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| datasets: | |
| - allenai/c4 | |
| library_name: transformers | |
| tags: | |
| - sentence-transformers | |
| - gte | |
| - mteb | |
| - transformers.js | |
| - sentence-similarity | |
| license: apache-2.0 | |
| language: | |
| - en | |
| model-index: | |
| - name: gte-large-en-v1.5 | |
| results: | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/amazon_counterfactual | |
| name: MTEB AmazonCounterfactualClassification (en) | |
| config: en | |
| split: test | |
| revision: e8379541af4e31359cca9fbcf4b00f2671dba205 | |
| metrics: | |
| - type: accuracy | |
| value: 73.01492537313432 | |
| - type: ap | |
| value: 35.05341696659522 | |
| - type: f1 | |
| value: 66.71270310883853 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/amazon_polarity | |
| name: MTEB AmazonPolarityClassification | |
| config: default | |
| split: test | |
| revision: e2d317d38cd51312af73b3d32a06d1a08b442046 | |
| metrics: | |
| - type: accuracy | |
| value: 93.97189999999999 | |
| - type: ap | |
| value: 90.5952493948908 | |
| - type: f1 | |
| value: 93.95848137716877 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/amazon_reviews_multi | |
| name: MTEB AmazonReviewsClassification (en) | |
| config: en | |
| split: test | |
| revision: 1399c76144fd37290681b995c656ef9b2e06e26d | |
| metrics: | |
| - type: accuracy | |
| value: 54.196 | |
| - type: f1 | |
| value: 53.80122334012787 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: mteb/arguana | |
| name: MTEB ArguAna | |
| config: default | |
| split: test | |
| revision: c22ab2a51041ffd869aaddef7af8d8215647e41a | |
| metrics: | |
| - type: map_at_1 | |
| value: 47.297 | |
| - type: map_at_10 | |
| value: 64.303 | |
| - type: map_at_100 | |
| value: 64.541 | |
| - type: map_at_1000 | |
| value: 64.541 | |
| - type: map_at_3 | |
| value: 60.728 | |
| - type: map_at_5 | |
| value: 63.114000000000004 | |
| - type: mrr_at_1 | |
| value: 48.435 | |
| - type: mrr_at_10 | |
| value: 64.657 | |
| - type: mrr_at_100 | |
| value: 64.901 | |
| - type: mrr_at_1000 | |
| value: 64.901 | |
| - type: mrr_at_3 | |
| value: 61.06 | |
| - type: mrr_at_5 | |
| value: 63.514 | |
| - type: ndcg_at_1 | |
| value: 47.297 | |
| - type: ndcg_at_10 | |
| value: 72.107 | |
| - type: ndcg_at_100 | |
| value: 72.963 | |
| - type: ndcg_at_1000 | |
| value: 72.963 | |
| - type: ndcg_at_3 | |
| value: 65.063 | |
| - type: ndcg_at_5 | |
| value: 69.352 | |
| - type: precision_at_1 | |
| value: 47.297 | |
| - type: precision_at_10 | |
| value: 9.623 | |
| - type: precision_at_100 | |
| value: 0.996 | |
| - type: precision_at_1000 | |
| value: 0.1 | |
| - type: precision_at_3 | |
| value: 25.865 | |
| - type: precision_at_5 | |
| value: 17.596 | |
| - type: recall_at_1 | |
| value: 47.297 | |
| - type: recall_at_10 | |
| value: 96.23 | |
| - type: recall_at_100 | |
| value: 99.644 | |
| - type: recall_at_1000 | |
| value: 99.644 | |
| - type: recall_at_3 | |
| value: 77.596 | |
| - type: recall_at_5 | |
| value: 87.98 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/arxiv-clustering-p2p | |
| name: MTEB ArxivClusteringP2P | |
| config: default | |
| split: test | |
| revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d | |
| metrics: | |
| - type: v_measure | |
| value: 48.467787861077475 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/arxiv-clustering-s2s | |
| name: MTEB ArxivClusteringS2S | |
| config: default | |
| split: test | |
| revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 | |
| metrics: | |
| - type: v_measure | |
| value: 43.39198391914257 | |
| - task: | |
| type: Reranking | |
| dataset: | |
| type: mteb/askubuntudupquestions-reranking | |
| name: MTEB AskUbuntuDupQuestions | |
| config: default | |
| split: test | |
| revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 | |
| metrics: | |
| - type: map | |
| value: 63.12794820591384 | |
| - type: mrr | |
| value: 75.9331442641692 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/biosses-sts | |
| name: MTEB BIOSSES | |
| config: default | |
| split: test | |
| revision: d3fb88f8f02e40887cd149695127462bbcf29b4a | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 87.85062993863319 | |
| - type: cos_sim_spearman | |
| value: 85.39049989733459 | |
| - type: euclidean_pearson | |
| value: 86.00222680278333 | |
| - type: euclidean_spearman | |
| value: 85.45556162077396 | |
| - type: manhattan_pearson | |
| value: 85.88769871785621 | |
| - type: manhattan_spearman | |
| value: 85.11760211290839 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/banking77 | |
| name: MTEB Banking77Classification | |
| config: default | |
| split: test | |
| revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 | |
| metrics: | |
| - type: accuracy | |
| value: 87.32792207792208 | |
| - type: f1 | |
| value: 87.29132945999555 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/biorxiv-clustering-p2p | |
| name: MTEB BiorxivClusteringP2P | |
| config: default | |
| split: test | |
| revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 | |
| metrics: | |
| - type: v_measure | |
| value: 40.5779328301945 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/biorxiv-clustering-s2s | |
| name: MTEB BiorxivClusteringS2S | |
| config: default | |
| split: test | |
| revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 | |
| metrics: | |
| - type: v_measure | |
| value: 37.94425623865118 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: mteb/cqadupstack-android | |
| name: MTEB CQADupstackAndroidRetrieval | |
| config: default | |
| split: test | |
| revision: f46a197baaae43b4f621051089b82a364682dfeb | |
| metrics: | |
| - type: map_at_1 | |
| value: 32.978 | |
| - type: map_at_10 | |
| value: 44.45 | |
| - type: map_at_100 | |
| value: 46.19 | |
| - type: map_at_1000 | |
| value: 46.303 | |
| - type: map_at_3 | |
| value: 40.849000000000004 | |
| - type: map_at_5 | |
| value: 42.55 | |
| - type: mrr_at_1 | |
| value: 40.629 | |
| - type: mrr_at_10 | |
| value: 50.848000000000006 | |
| - type: mrr_at_100 | |
| value: 51.669 | |
| - type: mrr_at_1000 | |
| value: 51.705 | |
| - type: mrr_at_3 | |
| value: 47.997 | |
| - type: mrr_at_5 | |
| value: 49.506 | |
| - type: ndcg_at_1 | |
| value: 40.629 | |
| - type: ndcg_at_10 | |
| value: 51.102000000000004 | |
| - type: ndcg_at_100 | |
| value: 57.159000000000006 | |
| - type: ndcg_at_1000 | |
| value: 58.669000000000004 | |
| - type: ndcg_at_3 | |
| value: 45.738 | |
| - type: ndcg_at_5 | |
| value: 47.632999999999996 | |
| - type: precision_at_1 | |
| value: 40.629 | |
| - type: precision_at_10 | |
| value: 9.700000000000001 | |
| - type: precision_at_100 | |
| value: 1.5970000000000002 | |
| - type: precision_at_1000 | |
| value: 0.202 | |
| - type: precision_at_3 | |
| value: 21.698 | |
| - type: precision_at_5 | |
| value: 15.393 | |
| - type: recall_at_1 | |
| value: 32.978 | |
| - type: recall_at_10 | |
| value: 63.711 | |
| - type: recall_at_100 | |
| value: 88.39399999999999 | |
| - type: recall_at_1000 | |
| value: 97.513 | |
| - type: recall_at_3 | |
| value: 48.025 | |
| - type: recall_at_5 | |
| value: 53.52 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: mteb/cqadupstack-english | |
| name: MTEB CQADupstackEnglishRetrieval | |
| config: default | |
| split: test | |
| revision: ad9991cb51e31e31e430383c75ffb2885547b5f0 | |
| metrics: | |
| - type: map_at_1 | |
| value: 30.767 | |
| - type: map_at_10 | |
| value: 42.195 | |
| - type: map_at_100 | |
| value: 43.541999999999994 | |
| - type: map_at_1000 | |
| value: 43.673 | |
| - type: map_at_3 | |
