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| tags: | |
| - mteb | |
| - sentence-similarity | |
| - sentence-transformers | |
| - Sentence Transformers | |
| model-index: | |
| - name: gte-base | |
| results: | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/amazon_counterfactual | |
| name: MTEB AmazonCounterfactualClassification (en) | |
| config: en | |
| split: test | |
| revision: e8379541af4e31359cca9fbcf4b00f2671dba205 | |
| metrics: | |
| - type: accuracy | |
| value: 74.17910447761193 | |
| - type: ap | |
| value: 36.827146398068926 | |
| - type: f1 | |
| value: 68.11292888046363 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/amazon_polarity | |
| name: MTEB AmazonPolarityClassification | |
| config: default | |
| split: test | |
| revision: e2d317d38cd51312af73b3d32a06d1a08b442046 | |
| metrics: | |
| - type: accuracy | |
| value: 91.77345000000001 | |
| - type: ap | |
| value: 88.33530426691347 | |
| - type: f1 | |
| value: 91.76549906404642 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/amazon_reviews_multi | |
| name: MTEB AmazonReviewsClassification (en) | |
| config: en | |
| split: test | |
| revision: 1399c76144fd37290681b995c656ef9b2e06e26d | |
| metrics: | |
| - type: accuracy | |
| value: 48.964 | |
| - type: f1 | |
| value: 48.22995586184998 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: arguana | |
| name: MTEB ArguAna | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 32.147999999999996 | |
| - type: map_at_10 | |
| value: 48.253 | |
| - type: map_at_100 | |
| value: 49.038 | |
| - type: map_at_1000 | |
| value: 49.042 | |
| - type: map_at_3 | |
| value: 43.433 | |
| - type: map_at_5 | |
| value: 46.182 | |
| - type: mrr_at_1 | |
| value: 32.717 | |
| - type: mrr_at_10 | |
| value: 48.467 | |
| - type: mrr_at_100 | |
| value: 49.252 | |
| - type: mrr_at_1000 | |
| value: 49.254999999999995 | |
| - type: mrr_at_3 | |
| value: 43.599 | |
| - type: mrr_at_5 | |
| value: 46.408 | |
| - type: ndcg_at_1 | |
| value: 32.147999999999996 | |
| - type: ndcg_at_10 | |
| value: 57.12199999999999 | |
| - type: ndcg_at_100 | |
| value: 60.316 | |
| - type: ndcg_at_1000 | |
| value: 60.402 | |
| - type: ndcg_at_3 | |
| value: 47.178 | |
| - type: ndcg_at_5 | |
| value: 52.146 | |
| - type: precision_at_1 | |
| value: 32.147999999999996 | |
| - type: precision_at_10 | |
| value: 8.542 | |
| - type: precision_at_100 | |
| value: 0.9900000000000001 | |
| - type: precision_at_1000 | |
| value: 0.1 | |
| - type: precision_at_3 | |
| value: 19.346 | |
| - type: precision_at_5 | |
| value: 14.026 | |
| - type: recall_at_1 | |
| value: 32.147999999999996 | |
| - type: recall_at_10 | |
| value: 85.42 | |
| - type: recall_at_100 | |
| value: 99.004 | |
| - type: recall_at_1000 | |
| value: 99.644 | |
| - type: recall_at_3 | |
| value: 58.037000000000006 | |
| - type: recall_at_5 | |
| value: 70.128 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/arxiv-clustering-p2p | |
| name: MTEB ArxivClusteringP2P | |
| config: default | |
| split: test | |
| revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d | |
| metrics: | |
| - type: v_measure | |
| value: 48.59706013699614 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/arxiv-clustering-s2s | |
| name: MTEB ArxivClusteringS2S | |
| config: default | |
| split: test | |
| revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 | |
| metrics: | |
| - type: v_measure | |
| value: 43.01463593002057 | |
| - task: | |
| type: Reranking | |
| dataset: | |
| type: mteb/askubuntudupquestions-reranking | |
| name: MTEB AskUbuntuDupQuestions | |
| config: default | |
| split: test | |
| revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 | |
| metrics: | |
| - type: map | |
| value: 61.80250355752458 | |
| - type: mrr | |
| value: 74.79455216989844 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/biosses-sts | |
| name: MTEB BIOSSES | |
| config: default | |
| split: test | |
| revision: d3fb88f8f02e40887cd149695127462bbcf29b4a | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 89.87448576082345 | |
| - type: cos_sim_spearman | |
| value: 87.64235843637468 | |
| - type: euclidean_pearson | |
| value: 88.4901825511062 | |
| - type: euclidean_spearman | |
| value: 87.74537283182033 | |
| - type: manhattan_pearson | |
| value: 88.39040638362911 | |
| - type: manhattan_spearman | |
| value: 87.62669542888003 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/banking77 | |
| name: MTEB Banking77Classification | |
| config: default | |
| split: test | |
| revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 | |
| metrics: | |
| - type: accuracy | |
| value: 85.06818181818183 | |
| - type: f1 | |
| value: 85.02524460098233 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/biorxiv-clustering-p2p | |
| name: MTEB BiorxivClusteringP2P | |
| config: default | |
| split: test | |
| revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 | |
| metrics: | |
| - type: v_measure | |
| value: 38.20471092679967 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/biorxiv-clustering-s2s | |
| name: MTEB BiorxivClusteringS2S | |
| config: default | |
| split: test | |
| revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 | |
| metrics: | |
| - type: v_measure | |
| value: 36.58967592147641 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackAndroidRetrieval | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 32.411 | |
| - type: map_at_10 | |
| value: 45.162 | |
| - type: map_at_100 | |
| value: 46.717 | |
| - type: map_at_1000 | |
| value: 46.836 | |
| - type: map_at_3 | |
| value: 41.428 | |
| - type: map_at_5 | |
| value: 43.54 | |
| - type: mrr_at_1 | |
| value: 39.914 | |
| - type: mrr_at_10 | |
| value: 51.534 | |
| - type: mrr_at_100 | |
| value: 52.185 | |
| - type: mrr_at_1000 | |
| value: 52.22 | |
| - type: mrr_at_3 | |
| value: 49.046 | |
| - type: mrr_at_5 | |
| value: 50.548 | |
| - type: ndcg_at_1 | |
| value: 39.914 | |
| - type: ndcg_at_10 | |
| value: 52.235 | |
| - type: ndcg_at_100 | |
| value: 57.4 | |
| - type: ndcg_at_1000 | |
| value: 58.982 | |
| - type: ndcg_at_3 | |
| value: 47.332 | |
| - type: ndcg_at_5 | |
| value: 49.62 | |
| - type: precision_at_1 | |
| value: 39.914 | |
| - type: precision_at_10 | |
| value: 10.258000000000001 | |
| - type: precision_at_100 | |
| value: 1.6219999999999999 | |
| - type: precision_at_1000 | |
| value: 0.20500000000000002 | |
| - type: precision_at_3 | |
| value: 23.462 | |
| - type: precision_at_5 | |
| value: 16.71 | |
| - type: recall_at_1 | |
| value: 32.411 | |
| - type: recall_at_10 | |
| value: 65.408 | |
| - type: recall_at_100 | |
| value: 87.248 | |
| - type: recall_at_1000 | |
| value: 96.951 | |
| - type: recall_at_3 | |
| value: 50.349999999999994 | |
| - type: recall_at_5 | |
| value: 57.431 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackEnglishRetrieval | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 31.911 | |
| - type: map_at_10 | |
| value: 42.608000000000004 | |
| - type: map_at_100 | |
| value: 43.948 | |
| - type: map_at_1000 | |
| value: 44.089 | |
| - type: map_at_3 | |
| value: 39.652 | |
| - type: map_at_5 | |
| value: 41.236 | |
| - type: mrr_at_1 | |
| value: 40.064 | |
| - type: mrr_at_10 | |
| value: 48.916 | |
| - type: mrr_at_100 | |
| value: 49.539 | |
| - type: mrr_at_1000 | |
| value: 49.583 | |
| - type: mrr_at_3 | |
| value: 46.741 | |
| - type: mrr_at_5 | |
| value: 48.037 | |
| - type: ndcg_at_1 | |
| value: 40.064 | |
| - type: ndcg_at_10 | |
| value: 48.442 | |
| - type: ndcg_at_100 | |
| value: 52.798 | |
| - type: ndcg_at_1000 | |
| value: 54.871 | |
| - type: ndcg_at_3 | |
| value: 44.528 | |
| - type: ndcg_at_5 | |
| value: 46.211 | |
| - type: precision_at_1 | |
| value: 40.064 | |
| - type: precision_at_10 | |
| value: 9.178 | |
| - type: precision_at_100 | |
| value: 1.452 | |
| - type: precision_at_1000 | |
| value: 0.193 | |
| - type: precision_at_3 | |
| value: 21.614 | |
| - type: precision_at_5 | |
| value: 15.185 | |
| - type: recall_at_1 | |
| value: 31.911 | |
| - type: recall_at_10 | |
| value: 58.155 | |
| - type: recall_at_100 | |
| value: 76.46300000000001 | |
| - type: recall_at_1000 | |
| value: 89.622 | |
| - type: recall_at_3 | |
| value: 46.195 | |
| - type: recall_at_5 | |
| value: 51.288999999999994 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackGamingRetrieval | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 40.597 | |
| - type: map_at_10 | |
| value: 54.290000000000006 | |
