--- base_model: infgrad/stella-base-en-v2 language: - en license: mit tags: - sentence-transformers - feature-extraction - sentence-similarity - mteb - llama-cpp - gguf-my-repo model-index: - name: stella-base-en-v2 results: - task: type: Classification dataset: name: MTEB AmazonCounterfactualClassification (en) type: mteb/amazon_counterfactual config: en split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics: - type: accuracy value: 77.19402985074628 - type: ap value: 40.43267503017359 - type: f1 value: 71.15585210518594 - task: type: Classification dataset: name: MTEB AmazonPolarityClassification type: mteb/amazon_polarity config: default split: test revision: e2d317d38cd51312af73b3d32a06d1a08b442046 metrics: - type: accuracy value: 93.256675 - type: ap value: 90.00824833079179 - type: f1 value: 93.2473146151734 - task: type: Classification dataset: name: MTEB AmazonReviewsClassification (en) type: mteb/amazon_reviews_multi config: en split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics: - type: accuracy value: 49.612 - type: f1 value: 48.530785631574304 - task: type: Retrieval dataset: name: MTEB ArguAna type: arguana config: default split: test revision: None metrics: - type: map_at_1 value: 37.411 - type: map_at_10 value: 52.673 - type: map_at_100 value: 53.410999999999994 - type: map_at_1000 value: 53.415 - type: map_at_3 value: 48.495 - type: map_at_5 value: 51.183 - type: mrr_at_1 value: 37.838 - type: mrr_at_10 value: 52.844 - type: mrr_at_100 value: 53.581999999999994 - type: mrr_at_1000 value: 53.586 - type: mrr_at_3 value: 48.672 - type: mrr_at_5 value: 51.272 - type: ndcg_at_1 value: 37.411 - type: ndcg_at_10 value: 60.626999999999995 - type: ndcg_at_100 value: 63.675000000000004 - type: ndcg_at_1000 value: 63.776999999999994 - type: ndcg_at_3 value: 52.148 - type: ndcg_at_5 value: 57.001999999999995 - type: precision_at_1 value: 37.411 - type: precision_at_10 value: 8.578 - type: precision_at_100 value: 0.989 - type: precision_at_1000 value: 0.1 - type: precision_at_3 value: 20.91 - type: precision_at_5 value: 14.908 - type: recall_at_1 value: 37.411 - type: recall_at_10 value: 85.775 - type: recall_at_100 value: 98.86200000000001 - type: recall_at_1000 value: 99.644 - type: recall_at_3 value: 62.731 - type: recall_at_5 value: 74.53800000000001 - task: type: Clustering dataset: name: MTEB ArxivClusteringP2P type: mteb/arxiv-clustering-p2p config: default split: test revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d metrics: - type: v_measure value: 47.24219029437865 - task: type: Clustering dataset: name: MTEB ArxivClusteringS2S type: mteb/arxiv-clustering-s2s config: default split: test revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 metrics: - type: v_measure value: 40.474604844291726 - task: type: Reranking dataset: name: MTEB AskUbuntuDupQuestions type: mteb/askubuntudupquestions-reranking config: default split: test revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 metrics: - type: map value: 62.720542706366054 - type: mrr value: 75.59633733456448 - task: type: STS dataset: name: MTEB BIOSSES type: mteb/biosses-sts config: default split: test revision: d3fb88f8f02e40887cd149695127462bbcf29b4a metrics: - type: cos_sim_pearson value: 86.31345008397868 - type: cos_sim_spearman value: 85.94292212320399 - type: euclidean_pearson value: 85.03974302774525 - type: euclidean_spearman value: 85.88087251659051 - type: manhattan_pearson value: 84.91900996712951 - type: manhattan_spearman value: 85.96701905781116 - task: type: Classification dataset: name: MTEB Banking77Classification type: mteb/banking77 config: default split: test revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 metrics: - type: accuracy value: 84.72727272727273 - type: f1 value: 84.29572512364581 - task: type: Clustering dataset: name: MTEB BiorxivClusteringP2P type: mteb/biorxiv-clustering-p2p config: default split: test revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 metrics: - type: v_measure value: 39.55532460397536 - task: type: Clustering dataset: name: MTEB BiorxivClusteringS2S type: mteb/biorxiv-clustering-s2s config: default split: test revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 metrics: - type: v_measure value: 35.91195973591251 - task: type: Retrieval dataset: name: MTEB CQADupstackAndroidRetrieval type: BeIR/cqadupstack config: default split: test revision: None metrics: - type: map_at_1 value: 32.822 - type: map_at_10 value: 44.139 - type: map_at_100 value: 45.786 - type: map_at_1000 value: 45.906000000000006 - type: map_at_3 value: 40.637 - type: map_at_5 value: 42.575 - type: mrr_at_1 value: 41.059 - type: mrr_at_10 value: 50.751000000000005 - type: mrr_at_100 value: 51.548 - type: mrr_at_1000 value: 51.583999999999996 - type: mrr_at_3 value: 48.236000000000004 - type: mrr_at_5 value: 49.838 - type: ndcg_at_1 value: 41.059 - type: ndcg_at_10 value: 50.573 - type: ndcg_at_100 value: 56.25 - type: ndcg_at_1000 value: 58.004 - type: ndcg_at_3 value: 45.995000000000005 - type: ndcg_at_5 value: 48.18 - type: precision_at_1 value: 41.059 - type: precision_at_10 value: 9.757 - type: precision_at_100 value: 1.609 - type: precision_at_1000 value: 0.20600000000000002 - type: precision_at_3 value: 22.222 - type: precision_at_5 value: 16.023 - type: recall_at_1 value: 32.822 - type: recall_at_10 value: 61.794000000000004 - type: recall_at_100 value: 85.64699999999999 - type: recall_at_1000 value: 96.836 - type: recall_at_3 value: 47.999 - type: recall_at_5 value: 54.376999999999995 - type: map_at_1 value: 29.579 - type: map_at_10 value: 39.787 - type: map_at_100 value: 40.976 - type: map_at_1000 value: 41.108 - type: map_at_3 value: 36.819 - type: map_at_5 value: 38.437 - type: mrr_at_1 value: 37.516 - type: mrr_at_10 value: 45.822 - type: mrr_at_100 value: 46.454 - type: mrr_at_1000 value: 46.495999999999995 - type: mrr_at_3 value: 43.556 - type: mrr_at_5 value: 44.814 - type: ndcg_at_1 value: 37.516 - type: ndcg_at_10 value: 45.5 - type: ndcg_at_100 value: 49.707 - type: ndcg_at_1000 value: 51.842 - type: ndcg_at_3 value: 