| value: 38.561 | |
| - type: map_at_5 | |
| value: 40.532000000000004 | |
| - type: mrr_at_1 | |
| value: 38.79 | |
| - type: mrr_at_10 | |
| value: 48.021 | |
| - type: mrr_at_100 | |
| value: 48.735 | |
| - type: mrr_at_1000 | |
| value: 48.776 | |
| - type: mrr_at_3 | |
| value: 45.594 | |
| - type: mrr_at_5 | |
| value: 46.986 | |
| - type: ndcg_at_1 | |
| value: 38.79 | |
| - type: ndcg_at_10 | |
| value: 48.468 | |
| - type: ndcg_at_100 | |
| value: 53.037 | |
| - type: ndcg_at_1000 | |
| value: 55.001999999999995 | |
| - type: ndcg_at_3 | |
| value: 43.409 | |
| - type: ndcg_at_5 | |
| value: 45.654 | |
| - type: precision_at_1 | |
| value: 38.79 | |
| - type: precision_at_10 | |
| value: 9.452 | |
| - type: precision_at_100 | |
| value: 1.518 | |
| - type: precision_at_1000 | |
| value: 0.201 | |
| - type: precision_at_3 | |
| value: 21.21 | |
| - type: precision_at_5 | |
| value: 15.171999999999999 | |
| - type: recall_at_1 | |
| value: 30.767 | |
| - type: recall_at_10 | |
| value: 60.118 | |
| - type: recall_at_100 | |
| value: 79.271 | |
| - type: recall_at_1000 | |
| value: 91.43299999999999 | |
| - type: recall_at_3 | |
| value: 45.36 | |
| - type: recall_at_5 | |
| value: 51.705 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: mteb/cqadupstack-gaming | |
| name: MTEB CQADupstackGamingRetrieval | |
| config: default | |
| split: test | |
| revision: 4885aa143210c98657558c04aaf3dc47cfb54340 | |
| metrics: | |
| - type: map_at_1 | |
| value: 40.007 | |
| - type: map_at_10 | |
| value: 53.529 | |
| - type: map_at_100 | |
| value: 54.602 | |
| - type: map_at_1000 | |
| value: 54.647 | |
| - type: map_at_3 | |
| value: 49.951 | |
| - type: map_at_5 | |
| value: 52.066 | |
| - type: mrr_at_1 | |
| value: 45.705 | |
| - type: mrr_at_10 | |
| value: 56.745000000000005 | |
| - type: mrr_at_100 | |
| value: 57.43899999999999 | |
| - type: mrr_at_1000 | |
| value: 57.462999999999994 | |
| - type: mrr_at_3 | |
| value: 54.25299999999999 | |
| - type: mrr_at_5 | |
| value: 55.842000000000006 | |
| - type: ndcg_at_1 | |
| value: 45.705 | |
| - type: ndcg_at_10 | |
| value: 59.809 | |
| - type: ndcg_at_100 | |
| value: 63.837999999999994 | |
| - type: ndcg_at_1000 | |
| value: 64.729 | |
| - type: ndcg_at_3 | |
| value: 53.994 | |
| - type: ndcg_at_5 | |
| value: 57.028 | |
| - type: precision_at_1 | |
| value: 45.705 | |
| - type: precision_at_10 | |
| value: 9.762 | |
| - type: precision_at_100 | |
| value: 1.275 | |
| - type: precision_at_1000 | |
| value: 0.13899999999999998 | |
| - type: precision_at_3 | |
| value: 24.368000000000002 | |
| - type: precision_at_5 | |
| value: 16.84 | |
| - type: recall_at_1 | |
| value: 40.007 | |
| - type: recall_at_10 | |
| value: 75.017 | |
| - type: recall_at_100 | |
| value: 91.99000000000001 | |
| - type: recall_at_1000 | |
| value: 98.265 | |
| - type: recall_at_3 | |
| value: 59.704 | |
| - type: recall_at_5 | |
| value: 67.109 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: mteb/cqadupstack-gis | |
| name: MTEB CQADupstackGisRetrieval | |
| config: default | |
| split: test | |
| revision: 5003b3064772da1887988e05400cf3806fe491f2 | |
| metrics: | |
| - type: map_at_1 | |
| value: 26.639000000000003 | |
| - type: map_at_10 | |
| value: 35.926 | |
| - type: map_at_100 | |
| value: 37.126999999999995 | |
| - type: map_at_1000 | |
| value: 37.202 | |
| - type: map_at_3 | |
| value: 32.989000000000004 | |
| - type: map_at_5 | |
| value: 34.465 | |
| - type: mrr_at_1 | |
| value: 28.475 | |
| - type: mrr_at_10 | |
| value: 37.7 | |
| - type: mrr_at_100 | |
| value: 38.753 | |
| - type: mrr_at_1000 | |
| value: 38.807 | |
| - type: mrr_at_3 | |
| value: 35.066 | |
| - type: mrr_at_5 | |
| value: 36.512 | |
| - type: ndcg_at_1 | |
| value: 28.475 | |
| - type: ndcg_at_10 | |