| - type: map_at_100 | |
| value: 55.340999999999994 | |
| - type: map_at_1000 | |
| value: 55.388999999999996 | |
| - type: map_at_3 | |
| value: 50.931000000000004 | |
| - type: map_at_5 | |
| value: 52.839999999999996 | |
| - type: mrr_at_1 | |
| value: 46.646 | |
| - type: mrr_at_10 | |
| value: 57.524 | |
| - type: mrr_at_100 | |
| value: 58.225 | |
| - type: mrr_at_1000 | |
| value: 58.245999999999995 | |
| - type: mrr_at_3 | |
| value: 55.235 | |
| - type: mrr_at_5 | |
| value: 56.589 | |
| - type: ndcg_at_1 | |
| value: 46.646 | |
| - type: ndcg_at_10 | |
| value: 60.324999999999996 | |
| - type: ndcg_at_100 | |
| value: 64.30900000000001 | |
| - type: ndcg_at_1000 | |
| value: 65.19 | |
| - type: ndcg_at_3 | |
| value: 54.983000000000004 | |
| - type: ndcg_at_5 | |
| value: 57.621 | |
| - type: precision_at_1 | |
| value: 46.646 | |
| - type: precision_at_10 | |
| value: 9.774 | |
| - type: precision_at_100 | |
| value: 1.265 | |
| - type: precision_at_1000 | |
| value: 0.13799999999999998 | |
| - type: precision_at_3 | |
| value: 24.911 | |
| - type: precision_at_5 | |
| value: 16.977999999999998 | |
| - type: recall_at_1 | |
| value: 40.597 | |
| - type: recall_at_10 | |
| value: 74.773 | |
| - type: recall_at_100 | |
| value: 91.61200000000001 | |
| - type: recall_at_1000 | |
| value: 97.726 | |
| - type: recall_at_3 | |
| value: 60.458 | |
| - type: recall_at_5 | |
| value: 66.956 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackGisRetrieval | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 27.122 | |
| - type: map_at_10 | |
| value: 36.711 | |
| - type: map_at_100 | |
| value: 37.775 | |
| - type: map_at_1000 | |
| value: 37.842999999999996 | |
| - type: map_at_3 | |
| value: 33.693 | |
| - type: map_at_5 | |
| value: 35.607 | |
| - type: mrr_at_1 | |
| value: 29.153000000000002 | |
| - type: mrr_at_10 | |
| value: 38.873999999999995 | |
| - type: mrr_at_100 | |
| value: 39.739000000000004 | |
| - type: mrr_at_1000 | |
| value: 39.794000000000004 | |
| - type: mrr_at_3 | |
| value: 36.102000000000004 | |
| - type: mrr_at_5 | |
| value: 37.876 | |
| - type: ndcg_at_1 | |
| value: 29.153000000000002 | |
| - type: ndcg_at_10 | |
| value: 42.048 | |
| - type: ndcg_at_100 | |
| value: 47.144999999999996 | |
| - type: ndcg_at_1000 | |
| value: 48.901 | |
| - type: ndcg_at_3 | |
| value: 36.402 | |
| - type: ndcg_at_5 | |
| value: 39.562999999999995 | |
| - type: precision_at_1 | |
| value: 29.153000000000002 | |
| - type: precision_at_10 | |
| value: 6.4750000000000005 | |
| - type: precision_at_100 | |
| value: 0.951 | |
| - type: precision_at_1000 | |
| value: 0.11299999999999999 | |
| - type: precision_at_3 | |
| value: 15.479999999999999 | |
| - type: precision_at_5 | |
| value: 11.028 | |
| - type: recall_at_1 | |
| value: 27.122 | |
| - type: recall_at_10 | |
| value: 56.279999999999994 | |
| - type: recall_at_100 | |
| value: 79.597 | |
| - type: recall_at_1000 | |
| value: 92.804 | |
| - type: recall_at_3 | |
| value: 41.437000000000005 | |
| - type: recall_at_5 | |
| value: 49.019 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackMathematicaRetrieval | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 17.757 | |
| - type: map_at_10 | |
| value: 26.739 | |
| - type: map_at_100 | |
| value: 28.015 | |
| - type: map_at_1000 | |
| value: 28.127999999999997 | |
| - type: map_at_3 | |
| value: 23.986 | |
| - type: map_at_5 | |
| value: 25.514 | |
| - type: mrr_at_1 | |
| value: 22.015 | |
| - type: mrr_at_10 | |
| value: 31.325999999999997 | |
| - type: mrr_at_100 | |
| value: 32.368 | |
| - type: mrr_at_1000 | |
| value: 32.426 | |
| - type: mrr_at_3 | |
| value: 28.897000000000002 | |
| - type: mrr_at_5 | |
| value: 30.147000000000002 | |
| - type: ndcg_at_1 | |
| value: 22.015 | |
| - type: ndcg_at_10 | |
| value: 32.225 | |
| - type: ndcg_at_100 | |
| value: 38.405 | |
| - type: ndcg_at_1000 | |
| value: 40.932 | |
| - type: ndcg_at_3 | |
| value: 27.403 | |
| - type: ndcg_at_5 | |
| value: 29.587000000000003 | |
| - type: precision_at_1 | |
| value: 22.015 | |
| - type: precision_at_10 | |
| value: 5.9830000000000005 | |
| - type: precision_at_100 | |
| value: 1.051 | |
| - type: precision_at_1000 | |
| value: 0.13899999999999998 | |
| - type: precision_at_3 | |
| value: 13.391 | |
| - type: precision_at_5 | |
| value: 9.602 | |
| - type: recall_at_1 | |
| value: 17.757 | |
| - type: recall_at_10 | |
| value: 44.467 | |
| - type: recall_at_100 | |
| value: 71.53699999999999 | |
| - type: recall_at_1000 | |
| value: 89.281 | |
| - type: recall_at_3 | |
| value: 31.095 | |
| - type: recall_at_5 | |
| value: 36.818 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackPhysicsRetrieval | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 30.354 | |
| - type: map_at_10 | |
| value: 42.134 | |
| - type: map_at_100 | |
| value: 43.429 | |
| - type: map_at_1000 | |
| value: 43.532 | |
| - type: map_at_3 | |
| value: 38.491 | |
| - type: map_at_5 | |
| value: 40.736 | |
| - type: mrr_at_1 | |
| value: 37.247 | |
| - type: mrr_at_10 | |
| value: 47.775 | |
| - type: mrr_at_100 | |
| value: 48.522999999999996 | |
| - type: mrr_at_1000 | |
| value: 48.567 | |
| - type: mrr_at_3 | |
| value: 45.059 | |
| - type: mrr_at_5 | |
| value: 46.811 | |
| - type: ndcg_at_1 | |
| value: 37.247 | |
| - type: ndcg_at_10 | |
| value: 48.609 | |
| - type: ndcg_at_100 | |
| value: 53.782 | |
| - type: ndcg_at_1000 | |
| value: 55.666000000000004 | |
| - type: ndcg_at_3 | |
| value: 42.866 | |
| - type: ndcg_at_5 | |
| value: 46.001 | |
| - type: precision_at_1 | |
| value: 37.247 | |
| - type: precision_at_10 | |
| value: 8.892999999999999 | |
| - type: precision_at_100 | |
| value: 1.341 | |
| - type: precision_at_1000 | |
| value: 0.168 | |
| - type: precision_at_3 | |
| value: 20.5 | |
| - type: precision_at_5 | |
| value: 14.976 | |
| - type: recall_at_1 | |
| value: 30.354 | |
| - type: recall_at_10 | |
| value: 62.273 | |
| - type: recall_at_100 | |
| value: 83.65599999999999 | |
| - type: recall_at_1000 | |
| value: 95.82000000000001 | |
| - type: recall_at_3 | |
| value: 46.464 | |
| - type: recall_at_5 | |
| value: 54.225 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackProgrammersRetrieval | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 26.949 | |
| - type: map_at_10 | |
| value: 37.230000000000004 | |
| - type: map_at_100 | |
| value: 38.644 | |
| - type: map_at_1000 | |
| value: 38.751999999999995 | |
| - type: map_at_3 | |
| value: 33.816 | |
| - type: map_at_5 | |
| value: 35.817 | |
| - type: mrr_at_1 | |
| value: 33.446999999999996 | |
| - type: mrr_at_10 | |
| value: 42.970000000000006 | |
| - type: mrr_at_100 | |
| value: 43.873 | |
| - type: mrr_at_1000 | |
| value: 43.922 | |
| - type: mrr_at_3 | |
| value: 40.467999999999996 | |
| - type: mrr_at_5 | |
| value: 41.861 | |
| - type: ndcg_at_1 | |
| value: 33.446999999999996 | |
| - type: ndcg_at_10 | |
| value: 43.403000000000006 | |
| - type: ndcg_at_100 | |
| value: 49.247 | |
| - type: ndcg_at_1000 | |
| value: 51.361999999999995 | |
| - type: ndcg_at_3 | |
| value: 38.155 | |
| - type: ndcg_at_5 | |
| value: 40.643 | |
| - type: precision_at_1 | |
| value: 33.446999999999996 | |
| - type: precision_at_10 | |
| value: 8.128 | |
| - type: precision_at_100 | |
| value: 1.274 | |
| - type: precision_at_1000 | |
| value: 0.163 | |
| - type: precision_at_3 | |
| value: 18.493000000000002 | |
| - type: precision_at_5 | |
| value: 13.333 | |
| - type: recall_at_1 | |
| value: 26.949 | |
| - type: recall_at_10 | |
| value: 56.006 | |
| - type: recall_at_100 | |
| value: 80.99199999999999 | |
| - type: recall_at_1000 | |
| value: 95.074 | |
| - type: recall_at_3 | |
| value: 40.809 | |
| - type: recall_at_5 | |
| value: 47.57 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackRetrieval | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 27.243583333333333 | |
| - type: map_at_10 | |
| value: 37.193250000000006 | |
| - type: map_at_100 | |
| value: 38.44833333333334 | |
| - type: map_at_1000 | |
| value: 38.56083333333333 | |
| - type: map_at_3 | |
| value: 34.06633333333333 | |
| - type: map_at_5 | |
| value: 35.87858333333334 | |
| - type: mrr_at_1 | |
| value: 32.291583333333335 | |
| - type: mrr_at_10 | |
| value: 41.482749999999996 | |
| - type: mrr_at_100 | |
| value: 42.33583333333333 | |
| - type: mrr_at_1000 | |
| value: 42.38683333333333 | |
| - type: mrr_at_3 | |
| value: 38.952999999999996 | |
| - type: mrr_at_5 | |
