diff --git "a/README.md" "b/README.md" --- "a/README.md" +++ "b/README.md" @@ -1,199 +1,2958 @@ --- -library_name: transformers -tags: [] +pipeline_tag: sentence-similarity +tags: +- sentence-transformers +- feature-extraction +- sentence-similarity +- mteb +model-index: +- name: modernbert-embed-large-unsupervised + results: + - task: + type: Classification + dataset: + type: None + name: MTEB AmazonCounterfactualClassification (en) + config: en + split: test + revision: e8379541af4e31359cca9fbcf4b00f2671dba205 + metrics: + - type: accuracy + value: 76.64179104477611 + - type: ap + value: 39.43815135661555 + - type: f1 + value: 70.47335737802807 + - task: + type: Classification + dataset: + type: None + name: MTEB AmazonPolarityClassification + config: default + split: test + revision: e2d317d38cd51312af73b3d32a06d1a08b442046 + metrics: + - type: accuracy + value: 91.830425 + - type: ap + value: 88.83626170006555 + - type: f1 + value: 91.82486904365354 + - task: + type: Classification + dataset: + type: None + name: MTEB AmazonReviewsClassification (en) + config: en + split: test + revision: 1399c76144fd37290681b995c656ef9b2e06e26d + metrics: + - type: accuracy + value: 47.864000000000004 + - type: f1 + value: 47.28133361073809 + - task: + type: Retrieval + dataset: + type: None + name: MTEB ArguAna + config: default + split: test + revision: c22ab2a51041ffd869aaddef7af8d8215647e41a + metrics: + - type: map_at_1 + value: 26.884999999999998 + - type: map_at_10 + value: 41.525 + - type: map_at_100 + value: 42.61 + - type: map_at_1000 + value: 42.617 + - type: map_at_20 + value: 42.422 + - type: map_at_3 + value: 36.143 + - type: map_at_5 + value: 39.215 + - type: mrr_at_1 + value: 27.168999999999997 + - type: mrr_at_10 + value: 41.659 + - type: mrr_at_100 + value: 42.737 + - type: mrr_at_1000 + value: 42.742999999999995 + - type: mrr_at_20 + value: 42.549 + - type: mrr_at_3 + value: 36.202 + - type: mrr_at_5 + value: 39.342 + - type: ndcg_at_1 + value: 26.884999999999998 + - type: ndcg_at_10 + value: 50.515 + - type: ndcg_at_100 + value: 54.94 + - type: ndcg_at_1000 + value: 55.092 + - type: ndcg_at_20 + value: 53.68000000000001 + - type: ndcg_at_3 + value: 39.357 + - type: ndcg_at_5 + value: 44.909 + - type: precision_at_1 + value: 26.884999999999998 + - type: precision_at_10 + value: 7.959 + - type: precision_at_100 + value: 0.985 + - type: precision_at_1000 + value: 0.1 + - type: precision_at_20 + value: 4.595 + - type: precision_at_3 + value: 16.24 + - type: precision_at_5 + value: 12.447 + - type: recall_at_1 + value: 26.884999999999998 + - type: recall_at_10 + value: 79.587 + - type: recall_at_100 + value: 98.506 + - type: recall_at_1000 + value: 99.644 + - type: recall_at_20 + value: 91.892 + - type: recall_at_3 + value: 48.72 + - type: recall_at_5 + value: 62.233000000000004 + - task: + type: Clustering + dataset: + type: None + name: MTEB ArxivClusteringP2P + config: default + split: test + revision: 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recall_at_1 + value: 28.796 + - type: recall_at_10 + value: 56.385 + - type: recall_at_100 + value: 79.244 + - type: recall_at_1000 + value: 91.959 + - type: recall_at_20 + value: 63.82600000000001 + - type: recall_at_3 + value: 42.594 + - type: recall_at_5 + value: 49.448 + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack + name: MTEB CQADupstackMathematicaRetrieval + config: default + split: test + revision: 90fceea13679c63fe563ded68f3b6f06e50061de + metrics: + - type: map_at_1 + value: 18.976000000000003 + - type: map_at_10 + value: 27.622000000000003 + - type: map_at_100 + value: 28.732999999999997 + - type: map_at_1000 + value: 28.849999999999998 + - type: map_at_20 + value: 28.217 + - type: map_at_3 + value: 