| value: 41.245 | |
| - type: ndcg_at_100 | |
| value: 46.814 | |
| - type: ndcg_at_1000 | |
| value: 48.571 | |
| - type: ndcg_at_3 | |
| value: 35.528999999999996 | |
| - type: ndcg_at_5 | |
| value: 38.066 | |
| - type: precision_at_1 | |
| value: 28.475 | |
| - type: precision_at_10 | |
| value: 6.497 | |
| - type: precision_at_100 | |
| value: 0.9650000000000001 | |
| - type: precision_at_1000 | |
| value: 0.11499999999999999 | |
| - type: precision_at_3 | |
| value: 15.065999999999999 | |
| - type: precision_at_5 | |
| value: 10.599 | |
| - type: recall_at_1 | |
| value: 26.639000000000003 | |
| - type: recall_at_10 | |
| value: 55.759 | |
| - type: recall_at_100 | |
| value: 80.913 | |
| - type: recall_at_1000 | |
| value: 93.929 | |
| - type: recall_at_3 | |
| value: 40.454 | |
| - type: recall_at_5 | |
| value: 46.439 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: mteb/cqadupstack-mathematica | |
| name: MTEB CQADupstackMathematicaRetrieval | |
| config: default | |
| split: test | |
| revision: 90fceea13679c63fe563ded68f3b6f06e50061de | |
| metrics: | |
| - type: map_at_1 | |
| value: 15.767999999999999 | |
| - type: map_at_10 | |
| value: 24.811 | |
| - type: map_at_100 | |
| value: 26.064999999999998 | |
| - type: map_at_1000 | |
| value: 26.186999999999998 | |
| - type: map_at_3 | |
| value: 21.736 | |
| - type: map_at_5 | |
| value: 23.283 | |
| - type: mrr_at_1 | |
| value: 19.527 | |
| - type: mrr_at_10 | |
| value: 29.179 | |
| - type: mrr_at_100 | |
| value: 30.153999999999996 | |
| - type: mrr_at_1000 | |
| value: 30.215999999999998 | |
| - type: mrr_at_3 | |
| value: 26.223000000000003 | |
| - type: mrr_at_5 | |
| value: 27.733999999999998 | |
| - type: ndcg_at_1 | |
| value: 19.527 | |
| - type: ndcg_at_10 | |
| value: 30.786 | |
| - type: ndcg_at_100 | |
| value: 36.644 | |
| - type: ndcg_at_1000 | |
| value: 39.440999999999995 | |
| - type: ndcg_at_3 | |
| value: 24.958 | |
| - type: ndcg_at_5 | |
| value: 27.392 | |
| - type: precision_at_1 | |
| value: 19.527 | |
| - type: precision_at_10 | |
| value: 5.995 | |
| - type: precision_at_100 | |
| value: 1.03 | |
| - type: precision_at_1000 | |
| value: 0.14100000000000001 | |
| - type: precision_at_3 | |
| value: 12.520999999999999 | |
| - type: precision_at_5 | |
| value: 9.129 | |
| - type: recall_at_1 | |
| value: 15.767999999999999 | |
| - type: recall_at_10 | |
| value: 44.824000000000005 | |
| - type: recall_at_100 | |
| value: 70.186 | |
| - type: recall_at_1000 | |
| value: 89.934 | |
| - type: recall_at_3 | |
| value: 28.607 | |
| - type: recall_at_5 | |
| value: 34.836 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: mteb/cqadupstack-physics | |
| name: MTEB CQADupstackPhysicsRetrieval | |
| config: default | |
| split: test | |
| revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4 | |
| metrics: | |
| - type: map_at_1 | |
| value: 31.952 | |
| - type: map_at_10 | |
| value: 44.438 | |
| - type: map_at_100 | |
| value: 45.778 | |
| - type: map_at_1000 | |
| value: 45.883 | |
| - type: map_at_3 | |
| value: 41.044000000000004 | |
| - type: map_at_5 | |
| value: 42.986000000000004 | |
| - type: mrr_at_1 | |
| value: 39.172000000000004 | |
| - type: mrr_at_10 | |
| value: 49.76 | |
| - type: mrr_at_100 | |
| value: 50.583999999999996 | |
| - type: mrr_at_1000 | |
| value: 50.621 | |
| - type: mrr_at_3 | |
| value: 47.353 | |
| - type: mrr_at_5 | |
| value: 48.739 | |
| - type: ndcg_at_1 | |
| value: 39.172000000000004 | |
| - type: ndcg_at_10 | |
| value: 50.760000000000005 | |
| - type: ndcg_at_100 | |
| value: 56.084 | |
| - type: ndcg_at_1000 | |
| value: 57.865 | |
| - type: ndcg_at_3 | |
| value: 45.663 | |
| - type: ndcg_at_5 | |
| value: 48.178 | |
| - type: precision_at_1 | |
| value: 39.172000000000004 | |
| - type: precision_at_10 | |