| value: 40.45333333333333 | |
| - type: ndcg_at_1 | |
| value: 32.291583333333335 | |
| - type: ndcg_at_10 | |
| value: 42.90533333333334 | |
| - type: ndcg_at_100 | |
| value: 48.138666666666666 | |
| - type: ndcg_at_1000 | |
| value: 50.229083333333335 | |
| - type: ndcg_at_3 | |
| value: 37.76133333333334 | |
| - type: ndcg_at_5 | |
| value: 40.31033333333334 | |
| - type: precision_at_1 | |
| value: 32.291583333333335 | |
| - type: precision_at_10 | |
| value: 7.585583333333333 | |
| - type: precision_at_100 | |
| value: 1.2045000000000001 | |
| - type: precision_at_1000 | |
| value: 0.15733333333333335 | |
| - type: precision_at_3 | |
| value: 17.485416666666666 | |
| - type: precision_at_5 | |
| value: 12.5145 | |
| - type: recall_at_1 | |
| value: 27.243583333333333 | |
| - type: recall_at_10 | |
| value: 55.45108333333334 | |
| - type: recall_at_100 | |
| value: 78.25858333333335 | |
| - type: recall_at_1000 | |
| value: 92.61716666666665 | |
| - type: recall_at_3 | |
| value: 41.130583333333334 | |
| - type: recall_at_5 | |
| value: 47.73133333333334 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackStatsRetrieval | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 26.325 | |
| - type: map_at_10 | |
| value: 32.795 | |
| - type: map_at_100 | |
| value: 33.96 | |
| - type: map_at_1000 | |
| value: 34.054 | |
| - type: map_at_3 | |
| value: 30.64 | |
| - type: map_at_5 | |
| value: 31.771 | |
| - type: mrr_at_1 | |
| value: 29.908 | |
| - type: mrr_at_10 | |
| value: 35.83 | |
| - type: mrr_at_100 | |
| value: 36.868 | |
| - type: mrr_at_1000 | |
| value: 36.928 | |
| - type: mrr_at_3 | |
| value: 33.896 | |
| - type: mrr_at_5 | |
| value: 34.893 | |
| - type: ndcg_at_1 | |
| value: 29.908 | |
| - type: ndcg_at_10 | |
| value: 36.746 | |
| - type: ndcg_at_100 | |
| value: 42.225 | |
| - type: ndcg_at_1000 | |
| value: 44.523 | |
| - type: ndcg_at_3 | |
| value: 32.82 | |
| - type: ndcg_at_5 | |
| value: 34.583000000000006 | |
| - type: precision_at_1 | |
| value: 29.908 | |
| - type: precision_at_10 | |
| value: 5.6129999999999995 | |
| - type: precision_at_100 | |
| value: 0.9079999999999999 | |
| - type: precision_at_1000 | |
| value: 0.11800000000000001 | |
| - type: precision_at_3 | |
| value: 13.753000000000002 | |
| - type: precision_at_5 | |
| value: 9.417 | |
| - type: recall_at_1 | |
| value: 26.325 | |
| - type: recall_at_10 | |
| value: 45.975 | |
| - type: recall_at_100 | |
| value: 70.393 | |
| - type: recall_at_1000 | |
| value: 87.217 | |
| - type: recall_at_3 | |
| value: 35.195 | |
| - type: recall_at_5 | |
| value: 39.69 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackTexRetrieval | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 17.828 | |
| - type: map_at_10 | |
| value: 25.759 | |
| - type: map_at_100 | |
| value: 26.961000000000002 | |
| - type: map_at_1000 | |
| value: 27.094 | |
| - type: map_at_3 | |
| value: 23.166999999999998 | |
| - type: map_at_5 | |
| value: 24.610000000000003 | |
| - type: mrr_at_1 | |
| value: 21.61 | |
| - type: mrr_at_10 | |
| value: 29.605999999999998 | |
| - type: mrr_at_100 | |
| value: 30.586000000000002 | |
| - type: mrr_at_1000 | |
| value: 30.664 | |
| - type: mrr_at_3 | |
| value: 27.214 | |
| - type: mrr_at_5 | |
| value: 28.571 | |
| - type: ndcg_at_1 | |
| value: 21.61 | |
| - type: ndcg_at_10 | |
| value: 30.740000000000002 | |
| - type: ndcg_at_100 | |
| value: 36.332 | |
| - type: ndcg_at_1000 | |
| value: 39.296 | |
| - type: ndcg_at_3 | |
| value: 26.11 | |
| - type: ndcg_at_5 | |
| value: 28.297 | |
| - type: precision_at_1 | |
| value: 21.61 | |
| - type: precision_at_10 | |
| value: 5.643 | |
| - type: precision_at_100 | |
| value: 1.0 | |
| - type: precision_at_1000 | |
| value: 0.14400000000000002 | |
| - type: precision_at_3 | |
| value: 12.4 | |
| - type: precision_at_5 | |
| value: 9.119 | |
| - type: recall_at_1 | |
| value: 17.828 | |
| - type: recall_at_10 | |
| value: 41.876000000000005 | |
| - type: recall_at_100 | |
| value: 66.648 | |
| - type: recall_at_1000 | |
| value: 87.763 | |
| - type: recall_at_3 | |
| value: 28.957 | |
| - type: recall_at_5 | |
| value: 34.494 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackUnixRetrieval | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 27.921000000000003 | |
| - type: map_at_10 | |
| value: 37.156 | |
| - type: map_at_100 | |
| value: 38.399 | |
| - type: map_at_1000 | |
| value: 38.498 | |
| - type: map_at_3 | |
| value: 34.134 | |
| - type: map_at_5 | |
| value: 35.936 | |
| - type: mrr_at_1 | |
| value: 32.649 | |
| - type: mrr_at_10 | |
| value: 41.19 | |
| - type: mrr_at_100 | |
| value: 42.102000000000004 | |
| - type: mrr_at_1000 | |
| value: 42.157 | |
| - type: mrr_at_3 | |
| value: 38.464 | |
| - type: mrr_at_5 | |
| value: 40.148 | |
| - type: ndcg_at_1 | |
| value: 32.649 | |
| - type: ndcg_at_10 | |
| value: 42.679 | |
| - type: ndcg_at_100 | |
| value: 48.27 | |
| - type: ndcg_at_1000 | |
| value: 50.312 | |
| - type: ndcg_at_3 | |
| value: 37.269000000000005 | |
| - type: ndcg_at_5 | |
| value: 40.055 | |
| - type: precision_at_1 | |
| value: 32.649 | |
| - type: precision_at_10 | |
| value: 7.155 | |
| - type: precision_at_100 | |
| value: 1.124 | |
| - type: precision_at_1000 | |
| value: 0.14100000000000001 | |
| - type: precision_at_3 | |
| value: 16.791 | |
| - type: precision_at_5 | |
| value: 12.015 | |
| - type: recall_at_1 | |
| value: 27.921000000000003 | |
| - type: recall_at_10 | |
| value: 55.357 | |
| - type: recall_at_100 | |
| value: 79.476 | |
| - type: recall_at_1000 | |
| value: 93.314 | |
| - type: recall_at_3 | |
| value: 40.891 | |
| - type: recall_at_5 | |
| value: 47.851 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackWebmastersRetrieval | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 25.524 | |
| - type: map_at_10 | |
| value: 35.135 | |
| - type: map_at_100 | |
| value: 36.665 | |
| - type: map_at_1000 | |
| value: 36.886 | |
| - type: map_at_3 | |
| value: 31.367 | |
| - type: map_at_5 | |
| value: 33.724 | |
| - type: mrr_at_1 | |
| value: 30.631999999999998 | |
| - type: mrr_at_10 | |
| value: 39.616 | |
| - type: mrr_at_100 | |
| value: 40.54 | |
| - type: mrr_at_1000 | |
| value: 40.585 | |
| - type: mrr_at_3 | |
| value: 36.462 | |
| - type: mrr_at_5 | |
| value: 38.507999999999996 | |
| - type: ndcg_at_1 | |
| value: 30.631999999999998 | |
| - type: ndcg_at_10 | |
| value: 41.61 | |
| - type: ndcg_at_100 | |
| value: 47.249 | |
| - type: ndcg_at_1000 | |
| value: 49.662 | |
| - type: ndcg_at_3 | |
| value: 35.421 | |
| - type: ndcg_at_5 | |
| value: 38.811 | |
| - type: precision_at_1 | |
| value: 30.631999999999998 | |
| - type: precision_at_10 | |
| value: 8.123 | |
| - type: precision_at_100 | |
| value: 1.5810000000000002 | |
| - type: precision_at_1000 | |
| value: 0.245 | |
| - type: precision_at_3 | |
| value: 16.337 | |
| - type: precision_at_5 | |
| value: 12.568999999999999 | |
| - type: recall_at_1 | |
| value: 25.524 | |
| - type: recall_at_10 | |
| value: 54.994 | |
| - type: recall_at_100 | |
| value: 80.03099999999999 | |
| - type: recall_at_1000 | |
| value: 95.25099999999999 | |
| - type: recall_at_3 | |
| value: 37.563 | |
| - type: recall_at_5 | |
| value: 46.428999999999995 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackWordpressRetrieval | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 22.224 | |
| - type: map_at_10 | |
| value: 30.599999999999998 | |
| - type: map_at_100 | |
| value: 31.526 | |
| - type: map_at_1000 | |
| value: 31.629 | |
| - type: map_at_3 | |
| value: 27.491 | |
| - type: map_at_5 | |
| value: 29.212 | |
| - type: mrr_at_1 | |
| value: 24.214 | |
| - type: mrr_at_10 | |
| value: 32.632 | |
| - type: mrr_at_100 | |
| value: 33.482 | |
| - type: mrr_at_1000 | |
| value: 33.550000000000004 | |
| - type: mrr_at_3 | |
| value: 29.852 | |
| - type: mrr_at_5 | |
| value: 31.451 | |
| - type: ndcg_at_1 | |
| value: 24.214 | |
| - type: ndcg_at_10 | |
| value: 35.802 | |
| - type: ndcg_at_100 | |
| value: 40.502 | |
| - type: ndcg_at_1000 | |
| value: 43.052 | |
| - type: ndcg_at_3 | |
| value: 29.847 | |
| - type: ndcg_at_5 | |
| value: 32.732 | |
| - type: precision_at_1 | |
| value: 24.214 | |
| - type: precision_at_10 | |
| value: 5.804 | |
| - type: precision_at_100 | |
| value: 0.885 | |
| - type: precision_at_1000 | |
| value: 0.121 | |
| - type: precision_at_3 | |
| value: 12.692999999999998 | |
| - type: precision_at_5 | |
| value: 9.242 | |
