076517150397 - type: dot_accuracy value: 84.63968528342374 - type: dot_ap value: 69.84683095084355 - type: dot_f1 value: 64.50606169727523 - type: dot_precision value: 59.1719885487778 - type: dot_recall value: 70.89709762532982 - type: euclidean_accuracy value: 84.76485664898374 - type: euclidean_ap value: 70.20556438685551 - type: euclidean_f1 value: 65.06796614516543 - type: euclidean_precision value: 63.29840319361277 - type: euclidean_recall value: 66.93931398416886 - type: manhattan_accuracy value: 84.72313286046374 - type: manhattan_ap value: 70.17151475534308 - type: manhattan_f1 value: 65.31379180759113 - type: manhattan_precision value: 62.17505366086334 - type: manhattan_recall value: 68.7862796833773 - type: max_accuracy value: 84.79465935506944 - type: max_ap value: 70.24589055290592 - type: max_f1 value: 65.31379180759113 - task: type: PairClassification dataset: name: MTEB TwitterURLCorpus type: mteb/twitterurlcorpus-pairclassification config: default split: test revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf metrics: - type: cos_sim_accuracy value: 88.95874568246207 - type: cos_sim_ap value: 85.82517548264127 - type: cos_sim_f1 value: 78.22288041466125 - type: cos_sim_precision value: 75.33875338753387 - type: cos_sim_recall value: 81.33661841700031 - type: dot_accuracy value: 88.836496293709 - type: dot_ap value: 85.53430720252186 - type: dot_f1 value: 78.10616085869725 - type: dot_precision value: 74.73269555430501 - type: dot_recall value: 81.79858330766862 - type: euclidean_accuracy value: 88.92769821865176 - type: euclidean_ap value: 85.65904346964223 - type: euclidean_f1 value: 77.98774074208407 - type: euclidean_precision value: 73.72282795035315 - type: euclidean_recall value: 82.77640899291654 - type: manhattan_accuracy value: 88.86366282454303 - type: manhattan_ap value: 85.61599642231819 - type: manhattan_f1 value: 78.01480509061737 - type: manhattan_precision value: 74.10460685833044 - type: manhattan_recall value: 82.36064059131506 - type: max_accuracy value: 88.95874568246207 - type: max_ap value: 85.82517548264127 - type: max_f1 value: 78.22288041466125 - task: type: Retrieval dataset: name: MTEB WikiCLIR type: None config: default split: test revision: None metrics: - type: map_at_1 value: 3.9539999999999997 - type: map_at_10 value: 7.407 - type: map_at_100 value: 8.677999999999999 - type: map_at_1000 value: 9.077 - type: map_at_3 value: 5.987 - type: map_at_5 value: 6.6979999999999995 - type: mrr_at_1 value: 35.65 - type: mrr_at_10 value: 45.097 - type: mrr_at_100 value: 45.83 - type: mrr_at_1000 value: 45.871 - type: mrr_at_3 value: 42.63 - type: mrr_at_5 value: 44.104 - type: ndcg_at_1 value: 29.215000000000003 - type: ndcg_at_10 value: 22.694 - type: ndcg_at_100 value: 22.242 - type: ndcg_at_1000 value: 27.069 - type: ndcg_at_3 value: 27.641 - type: ndcg_at_5 value: 25.503999999999998 - type: precision_at_1 value: 35.65 - type: precision_at_10 value: 12.795000000000002 - type: precision_at_100 value: 3.354 - type: precision_at_1000 value: 0.743 - type: precision_at_3 value: 23.403 - type: precision_at_5 value: 18.474 - type: recall_at_1 value: 3.9539999999999997 - type: recall_at_10 value: 11.301 - type: recall_at_100 value: 22.919999999999998 - type: recall_at_1000 value: 40.146 - type: recall_at_3 value: 7.146 - type: recall_at_5 value: 8.844000000000001 - task: type: Retrieval dataset: name: MTEB XMarket type: jinaai/xmarket_de config: default split: test revision: 2336818db4c06570fcdf263e1bcb9993b786f67a metrics: - type: map_at_1 value: 4.872 - type: map_at_10 value: 10.658 - type: map_at_100 value: 13.422999999999998 - type: map_at_1000 value: 14.245 - type: map_at_3 value: 7.857 - type: map_at_5 value: 9.142999999999999 - type: mrr_at_1 value: 16.744999999999997 - type: mrr_at_10 value: 24.416 - type: mrr_at_100 value: 25.432 - type: mrr_at_1000 value: 25.502999999999997 - type: mrr_at_3 value: 22.096 - type: mrr_at_5 value: 23.421 - type: ndcg_at_1 value: 16.695999999999998 - type: ndcg_at_10 value: 18.66 - type: ndcg_at_100 value: 24.314 - type: ndcg_at_1000 value: 29.846 - type: ndcg_at_3 value: 17.041999999999998 - type: ndcg_at_5 value: 17.585 - type: precision_at_1 value: 16.695999999999998 - type: precision_at_10 value: 10.374 - type: precision_at_100 value: 3.988 - type: precision_at_1000 value: 1.1860000000000002 - type: precision_at_3 value: 14.21 - type: precision_at_5 value: 12.623000000000001 - type: recall_at_1 value: 4.872 - type: recall_at_10 value: 18.624 - type: recall_at_100 value: 40.988 - type: recall_at_1000 value: 65.33 - type: recall_at_3 value: 10.162 - type: recall_at_5 value: 13.517999999999999 --- # chris-code/jina-embeddings-v2-base-de-Q8_0-GGUF This model was converted to GGUF format from [`jinaai/jina-embeddings-v2-base-de`](https://huggingface.co/jinaai/jina-embeddings-v2-base-de) 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/jinaai/jina-embeddings-v2-base-de) 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 chris-code/jina-embeddings-v2-base-de-Q8_0-GGUF --hf-file jina-embeddings-v2-base-de-q8_0.gguf -p "The meaning to life and the universe is" ``` ### Server: ```bash llama-server --hf-repo chris-code/jina-embeddings-v2-base-de-Q8_0-GGUF --hf-file jina-embeddings-v2-base-de-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 chris-code/jina-embeddings-v2-base-de-Q8_0-GGUF --hf-file jina-embeddings-v2-base-de-q8_0.gguf -p "The meaning to life and the universe is" ``` or ``` ./llama-server --hf-repo chris-code/jina-embeddings-v2-base-de-Q8_0-GGUF --hf-file jina-embeddings-v2-base-de-q8_0.gguf -c 2048 ```