| value: 9.22 | |
| - type: precision_at_100 | |
| value: 1.387 | |
| - type: precision_at_1000 | |
| value: 0.17099999999999999 | |
| - type: precision_at_3 | |
| value: 21.976000000000003 | |
| - type: precision_at_5 | |
| value: 15.457 | |
| - type: recall_at_1 | |
| value: 31.952 | |
| - type: recall_at_10 | |
| value: 63.900999999999996 | |
| - type: recall_at_100 | |
| value: 85.676 | |
| - type: recall_at_1000 | |
| value: 97.03699999999999 | |
| - type: recall_at_3 | |
| value: 49.781 | |
| - type: recall_at_5 | |
| value: 56.330000000000005 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: mteb/cqadupstack-programmers | |
| name: MTEB CQADupstackProgrammersRetrieval | |
| config: default | |
| split: test | |
| revision: 6184bc1440d2dbc7612be22b50686b8826d22b32 | |
| metrics: | |
| - type: map_at_1 | |
| value: 25.332 | |
| - type: map_at_10 | |
| value: 36.874 | |
| - type: map_at_100 | |
| value: 38.340999999999994 | |
| - type: map_at_1000 | |
| value: 38.452 | |
| - type: map_at_3 | |
| value: 33.068 | |
| - type: map_at_5 | |
| value: 35.324 | |
| - type: mrr_at_1 | |
| value: 30.822 | |
| - type: mrr_at_10 | |
| value: 41.641 | |
| - type: mrr_at_100 | |
| value: 42.519 | |
| - type: mrr_at_1000 | |
| value: 42.573 | |
| - type: mrr_at_3 | |
| value: 38.413000000000004 | |
| - type: mrr_at_5 | |
| value: 40.542 | |
| - type: ndcg_at_1 | |
| value: 30.822 | |
| - type: ndcg_at_10 | |
| value: 43.414 | |
| - type: ndcg_at_100 | |
| value: 49.196 | |
| - type: ndcg_at_1000 | |
| value: 51.237 | |
| - type: ndcg_at_3 | |
| value: 37.230000000000004 | |
| - type: ndcg_at_5 | |
| value: 40.405 | |
| - type: precision_at_1 | |
| value: 30.822 | |
| - type: precision_at_10 | |
| value: 8.379 | |
| - type: precision_at_100 | |
| value: 1.315 | |
| - type: precision_at_1000 | |
| value: 0.168 | |
| - type: precision_at_3 | |
| value: 18.417 | |
| - type: precision_at_5 | |
| value: 13.744 | |
| - type: recall_at_1 | |
| value: 25.332 | |
| - type: recall_at_10 | |
| value: 57.774 | |
| - type: recall_at_100 | |
| value: 82.071 | |
| - type: recall_at_1000 | |
| value: 95.60600000000001 | |
| - type: recall_at_3 | |
| value: 40.722 | |
| - type: recall_at_5 | |
| value: 48.754999999999995 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: mteb/cqadupstack | |
| name: MTEB CQADupstackRetrieval | |
| config: default | |
| split: test | |
| revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4 | |
| metrics: | |
| - type: map_at_1 | |
| value: 25.91033333333334 | |
| - type: map_at_10 | |
| value: 36.23225000000001 | |
| - type: map_at_100 | |
| value: 37.55766666666667 | |
| - type: map_at_1000 | |
| value: 37.672583333333336 | |
| - type: map_at_3 | |
| value: 32.95666666666667 | |
| - type: map_at_5 | |
| value: 34.73375 | |
| - type: mrr_at_1 | |
| value: 30.634 | |
| - type: mrr_at_10 | |
| value: 40.19449999999999 | |
| - type: mrr_at_100 | |
| value: 41.099250000000005 | |
| - type: mrr_at_1000 | |
| value: 41.15091666666667 | |
| - type: mrr_at_3 | |
| value: 37.4615 | |
| - type: mrr_at_5 | |
| value: 39.00216666666667 | |
| - type: ndcg_at_1 | |
| value: 30.634 | |
| - type: ndcg_at_10 | |
| value: 42.162166666666664 | |
| - type: ndcg_at_100 | |
| value: 47.60708333333333 | |
| - type: ndcg_at_1000 | |
| value: 49.68616666666666 | |
| - type: ndcg_at_3 | |
| value: 36.60316666666666 | |
| - type: ndcg_at_5 | |
| value: 39.15616666666668 | |
| - type: precision_at_1 | |
| value: 30.634 | |
| - type: precision_at_10 | |
| value: 7.6193333333333335 | |
| - type: precision_at_100 | |
| value: 1.2198333333333333 | |
| - type: precision_at_1000 | |
| value: 0.15975000000000003 | |
| - type: precision_at_3 | |
| value: 17.087 | |
| - type: precision_at_5 | |
| value: 12.298333333333334 | |
| - type: recall_at_1 | |