24.631 + - type: map_at_5 + value: 26.365 + - type: mrr_at_1 + value: 23.383000000000003 + - type: mrr_at_10 + value: 32.296 + - type: mrr_at_100 + value: 33.156 + - type: mrr_at_1000 + value: 33.222 + - type: mrr_at_20 + value: 32.775 + - type: mrr_at_3 + value: 29.333 + - type: mrr_at_5 + value: 31.197999999999997 + - type: ndcg_at_1 + value: 23.383000000000003 + - type: ndcg_at_10 + value: 33.241 + - type: ndcg_at_100 + value: 38.494 + - type: ndcg_at_1000 + value: 41.096 + - type: ndcg_at_20 + value: 35.193999999999996 + - type: ndcg_at_3 + value: 27.728 + - type: ndcg_at_5 + value: 30.574 + - type: precision_at_1 + value: 23.383000000000003 + - type: precision_at_10 + value: 6.132 + - type: precision_at_100 + value: 1.0070000000000001 + - type: precision_at_1000 + value: 0.13699999999999998 + - type: precision_at_20 + value: 3.6380000000000003 + - type: precision_at_3 + value: 13.267000000000001 + - type: precision_at_5 + value: 9.950000000000001 + - type: recall_at_1 + value: 18.976000000000003 + - type: recall_at_10 + value: 45.906000000000006 + - type: recall_at_100 + value: 68.59100000000001 + - type: recall_at_1000 + value: 86.574 + - type: recall_at_20 + value: 52.851000000000006 + - type: recall_at_3 + value: 30.880000000000003 + - type: recall_at_5 + value: 38.01 + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack + name: MTEB CQADupstackPhysicsRetrieval + config: default + split: test + revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4 + metrics: + - type: map_at_1 + value: 33.077 + - type: map_at_10 + value: 43.877 + - type: map_at_100 + value: 45.243 + - type: map_at_1000 + value: 45.344 + - type: map_at_20 + value: 44.657000000000004 + - type: map_at_3 + value: 40.474 + - type: map_at_5 + value: 42.449999999999996 + - type: mrr_at_1 + value: 40.711999999999996 + - type: mrr_at_10 + value: 49.918 + - type: mrr_at_100 + value: 50.754 + - type: mrr_at_1000 + value: 50.797000000000004 + - type: mrr_at_20 + value: 50.461 + - type: mrr_at_3 + value: 47.53 + - type: mrr_at_5 + value: 48.94 + - type: ndcg_at_1 + value: 40.711999999999996 + - type: ndcg_at_10 + value: 49.863 + - type: ndcg_at_100 + value: 55.228 + - type: ndcg_at_1000 + value: 56.962999999999994 + - type: ndcg_at_20 + value: 52.181 + - type: ndcg_at_3 + value: 44.79 + - type: ndcg_at_5 + value: 47.331 + - type: precision_at_1 + value: 40.711999999999996 + - type: precision_at_10 + value: 8.892999999999999 + - type: precision_at_100 + value: 1.346 + - type: precision_at_1000 + value: 0.166 + - type: precision_at_20 + value: 5.226 + - type: precision_at_3 + value: 21.014 + - type: precision_at_5 + value: 14.957 + - type: recall_at_1 + value: 33.077 + - type: recall_at_10 + value: 61.641 + - type: recall_at_100 + value: 83.612 + - type: recall_at_1000 + value: 94.643 + - type: recall_at_20 + value: 69.717 + - type: recall_at_3 + value: 47.247 + - type: recall_at_5 + value: 53.93 + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack + name: MTEB CQADupstackProgrammersRetrieval + config: default + split: test + revision: 6184bc1440d2dbc7612be22b50686b8826d22b32 + metrics: + - type: map_at_1 + value: 30.275999999999996 + - type: map_at_10 + value: 41.343999999999994 + - type: map_at_100 + value: 42.651 + - type: map_at_1000 + value: 42.75 + - type: map_at_20 + value: 42.077 + - type: map_at_3 + value: 37.894 + - type: map_at_5 + value: 39.896 + - type: mrr_at_1 + value: 37.329 + - type: mrr_at_10 + value: 46.842 + - type: mrr_at_100 + value: 47.699000000000005 + - type: mrr_at_1000 + value: 47.744 + - type: mrr_at_20 + value: 47.367 + - type: mrr_at_3 + value: 44.330000000000005 + - type: mrr_at_5 + value: 45.928000000000004 + - type: ndcg_at_1 + value: 37.329 + - type: ndcg_at_10 + value: 47.473 + - type: ndcg_at_100 + value: 52.793 + - type: ndcg_at_1000 + value: 54.69199999999999 + - type: ndcg_at_20 + value: 49.685 + - type: ndcg_at_3 + value: 42.254999999999995 + - type: ndcg_at_5 + value: 44.859 + - type: precision_at_1 + value: 37.329 + - type: precision_at_10 + value: 8.619 + - type: precision_at_100 + value: 1.304 + - type: precision_at_1000 + value: 0.164 + - type: precision_at_20 + value: 5.0 + - type: precision_at_3 + value: 20.091 + - type: precision_at_5 + value: 14.405999999999999 + - type: recall_at_1 + value: 30.275999999999996 + - type: recall_at_10 + value: 60.168 + - type: recall_at_100 + value: 82.402 + - type: recall_at_1000 + value: 94.925 + - type: recall_at_20 + value: 68.068 + - type: recall_at_3 + value: 45.660000000000004 + - type: recall_at_5 + value: 52.443 + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack + name: MTEB CQADupstackRetrieval + config: default + split: test + revision: 90fceea13679c63fe563ded68f3b6f06e50061de + metrics: + - type: map_at_1 + value: 30.108083333333337 + - type: map_at_10 + value: 39.95216666666666 + - type: map_at_100 + value: 41.14641666666667 + - type: map_at_1000 + value: 41.253916666666676 + - type: map_at_20 + value: 40.60283333333333 + - type: map_at_3 + value: 36.947750000000006 + - type: map_at_5 + value: 38.69591666666666 + - type: mrr_at_1 + value: 35.64074999999999 + - type: mrr_at_10 + value: 44.3555 + - type: mrr_at_100 + value: 45.15133333333334 + - type: mrr_at_1000 + value: 45.200500000000005 + - type: mrr_at_20 + value: 44.81816666666668 + - type: mrr_at_3 + value: 41.940083333333334 + - type: mrr_at_5 + value: 43.430499999999995 + - type: ndcg_at_1 + value: 35.64074999999999 + - type: ndcg_at_10 + value: 45.47233333333333 + - type: ndcg_at_100 + value: 50.36216666666667 + - type: ndcg_at_1000 + value: 52.32325 + - type: ndcg_at_20 + value: 47.371 + - type: ndcg_at_3 + value: 40.630583333333334 + - type: ndcg_at_5 + value: 43.072916666666664 + - type: precision_at_1 + value: 35.64074999999999 + - type: precision_at_10 + value: 7.861833333333333 + - type: precision_at_100 + value: 1.214 + - type: precision_at_1000 + value: 0.15641666666666668 + - type: precision_at_20 + value: 4.578833333333334 + - type: precision_at_3 + value: 18.608999999999998 + - type: precision_at_5 + value: 13.18025 + - type: recall_at_1 + value: 30.108083333333337 + - type: recall_at_10 + value: 57.2905 + - type: recall_at_100 + value: 78.5085 + - type: recall_at_1000 + value: 91.88283333333334 + - type: recall_at_20 + value: 64.17899999999999 + - type: recall_at_3 + value: 43.79366666666667 + - type: recall_at_5 + value: 50.15716666666666 + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack + name: MTEB CQADupstackStatsRetrieval + config: default + split: test + revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a + metrics: + - type: map_at_1 + value: 27.383000000000003 + - type: map_at_10 + value: 35.071000000000005 + - type: map_at_100 + value: 36.019 + - type: map_at_1000 + value: 36.112 + - type: map_at_20 + value: 35.577999999999996 + - type: map_at_3 + value: 32.952 + - type: map_at_5 + value: 34.109 + - type: mrr_at_1 + value: 30.520999999999997 + - type: mrr_at_10 + value: 38.175 + - type: mrr_at_100 + value: 38.955 + - type: mrr_at_1000 + value: 39.021 + - type: mrr_at_20 + value: 38.619 + - type: mrr_at_3 + value: 36.272999999999996 + - type: mrr_at_5 + value: 37.330999999999996 + - type: ndcg_at_1 + value: 30.520999999999997 + - type: ndcg_at_10 + value: 39.461 + - type: ndcg_at_100 + value: 43.919999999999995 + - type: ndcg_at_1000 + value: 46.331 + - type: ndcg_at_20 + value: 41.128 + - type: ndcg_at_3 + value: 35.642 + - type: ndcg_at_5 + value: 37.407000000000004 + - type: precision_at_1 + value: 30.520999999999997 + - type: precision_at_10 + value: 6.104 + - type: precision_at_100 + value: 0.905 + - type: precision_at_1000 + value: 0.11900000000000001 + - type: precision_at_20 + value: 3.497 + - type: precision_at_3 + value: 15.389 + - type: precision_at_5 + value: 10.428999999999998 + - type: recall_at_1 + value: 27.383000000000003 + - type: recall_at_10 + value: 49.733 + - type: recall_at_100 + value: 69.77799999999999 + - type: recall_at_1000 + value: 87.711 + - type: recall_at_20 + value: 55.94 + - type: recall_at_3 + value: 38.858 + - type: recall_at_5 + value: 43.497 + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack + name: MTEB CQADupstackTexRetrieval + config: default + split: test + revision: 46989137a86843e03a6195de44b09deda022eec7 + metrics: + - type: map_at_1 + value: 19.963 + - type: map_at_10 + value: 27.425 + - type: map_at_100 + value: 28.563 + - type: map_at_1000 + value: 28.683999999999997 + - type: map_at_20 + value: 28.060000000000002 + - type: map_at_3 + value: 25.22 + - type: map_at_5 + value: 26.345000000000002 + - type: mrr_at_1 + value: 24.329 + - type: mrr_at_10 + value: 31.775 + - type: mrr_at_100 + value: 32.724 + - type: mrr_at_1000 + value: 32.794000000000004 + - type: mrr_at_20 + value: 32.335 + - type: mrr_at_3 + value: 29.812 + - type: mrr_at_5 + value: 30.839 + - type: ndcg_at_1 + value: 24.329 + - type: ndcg_at_10 + value: 32.206 + - type: ndcg_at_100 + value: 37.469 + - type: ndcg_at_1000 + value: 40.251 + - type: ndcg_at_20 + value: 34.282000000000004 + - type: ndcg_at_3 + value: 28.364 + - type: ndcg_at_5 + value: 29.929 + - type: precision_at_1 + value: 24.329 + - type: precision_at_10 + value: 5.7669999999999995 + - type: precision_at_100 + value: 0.975 + - type: precision_at_1000 + value: 0.13899999999999998 + - type: precision_at_20 + value: 3.486 + - type: precision_at_3 + value: 13.375 + - type: precision_at_5 + value: 9.374 + - type: recall_at_1 + value: 19.963 + - type: recall_at_10 + value: 42.272999999999996 + - type: recall_at_100 + value: 65.668 + - type: recall_at_1000 + value: 85.487 + - type: recall_at_20 + value: 50.01 + - type: recall_at_3 + value: 31.136000000000003 + - type: recall_at_5 + value: 35.353 + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack + name: MTEB CQADupstackUnixRetrieval + config: default + split: test + revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53 + metrics: + - type: map_at_1 + value: 32.568999999999996 + - type: map_at_10 + value: 41.551 + - type: map_at_100 + value: 42.655 + - type: map_at_1000 + value: 42.75 + - type: map_at_20 + value: 42.083999999999996 + - type: map_at_3 + value: 38.956 + - type: map_at_5 + value: 40.502 + - type: mrr_at_1 + value: 37.966 + - type: mrr_at_10 + value: 46.013999999999996 + - type: mrr_at_100 + value: 46.807 + - type: mrr_at_1000 + value: 46.855999999999995 + - type: mrr_at_20 + value: 46.409 + - type: mrr_at_3 + value: 43.874 + - type: mrr_at_5 + value: 45.176 + - type: ndcg_at_1 + value: 37.966 + - type: ndcg_at_10 + value: 46.592 + - type: ndcg_at_100 + value: 51.665000000000006 + - type: ndcg_at_1000 + value: 53.677 + - type: ndcg_at_20 + value: 48.244 + - type: ndcg_at_3 + value: 42.224000000000004 + - type: ndcg_at_5 + value: 44.399 + - type: precision_at_1 + value: 37.966 + - type: precision_at_10 + value: 7.519000000000001 + - type: precision_at_100 + value: 1.131 + - type: precision_at_1000 + value: 0.14100000000000001 + - type: precision_at_20 + value: 4.2540000000000004 + - type: precision_at_3 + value: 18.843 + - type: precision_at_5 + value: 12.966 + - type: recall_at_1 + value: 32.568999999999996 + - type: recall_at_10 + value: 57.364000000000004 + - type: recall_at_100 + value: 79.512 + - type: recall_at_1000 + value: 93.298 + - type: recall_at_20 + value: 63.173 + - type: recall_at_3 + value: 45.28 + - type: recall_at_5 + value: 50.974 + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack + name: MTEB CQADupstackWebmastersRetrieval + config: default + split: test + revision: 160c094312a0e1facb97e55eeddb698c0abe3571 + metrics: + - type: map_at_1 + value: 29.814 + - type: map_at_10 + value: 39.215 + - type: map_at_100 + value: 41.007 + - type: map_at_1000 + value: 41.232 + - type: map_at_20 + value: 40.221000000000004 + - type: map_at_3 + value: 35.814 + - type: map_at_5 + value: 37.747 + - type: mrr_at_1 + value: 35.771 + - type: mrr_at_10 + value: 44.131 + - type: mrr_at_100 + value: 45.09 + - type: mrr_at_1000 + value: 45.135999999999996 + - type: mrr_at_20 + value: 44.738 + - type: mrr_at_3 + value: 41.173 + - type: mrr_at_5 + value: 43.05 + - type: ndcg_at_1 + value: 35.771 + - type: ndcg_at_10 + value: 45.461 + - type: ndcg_at_100 + value: 51.278 + - type: ndcg_at_1000 + value: 53.40899999999999 + - type: ndcg_at_20 + value: 47.957 + - type: ndcg_at_3 + value: 39.919 + - type: ndcg_at_5 + value: 42.773 + - type: precision_at_1 + value: 35.771 + - type: precision_at_10 + value: 8.538 + - type: precision_at_100 + value: 1.696 + - type: precision_at_1000 + value: 0.248 + - type: precision_at_20 + value: 5.524 + - type: precision_at_3 + value: 18.314 + - type: precision_at_5 + value: 13.517999999999999 + - type: recall_at_1 + value: 29.814 + - type: recall_at_10 + value: 57.30499999999999 + - type: recall_at_100 + value: 82.21300000000001 + - type: recall_at_1000 + value: 95.379 + - type: recall_at_20 + value: 66.295 + - type: recall_at_3 + value: 41.929 + - type: recall_at_5 + value: 49.515 + - task: + type: Retrieval + dataset: + type: BeIR/cqadupstack + name: MTEB CQADupstackWordpressRetrieval + config: default + split: test + revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4 + metrics: + - type: map_at_1 + value: 23.788999999999998 + - type: map_at_10 + value: 32.308 + - type: map_at_100 + value: 33.211 + - type: map_at_1000 + value: 33.302 + - type: map_at_20 + value: 32.725 + - type: map_at_3 + value: 29.38 + - type: map_at_5 + value: 31.161 + - type: mrr_at_1 + value: 26.063 + - type: mrr_at_10 + value: 34.284 + - type: mrr_at_100 + value: 35.083 + - type: mrr_at_1000 + value: 35.143 + - type: mrr_at_20 + value: 34.627 + - type: mrr_at_3 + value: 31.391999999999996 + - type: mrr_at_5 + value: 33.129999999999995 + - type: ndcg_at_1 + value: 26.063 + - type: ndcg_at_10 + value: 37.289 + - type: ndcg_at_100 + value: 42.067 + - type: ndcg_at_1000 + value: 44.122 + - type: ndcg_at_20 + value: 38.634 + - type: ndcg_at_3 + value: 31.557000000000002 + - type: ndcg_at_5 + value: 34.596 + - type: precision_at_1 + value: 26.063 + - type: precision_at_10 + value: 5.86 + - type: precision_at_100 + value: 0.8909999999999999 + - type: precision_at_1000 + value: 0.11800000000000001 + - type: precision_at_20 + value: 3.2620000000000005 + - type: precision_at_3 + value: 13.309000000000001 + - type: precision_at_5 + value: 9.76 + - type: recall_at_1 + value: 23.788999999999998 + - type: recall_at_10 + value: 50.822 + - type: recall_at_100 + value: 73.345 + - type: recall_at_1000 + value: 88.249 + - type: recall_at_20 + value: 55.757999999999996 + - type: recall_at_3 + value: 35.662 + - type: recall_at_5 + value: 42.862 + - task: + type: Retrieval + dataset: + type: None + name: MTEB ClimateFEVER + config: default + split: test + revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380 + metrics: + - type: map_at_1 + value: 7.251 + - type: map_at_10 + value: 13.541 + - type: map_at_100 + value: 15.242 + - type: map_at_1000 + value: 15.442 + - type: map_at_20 + value: 14.358 + - type: map_at_3 + value: 10.751 + - type: map_at_5 + value: 12.149000000000001 + - type: mrr_at_1 + value: 16.547 + - type: mrr_at_10 + value: 26.590999999999998 + - type: mrr_at_100 + value: 27.767999999999997 + - type: 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recall_at_5 + value: 19.244 + - task: + type: Retrieval + dataset: + type: None + name: MTEB DBPedia + config: default + split: test + revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659 + metrics: + - type: map_at_1 + value: 8.333 + - type: map_at_10 + value: 19.355 + - type: map_at_100 + value: 27.261000000000003 + - type: map_at_1000 + value: 28.792 + - type: map_at_20 + value: 22.412000000000003 + - type: map_at_3 + value: 13.425999999999998 + - type: map_at_5 + value: 16.075 + - type: mrr_at_1 + value: 61.5 + - type: mrr_at_10 + value: 71.673 + - type: mrr_at_100 + value: 71.95 + - type: mrr_at_1000 + value: 71.956 + - type: mrr_at_20 + value: 71.832 + - type: mrr_at_3 + value: 69.583 + - type: mrr_at_5 + value: 71.083 + - type: ndcg_at_1 + value: 50.125 + - type: ndcg_at_10 + value: 40.128 + - type: ndcg_at_100 + value: 44.661 + - type: ndcg_at_1000 + value: 51.873999999999995 + - type: ndcg_at_20 + value: 39.53 + - type: ndcg_at_3 + value: 43.117 + - type: ndcg_at_5 + value: 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value: 56.405001024800164 + - type: cos_sim_recall + value: 72.61213720316623 + - type: dot_accuracy + value: 81.4805984383382 + - type: dot_ap + value: 59.99163409844457 + - type: dot_f1 + value: 58.40137516115169 + - type: dot_precision + value: 49.256977165639725 + - type: dot_recall + value: 71.71503957783642 + - type: euclidean_accuracy + value: 84.2284079394409 + - type: euclidean_ap + value: 68.28553930921828 + - type: euclidean_f1 + value: 64.2380085003036 + - type: euclidean_precision + value: 59.5050618672666 + - type: euclidean_recall + value: 69.78891820580475 + - type: manhattan_accuracy + value: 84.20456577457233 + - type: manhattan_ap + value: 68.27166753842906 + - type: manhattan_f1 + value: 64.20813939610932 + - type: manhattan_precision + value: 58.61843538897363 + - type: manhattan_recall + value: 70.97625329815304 + - type: max_accuracy + value: 84.2284079394409 + - type: max_ap + value: 68.3722067037148 + - type: max_f1 + value: 64.2380085003036 + - task: + type: PairClassification + dataset: + type: None + name: MTEB TwitterURLCorpus + config: default + split: test + revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf + metrics: + - type: cos_sim_accuracy + value: 89.0441262079404 + - type: cos_sim_ap + value: 86.07872513441609 + - type: cos_sim_f1 + value: 78.49620737904117 + - type: cos_sim_precision + value: 75.22230063514466 + - type: cos_sim_recall + value: 82.06806282722513 + - type: dot_accuracy + value: 88.44646252959211 + - type: dot_ap + value: 84.64714868476264 + - type: dot_f1 + value: 77.21275126313111 + - type: dot_precision + value: 73.13227294636094 + - type: dot_recall + value: 81.7754850631352 + - type: euclidean_accuracy + value: 88.59781891566733 + - type: euclidean_ap + value: 85.2557919112934 + - type: euclidean_f1 + value: 77.82533933340649 + - type: euclidean_precision + value: 74.14430115022655 + - type: euclidean_recall + value: 81.89097628580228 + - type: manhattan_accuracy + value: 88.60364031513176 + - type: manhattan_ap + value: 85.22656880722035 + - type: manhattan_f1 + value: 77.79835166830047 + - type: manhattan_precision + value: 73.61044314668499 + - type: manhattan_recall + value: 82.49153064367108 + - type: max_accuracy + value: 89.0441262079404 + - type: max_ap + value: 86.07872513441609 + - type: max_f1 + value: 78.49620737904117 +license: apache-2.0 +language: +- en +base_model: +- answerdotai/ModernBERT-large --- -# Model Card for Model ID - - - - - -## Model Details - -### Model Description - - - -This is the model card of a 🤗 transformers model that has been pushed on the Hub. 