41.369 - type: ndcg_at_5 value: 43.161 - type: precision_at_1 value: 37.516 - type: precision_at_10 value: 8.713 - type: precision_at_100 value: 1.38 - type: precision_at_1000 value: 0.188 - type: precision_at_3 value: 20.233999999999998 - type: precision_at_5 value: 14.280000000000001 - type: recall_at_1 value: 29.579 - type: recall_at_10 value: 55.458 - type: recall_at_100 value: 73.49799999999999 - type: recall_at_1000 value: 87.08200000000001 - type: recall_at_3 value: 42.858000000000004 - type: recall_at_5 value: 48.215 - type: map_at_1 value: 40.489999999999995 - type: map_at_10 value: 53.313 - type: map_at_100 value: 54.290000000000006 - type: map_at_1000 value: 54.346000000000004 - type: map_at_3 value: 49.983 - type: map_at_5 value: 51.867 - type: mrr_at_1 value: 46.27 - type: mrr_at_10 value: 56.660999999999994 - type: mrr_at_100 value: 57.274 - type: mrr_at_1000 value: 57.301 - type: mrr_at_3 value: 54.138 - type: mrr_at_5 value: 55.623999999999995 - type: ndcg_at_1 value: 46.27 - type: ndcg_at_10 value: 59.192 - type: ndcg_at_100 value: 63.026 - type: ndcg_at_1000 value: 64.079 - type: ndcg_at_3 value: 53.656000000000006 - type: ndcg_at_5 value: 56.387 - type: precision_at_1 value: 46.27 - type: precision_at_10 value: 9.511 - type: precision_at_100 value: 1.23 - type: precision_at_1000 value: 0.136 - type: precision_at_3 value: 24.096 - type: precision_at_5 value: 16.476 - type: recall_at_1 value: 40.489999999999995 - type: recall_at_10 value: 73.148 - type: recall_at_100 value: 89.723 - type: recall_at_1000 value: 97.073 - type: recall_at_3 value: 58.363 - type: recall_at_5 value: 65.083 - type: map_at_1 value: 26.197 - type: map_at_10 value: 35.135 - type: map_at_100 value: 36.14 - type: map_at_1000 value: 36.216 - type: map_at_3 value: 32.358 - type: map_at_5 value: 33.814 - type: mrr_at_1 value: 28.475 - type: mrr_at_10 value: 37.096000000000004 - type: mrr_at_100 value: 38.006 - type: mrr_at_1000 value: 38.06 - type: mrr_at_3 value: 34.52 - type: mrr_at_5 value: 35.994 - type: ndcg_at_1 value: 28.475 - type: ndcg_at_10 value: 40.263 - type: ndcg_at_100 value: 45.327 - type: ndcg_at_1000 value: 47.225 - type: ndcg_at_3 value: 34.882000000000005 - type: ndcg_at_5 value: 37.347 - type: precision_at_1 value: 28.475 - type: precision_at_10 value: 6.249 - type: precision_at_100 value: 0.919 - type: precision_at_1000 value: 0.11199999999999999 - type: precision_at_3 value: 14.689 - type: precision_at_5 value: 10.237 - type: recall_at_1 value: 26.197 - type: recall_at_10 value: 54.17999999999999 - type: recall_at_100 value: 77.768 - type: recall_at_1000 value: 91.932 - type: recall_at_3 value: 39.804 - type: recall_at_5 value: 45.660000000000004 - type: map_at_1 value: 16.683 - type: map_at_10 value: 25.013999999999996 - type: map_at_100 value: 26.411 - type: map_at_1000 value: 26.531 - type: map_at_3 value: 22.357 - type: map_at_5 value: 23.982999999999997 - type: mrr_at_1 value: 20.896 - type: mrr_at_10 value: 29.758000000000003 - type: mrr_at_100 value: 30.895 - type: mrr_at_1000 value: 30.964999999999996 - type: mrr_at_3 value: 27.177 - type: mrr_at_5 value: 28.799999999999997 - type: ndcg_at_1 value: 20.896 - type: ndcg_at_10 value: 30.294999999999998 - type: ndcg_at_100 value: 36.68 - type: ndcg_at_1000 value: 39.519 - type: ndcg_at_3 value: 25.480999999999998 - type: ndcg_at_5 value: 28.027 - type: precision_at_1 value: 20.896 - type: precision_at_10 value: 5.56 - type: precision_at_100 value: 1.006 - type: precision_at_1000 value: 0.13899999999999998 - type: precision_at_3 value: 12.231 - type: precision_at_5 value: 9.104 - type: recall_at_1 value: 16.683 - type: recall_at_10 value: 41.807 - type: recall_at_100 value: 69.219 - type: recall_at_1000 value: 89.178 - type: recall_at_3 value: 28.772 - type: recall_at_5 value: 35.167 - type: map_at_1 value: 30.653000000000002 - type: map_at_10 value: 41.21 - type: map_at_100 value: 42.543 - type: map_at_1000 value: 42.657000000000004 - type: map_at_3 value: 38.094 - type: map_at_5 value: 39.966 - type: mrr_at_1 value: 37.824999999999996 - type: mrr_at_10 value: 47.087 - type: mrr_at_100 value: 47.959 - type: mrr_at_1000 value: 48.003 - type: mrr_at_3 value: 45.043 - type: mrr_at_5 value: 46.352 - type: ndcg_at_1 value: 37.824999999999996 - type: ndcg_at_10 value: 47.158 - type: ndcg_at_100 value: 52.65 - type: ndcg_at_1000 value: 54.644999999999996 - type: ndcg_at_3 value: 42.632999999999996 - type: ndcg_at_5 value: 44.994 - type: precision_at_1 value: 37.824999999999996 - type: precision_at_10 value: 8.498999999999999 - type: precision_at_100 value: 1.308 - type: precision_at_1000 value: 0.166 - type: precision_at_3 value: 20.308 - type: precision_at_5 value: 14.283000000000001 - type: recall_at_1 value: 30.653000000000002 - type: recall_at_10 value: 58.826 - type: recall_at_100 value: 81.94 - type: recall_at_1000 value: 94.71000000000001 - type: recall_at_3 value: 45.965 - type: recall_at_5 value: 52.294 - type: map_at_1 value: 26.71 - type: map_at_10 value: 36.001 - type: map_at_100 value: 37.416 - type: map_at_1000 value: 37.522 - type: map_at_3 value: 32.841 - type: map_at_5 value: 34.515 - type: mrr_at_1 value: 32.647999999999996 - type: mrr_at_10 value: 41.43 - type: mrr_at_100 value: 42.433 - type: mrr_at_1000 value: 42.482 - type: mrr_at_3 value: 39.117000000000004 - type: mrr_at_5 value: 40.35 - type: ndcg_at_1 value: 32.647999999999996 - type: ndcg_at_10 value: 41.629 - type: ndcg_at_100 value: 47.707 - type: ndcg_at_1000 value: 49.913000000000004 - type: ndcg_at_3 value: 36.598000000000006 - type: ndcg_at_5 value: 38.696000000000005 - type: precision_at_1 value: 32.647999999999996 - type: precision_at_10 value: 7.704999999999999 - type: precision_at_100 value: 1.242 - type: precision_at_1000 value: 0.16 - type: precision_at_3 value: 17.314 - type: precision_at_5 value: 12.374 - type: recall_at_1 value: 26.71 - type: recall_at_10 value: 52.898 - type: recall_at_100 value: 79.08 - type: recall_at_1000 value: 93.94 - type: recall_at_3 value: 38.731 - type: recall_at_5 value: 44.433 - type: map_at_1 