| value: 25.91033333333334 | |
| - type: recall_at_10 | |
| value: 55.67300000000001 | |
| - type: recall_at_100 | |
| value: 79.20608333333334 | |
| - type: recall_at_1000 | |
| value: 93.34866666666667 | |
| - type: recall_at_3 | |
| value: 40.34858333333333 | |
| - type: recall_at_5 | |
| value: 46.834083333333325 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: mteb/cqadupstack-stats | |
| name: MTEB CQADupstackStatsRetrieval | |
| config: default | |
| split: test | |
| revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a | |
| metrics: | |
| - type: map_at_1 | |
| value: 25.006 | |
| - type: map_at_10 | |
| value: 32.177 | |
| - type: map_at_100 | |
| value: 33.324999999999996 | |
| - type: map_at_1000 | |
| value: 33.419 | |
| - type: map_at_3 | |
| value: 29.952 | |
| - type: map_at_5 | |
| value: 31.095 | |
| - type: mrr_at_1 | |
| value: 28.066999999999997 | |
| - type: mrr_at_10 | |
| value: 34.995 | |
| - type: mrr_at_100 | |
| value: 35.978 | |
| - type: mrr_at_1000 | |
| value: 36.042 | |
| - type: mrr_at_3 | |
| value: 33.103 | |
| - type: mrr_at_5 | |
| value: 34.001 | |
| - type: ndcg_at_1 | |
| value: 28.066999999999997 | |
| - type: ndcg_at_10 | |
| value: 36.481 | |
| - type: ndcg_at_100 | |
| value: 42.022999999999996 | |
| - type: ndcg_at_1000 | |
| value: 44.377 | |
| - type: ndcg_at_3 | |
| value: 32.394 | |
| - type: ndcg_at_5 | |
| value: 34.108 | |
| - type: precision_at_1 | |
| value: 28.066999999999997 | |
| - type: precision_at_10 | |
| value: 5.736 | |
| - type: precision_at_100 | |
| value: 0.9259999999999999 | |
| - type: precision_at_1000 | |
| value: 0.12 | |
| - type: precision_at_3 | |
| value: 13.804 | |
| - type: precision_at_5 | |
| value: 9.508999999999999 | |
| - type: recall_at_1 | |
| value: 25.006 | |
| - type: recall_at_10 | |
| value: 46.972 | |
| - type: recall_at_100 | |
| value: 72.138 | |
| - type: recall_at_1000 | |
| value: 89.479 | |
| - type: recall_at_3 | |
| value: 35.793 | |
| - type: recall_at_5 | |
| value: 39.947 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: mteb/cqadupstack-tex | |
| name: MTEB CQADupstackTexRetrieval | |
| config: default | |
| split: test | |
| revision: 46989137a86843e03a6195de44b09deda022eec7 | |
| metrics: | |
| - type: map_at_1 | |
| value: 16.07 | |
| - type: map_at_10 | |
| value: 24.447 | |
| - type: map_at_100 | |
| value: 25.685999999999996 | |
| - type: map_at_1000 | |
| value: 25.813999999999997 | |
| - type: map_at_3 | |
| value: 21.634 | |
| - type: map_at_5 | |
| value: 23.133 | |
| - type: mrr_at_1 | |
| value: 19.580000000000002 | |
| - type: mrr_at_10 | |
| value: 28.127999999999997 | |
| - type: mrr_at_100 | |
| value: 29.119 | |
| - type: mrr_at_1000 | |
| value: 29.192 | |
| - type: mrr_at_3 | |
| value: 25.509999999999998 | |
| - type: mrr_at_5 | |
| value: 26.878 | |
| - type: ndcg_at_1 | |
| value: 19.580000000000002 | |
| - type: ndcg_at_10 | |
| value: 29.804000000000002 | |
| - type: ndcg_at_100 | |
| value: 35.555 | |
| - type: ndcg_at_1000 | |
| value: 38.421 | |
| - type: ndcg_at_3 | |
| value: 24.654999999999998 | |
| - type: ndcg_at_5 | |
| value: 26.881 | |
| - type: precision_at_1 | |
| value: 19.580000000000002 | |
| - type: precision_at_10 | |
| value: 5.736 | |
| - type: precision_at_100 | |
| value: 1.005 | |
| - type: precision_at_1000 | |
| value: 0.145 | |
| - type: precision_at_3 | |
| value: 12.033000000000001 | |
| - type: precision_at_5 | |
| value: 8.871 | |
| - type: recall_at_1 | |
| value: 16.07 | |
| - type: recall_at_10 | |
| value: 42.364000000000004 | |
| - type: recall_at_100 | |
| value: 68.01899999999999 | |
| - type: recall_at_1000 | |
| value: 88.122 | |
| - type: recall_at_3 | |
| value: 27.846 | |
| - type: recall_at_5 | |
| value: 33.638 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: mteb/cqadupstack-unix | |