| - type: recall_at_1 | |
| value: 22.224 | |
| - type: recall_at_10 | |
| value: 49.849 | |
| - type: recall_at_100 | |
| value: 71.45 | |
| - type: recall_at_1000 | |
| value: 90.583 | |
| - type: recall_at_3 | |
| value: 34.153 | |
| - type: recall_at_5 | |
| value: 41.004000000000005 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: climate-fever | |
| name: MTEB ClimateFEVER | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 12.386999999999999 | |
| - type: map_at_10 | |
| value: 20.182 | |
| - type: map_at_100 | |
| value: 21.86 | |
| - type: map_at_1000 | |
| value: 22.054000000000002 | |
| - type: map_at_3 | |
| value: 17.165 | |
| - type: map_at_5 | |
| value: 18.643 | |
| - type: mrr_at_1 | |
| value: 26.906000000000002 | |
| - type: mrr_at_10 | |
| value: 37.907999999999994 | |
| - type: mrr_at_100 | |
| value: 38.868 | |
| - type: mrr_at_1000 | |
| value: 38.913 | |
| - type: mrr_at_3 | |
| value: 34.853 | |
| - type: mrr_at_5 | |
| value: 36.567 | |
| - type: ndcg_at_1 | |
| value: 26.906000000000002 | |
| - type: ndcg_at_10 | |
| value: 28.103 | |
| - type: ndcg_at_100 | |
| value: 35.073 | |
| - type: ndcg_at_1000 | |
| value: 38.653 | |
| - type: ndcg_at_3 | |
| value: 23.345 | |
| - type: ndcg_at_5 | |
| value: 24.828 | |
| - type: precision_at_1 | |
| value: 26.906000000000002 | |
| - type: precision_at_10 | |
| value: 8.547 | |
| - type: precision_at_100 | |
| value: 1.617 | |
| - type: precision_at_1000 | |
| value: 0.22799999999999998 | |
| - type: precision_at_3 | |
| value: 17.025000000000002 | |
| - type: precision_at_5 | |
| value: 12.834000000000001 | |
| - type: recall_at_1 | |
| value: 12.386999999999999 | |
| - type: recall_at_10 | |
| value: 33.306999999999995 | |
| - type: recall_at_100 | |
| value: 57.516 | |
| - type: recall_at_1000 | |
| value: 77.74799999999999 | |
| - type: recall_at_3 | |
| value: 21.433 | |
| - type: recall_at_5 | |
| value: 25.915 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: dbpedia-entity | |
| name: MTEB DBPedia | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 9.322 | |
| - type: map_at_10 | |
| value: 20.469 | |
| - type: map_at_100 | |
| value: 28.638 | |
| - type: map_at_1000 | |
| value: 30.433 | |
| - type: map_at_3 | |
| value: 14.802000000000001 | |
| - type: map_at_5 | |
| value: 17.297 | |
| - type: mrr_at_1 | |
| value: 68.75 | |
| - type: mrr_at_10 | |
| value: 76.29599999999999 | |
| - type: mrr_at_100 | |
| value: 76.62400000000001 | |
| - type: mrr_at_1000 | |
| value: 76.633 | |
| - type: mrr_at_3 | |
| value: 75.083 | |
| - type: mrr_at_5 | |
| value: 75.771 | |
| - type: ndcg_at_1 | |
| value: 54.87499999999999 | |
| - type: ndcg_at_10 | |
| value: 41.185 | |
| - type: ndcg_at_100 | |
| value: 46.400000000000006 | |
| - type: ndcg_at_1000 | |
| value: 54.223 | |
| - type: ndcg_at_3 | |
| value: 45.489000000000004 | |
| - type: ndcg_at_5 | |
| value: 43.161 | |
| - type: precision_at_1 | |
| value: 68.75 | |
| - type: precision_at_10 | |
| value: 32.300000000000004 | |
| - type: precision_at_100 | |
| value: 10.607999999999999 | |
| - type: precision_at_1000 | |
| value: 2.237 | |
| - type: precision_at_3 | |
| value: 49.083 | |
| - type: precision_at_5 | |
| value: 41.6 | |
| - type: recall_at_1 | |
| value: 9.322 | |
| - type: recall_at_10 | |
| value: 25.696 | |
| - type: recall_at_100 | |
| value: 52.898 | |
| - type: recall_at_1000 | |
| value: 77.281 | |
| - type: recall_at_3 | |
| value: 15.943 | |
| - type: recall_at_5 | |
| value: 19.836000000000002 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/emotion | |
| name: MTEB EmotionClassification | |
| config: default | |
| split: test | |
| revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 | |
| metrics: | |
| - type: accuracy | |
| value: 48.650000000000006 | |
| - type: f1 | |
| value: 43.528467245539396 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: fever | |
| name: MTEB FEVER | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 66.56 | |
| - type: map_at_10 | |
| value: 76.767 | |
| - type: map_at_100 | |
| value: 77.054 | |
| - type: map_at_1000 | |
| value: 77.068 | |
| - type: map_at_3 | |
| value: 75.29299999999999 | |
| - type: map_at_5 | |
| value: 76.24 | |
| - type: mrr_at_1 | |
| value: 71.842 | |
| - type: mrr_at_10 | |
| value: 81.459 | |
| - type: mrr_at_100 | |
| value: 81.58800000000001 | |
| - type: mrr_at_1000 | |
| value: 81.59100000000001 | |
| - type: mrr_at_3 | |
| value: 80.188 | |
| - type: mrr_at_5 | |
| value: 81.038 | |
| - type: ndcg_at_1 | |
| value: 71.842 | |
| - type: ndcg_at_10 | |
| value: 81.51899999999999 | |
| - type: ndcg_at_100 | |
| value: 82.544 | |
| - type: ndcg_at_1000 | |
| value: 82.829 | |
| - type: ndcg_at_3 | |
| value: 78.92 | |
| - type: ndcg_at_5 | |
| value: 80.406 | |
| - type: precision_at_1 | |
| value: 71.842 | |
| - type: precision_at_10 | |
| value: 10.066 | |
| - type: precision_at_100 | |
| value: 1.076 | |
| - type: precision_at_1000 | |
| value: 0.11199999999999999 | |
| - type: precision_at_3 | |
| value: 30.703000000000003 | |
| - type: precision_at_5 | |
| value: 19.301 | |
| - type: recall_at_1 | |
| value: 66.56 | |
| - type: recall_at_10 | |
| value: 91.55 | |
| - type: recall_at_100 | |
| value: 95.67099999999999 | |
| - type: recall_at_1000 | |
| value: 97.539 | |
| - type: recall_at_3 | |
| value: 84.46900000000001 | |
| - type: recall_at_5 | |
| value: 88.201 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: fiqa | |
| name: MTEB FiQA2018 | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 20.087 | |
| - type: map_at_10 | |
| value: 32.830999999999996 | |
| - type: map_at_100 | |
| value: 34.814 | |
| - type: map_at_1000 | |
| value: 34.999 | |
| - type: map_at_3 | |
| value: 28.198 | |
| - type: map_at_5 | |
| value: 30.779 | |
| - type: mrr_at_1 | |
| value: 38.889 | |
| - type: mrr_at_10 | |
| value: 48.415 | |
| - type: mrr_at_100 | |
| value: 49.187 | |
| - type: mrr_at_1000 | |
| value: 49.226 | |
| - type: mrr_at_3 | |
| value: 45.705 | |
| - type: mrr_at_5 | |
| value: 47.225 | |
| - type: ndcg_at_1 | |
| value: 38.889 | |
| - type: ndcg_at_10 | |
| value: 40.758 | |
| - type: ndcg_at_100 | |
| value: 47.671 | |
| - type: ndcg_at_1000 | |
| value: 50.744 | |
| - type: ndcg_at_3 | |
| value: 36.296 | |
| - type: ndcg_at_5 | |
| value: 37.852999999999994 | |
| - type: precision_at_1 | |
| value: 38.889 | |
| - type: precision_at_10 | |
| value: 11.466 | |
| - type: precision_at_100 | |
| value: 1.8499999999999999 | |
| - type: precision_at_1000 | |
| value: 0.24 | |
| - type: precision_at_3 | |
| value: 24.126 | |
| - type: precision_at_5 | |
| value: 18.21 | |
| - type: recall_at_1 | |
| value: 20.087 | |
| - type: recall_at_10 | |
| value: 48.042 | |
| - type: recall_at_100 | |
| value: 73.493 | |
| - type: recall_at_1000 | |
| value: 91.851 | |
| - type: recall_at_3 | |
| value: 32.694 | |
| - type: recall_at_5 | |
| value: 39.099000000000004 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: hotpotqa | |
| name: MTEB HotpotQA | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 38.096000000000004 | |
| - type: map_at_10 | |
| value: 56.99999999999999 | |
| - type: map_at_100 | |
| value: 57.914 | |
| - type: map_at_1000 | |
| value: 57.984 | |
| - type: map_at_3 | |
| value: 53.900999999999996 | |
| - type: map_at_5 | |
| value: 55.827000000000005 | |
| - type: mrr_at_1 | |
| value: 76.19200000000001 | |
| - type: mrr_at_10 | |
| value: 81.955 | |
| - type: mrr_at_100 | |
| value: 82.164 | |
| - type: mrr_at_1000 | |
| value: 82.173 | |
| - type: mrr_at_3 | |
| value: 80.963 | |
| - type: mrr_at_5 | |
| value: 81.574 | |
| - type: ndcg_at_1 | |
| value: 76.19200000000001 | |
| - type: ndcg_at_10 | |
| value: 65.75 | |
| - type: ndcg_at_100 | |
| value: 68.949 | |
| - type: ndcg_at_1000 | |
| value: 70.342 | |
| - type: ndcg_at_3 | |
| value: 61.29 | |
| - type: ndcg_at_5 | |
| value: 63.747 | |
| - type: precision_at_1 | |
| value: 76.19200000000001 | |
| - type: precision_at_10 | |
| value: 13.571 | |
| - type: precision_at_100 | |
| value: 1.6070000000000002 | |
| - type: precision_at_1000 | |
| value: 0.179 | |
| - type: precision_at_3 | |
| value: 38.663 | |
| - type: precision_at_5 | |
| value: 25.136999999999997 | |
| - type: recall_at_1 | |
| value: 38.096000000000004 | |
| - type: recall_at_10 | |
| value: 67.853 | |
| - type: recall_at_100 | |
| value: 80.365 | |
| - type: recall_at_1000 | |
| value: 89.629 | |
| - type: recall_at_3 | |
| value: 57.995 | |