value: 26.510999999999996 - type: map_at_10 value: 35.755333333333326 - type: map_at_100 value: 36.97525 - type: map_at_1000 value: 37.08741666666667 - type: map_at_3 value: 32.921 - type: map_at_5 value: 34.45041666666667 - type: mrr_at_1 value: 31.578416666666666 - type: mrr_at_10 value: 40.06066666666667 - type: mrr_at_100 value: 40.93350000000001 - type: mrr_at_1000 value: 40.98716666666667 - type: mrr_at_3 value: 37.710499999999996 - type: mrr_at_5 value: 39.033249999999995 - type: ndcg_at_1 value: 31.578416666666666 - type: ndcg_at_10 value: 41.138666666666666 - type: ndcg_at_100 value: 46.37291666666666 - type: ndcg_at_1000 value: 48.587500000000006 - type: ndcg_at_3 value: 36.397083333333335 - type: ndcg_at_5 value: 38.539 - type: precision_at_1 value: 31.578416666666666 - type: precision_at_10 value: 7.221583333333332 - type: precision_at_100 value: 1.1581666666666668 - type: precision_at_1000 value: 0.15416666666666667 - type: precision_at_3 value: 16.758 - type: precision_at_5 value: 11.830916666666665 - type: recall_at_1 value: 26.510999999999996 - type: recall_at_10 value: 52.7825 - type: recall_at_100 value: 75.79675 - type: recall_at_1000 value: 91.10483333333335 - type: recall_at_3 value: 39.48233333333334 - type: recall_at_5 value: 45.07116666666667 - type: map_at_1 value: 24.564 - type: map_at_10 value: 31.235000000000003 - type: map_at_100 value: 32.124 - type: map_at_1000 value: 32.216 - type: map_at_3 value: 29.330000000000002 - type: map_at_5 value: 30.379 - type: mrr_at_1 value: 27.761000000000003 - type: mrr_at_10 value: 34.093 - type: mrr_at_100 value: 34.885 - type: mrr_at_1000 value: 34.957 - type: mrr_at_3 value: 32.388 - type: mrr_at_5 value: 33.269 - type: ndcg_at_1 value: 27.761000000000003 - type: ndcg_at_10 value: 35.146 - type: ndcg_at_100 value: 39.597 - type: ndcg_at_1000 value: 42.163000000000004 - type: ndcg_at_3 value: 31.674000000000003 - type: ndcg_at_5 value: 33.224 - type: precision_at_1 value: 27.761000000000003 - type: precision_at_10 value: 5.383 - type: precision_at_100 value: 0.836 - type: precision_at_1000 value: 0.11199999999999999 - type: precision_at_3 value: 13.599 - type: precision_at_5 value: 9.202 - type: recall_at_1 value: 24.564 - type: recall_at_10 value: 44.36 - type: recall_at_100 value: 64.408 - type: recall_at_1000 value: 83.892 - type: recall_at_3 value: 34.653 - type: recall_at_5 value: 38.589 - type: map_at_1 value: 17.01 - type: map_at_10 value: 24.485 - type: map_at_100 value: 25.573 - type: map_at_1000 value: 25.703 - type: map_at_3 value: 21.953 - type: map_at_5 value: 23.294999999999998 - type: mrr_at_1 value: 20.544 - type: mrr_at_10 value: 28.238000000000003 - type: mrr_at_100 value: 29.142000000000003 - type: mrr_at_1000 value: 29.219 - type: mrr_at_3 value: 25.802999999999997 - type: mrr_at_5 value: 27.105 - type: ndcg_at_1 value: 20.544 - type: ndcg_at_10 value: 29.387999999999998 - type: ndcg_at_100 value: 34.603 - type: ndcg_at_1000 value: 37.564 - type: ndcg_at_3 value: 24.731 - type: ndcg_at_5 value: 26.773000000000003 - type: precision_at_1 value: 20.544 - type: precision_at_10 value: 5.509 - type: precision_at_100 value: 0.9450000000000001 - type: precision_at_1000 value: 0.13799999999999998 - type: precision_at_3 value: 11.757 - type: precision_at_5 value: 8.596 - type: recall_at_1 value: 17.01 - type: recall_at_10 value: 40.392 - type: recall_at_100 value: 64.043 - type: recall_at_1000 value: 85.031 - type: recall_at_3 value: 27.293 - type: recall_at_5 value: 32.586999999999996 - type: map_at_1 value: 27.155 - type: map_at_10 value: 35.92 - type: map_at_100 value: 37.034 - type: map_at_1000 value: 37.139 - type: map_at_3 value: 33.263999999999996 - type: map_at_5 value: 34.61 - type: mrr_at_1 value: 32.183 - type: mrr_at_10 value: 40.099000000000004 - type: mrr_at_100 value: 41.001 - type: mrr_at_1000 value: 41.059 - type: mrr_at_3 value: 37.889 - type: mrr_at_5 value: 39.007999999999996 - type: ndcg_at_1 value: 32.183 - type: ndcg_at_10 value: 41.127 - type: ndcg_at_100 value: 46.464 - type: ndcg_at_1000 value: 48.67 - type: ndcg_at_3 value: 36.396 - type: ndcg_at_5 value: 38.313 - type: precision_at_1 value: 32.183 - type: precision_at_10 value: 6.847 - type: precision_at_100 value: 1.0739999999999998 - type: precision_at_1000 value: 0.13699999999999998 - type: precision_at_3 value: 16.356 - type: precision_at_5 value: 11.362 - type: recall_at_1 value: 27.155 - type: recall_at_10 value: 52.922000000000004 - type: recall_at_100 value: 76.39 - type: recall_at_1000 value: 91.553 - type: recall_at_3 value: 39.745999999999995 - type: recall_at_5 value: 44.637 - type: map_at_1 value: 25.523 - type: map_at_10 value: 34.268 - type: map_at_100 value: 35.835 - type: map_at_1000 value: 36.046 - type: map_at_3 value: 31.662000000000003 - type: map_at_5 value: 32.71 - type: mrr_at_1 value: 31.028 - type: mrr_at_10 value: 38.924 - type: mrr_at_100 value: 39.95 - type: mrr_at_1000 value: 40.003 - type: mrr_at_3 value: 36.594 - type: mrr_at_5 value: 37.701 - type: ndcg_at_1 value: 31.028 - type: ndcg_at_10 value: 39.848 - type: ndcg_at_100 value: 45.721000000000004 - type: ndcg_at_1000 value: 48.424 - type: ndcg_at_3 value: 35.329 - type: ndcg_at_5 value: 36.779 - type: precision_at_1 value: 31.028 - type: precision_at_10 value: 7.51 - type: precision_at_100 value: 1.478 - type: precision_at_1000 value: 0.24 - type: precision_at_3 value: 16.337 - type: precision_at_5 value: 11.383000000000001 - type: recall_at_1 value: 25.523 - type: recall_at_10 value: 50.735 - type: recall_at_100 value: 76.593 - type: recall_at_1000 value: 93.771 - type: recall_at_3 value: 37.574000000000005 - type: recall_at_5 value: 41.602 - type: map_at_1 value: 20.746000000000002 - type: map_at_10 value: 28.557 - type: map_at_100 value: 29.575000000000003 - type: map_at_1000 value: 29.659000000000002 - type: map_at_3 value: 25.753999999999998 - type: map_at_5 value: 27.254 - type: mrr_at_1 value: 22.736 - type: mrr_at_10 value: 30.769000000000002 - type: mrr_at_100 value: 31.655 - type: mrr_at_1000 value: 31.717000000000002 - type: mrr_at_3 value: 28.065 - type: mrr_at_5 value: 29.543999999999997 - type: ndcg_at_1 value: 22.736 - type: ndcg_at_10 value: 33.545 - type: ndcg_at_100 value: 38.743 - type: ndcg_at_1000 value: 41.002 - type: ndcg_at_3 value: 28.021 - type: ndcg_at_5 value: 30.586999999999996 - type: precision_at_1 value: 22.736 - type: precision_at_10 value: 5.416 - type: precision_at_100 value: 0.8710000000000001 - type: precision_at_1000 value: 0.116 - type: precision_at_3 value: 11.953 - type: precision_at_5 value: 8.651 - type: recall_at_1 value: 20.746000000000002 - type: recall_at_10 value: 46.87 - type: recall_at_100 value: 71.25200000000001 - type: recall_at_1000 value: 88.26 - type: recall_at_3 value: 32.029999999999994 - type: recall_at_5 value: 38.21 - task: type: Retrieval dataset: name: MTEB ClimateFEVER type: climate-fever config: default split: test revision: None metrics: - type: map_at_1 value: 12.105 - type: map_at_10 value: 20.577 - type: map_at_100 value: 22.686999999999998 - type: map_at_1000 value: 22.889 - type: map_at_3 value: 17.174 - type: map_at_5 value: 18.807 - type: mrr_at_1 value: 27.101 - type: mrr_at_10 value: 38.475 - type: mrr_at_100 value: 39.491 - type: mrr_at_1000 value: 39.525 - type: mrr_at_3 value: 34.886 - type: mrr_at_5 value: 36.922 - type: ndcg_at_1 value: 27.101 - type: ndcg_at_10 value: 29.002 - type: ndcg_at_100 value: 37.218 - type: ndcg_at_1000 value: 40.644000000000005 - type: ndcg_at_3 value: 23.464 - type: ndcg_at_5 value: 25.262 - type: precision_at_1 value: 27.101 - type: precision_at_10 value: 9.179 - type: precision_at_100 value: 1.806 - type: precision_at_1000 value: 0.244 - type: precision_at_3 value: 17.394000000000002 - type: precision_at_5 value: 13.342 - type: recall_at_1 value: 12.105 - type: recall_at_10 value: 35.143 - type: recall_at_100 value: 63.44499999999999 - type: recall_at_1000 value: 82.49499999999999 - type: recall_at_3 value: 21.489 - type: recall_at_5 value: 26.82 - task: type: Retrieval dataset: name: MTEB DBPedia type: dbpedia-entity config: default split: test revision: None metrics: - type: map_at_1 value: 8.769 - type: map_at_10 value: 18.619 - type: map_at_100 value: 26.3 - type: map_at_1000 value: 28.063 - type: map_at_3 value: 13.746 - type: map_at_5 value: 16.035 - type: mrr_at_1 value: 65.25 - type: mrr_at_10 value: 73.678 - type: mrr_at_100 value: 73.993 - type: mrr_at_1000 value: 74.003 - type: mrr_at_3 value: 72.042 - type: mrr_at_5 value: 72.992 - type: ndcg_at_1 value: 53.625 - type: ndcg_at_10 value: 39.638 - type: ndcg_at_100 value: 44.601 - type: ndcg_at_1000 value: 52.80200000000001 - type: ndcg_at_3 value: 44.727 - type: ndcg_at_5 value: 42.199 - type: precision_at_1 value: 65.25 - type: precision_at_10 value: 31.025000000000002 - type: precision_at_100 value: 10.174999999999999 - type: precision_at_1000 value: 2.0740000000000003 - type: precision_at_3 value: 48.083 - type: precision_at_5 value: 40.6 - type: recall_at_1 value: 8.769 - type: recall_at_10 value: 23.910999999999998 - type: recall_at_100 value: 51.202999999999996 - type: recall_at_1000 value: 77.031 - type: recall_at_3 value: 15.387999999999998 - type: recall_at_5 value: 18.919 - task: type: Classification dataset: name: MTEB EmotionClassification type: mteb/emotion config: default split: test revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 metrics: - type: accuracy value: 54.47 - type: f1 value: 48.21839043361556 - task: type: Retrieval dataset: name: MTEB FEVER type: fever config: default split: test revision: None metrics: - type: map_at_1 value: 63.564 - type: map_at_10 value: 74.236 - type: map_at_100 value: 74.53699999999999 - type: map_at_1000 value: 74.557 - type: map_at_3 value: 72.556 - type: map_at_5 value: 73.656 - type: mrr_at_1 value: 68.497 - type: mrr_at_10 value: 78.373 - type: mrr_at_100 value: 78.54299999999999 - type: mrr_at_1000 value: 78.549 - type: mrr_at_3 value: 77.03 - type: mrr_at_5 value: 77.938 - type: ndcg_at_1 value: 68.497 - type: ndcg_at_10 value: 79.12599999999999 - type: ndcg_at_100 value: 80.319 - type: ndcg_at_1000 value: 80.71199999999999 - type: ndcg_at_3 value: 76.209 - type: ndcg_at_5 value: 77.90700000000001 - type: precision_at_1 value: 68.497 - type: precision_at_10 value: 9.958 - type: precision_at_100 value: 1.077 - type: precision_at_1000 value: 0.11299999999999999 - type: precision_at_3 value: 29.908 - type: precision_at_5 value: 18.971 - type: recall_at_1 value: 63.564 - type: recall_at_10 value: 90.05199999999999 - type: recall_at_100 value: 95.028 - type: recall_at_1000 value: 97.667 - type: recall_at_3 value: 82.17999999999999 - type: recall_at_5 value: 86.388 - task: type: Retrieval dataset: name: MTEB FiQA2018 type: fiqa config: default split: test revision: None metrics: - type: map_at_1 value: 19.042 - type: map_at_10 value: 30.764999999999997 - type: map_at_100 value: 32.678000000000004 - type: map_at_1000 value: 32.881 - type: map_at_3 value: 26.525 - type: map_at_5 value: 28.932000000000002 - type: mrr_at_1 value: 37.653999999999996 - type: mrr_at_10 value: 46.597 - type: mrr_at_100 value: 47.413 - type: mrr_at_1000 value: 47.453 - type: mrr_at_3 value: 43.775999999999996 - type: mrr_at_5 value: 45.489000000000004 - type: ndcg_at_1 value: 37.653999999999996 - type: ndcg_at_10 value: 38.615 - type: ndcg_at_100 value: 45.513999999999996 - type: ndcg_at_1000 value: 48.815999999999995 - type: ndcg_at_3 value: 34.427 - type: ndcg_at_5 value: 35.954 - type: precision_at_1 value: 37.653999999999996 - type: precision_at_10 value: 10.864 - type: precision_at_100 value: 1.7850000000000001 - type: precision_at_1000 value: 0.23800000000000002 - type: precision_at_3 value: 22.788 - type: precision_at_5 value: 17.346 - type: recall_at_1 value: 19.042 - type: recall_at_10 value: 45.707 - type: recall_at_100 value: 71.152 - type: recall_at_1000 value: 90.7 - type: recall_at_3 value: 30.814000000000004 - type: recall_at_5 value: 37.478 - task: type: Retrieval dataset: name: MTEB HotpotQA type: hotpotqa config: default split: test revision: None metrics: - type: map_at_1 value: 