| name: MTEB CQADupstackUnixRetrieval | |
| config: default | |
| split: test | |
| revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53 | |
| metrics: | |
| - type: map_at_1 | |
| value: 26.365 | |
| - type: map_at_10 | |
| value: 36.591 | |
| - type: map_at_100 | |
| value: 37.730000000000004 | |
| - type: map_at_1000 | |
| value: 37.84 | |
| - type: map_at_3 | |
| value: 33.403 | |
| - type: map_at_5 | |
| value: 35.272999999999996 | |
| - type: mrr_at_1 | |
| value: 30.503999999999998 | |
| - type: mrr_at_10 | |
| value: 39.940999999999995 | |
| - type: mrr_at_100 | |
| value: 40.818 | |
| - type: mrr_at_1000 | |
| value: 40.876000000000005 | |
| - type: mrr_at_3 | |
| value: 37.065 | |
| - type: mrr_at_5 | |
| value: 38.814 | |
| - type: ndcg_at_1 | |
| value: 30.503999999999998 | |
| - type: ndcg_at_10 | |
| value: 42.185 | |
| - type: ndcg_at_100 | |
| value: 47.416000000000004 | |
| - type: ndcg_at_1000 | |
| value: 49.705 | |
| - type: ndcg_at_3 | |
| value: 36.568 | |
| - type: ndcg_at_5 | |
| value: 39.416000000000004 | |
| - type: precision_at_1 | |
| value: 30.503999999999998 | |
| - type: precision_at_10 | |
| value: 7.276000000000001 | |
| - type: precision_at_100 | |
| value: 1.118 | |
| - type: precision_at_1000 | |
| value: 0.14300000000000002 | |
| - type: precision_at_3 | |
| value: 16.729 | |
| - type: precision_at_5 | |
| value: 12.107999999999999 | |
| - type: recall_at_1 | |
| value: 26.365 | |
| - type: recall_at_10 | |
| value: 55.616 | |
| - type: recall_at_100 | |
| value: 78.129 | |
| - type: recall_at_1000 | |
| value: 93.95599999999999 | |
| - type: recall_at_3 | |
| value: 40.686 | |
| - type: recall_at_5 | |
| value: 47.668 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: mteb/cqadupstack-webmasters | |
| name: MTEB CQADupstackWebmastersRetrieval | |
| config: default | |
| split: test | |
| revision: 160c094312a0e1facb97e55eeddb698c0abe3571 | |
| metrics: | |
| - type: map_at_1 | |
| value: 22.750999999999998 | |
| - type: map_at_10 | |
| value: 33.446 | |
| - type: map_at_100 | |
| value: 35.235 | |
| - type: map_at_1000 | |
| value: 35.478 | |
| - type: map_at_3 | |
| value: 29.358 | |
| - type: map_at_5 | |
| value: 31.525 | |
| - type: mrr_at_1 | |
| value: 27.668 | |
| - type: mrr_at_10 | |
| value: 37.694 | |
| - type: mrr_at_100 | |
| value: 38.732 | |
| - type: mrr_at_1000 | |
| value: 38.779 | |
| - type: mrr_at_3 | |
| value: 34.223 | |
| - type: mrr_at_5 | |
| value: 36.08 | |
| - type: ndcg_at_1 | |
| value: 27.668 | |
| - type: ndcg_at_10 | |
| value: 40.557 | |
| - type: ndcg_at_100 | |
| value: 46.605999999999995 | |
| - type: ndcg_at_1000 | |
| value: 48.917 | |
| - type: ndcg_at_3 | |
| value: 33.677 | |
| - type: ndcg_at_5 | |
| value: 36.85 | |
| - type: precision_at_1 | |
| value: 27.668 | |
| - type: precision_at_10 | |
| value: 8.3 | |
| - type: precision_at_100 | |
| value: 1.6260000000000001 | |
| - type: precision_at_1000 | |
| value: 0.253 | |
| - type: precision_at_3 | |
| value: 16.008 | |
| - type: precision_at_5 | |
| value: 12.292 | |
| - type: recall_at_1 | |
| value: 22.750999999999998 | |
| - type: recall_at_10 | |
| value: 55.643 | |
| - type: recall_at_100 | |
| value: 82.151 | |
| - type: recall_at_1000 | |
| value: 95.963 | |
| - type: recall_at_3 | |
| value: 36.623 | |
| - type: recall_at_5 | |
| value: 44.708 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: mteb/cqadupstack-wordpress | |
| name: MTEB CQADupstackWordpressRetrieval | |
| config: default | |
| split: test | |
| revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4 | |
| metrics: | |
| - type: map_at_1 | |
| value: 17.288999999999998 | |
| - type: map_at_10 | |
| value: 25.903 | |
| - type: map_at_100 | |
| value: 27.071 | |