| - type: recall_at_5 | |
| value: 62.843 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/imdb | |
| name: MTEB ImdbClassification | |
| config: default | |
| split: test | |
| revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 | |
| metrics: | |
| - type: accuracy | |
| value: 85.95200000000001 | |
| - type: ap | |
| value: 80.73847277002109 | |
| - type: f1 | |
| value: 85.92406135678594 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: msmarco | |
| name: MTEB MSMARCO | |
| config: default | |
| split: dev | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 20.916999999999998 | |
| - type: map_at_10 | |
| value: 33.23 | |
| - type: map_at_100 | |
| value: 34.427 | |
| - type: map_at_1000 | |
| value: 34.477000000000004 | |
| - type: map_at_3 | |
| value: 29.292 | |
| - type: map_at_5 | |
| value: 31.6 | |
| - type: mrr_at_1 | |
| value: 21.547 | |
| - type: mrr_at_10 | |
| value: 33.839999999999996 | |
| - type: mrr_at_100 | |
| value: 34.979 | |
| - type: mrr_at_1000 | |
| value: 35.022999999999996 | |
| - type: mrr_at_3 | |
| value: 29.988 | |
| - type: mrr_at_5 | |
| value: 32.259 | |
| - type: ndcg_at_1 | |
| value: 21.519 | |
| - type: ndcg_at_10 | |
| value: 40.209 | |
| - type: ndcg_at_100 | |
| value: 45.954 | |
| - type: ndcg_at_1000 | |
| value: 47.187 | |
| - type: ndcg_at_3 | |
| value: 32.227 | |
| - type: ndcg_at_5 | |
| value: 36.347 | |
| - type: precision_at_1 | |
| value: 21.519 | |
| - type: precision_at_10 | |
| value: 6.447 | |
| - type: precision_at_100 | |
| value: 0.932 | |
| - type: precision_at_1000 | |
| value: 0.104 | |
| - type: precision_at_3 | |
| value: 13.877999999999998 | |
| - type: precision_at_5 | |
| value: 10.404 | |
| - type: recall_at_1 | |
| value: 20.916999999999998 | |
| - type: recall_at_10 | |
| value: 61.7 | |
| - type: recall_at_100 | |
| value: 88.202 | |
| - type: recall_at_1000 | |
| value: 97.588 | |
| - type: recall_at_3 | |
| value: 40.044999999999995 | |
| - type: recall_at_5 | |
| value: 49.964999999999996 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/mtop_domain | |
| name: MTEB MTOPDomainClassification (en) | |
| config: en | |
| split: test | |
| revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf | |
| metrics: | |
| - type: accuracy | |
| value: 93.02781577747379 | |
| - type: f1 | |
| value: 92.83653922768306 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/mtop_intent | |
| name: MTEB MTOPIntentClassification (en) | |
| config: en | |
| split: test | |
| revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba | |
| metrics: | |
| - type: accuracy | |
| value: 72.04286365709075 | |
| - type: f1 | |
| value: 53.43867658525793 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/amazon_massive_intent | |
| name: MTEB MassiveIntentClassification (en) | |
| config: en | |
| split: test | |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 | |
| metrics: | |
| - type: accuracy | |
| value: 71.47276395427035 | |
| - type: f1 | |
| value: 69.77017399597342 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/amazon_massive_scenario | |
| name: MTEB MassiveScenarioClassification (en) | |
| config: en | |
| split: test | |
| revision: 7d571f92784cd94a019292a1f45445077d0ef634 | |
| metrics: | |
| - type: accuracy | |
| value: 76.3819771351715 | |
| - type: f1 | |
| value: 76.8484533435409 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/medrxiv-clustering-p2p | |
| name: MTEB MedrxivClusteringP2P | |
| config: default | |
| split: test | |
| revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 | |
| metrics: | |
| - type: v_measure | |
| value: 33.16515993299593 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/medrxiv-clustering-s2s | |
| name: MTEB MedrxivClusteringS2S | |
| config: default | |
| split: test | |
| revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 | |
| metrics: | |
| - type: v_measure | |
| value: 31.77145323314774 | |
| - task: | |
| type: Reranking | |
| dataset: | |
| type: mteb/mind_small | |
| name: MTEB MindSmallReranking | |
| config: default | |
| split: test | |
| revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 | |
| metrics: | |
| - type: map | |
| value: 32.53637706586391 | |
| - type: mrr | |
| value: 33.7312926288863 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: nfcorpus | |
| name: MTEB NFCorpus | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 7.063999999999999 | |
| - type: map_at_10 | |
| value: 15.046999999999999 | |
| - type: map_at_100 | |
| value: 19.116 | |
| - type: map_at_1000 | |
| value: 20.702 | |
| - type: map_at_3 | |
| value: 10.932 | |
| - type: map_at_5 | |
| value: 12.751999999999999 | |
| - type: mrr_at_1 | |
| value: 50.464 | |
| - type: mrr_at_10 | |
| value: 58.189 | |
| - type: mrr_at_100 | |
| value: 58.733999999999995 | |
| - type: mrr_at_1000 | |
| value: 58.769000000000005 | |
| - type: mrr_at_3 | |
| value: 56.24400000000001 | |
| - type: mrr_at_5 | |
| value: 57.68299999999999 | |
| - type: ndcg_at_1 | |
| value: 48.142 | |
| - type: ndcg_at_10 | |
| value: 37.897 | |
| - type: ndcg_at_100 | |
| value: 35.264 | |
| - type: ndcg_at_1000 | |
| value: 44.033 | |
| - type: ndcg_at_3 | |
| value: 42.967 | |
| - type: ndcg_at_5 | |
| value: 40.815 | |
| - type: precision_at_1 | |
| value: 50.15500000000001 | |
| - type: precision_at_10 | |
| value: 28.235 | |
| - type: precision_at_100 | |
| value: 8.994 | |
| - type: precision_at_1000 | |
| value: 2.218 | |
| - type: precision_at_3 | |
| value: 40.041 | |
| - type: precision_at_5 | |
| value: 35.046 | |
| - type: recall_at_1 | |
| value: 7.063999999999999 | |
| - type: recall_at_10 | |
| value: 18.598 | |
| - type: recall_at_100 | |
| value: 35.577999999999996 | |
| - type: recall_at_1000 | |
| value: 67.43 | |
| - type: recall_at_3 | |
| value: 11.562999999999999 | |
| - type: recall_at_5 | |
| value: 14.771 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: nq | |
| name: MTEB NQ | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 29.046 | |
| - type: map_at_10 | |
| value: 44.808 | |
| - type: map_at_100 | |
| value: 45.898 | |
| - type: map_at_1000 | |
| value: 45.927 | |
| - type: map_at_3 | |
| value: 40.19 | |
| - type: map_at_5 | |
| value: 42.897 | |
| - type: mrr_at_1 | |
| value: 32.706 | |
| - type: mrr_at_10 | |
| value: 47.275 | |
| - type: mrr_at_100 | |
| value: 48.075 | |
| - type: mrr_at_1000 | |
| value: 48.095 | |
| - type: mrr_at_3 | |
| value: 43.463 | |
| - type: mrr_at_5 | |
| value: 45.741 | |
| - type: ndcg_at_1 | |
| value: 32.706 | |
| - type: ndcg_at_10 | |
| value: 52.835 | |
| - type: ndcg_at_100 | |
| value: 57.345 | |
| - type: ndcg_at_1000 | |
| value: 57.985 | |
| - type: ndcg_at_3 | |
| value: 44.171 | |
| - type: ndcg_at_5 | |
| value: 48.661 | |
| - type: precision_at_1 | |
| value: 32.706 | |
| - type: precision_at_10 | |
| value: 8.895999999999999 | |
| - type: precision_at_100 | |
| value: 1.143 | |
| - type: precision_at_1000 | |
| value: 0.12 | |
| - type: precision_at_3 | |
| value: 20.238999999999997 | |
| - type: precision_at_5 | |
| value: 14.728 | |
| - type: recall_at_1 | |
| value: 29.046 | |
| - type: recall_at_10 | |
| value: 74.831 | |
| - type: recall_at_100 | |
| value: 94.192 | |
| - type: recall_at_1000 | |
| value: 98.897 | |
| - type: recall_at_3 | |
| value: 52.37500000000001 | |
| - type: recall_at_5 | |
| value: 62.732 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: quora | |
| name: MTEB QuoraRetrieval | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 70.38799999999999 | |
| - type: map_at_10 | |
| value: 84.315 | |
| - type: map_at_100 | |
| value: 84.955 | |
| - type: map_at_1000 | |
| value: 84.971 | |
| - type: map_at_3 | |
| value: 81.33399999999999 | |
| - type: map_at_5 | |
| value: 83.21300000000001 | |
| - type: mrr_at_1 | |
| value: 81.03 | |
| - type: mrr_at_10 | |
| value: 87.395 | |
| - type: mrr_at_100 | |
| value: 87.488 | |
| - type: mrr_at_1000 | |
| value: 87.48899999999999 | |
| - type: mrr_at_3 | |
| value: 86.41499999999999 | |
| - type: mrr_at_5 | |
| value: 87.074 | |
| - type: ndcg_at_1 | |
| value: 81.04 | |
| - type: ndcg_at_10 | |
| value: 88.151 | |
| - type: ndcg_at_100 | |
| value: 89.38199999999999 | |
| - type: ndcg_at_1000 | |
| value: 89.479 | |
| - type: ndcg_at_3 | |
| value: 85.24000000000001 | |
| - type: ndcg_at_5 | |
| value: 86.856 | |
| - type: precision_at_1 | |
| value: 81.04 | |
| - type: precision_at_10 | |
| value: 13.372 | |
| - type: precision_at_100 | |