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(2019)](https://arxiv.org/abs/1910.09700). - -- **Hardware Type:** [More Information Needed] -- **Hours used:** [More Information Needed] -- **Cloud Provider:** [More Information Needed] -- **Compute Region:** [More Information Needed] -- **Carbon Emitted:** [More Information Needed] - -## Technical Specifications [optional] - -### Model Architecture and Objective - -[More Information Needed] - -### Compute Infrastructure - -[More Information Needed] - -#### Hardware - -[More Information Needed] - -#### Software - -[More Information Needed] - -## Citation [optional] - - - -**BibTeX:** - -[More Information Needed] - -**APA:** - -[More Information Needed] - -## Glossary [optional] - - - -[More Information Needed] - -## More Information [optional] - -[More Information Needed] - -## Model Card Authors [optional] - -[More Information Needed] - -## Model Card Contact - -[More Information Needed] \ No newline at end of file +# ModernBERT-embed-large-unsupervised + +`modernbert-embed-unsupervised-large` is the unsupervised checkpoint trained with the [contrastors](https://github.com/nomic-ai/contrastors) library +for 1 epoch over the 235M weakly-supervised contrastive pairs curated in [Nomic Embed](https://arxiv.org/abs/2402.01613). + +We suggest using [moderbert-embed-large](https://huggingface.co/lightonai/modernbert-embed-large) for embedding tasks. + +## Performance + + +| Model | Average (56) | Classification (12) | Clustering (11) | Pair Classification (3) | Reranking (4) | Retrieval (15) | STS (10) | Overall | +|-------|--------------|--------------------:|-----------------|------------------------|---------------|----------------|-----------|----------| +| nomic-embed-text-v1_unsup | 59.9 | 71.2 | 42.5 | 83.7 | 55.0 | 48.0 | 80.8 | 30.7 | +| modernbert-embed-base-unsupervised | 60.03 | 72.11 | 44.34 | 82.78 | 55.0 | 47.05 | 80.33 | 31.2 | +| modernbert-embed-large-unsupervised | 60.71 | 72.90 | 44.96 | 83.44 | 55.54 | 47.90 | 80.95 | 29.86 | + + +## Acknowledgment +We wanted to thank [Zach Nussbaum](https://huggingface.co/zpn) from [Nomic AI](https://huggingface.co/nomic-ai) for building and sharing the Nomic Embed recipe and tools and its support during the training of this model! + +The training has been run on Orange Business Cloud Avenue infrastructure. + +## Citation + +If you find the model, dataset, or training code useful, please considering citing ModernBERT as well as Nomic Embed: +```bibtex +@misc{modernbert, + title={Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference}, + author={Benjamin Warner and Antoine Chaffin and Benjamin Clavié and Orion Weller and Oskar Hallström and Said Taghadouini and Alexis Gallagher and Raja Biswas and Faisal Ladhak and Tom Aarsen and Nathan Cooper and Griffin Adams and Jeremy Howard and Iacopo Poli}, + year={2024}, + eprint={2412.13663}, + archivePrefix={arXiv}, + primaryClass={cs.CL}, + url={https://arxiv.org/abs/2412.13663}, +} +``` + +```bibtex +@misc{nussbaum2024nomic, + title={Nomic Embed: Training a Reproducible Long Context Text Embedder}, + author={Zach Nussbaum and John X. Morris and Brandon Duderstadt and Andriy Mulyar}, + year={2024}, + eprint={2402.01613}, + archivePrefix={arXiv}, + primaryClass={cs.CL} +} +``` + +And if you want to cite this fine-tuning in particular, please use: +```bibtex +@misc{ModernBERT-embed-large, + title={ModernBERT-embed-large}, + author={Chaffin, Antoine}, + url={https://huggingface.co/lightonai/modernbert-embed-large}, + year={2025} +} +``` \ No newline at end of file