38.001000000000005 - type: map_at_10 value: 59.611000000000004 - type: map_at_100 value: 60.582 - type: map_at_1000 value: 60.646 - type: map_at_3 value: 56.031 - type: map_at_5 value: 58.243 - type: mrr_at_1 value: 76.003 - type: mrr_at_10 value: 82.15400000000001 - type: mrr_at_100 value: 82.377 - type: mrr_at_1000 value: 82.383 - type: mrr_at_3 value: 81.092 - type: mrr_at_5 value: 81.742 - type: ndcg_at_1 value: 76.003 - type: ndcg_at_10 value: 68.216 - type: ndcg_at_100 value: 71.601 - type: ndcg_at_1000 value: 72.821 - type: ndcg_at_3 value: 63.109 - type: ndcg_at_5 value: 65.902 - type: precision_at_1 value: 76.003 - type: precision_at_10 value: 14.379 - type: precision_at_100 value: 1.702 - type: precision_at_1000 value: 0.186 - type: precision_at_3 value: 40.396 - type: precision_at_5 value: 26.442 - type: recall_at_1 value: 38.001000000000005 - type: recall_at_10 value: 71.897 - type: recall_at_100 value: 85.105 - type: recall_at_1000 value: 93.133 - type: recall_at_3 value: 60.594 - type: recall_at_5 value: 66.104 - task: type: Classification dataset: name: MTEB ImdbClassification type: mteb/imdb config: default split: test revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 metrics: - type: accuracy value: 91.31280000000001 - type: ap value: 87.53723467501632 - type: f1 value: 91.30282906596291 - task: type: Retrieval dataset: name: MTEB MSMARCO type: msmarco config: default split: dev revision: None metrics: - type: map_at_1 value: 21.917 - type: map_at_10 value: 34.117999999999995 - type: map_at_100 value: 35.283 - type: map_at_1000 value: 35.333999999999996 - type: map_at_3 value: 30.330000000000002 - type: map_at_5 value: 32.461 - type: mrr_at_1 value: 22.579 - type: mrr_at_10 value: 34.794000000000004 - type: mrr_at_100 value: 35.893 - type: mrr_at_1000 value: 35.937000000000005 - type: mrr_at_3 value: 31.091 - type: mrr_at_5 value: 33.173 - type: ndcg_at_1 value: 22.579 - type: ndcg_at_10 value: 40.951 - type: ndcg_at_100 value: 46.558 - type: ndcg_at_1000 value: 47.803000000000004 - type: ndcg_at_3 value: 33.262 - type: ndcg_at_5 value: 37.036 - type: precision_at_1 value: 22.579 - type: precision_at_10 value: 6.463000000000001 - type: precision_at_100 value: 0.928 - type: precision_at_1000 value: 0.104 - type: precision_at_3 value: 14.174000000000001 - type: precision_at_5 value: 10.421 - type: recall_at_1 value: 21.917 - type: recall_at_10 value: 61.885 - type: recall_at_100 value: 87.847 - type: recall_at_1000 value: 97.322 - type: recall_at_3 value: 41.010000000000005 - type: recall_at_5 value: 50.031000000000006 - task: type: Classification dataset: name: MTEB MTOPDomainClassification (en) type: mteb/mtop_domain config: en split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics: - type: accuracy value: 93.49521203830369 - type: f1 value: 93.30882341740241 - task: type: Classification dataset: name: MTEB MTOPIntentClassification (en) type: mteb/mtop_intent config: en split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics: - type: accuracy value: 71.0579115367077 - type: f1 value: 51.2368258319339 - task: type: Classification dataset: name: MTEB MassiveIntentClassification (en) type: mteb/amazon_massive_intent config: en split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 73.88029589778077 - type: f1 value: 72.34422048584663 - task: type: Classification dataset: name: MTEB MassiveScenarioClassification (en) type: mteb/amazon_massive_scenario config: en split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 78.2817753866846 - type: f1 value: 77.87746050004304 - task: type: Clustering dataset: name: MTEB MedrxivClusteringP2P type: mteb/medrxiv-clustering-p2p config: default split: test revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 metrics: - type: v_measure value: 33.247341454119216 - task: type: Clustering dataset: name: MTEB MedrxivClusteringS2S type: mteb/medrxiv-clustering-s2s config: default split: test revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 metrics: - type: v_measure value: 31.9647477166234 - task: type: Reranking dataset: name: MTEB MindSmallReranking type: mteb/mind_small config: default split: test revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 metrics: - type: map value: 31.90698374676892 - type: mrr value: 33.07523683771251 - task: type: Retrieval dataset: name: MTEB NFCorpus type: nfcorpus config: default split: test revision: None metrics: - type: map_at_1 value: 6.717 - type: map_at_10 value: 14.566 - type: map_at_100 value: 18.465999999999998 - type: map_at_1000 value: 20.033 - type: map_at_3 value: 10.863 - type: map_at_5 value: 12.589 - type: mrr_at_1 value: 49.845 - type: mrr_at_10 value: 58.385 - type: mrr_at_100 value: 58.989999999999995 - type: mrr_at_1000 value: 59.028999999999996 - type: mrr_at_3 value: 56.76 - type: mrr_at_5 value: 57.766 - type: ndcg_at_1 value: 47.678 - type: ndcg_at_10 value: 37.511 - type: ndcg_at_100 value: 34.537 - type: ndcg_at_1000 value: 43.612 - type: ndcg_at_3 value: 43.713 - type: ndcg_at_5 value: 41.303 - type: precision_at_1 value: 49.845 - type: precision_at_10 value: 27.307 - type: precision_at_100 value: 8.746 - type: precision_at_1000 value: 2.182 - type: precision_at_3 value: 40.764 - type: precision_at_5 value: 35.232 - type: recall_at_1 value: 6.717 - type: recall_at_10 value: 18.107 - type: recall_at_100 value: 33.759 - type: recall_at_1000 value: 67.31 - type: recall_at_3 value: 11.68 - type: recall_at_5 value: 14.557999999999998 - task: type: Retrieval dataset: name: MTEB NQ type: nq config: default split: test revision: None metrics: - type: map_at_1 value: 27.633999999999997 - type: map_at_10 value: 42.400999999999996 - type: map_at_100 value: 43.561 - type: map_at_1000 value: 43.592 - type: map_at_3 value: 37.865 - type: map_at_5 value: 40.650999999999996 - type: mrr_at_1 value: 31.286 - type: mrr_at_10 value: 44.996 - type: mrr_at_100 value: 45.889 - type: mrr_at_1000 value: 45.911 - type: mrr_at_3 value: 41.126000000000005 - type: mrr_at_5 value: 43.536 - type: ndcg_at_1 value: 31.257 - type: ndcg_at_10 value: 50.197 - type: ndcg_at_100 value: 55.062 - type: ndcg_at_1000 value: 55.81700000000001 - type: ndcg_at_3 value: 41.650999999999996 - type: ndcg_at_5 value: 46.324 - type: precision_at_1 value: 31.257 - type: precision_at_10 value: 8.508000000000001 - type: precision_at_100 value: 1.121 - type: precision_at_1000 value: 0.11900000000000001 - type: precision_at_3 value: 19.1 - type: precision_at_5 value: 14.16 - type: recall_at_1 value: 27.633999999999997 - type: recall_at_10 value: 71.40100000000001 - type: recall_at_100 value: 92.463 - type: recall_at_1000 value: 98.13199999999999 - type: recall_at_3 value: 49.382 - type: recall_at_5 value: 60.144 - task: type: Retrieval dataset: name: MTEB QuoraRetrieval type: quora config: default split: test revision: None metrics: - type: map_at_1 value: 71.17099999999999 - type: map_at_10 value: 85.036 - type: map_at_100 value: 85.67099999999999 - type: map_at_1000 value: 85.68599999999999 - type: map_at_3 value: 82.086 - type: map_at_5 value: 83.956 - type: mrr_at_1 value: 82.04 - type: mrr_at_10 value: 88.018 - type: mrr_at_100 value: 88.114 - type: mrr_at_1000 value: 88.115 - type: mrr_at_3 value: 87.047 - type: mrr_at_5 value: 87.73100000000001 - type: ndcg_at_1 value: 82.03 - type: ndcg_at_10 value: 88.717 - type: ndcg_at_100 value: 89.904 - type: ndcg_at_1000 value: 89.991 - type: ndcg_at_3 value: 85.89099999999999 - type: ndcg_at_5 value: 87.485 - type: precision_at_1 value: 82.03 - type: precision_at_10 value: 13.444999999999999 - type: precision_at_100 value: 1.533 - type: precision_at_1000 value: 0.157 - type: precision_at_3 value: 37.537 - type: precision_at_5 value: 24.692 - type: recall_at_1 value: 71.17099999999999 - type: recall_at_10 value: 95.634 - type: recall_at_100 value: 99.614 - type: recall_at_1000 value: 99.99 - type: recall_at_3 value: 87.48 - type: recall_at_5 value: 91.996 - task: type: Clustering dataset: name: MTEB RedditClustering type: mteb/reddit-clustering config: default split: test revision: 24640382cdbf8abc73003fb0fa6d111a705499eb metrics: - type: v_measure value: 55.067219624685315 - task: type: Clustering dataset: name: MTEB RedditClusteringP2P type: mteb/reddit-clustering-p2p config: default split: test revision: 282350215ef01743dc01b456c7f5241fa8937f16 metrics: - type: v_measure value: 62.121822992300444 - task: type: Retrieval dataset: name: MTEB SCIDOCS type: scidocs config: default split: test revision: None metrics: - type: map_at_1 value: 4.153 - type: map_at_10 value: 11.024000000000001 - type: map_at_100 value: 13.233 - type: map_at_1000 value: 13.62 - type: map_at_3 value: 7.779999999999999 - type: map_at_5 value: 9.529 - type: mrr_at_1 value: 20.599999999999998 - type: mrr_at_10 value: 31.361 - type: mrr_at_100 value: 32.738 - type: mrr_at_1000 value: 32.792 - type: mrr_at_3 value: 28.15 - type: mrr_at_5 value: 30.085 - type: ndcg_at_1 value: 20.599999999999998 - type: ndcg_at_10 value: 18.583 - type: ndcg_at_100 value: 27.590999999999998 - type: ndcg_at_1000 value: 34.001 - type: ndcg_at_3 value: 17.455000000000002 - type: ndcg_at_5 value: 15.588 - type: precision_at_1 value: 20.599999999999998 - type: precision_at_10 value: 9.74 - type: precision_at_100 value: 2.284 - type: precision_at_1000 value: 0.381 - type: precision_at_3 value: 16.533 - type: precision_at_5 value: 14.02 - type: recall_at_1 value: 4.153 - type: recall_at_10 value: 19.738 - type: recall_at_100 value: 46.322 - type: recall_at_1000 value: 77.378 - type: recall_at_3 value: 10.048 - type: recall_at_5 value: 14.233 - task: type: STS dataset: name: MTEB SICK-R type: mteb/sickr-sts config: default split: test revision: a6ea5a8cab320b040a23452cc28066d9beae2cee metrics: - type: cos_sim_pearson value: 85.07097501003639 - type: cos_sim_spearman value: 81.05827848407056 - type: euclidean_pearson value: 82.6279003372546 - type: euclidean_spearman value: 81.00031515279802 - type: manhattan_pearson value: 82.59338284959495 - type: manhattan_spearman value: 80.97432711064945 - task: type: STS dataset: name: MTEB STS12 type: mteb/sts12-sts config: default split: test revision: a0d554a64d88156834ff5ae9920b964011b16384 metrics: - type: cos_sim_pearson value: 86.28991993621685 - type: cos_sim_spearman value: 78.71828082424351 - type: euclidean_pearson value: 83.4881331520832 - type: euclidean_spearman value: 78.51746826842316 - type: manhattan_pearson value: 83.4109223774324 - type: manhattan_spearman value: 78.431544382179 - task: type: STS dataset: name: MTEB STS13 type: mteb/sts13-sts config: default split: test revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca metrics: - type: cos_sim_pearson value: 83.16651661072123 - type: cos_sim_spearman value: 84.88094386637867 - type: euclidean_pearson value: 84.3547603585416 - type: euclidean_spearman value: 84.85148665860193 - type: manhattan_pearson value: 84.29648369879266 - type: manhattan_spearman value: 84.76074870571124 - task: type: STS dataset: name: MTEB STS14 type: mteb/sts14-sts config: default split: test revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 metrics: - type: cos_sim_pearson value: 83.40596254292149 - type: cos_sim_spearman value: 83.10699573133829 - type: euclidean_pearson value: 83.22794776876958 - type: euclidean_spearman value: 83.22583316084712 - type: manhattan_pearson value: 83.15899233935681 - type: manhattan_spearman value: 83.17668293648019 - task: type: STS dataset: name: MTEB STS15 type: mteb/sts15-sts config: default split: test revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 metrics: - type: cos_sim_pearson value: 87.27977121352563 - type: cos_sim_spearman value: 88.73903130248591 - type: euclidean_pearson value: 88.30685958438735 - type: euclidean_spearman value: 88.79755484280406 - type: manhattan_pearson value: 88.30305607758652 - type: manhattan_spearman value: 88.80096577072784 - task: type: STS dataset: name: MTEB STS16 type: mteb/sts16-sts config: default split: test revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 metrics: - type: cos_sim_pearson value: 84.08819031430218 - type: cos_sim_spearman value: 86.35414445951125 - type: euclidean_pearson value: 85.4683192388315 - type: euclidean_spearman value: 86.2079674669473 - type: manhattan_pearson value: 85.35835702257341 - type: manhattan_spearman value: 86.08483380002187 - task: type: STS dataset: name: MTEB STS17 (en-en) type: mteb/sts17-crosslingual-sts config: en-en split: test revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d metrics: - type: cos_sim_pearson value: 87.36149449801478 - type: cos_sim_spearman value: 87.7102980757725 - type: euclidean_pearson value: 88.16457177837161 - type: euclidean_spearman value: 87.6598652482716 - type: manhattan_pearson value: 88.23894728971618 - type: manhattan_spearman value: 87.74470156709361 - task: type: STS dataset: name: MTEB STS22 (en) type: mteb/sts22-crosslingual-sts config: en split: test revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 metrics: - type: cos_sim_pearson value: 64.54023758394433 - type: cos_sim_spearman value: 66.28491960187773 - type: euclidean_pearson value: 67.0853128483472 - type: euclidean_spearman value: 66.10307543766307 - type: manhattan_pearson value: 66.7635365592556 - type: manhattan_spearman value: 65.76408004780167 - task: type: STS dataset: name: MTEB STSBenchmark type: mteb/stsbenchmark-sts config: default split: test revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 metrics: - type: cos_sim_pearson value: 85.15858398195317 - type: cos_sim_spearman value: 87.44850004752102 - type: euclidean_pearson value: 86.60737082550408 - type: euclidean_spearman value: 87.31591549824242 - type: manhattan_pearson value: 86.56187011429977 - type: manhattan_spearman value: 87.23854795795319 - task: type: Reranking dataset: name: MTEB SciDocsRR type: mteb/scidocs-reranking config: default split: test revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab metrics: - type: map value: 86.66210488769109 - type: mrr value: 96.23100664767331 - task: type: Retrieval dataset: name: MTEB SciFact type: scifact config: default split: test revision: None metrics: - type: map_at_1 value: 56.094 - type: map_at_10 value: 67.486 - type: map_at_100 value: 67.925 - type: map_at_1000 value: 67.949 - type: map_at_3 value: 64.857 - type: map_at_5 value: 66.31 - type: mrr_at_1 value: 58.667 - type: mrr_at_10 value: 68.438 - type: mrr_at_100 value: 68.733 - type: mrr_at_1000 value: 68.757 - type: mrr_at_3 value: 66.389 - type: mrr_at_5 value: 67.456 - type: ndcg_at_1 value: 58.667 - type: ndcg_at_10 value: 72.506 - type: ndcg_at_100 value: 74.27 - type: ndcg_at_1000 value: 74.94800000000001 - type: ndcg_at_3 value: 67.977 - type: ndcg_at_5 value: 70.028 - type: precision_at_1 value: 58.667 - type: precision_at_10 value: 9.767000000000001 - type: precision_at_100 value: 1.073 - type: precision_at_1000 value: 0.11299999999999999 - type: precision_at_3 value: 27.0 - type: precision_at_5 value: 17.666999999999998 - type: recall_at_1 value: 56.094 - type: recall_at_10 value: 86.68900000000001 - type: recall_at_100 value: 94.333 - type: recall_at_1000 value: 99.667 - type: recall_at_3 value: 74.522 - type: recall_at_5 value: 79.611 - task: type: PairClassification dataset: name: MTEB SprintDuplicateQuestions type: mteb/sprintduplicatequestions-pairclassification config: default split: test revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 metrics: - type: cos_sim_accuracy value: 99.83069306930693 - type: cos_sim_ap value: 95.69184662911199 - type: cos_sim_f1 value: 91.4027149321267 - type: cos_sim_precision value: 91.91102123356926 - type: cos_sim_recall value: 90.9 - type: dot_accuracy value: 99.69405940594059 - type: dot_ap value: 90.21674151456216 - type: dot_f1 value: 84.4489179667841 - type: dot_precision value: 85.00506585612969 - type: dot_recall value: 83.89999999999999 - type: euclidean_accuracy value: 99.83069306930693 - type: euclidean_ap value: 95.67760109671087 - type: euclidean_f1 value: 91.19754350051177 - type: euclidean_precision value: 93.39622641509435 - type: euclidean_recall value: 89.1 - type: manhattan_accuracy value: 99.83267326732673 - type: manhattan_ap value: 95.69771347732625 - type: manhattan_f1 value: 91.32420091324201 - type: manhattan_precision value: 92.68795056642637 - type: manhattan_recall value: 90.0 - type: max_accuracy value: 99.83267326732673 - type: max_ap value: 95.69771347732625 - type: max_f1 value: 91.4027149321267 - task: type: Clustering dataset: name: MTEB StackExchangeClustering type: mteb/stackexchange-clustering config: default split: test revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 metrics: - type: v_measure value: 64.47378332953092 - task: type: Clustering dataset: name: MTEB StackExchangeClusteringP2P type: mteb/stackexchange-clustering-p2p config: default split: test revision: 815ca46b2622cec33ccafc3735d572c266efdb44 metrics: - type: v_measure value: 33.79602531604151 - task: type: Reranking dataset: name: MTEB StackOverflowDupQuestions type: mteb/stackoverflowdupquestions-reranking config: default split: test revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 metrics: - type: map value: 53.80707639107175 - type: mrr value: 54.64886522790935 - task: type: Summarization dataset: name: MTEB SummEval type: mteb/summeval config: default split: test revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c metrics: - type: cos_sim_pearson value: 30.852448373051395 - type: cos_sim_spearman value: 32.51821499493775 - type: dot_pearson value: 30.390650062190456 - type: dot_spearman value: 30.588836159667636 - 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: 1.51 - type: map_at_100 value: 8.882 - type: map_at_1000 value: 22.181 - type: map_at_3 value: 0.553 - type: map_at_5 value: 0.843 - type: mrr_at_1 value: 74.0 - type: mrr_at_10 value: 84.89999999999999 - type: mrr_at_100 value: 84.89999999999999 - type: mrr_at_1000 value: 84.89999999999999 - type: mrr_at_3 value: 84.0 - type: mrr_at_5 value: 84.89999999999999 - type: ndcg_at_1 value: 68.0 - type: ndcg_at_10 value: 64.792 - type: ndcg_at_100 value: 51.37199999999999 - type: ndcg_at_1000 value: 47.392 - type: ndcg_at_3 value: 68.46900000000001 - type: ndcg_at_5 value: 67.084 - type: precision_at_1 value: 74.0 - type: precision_at_10 value: 69.39999999999999 - type: precision_at_100 value: 53.080000000000005 - type: precision_at_1000 value: 21.258 - type: precision_at_3 value: 76.0 - type: precision_at_5 value: 73.2 - type: recall_at_1 value: 0.198 - type: recall_at_10 value: 1.7950000000000002 - type: recall_at_100 value: 12.626999999999999 - type: recall_at_1000 value: 44.84 - type: recall_at_3 value: 0.611 - type: recall_at_5 value: 0.959 - task: type: Retrieval dataset: name: MTEB Touche2020 type: webis-touche2020 config: default split: test revision: None metrics: - type: map_at_1 value: 1.4949999999999999 - type: map_at_10 value: 8.797 - type: map_at_100 value: 14.889 - type: map_at_1000 value: 16.309 - type: map_at_3 value: 4.389 - type: map_at_5 value: 6.776 - type: mrr_at_1 value: 18.367 - type: mrr_at_10 value: 35.844 - type: mrr_at_100 value: 37.119 - type: mrr_at_1000 value: 37.119 - type: mrr_at_3 value: 30.612000000000002 - type: mrr_at_5 value: 33.163 - type: ndcg_at_1 value: 16.326999999999998 - type: ndcg_at_10 value: 21.9 - type: ndcg_at_100 value: 34.705000000000005 - type: ndcg_at_1000 value: 45.709 - type: ndcg_at_3 value: 22.7 - type: ndcg_at_5 value: 23.197000000000003 - type: precision_at_1 value: 18.367 - type: precision_at_10 value: 21.02 - type: precision_at_100 value: 7.714 - type: precision_at_1000 value: 1.504 - type: precision_at_3 value: 26.531 - type: precision_at_5 value: 26.122 - type: recall_at_1 value: 1.4949999999999999 - type: recall_at_10 value: 15.504000000000001 - type: recall_at_100 value: 47.978 - type: recall_at_1000 value: 81.56 - type: recall_at_3 value: 5.569 - type: recall_at_5 value: 9.821 - task: type: Classification dataset: name: MTEB ToxicConversationsClassification type: mteb/toxic_conversations_50k config: default split: test revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c metrics: - type: accuracy value: 72.99279999999999 - type: ap value: 15.459189680101492 - type: f1 value: 56.33023271441895 - task: type: Classification dataset: name: MTEB TweetSentimentExtractionClassification type: mteb/tweet_sentiment_extraction config: default split: test revision: d604517c81ca91fe16a244d1248fc021f9ecee7a metrics: - type: accuracy value: 63.070175438596486 - type: f1 value: 63.28070758709465 - task: type: Clustering dataset: name: MTEB TwentyNewsgroupsClustering type: mteb/twentynewsgroups-clustering config: default split: test revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 metrics: - type: v_measure value: 50.076231309703054 - task: type: PairClassification dataset: name: MTEB TwitterSemEval2015 type: mteb/twittersemeval2015-pairclassification config: default split: test revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 metrics: - type: cos_sim_accuracy value: 87.21463908922931 - type: cos_sim_ap value: 77.67287017966282 - type: cos_sim_f1 value: 70.34412955465588 - type: cos_sim_precision value: 67.57413709285368 - type: cos_sim_recall value: 73.35092348284961 - type: dot_accuracy value: 85.04500208618943 - type: dot_ap value: 70.4075203869744 - type: dot_f1 value: 66.18172537008678 - type: dot_precision value: 64.08798813643104 - type: dot_recall value: 68.41688654353561 - type: euclidean_accuracy value: 87.17887584192646 - type: euclidean_ap value: 77.5774128274464 - type: euclidean_f1 value: 70.09307972480777 - type: euclidean_precision value: 71.70852884349986 - type: euclidean_recall value: 68.54881266490766 - type: manhattan_accuracy value: 87.28020504261787 - type: manhattan_ap value: 77.57835820297892 - type: manhattan_f1 value: 70.23063591521131 - type: manhattan_precision value: 70.97817299919159 - type: manhattan_recall value: 69.49868073878628 - type: max_accuracy value: 87.28020504261787 - type: max_ap value: 77.67287017966282 - type: max_f1 value: 70.34412955465588 - task: type: PairClassification dataset: name: MTEB TwitterURLCorpus type: mteb/twitterurlcorpus-pairclassification config: default split: test revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf metrics: - type: cos_sim_accuracy value: 88.96650754841464 - type: cos_sim_ap value: 86.00185968965064 - type: cos_sim_f1 value: 77.95861256351718 - type: cos_sim_precision value: 74.70712773465067 - type: cos_sim_recall value: 81.50600554357868 - type: dot_accuracy value: 87.36950362867233 - type: dot_ap value: 82.22071181147555 - type: dot_f1 value: 74.85680716698488 - type: dot_precision value: 71.54688377316114 - type: dot_recall value: 78.48783492454572 - type: euclidean_accuracy value: 88.99561454573679 - type: euclidean_ap value: 86.15882097229648 - type: euclidean_f1 value: 78.18463125322332 - type: euclidean_precision value: 74.95408956067241 - type: euclidean_recall value: 81.70619032953496 - type: manhattan_accuracy value: 88.96650754841464 - type: manhattan_ap value: 86.13133111232099 - type: manhattan_f1 value: 78.10771470160115 - type: manhattan_precision value: 74.05465084184377 - type: manhattan_recall value: 82.63012011087157 - type: max_accuracy value: 88.99561454573679 - type: max_ap value: 86.15882097229648 - type: max_f1 value: 78.18463125322332 --- # djuna/stella-base-en-v2-Q5_K_M-GGUF This model was converted to GGUF format from [`infgrad/stella-base-en-v2`](https://huggingface.co/infgrad/stella-base-en-v2) 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/infgrad/stella-base-en-v2) 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 djuna/stella-base-en-v2-Q5_K_M-GGUF --hf-file stella-base-en-v2-q5_k_m.gguf -p "The meaning to life and the universe is" ``` ### Server: ```bash llama-server --hf-repo djuna/stella-base-en-v2-Q5_K_M-GGUF --hf-file stella-base-en-v2-q5_k_m.gguf -c 2048 ``` Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well. 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 djuna/stella-base-en-v2-Q5_K_M-GGUF --hf-file stella-base-en-v2-q5_k_m.gguf -p "The meaning to life and the universe is" ``` or ``` ./llama-server --hf-repo djuna/stella-base-en-v2-Q5_K_M-GGUF --hf-file stella-base-en-v2-q5_k_m.gguf -c 2048 ```