| value: 1.526 | |
| - type: precision_at_1000 | |
| value: 0.157 | |
| - type: precision_at_3 | |
| value: 37.217 | |
| - type: precision_at_5 | |
| value: 24.502 | |
| - type: recall_at_1 | |
| value: 70.38799999999999 | |
| - type: recall_at_10 | |
| value: 95.452 | |
| - type: recall_at_100 | |
| value: 99.59700000000001 | |
| - type: recall_at_1000 | |
| value: 99.988 | |
| - type: recall_at_3 | |
| value: 87.11 | |
| - type: recall_at_5 | |
| value: 91.662 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/reddit-clustering | |
| name: MTEB RedditClustering | |
| config: default | |
| split: test | |
| revision: 24640382cdbf8abc73003fb0fa6d111a705499eb | |
| metrics: | |
| - type: v_measure | |
| value: 59.334991029213235 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/reddit-clustering-p2p | |
| name: MTEB RedditClusteringP2P | |
| config: default | |
| split: test | |
| revision: 282350215ef01743dc01b456c7f5241fa8937f16 | |
| metrics: | |
| - type: v_measure | |
| value: 62.586500854616666 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: scidocs | |
| name: MTEB SCIDOCS | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 5.153 | |
| - type: map_at_10 | |
| value: 14.277000000000001 | |
| - type: map_at_100 | |
| value: 16.922 | |
| - type: map_at_1000 | |
| value: 17.302999999999997 | |
| - type: map_at_3 | |
| value: 9.961 | |
| - type: map_at_5 | |
| value: 12.257 | |
| - type: mrr_at_1 | |
| value: 25.4 | |
| - type: mrr_at_10 | |
| value: 37.458000000000006 | |
| - type: mrr_at_100 | |
| value: 38.681 | |
| - type: mrr_at_1000 | |
| value: 38.722 | |
| - type: mrr_at_3 | |
| value: 34.1 | |
| - type: mrr_at_5 | |
| value: 36.17 | |
| - type: ndcg_at_1 | |
| value: 25.4 | |
| - type: ndcg_at_10 | |
| value: 23.132 | |
| - type: ndcg_at_100 | |
| value: 32.908 | |
| - type: ndcg_at_1000 | |
| value: 38.754 | |
| - type: ndcg_at_3 | |
| value: 21.82 | |
| - type: ndcg_at_5 | |
| value: 19.353 | |
| - type: precision_at_1 | |
| value: 25.4 | |
| - type: precision_at_10 | |
| value: 12.1 | |
| - type: precision_at_100 | |
| value: 2.628 | |
| - type: precision_at_1000 | |
| value: 0.402 | |
| - type: precision_at_3 | |
| value: 20.732999999999997 | |
| - type: precision_at_5 | |
| value: 17.34 | |
| - type: recall_at_1 | |
| value: 5.153 | |
| - type: recall_at_10 | |
| value: 24.54 | |
| - type: recall_at_100 | |
| value: 53.293 | |
| - type: recall_at_1000 | |
| value: 81.57 | |
| - type: recall_at_3 | |
| value: 12.613 | |
| - type: recall_at_5 | |
| value: 17.577 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/sickr-sts | |
| name: MTEB SICK-R | |
| config: default | |
| split: test | |
| revision: a6ea5a8cab320b040a23452cc28066d9beae2cee | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 84.86284404925333 | |
| - type: cos_sim_spearman | |
| value: 78.85870555294795 | |
| - type: euclidean_pearson | |
| value: 82.20105295276093 | |
| - type: euclidean_spearman | |
| value: 78.92125617009592 | |
| - type: manhattan_pearson | |
| value: 82.15840025289069 | |
| - type: manhattan_spearman | |
| value: 78.85955732900803 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/sts12-sts | |
| name: MTEB STS12 | |
| config: default | |
| split: test | |
| revision: a0d554a64d88156834ff5ae9920b964011b16384 | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 84.98747423389027 | |
| - type: cos_sim_spearman | |
| value: 75.71298531799367 | |
| - type: euclidean_pearson | |
| value: 81.59709559192291 | |
| - type: euclidean_spearman | |
| value: 75.40622749225653 | |
| - type: manhattan_pearson | |
| value: 81.55553547608804 | |
| - type: manhattan_spearman | |
| value: 75.39380235424899 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/sts13-sts | |
| name: MTEB STS13 | |
| config: default | |
| split: test | |
| revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 83.76861330695503 | |
| - type: cos_sim_spearman | |
| value: 85.72991921531624 | |
| - type: euclidean_pearson | |
| value: 84.84504307397536 | |
| - type: euclidean_spearman | |
| value: 86.02679162824732 | |
| - type: manhattan_pearson | |
| value: 84.79969439220142 | |
| - type: manhattan_spearman | |
| value: 85.99238837291625 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/sts14-sts | |
| name: MTEB STS14 | |
| config: default | |
| split: test | |
| revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 83.31929747511796 | |
| - type: cos_sim_spearman | |
| value: 81.50806522502528 | |
| - type: euclidean_pearson | |
| value: 82.93936686512777 | |
| - type: euclidean_spearman | |
| value: 81.54403447993224 | |
| - type: manhattan_pearson | |
| value: 82.89696981900828 | |
| - type: manhattan_spearman | |
| value: 81.52817825470865 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/sts15-sts | |
| name: MTEB STS15 | |
| config: default | |
| split: test | |
| revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 87.14413295332908 | |
| - type: cos_sim_spearman | |
| value: 88.81032027008195 | |
| - type: euclidean_pearson | |
| value: 88.19205563407645 | |
| - type: euclidean_spearman | |
| value: 88.89738339479216 | |
| - type: manhattan_pearson | |
| value: 88.11075942004189 | |
| - type: manhattan_spearman | |
| value: 88.8297061675564 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/sts16-sts | |
| name: MTEB STS16 | |
| config: default | |
| split: test | |
| revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 82.15980075557017 | |
| - type: cos_sim_spearman | |
| value: 83.81896308594801 | |
| - type: euclidean_pearson | |
| value: 83.11195254311338 | |
| - type: euclidean_spearman | |
| value: 84.10479481755407 | |
| - type: manhattan_pearson | |
| value: 83.13915225100556 | |
| - type: manhattan_spearman | |
| value: 84.09895591027859 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/sts17-crosslingual-sts | |
| name: MTEB STS17 (en-en) | |
| config: en-en | |
| split: test | |
| revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 87.93669480147919 | |
| - type: cos_sim_spearman | |
| value: 87.89861394614361 | |
| - type: euclidean_pearson | |
| value: 88.37316413202339 | |
| - type: euclidean_spearman | |
| value: 88.18033817842569 | |
| - type: manhattan_pearson | |
| value: 88.39427578879469 | |
| - type: manhattan_spearman | |
| value: 88.09185009236847 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/sts22-crosslingual-sts | |
| name: MTEB STS22 (en) | |
| config: en | |
| split: test | |
| revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 66.62215083348255 | |
| - type: cos_sim_spearman | |
| value: 67.33243665716736 | |
| - type: euclidean_pearson | |
| value: 67.60871701996284 | |
| - type: euclidean_spearman | |
| value: 66.75929225238659 | |
| - type: manhattan_pearson | |
| value: 67.63907838970992 | |
| - type: manhattan_spearman | |
| value: 66.79313656754846 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/stsbenchmark-sts | |
| name: MTEB STSBenchmark | |
| config: default | |
| split: test | |
| revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 84.65549191934764 | |
| - type: cos_sim_spearman | |
| value: 85.73266847750143 | |
| - type: euclidean_pearson | |
| value: 85.75609932254318 | |
| - type: euclidean_spearman | |
| value: 85.9452287759371 | |
| - type: manhattan_pearson | |
| value: 85.69717413063573 | |
| - type: manhattan_spearman | |
| value: 85.86546318377046 | |
| - task: | |
| type: Reranking | |
| dataset: | |
| type: mteb/scidocs-reranking | |
| name: MTEB SciDocsRR | |
| config: default | |
| split: test | |
| revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab | |
| metrics: | |
| - type: map | |
| value: 87.08164129085783 | |
| - type: mrr | |
| value: 96.2877273416489 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: scifact | |
| name: MTEB SciFact | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 62.09400000000001 | |
| - type: map_at_10 | |
| value: 71.712 | |
| - type: map_at_100 | |
| value: 72.128 | |
| - type: map_at_1000 | |
| value: 72.14399999999999 | |
| - type: map_at_3 | |
| value: 68.93 | |
| - type: map_at_5 | |
| value: 70.694 | |
| - type: mrr_at_1 | |
| value: 65.0 | |
| - type: mrr_at_10 | |
| value: 72.572 | |
| - type: mrr_at_100 | |
| value: 72.842 | |
| - type: mrr_at_1000 | |
| value: 72.856 | |
| - type: mrr_at_3 | |
| value: 70.44399999999999 | |
| - type: mrr_at_5 | |
| value: 71.744 | |
| - type: ndcg_at_1 | |
| value: 65.0 | |
| - type: ndcg_at_10 | |
| value: 76.178 | |
| - type: ndcg_at_100 | |
| value: 77.887 | |
| - type: ndcg_at_1000 | |
| value: 78.227 | |
| - type: ndcg_at_3 | |
| value: 71.367 | |
| - type: ndcg_at_5 | |
| value: 73.938 | |
| - type: precision_at_1 | |
| value: 65.0 | |
| - type: precision_at_10 | |
| value: 10.033 | |
| - type: precision_at_100 | |
| value: 1.097 | |
| - type: precision_at_1000 | |
| value: 0.11199999999999999 | |
| - type: precision_at_3 | |
| value: 27.667 | |
| - type: precision_at_5 | |
| value: 18.4 | |
| - type: recall_at_1 | |
| value: 62.09400000000001 | |
| - type: recall_at_10 | |
| value: 89.022 | |
| - type: recall_at_100 | |
| value: 96.833 | |
| - type: recall_at_1000 | |
| value: 99.333 | |
| - type: recall_at_3 | |
| value: 75.922 | |
| - type: recall_at_5 | |
| value: 82.428 | |
| - task: | |
| type: PairClassification | |
| dataset: | |
| type: mteb/sprintduplicatequestions-pairclassification | |
| name: MTEB SprintDuplicateQuestions | |
| config: default | |
| split: test | |
| revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 | |
| metrics: | |
| - type: cos_sim_accuracy | |
| value: 99.82178217821782 | |
| - type: cos_sim_ap | |
| value: 95.71282508220798 | |
| - type: cos_sim_f1 | |
| value: 90.73120494335737 | |
| - type: cos_sim_precision | |
| value: 93.52441613588111 | |
| - type: cos_sim_recall | |
| value: 88.1 | |
| - type: dot_accuracy | |
| value: 99.73960396039604 | |
| - type: dot_ap | |
| value: 92.98534606529098 | |
| - type: dot_f1 | |
| value: 86.83024536805209 | |
| - type: dot_precision | |
| value: 86.96088264794383 | |
| - type: dot_recall | |
| value: 86.7 | |
| - type: euclidean_accuracy | |
| value: 99.82475247524752 | |
| - type: euclidean_ap | |
| value: 95.72927039014849 | |
| - type: euclidean_f1 | |
| value: 90.89974293059126 | |
| - type: euclidean_precision | |
| value: 93.54497354497354 | |
| - type: euclidean_recall | |
| value: 88.4 | |
| - type: manhattan_accuracy | |
| value: 99.82574257425742 | |
| - type: manhattan_ap | |
| value: 95.72142177390405 | |
| - type: manhattan_f1 | |
| value: 91.00152516522625 | |
| - type: manhattan_precision | |
| value: 92.55429162357808 | |
| - type: manhattan_recall | |
| value: 89.5 | |
| - type: max_accuracy | |
| value: 99.82574257425742 | |
| - type: max_ap | |
| value: 95.72927039014849 | |
| - type: max_f1 | |
| value: 91.00152516522625 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/stackexchange-clustering | |
| name: MTEB StackExchangeClustering | |
| config: default | |
| split: test | |
| revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 | |
| metrics: | |
| - type: v_measure | |
| value: 66.63957663468679 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/stackexchange-clustering-p2p | |
| name: MTEB StackExchangeClusteringP2P | |
| config: default | |
| split: test | |
| revision: 815ca46b2622cec33ccafc3735d572c266efdb44 | |
| metrics: | |
| - type: v_measure | |
| value: 36.003307257923964 | |
| - task: | |
| type: Reranking | |
| dataset: | |
| type: mteb/stackoverflowdupquestions-reranking | |
| name: MTEB StackOverflowDupQuestions | |
| config: default | |
| split: test | |
| revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 | |
| metrics: | |
| - type: map | |
| value: 53.005825525863905 | |
| - type: mrr | |
| value: 53.854683919022165 | |
| - task: | |
| type: Summarization | |
| dataset: | |
| type: mteb/summeval | |
| name: MTEB SummEval | |
| config: default | |
| split: test | |
| revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 30.503611569974098 | |
| - type: cos_sim_spearman | |
| value: 31.17155564248449 | |
| - type: dot_pearson | |
| value: 26.740428413981306 | |
| - type: dot_spearman | |
| value: 26.55727635469746 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: trec-covid | |
| name: MTEB TRECCOVID | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 0.23600000000000002 | |
| - type: map_at_10 | |
| value: 1.7670000000000001 | |
| - type: map_at_100 | |
| value: 10.208 | |
| - type: map_at_1000 | |
| value: 25.997999999999998 | |
| - type: map_at_3 | |
| value: 0.605 | |
| - type: map_at_5 | |
| value: 0.9560000000000001 | |
| - type: mrr_at_1 | |
| value: 84.0 | |
| - type: mrr_at_10 | |
| value: 90.167 | |
| - type: mrr_at_100 | |
| value: 90.167 | |
| - type: mrr_at_1000 | |
| value: 90.167 | |
| - type: mrr_at_3 | |
| value: 89.667 | |
| - type: mrr_at_5 | |
| value: 90.167 | |
| - type: ndcg_at_1 | |
| value: 77.0 | |
| - type: ndcg_at_10 | |
| value: 68.783 | |
| - type: ndcg_at_100 | |
| value: 54.196 | |
| - type: ndcg_at_1000 | |
| value: 52.077 | |
| - type: ndcg_at_3 | |
| value: 71.642 | |
| - type: ndcg_at_5 | |
| value: 70.45700000000001 | |
| - type: precision_at_1 | |
| value: 84.0 | |
| - type: precision_at_10 | |
| value: 73.0 | |
| - type: precision_at_100 | |
| value: 55.48 | |
| - type: precision_at_1000 | |
| value: 23.102 | |
| - type: precision_at_3 | |
| value: 76.0 | |
| - type: precision_at_5 | |
| value: 74.8 | |
| - type: recall_at_1 | |
| value: 0.23600000000000002 | |
| - type: recall_at_10 | |
| value: 1.9869999999999999 | |
| - type: recall_at_100 | |
| value: 13.749 | |
| - type: recall_at_1000 | |
| value: 50.157 | |
| - type: recall_at_3 | |
| value: 0.633 | |
| - type: recall_at_5 | |
| value: 1.0290000000000001 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: webis-touche2020 | |
| name: MTEB Touche2020 | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 1.437 | |
| - type: map_at_10 | |
| value: 8.791 | |
| - type: map_at_100 | |
| value: 15.001999999999999 | |
| - type: map_at_1000 | |
| value: 16.549 | |
| - type: map_at_3 | |
| value: 3.8080000000000003 | |
| - type: map_at_5 | |
| value: 5.632000000000001 | |
| - type: mrr_at_1 | |
| value: 20.408 | |
| - type: mrr_at_10 | |
| value: 36.96 | |
| - type: mrr_at_100 | |
| value: 37.912 | |
| - type: mrr_at_1000 | |
| value: 37.912 | |
| - type: mrr_at_3 | |
| value: 29.592000000000002 | |
| - type: mrr_at_5 | |
| value: 34.489999999999995 | |
| - type: ndcg_at_1 | |
| value: 19.387999999999998 | |
| - type: ndcg_at_10 | |
| value: 22.554 | |
| - type: ndcg_at_100 | |
| value: 35.197 | |
| - type: ndcg_at_1000 | |
| value: 46.58 | |
| - type: ndcg_at_3 | |
| value: 20.285 | |
| - type: ndcg_at_5 | |
| value: 21.924 | |
| - type: precision_at_1 | |
| value: 20.408 | |
| - type: precision_at_10 | |
| value: 21.837 | |
| - type: precision_at_100 | |
| value: 7.754999999999999 | |
| - type: precision_at_1000 | |
| value: 1.537 | |
| - type: precision_at_3 | |
| value: 21.769 | |
| - type: precision_at_5 | |
| value: 23.673 | |
| - type: recall_at_1 | |
| value: 1.437 | |
| - type: recall_at_10 | |
| value: 16.314999999999998 | |
| - type: recall_at_100 | |
| value: 47.635 | |
| - type: recall_at_1000 | |
| value: 82.963 | |
| - type: recall_at_3 | |
| value: 4.955 | |
| - type: recall_at_5 | |
| value: 8.805 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/toxic_conversations_50k | |
| name: MTEB ToxicConversationsClassification | |
| config: default | |
| split: test | |
| revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c | |
| metrics: | |
| - type: accuracy | |
| value: 71.6128 | |
| - type: ap | |
| value: 14.279639861175664 | |
| - type: f1 | |
| value: 54.922292491204274 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/tweet_sentiment_extraction | |
| name: MTEB TweetSentimentExtractionClassification | |
| config: default | |
| split: test | |
| revision: d604517c81ca91fe16a244d1248fc021f9ecee7a | |
| metrics: | |
| - type: accuracy | |
| value: 57.01188455008489 | |
| - type: f1 | |
| value: 57.377953019225515 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/twentynewsgroups-clustering | |
| name: MTEB TwentyNewsgroupsClustering | |
| config: default | |
| split: test | |
| revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 | |
| metrics: | |
| - type: v_measure | |
| value: 52.306769136544254 | |
| - task: | |
| type: PairClassification | |
| dataset: | |
| type: mteb/twittersemeval2015-pairclassification | |
| name: MTEB TwitterSemEval2015 | |
| config: default | |
| split: test | |
| revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 | |
| metrics: | |
| - type: cos_sim_accuracy | |
| value: 85.64701674912082 | |
| - type: cos_sim_ap | |
| value: 72.46600945328552 | |
| - type: cos_sim_f1 | |
| value: 67.96572367648784 | |
| - type: cos_sim_precision | |
| value: 61.21801649397336 | |
| - type: cos_sim_recall | |
| value: 76.38522427440633 | |
| - type: dot_accuracy | |
| value: 82.33295583238957 | |
| - type: dot_ap | |
| value: 62.54843443071716 | |
| - type: dot_f1 | |
| value: 60.38378562507096 | |
| - type: dot_precision | |
| value: 52.99980067769583 | |
| - type: dot_recall | |
| value: 70.15831134564644 | |
| - type: euclidean_accuracy | |
| value: 85.7423854085951 | |
| - type: euclidean_ap | |
| value: 72.76873850945174 | |
| - type: euclidean_f1 | |
| value: 68.23556960543262 | |
| - type: euclidean_precision | |
| value: 61.3344559040202 | |
| - type: euclidean_recall | |
| value: 76.88654353562005 | |
| - type: manhattan_accuracy | |
| value: 85.74834594981225 | |
| - type: manhattan_ap | |
| value: 72.66825372446462 | |
| - type: manhattan_f1 | |
| value: 68.21539194662853 | |
| - type: manhattan_precision | |
| value: 62.185056472632496 | |
| - type: manhattan_recall | |
| value: 75.54089709762533 | |
| - type: max_accuracy | |
| value: 85.74834594981225 | |
| - type: max_ap | |
| value: 72.76873850945174 | |
| - type: max_f1 | |
| value: 68.23556960543262 | |
| - task: | |
| type: PairClassification | |
| dataset: | |
| type: mteb/twitterurlcorpus-pairclassification | |
| name: MTEB TwitterURLCorpus | |
| config: default | |
| split: test | |
| revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf | |
| metrics: | |
| - type: cos_sim_accuracy | |
| value: 88.73171110334924 | |
| - type: cos_sim_ap | |
| value: 85.51855542063649 | |
| - type: cos_sim_f1 | |
| value: 77.95706775700934 | |
| - type: cos_sim_precision | |
| value: 74.12524298805887 | |
| - type: cos_sim_recall | |
| value: 82.20665229442562 | |
| - type: dot_accuracy | |
| value: 86.94842240074514 | |
| - type: dot_ap | |
| value: 80.90995345771762 | |
| - type: dot_f1 | |
| value: 74.20765027322403 | |
| - type: dot_precision | |
| value: 70.42594385285575 | |
| - type: dot_recall | |
| value: 78.41854019094548 | |
| - type: euclidean_accuracy | |
| value: 88.73753250281368 | |
| - type: euclidean_ap | |
| value: 85.54712254033734 | |
| - type: euclidean_f1 | |
| value: 78.07565728654365 | |
| - type: euclidean_precision | |
| value: 75.1120597652081 | |
| - type: euclidean_recall | |
| value: 81.282722513089 | |
| - type: manhattan_accuracy | |
| value: 88.72588970388482 | |
| - type: manhattan_ap | |
| value: 85.52118291594071 | |
| - type: manhattan_f1 | |
| value: 78.04428724070593 | |
| - type: manhattan_precision | |
| value: 74.83219105490002 | |
| - type: manhattan_recall | |
| value: 81.54450261780106 | |
| - type: max_accuracy | |
| value: 88.73753250281368 | |
| - type: max_ap | |
| value: 85.54712254033734 | |
| - type: max_f1 | |
| value: 78.07565728654365 | |
| language: | |
| - en | |
| license: mit | |
| # gte-base | |
| General Text Embeddings (GTE) model. [Towards General Text Embeddings with Multi-stage Contrastive Learning](https://arxiv.org/abs/2308.03281) | |
| The GTE models are trained by Alibaba DAMO Academy. They are mainly based on the BERT framework and currently offer three different sizes of models, including [GTE-large](https://huggingface.co/thenlper/gte-large), [GTE-base](https://huggingface.co/thenlper/gte-base), and [GTE-small](https://huggingface.co/thenlper/gte-small). The GTE models are trained on a large-scale corpus of relevance text pairs, covering a wide range of domains and scenarios. This enables the GTE models to be applied to various downstream tasks of text embeddings, including **information retrieval**, **semantic textual similarity**, **text reranking**, etc. | |
| ## Metrics | |
| We compared the performance of the GTE models with other popular text embedding models on the MTEB benchmark. For more detailed comparison results, please refer to the [MTEB leaderboard](https://huggingface.co/spaces/mteb/leaderboard). | |
| | Model Name | Model Size (GB) | Dimension | Sequence Length | Average (56) | Clustering (11) | Pair Classification (3) | Reranking (4) | Retrieval (15) | STS (10) | Summarization (1) | Classification (12) | | |
| |:----:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:| | |
| | [**gte-large**](https://huggingface.co/thenlper/gte-large) | 0.67 | 1024 | 512 | **63.13** | 46.84 | 85.00 | 59.13 | 52.22 | 83.35 | 31.66 | 73.33 | | |
| | [**gte-base**](https://huggingface.co/thenlper/gte-base) | 0.22 | 768 | 512 | **62.39** | 46.2 | 84.57 | 58.61 | 51.14 | 82.3 | 31.17 | 73.01 | | |
| | [e5-large-v2](https://huggingface.co/intfloat/e5-large-v2) | 1.34 | 1024| 512 | 62.25 | 44.49 | 86.03 | 56.61 | 50.56 | 82.05 | 30.19 | 75.24 | | |
| | [e5-base-v2](https://huggingface.co/intfloat/e5-base-v2) | 0.44 | 768 | 512 | 61.5 | 43.80 | 85.73 | 55.91 | 50.29 | 81.05 | 30.28 | 73.84 | | |
| | [**gte-small**](https://huggingface.co/thenlper/gte-small) | 0.07 | 384 | 512 | **61.36** | 44.89 | 83.54 | 57.7 | 49.46 | 82.07 | 30.42 | 72.31 | | |
| | [text-embedding-ada-002](https://platform.openai.com/docs/guides/embeddings) | - | 1536 | 8192 | 60.99 | 45.9 | 84.89 | 56.32 | 49.25 | 80.97 | 30.8 | 70.93 | | |
| | [e5-small-v2](https://huggingface.co/intfloat/e5-base-v2) | 0.13 | 384 | 512 | 59.93 | 39.92 | 84.67 | 54.32 | 49.04 | 80.39 | 31.16 | 72.94 | | |
| | [sentence-t5-xxl](https://huggingface.co/sentence-transformers/sentence-t5-xxl) | 9.73 | 768 | 512 | 59.51 | 43.72 | 85.06 | 56.42 | 42.24 | 82.63 | 30.08 | 73.42 | | |
| | [all-mpnet-base-v2](https://huggingface.co/sentence-transformers/all-mpnet-base-v2) | 0.44 | 768 | 514 | 57.78 | 43.69 | 83.04 | 59.36 | 43.81 | 80.28 | 27.49 | 65.07 | | |
| | [sgpt-bloom-7b1-msmarco](https://huggingface.co/bigscience/sgpt-bloom-7b1-msmarco) | 28.27 | 4096 | 2048 | 57.59 | 38.93 | 81.9 | 55.65 | 48.22 | 77.74 | 33.6 | 66.19 | | |
| | [all-MiniLM-L12-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L12-v2) | 0.13 | 384 | 512 | 56.53 | 41.81 | 82.41 | 58.44 | 42.69 | 79.8 | 27.9 | 63.21 | | |
| | [all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2) | 0.09 | 384 | 512 | 56.26 | 42.35 | 82.37 | 58.04 | 41.95 | 78.9 | 30.81 | 63.05 | | |
| | [contriever-base-msmarco](https://huggingface.co/nthakur/contriever-base-msmarco) | 0.44 | 768 | 512 | 56.00 | 41.1 | 82.54 | 53.14 | 41.88 | 76.51 | 30.36 | 66.68 | | |
| | [sentence-t5-base](https://huggingface.co/sentence-transformers/sentence-t5-base) | 0.22 | 768 | 512 | 55.27 | 40.21 | 85.18 | 53.09 | 33.63 | 81.14 | 31.39 | 69.81 | | |
| ## Usage | |
| Code example | |
| ```python | |
| import torch.nn.functional as F | |
| from torch import Tensor | |
| from transformers import AutoTokenizer, AutoModel | |
| def average_pool(last_hidden_states: Tensor, | |
| attention_mask: Tensor) -> Tensor: | |
| last_hidden = last_hidden_states.masked_fill(~attention_mask[..., None].bool(), 0.0) | |
| return last_hidden.sum(dim=1) / attention_mask.sum(dim=1)[..., None] | |
| input_texts = [ | |
| "what is the capital of China?", | |
| "how to implement quick sort in python?", | |
| "Beijing", | |
| "sorting algorithms" | |
| ] | |
| tokenizer = AutoTokenizer.from_pretrained("thenlper/gte-base") | |
| model = AutoModel.from_pretrained("thenlper/gte-base") | |
| # Tokenize the input texts | |
| batch_dict = tokenizer(input_texts, max_length=512, padding=True, truncation=True, return_tensors='pt') | |
| outputs = model(**batch_dict) | |
| embeddings = average_pool(outputs.last_hidden_state, batch_dict['attention_mask']) | |
| # (Optionally) normalize embeddings | |
| embeddings = F.normalize(embeddings, p=2, dim=1) | |
| scores = (embeddings[:1] @ embeddings[1:].T) * 100 | |
| print(scores.tolist()) | |
| ``` | |
| Use with sentence-transformers: | |
| ```python | |
| from sentence_transformers import SentenceTransformer | |
| from sentence_transformers.util import cos_sim | |
| sentences = ['That is a happy person', 'That is a very happy person'] | |
| model = SentenceTransformer('thenlper/gte-base') | |
| embeddings = model.encode(sentences) | |
| print(cos_sim(embeddings[0], embeddings[1])) | |
| ``` | |
| ### Limitation | |
| This model exclusively caters to English texts, and any lengthy texts will be truncated to a maximum of 512 tokens. | |
| ### Citation | |
| If you find our paper or models helpful, please consider citing them as follows: | |
| ``` | |
| @article{li2023towards, | |
| title={Towards general text embeddings with multi-stage contrastive learning}, | |
| author={Li, Zehan and Zhang, Xin and Zhang, Yanzhao and Long, Dingkun and Xie, Pengjun and Zhang, Meishan}, | |
| journal={arXiv preprint arXiv:2308.03281}, | |
| year={2023} | |
| } | |
| ``` | |