| - type: map_at_1000 | |
| value: 27.173000000000002 | |
| - type: map_at_3 | |
| value: 22.935 | |
| - type: map_at_5 | |
| value: 24.573 | |
| - type: mrr_at_1 | |
| value: 18.669 | |
| - type: mrr_at_10 | |
| value: 27.682000000000002 | |
| - type: mrr_at_100 | |
| value: 28.691 | |
| - type: mrr_at_1000 | |
| value: 28.761 | |
| - type: mrr_at_3 | |
| value: 24.738 | |
| - type: mrr_at_5 | |
| value: 26.392 | |
| - type: ndcg_at_1 | |
| value: 18.669 | |
| - type: ndcg_at_10 | |
| value: 31.335 | |
| - type: ndcg_at_100 | |
| value: 36.913000000000004 | |
| - type: ndcg_at_1000 | |
| value: 39.300000000000004 | |
| - type: ndcg_at_3 | |
| value: 25.423000000000002 | |
| - type: ndcg_at_5 | |
| value: 28.262999999999998 | |
| - type: precision_at_1 | |
| value: 18.669 | |
| - type: precision_at_10 | |
| value: 5.379 | |
| - type: precision_at_100 | |
| value: 0.876 | |
| - type: precision_at_1000 | |
| value: 0.11900000000000001 | |
| - type: precision_at_3 | |
| value: 11.214 | |
| - type: precision_at_5 | |
| value: 8.466 | |
| - type: recall_at_1 | |
| value: 17.288999999999998 | |
| - type: recall_at_10 | |
| value: 46.377 | |
| - type: recall_at_100 | |
| value: 71.53500000000001 | |
| - type: recall_at_1000 | |
| value: 88.947 | |
| - type: recall_at_3 | |
| value: 30.581999999999997 | |
| - type: recall_at_5 | |
| value: 37.354 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: mteb/climate-fever | |
| name: MTEB ClimateFEVER | |
| config: default | |
| split: test | |
| revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380 | |
| metrics: | |
| - type: map_at_1 | |
| value: 21.795 | |
| - type: map_at_10 | |
| value: 37.614999999999995 | |
| - type: map_at_100 | |
| value: 40.037 | |
| - type: map_at_1000 | |
| value: 40.184999999999995 | |
| - type: map_at_3 | |
| value: 32.221 | |
| - type: map_at_5 | |
| value: 35.154999999999994 | |
| - type: mrr_at_1 | |
| value: 50.358000000000004 | |
| - type: mrr_at_10 | |
| value: 62.129 | |
| - type: mrr_at_100 | |
| value: 62.613 | |
| - type: mrr_at_1000 | |
| value: 62.62 | |
| - type: mrr_at_3 | |
| value: 59.272999999999996 | |
| - type: mrr_at_5 | |
| value: 61.138999999999996 | |
| - type: ndcg_at_1 | |
| value: 50.358000000000004 | |
| - type: ndcg_at_10 | |
| value: 48.362 | |
| - type: ndcg_at_100 | |
| value: 55.932 | |
| - type: ndcg_at_1000 | |
| value: 58.062999999999995 | |
| - type: ndcg_at_3 | |
| value: 42.111 | |
| - type: ndcg_at_5 | |
| value: 44.063 | |
| - type: precision_at_1 | |
| value: 50.358000000000004 | |
| - type: precision_at_10 | |
| value: 14.677999999999999 | |
| - type: precision_at_100 | |
| value: 2.2950000000000004 | |
| - type: precision_at_1000 | |
| value: 0.271 | |
| - type: precision_at_3 | |
| value: 31.77 | |
| - type: precision_at_5 | |
| value: 23.375 | |
| - type: recall_at_1 | |
| value: 21.795 | |
| - type: recall_at_10 | |
| value: 53.846000000000004 | |
| - type: recall_at_100 | |
| value: 78.952 | |
| - type: recall_at_1000 | |
| value: 90.41900000000001 | |
| - type: recall_at_3 | |
| value: 37.257 | |
| - type: recall_at_5 | |
| value: 44.661 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: mteb/dbpedia | |
| name: MTEB DBPedia | |
| config: default | |
| split: test | |
| revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659 | |
| metrics: | |
| - type: map_at_1 | |
| value: 9.728 | |
| - type: map_at_10 | |
| value: 22.691 | |
| - type: map_at_100 | |
| value: 31.734 | |
| - type: map_at_1000 | |
| value: 33.464 | |
| - type: map_at_3 | |
| value: 16.273 | |
| - type: map_at_5 | |
| value: 19.016 | |
| - type: mrr_at_1 | |
| value: 73.25 | |
| - type: mrr_at_10 | |
| value: 80.782 | |
| - type: mrr_at_100 | |
| value: 81.01899999999999 | |
| - type: mrr_at_1000 | |
| value: 81.021 | |
| - type: mrr_at_3 | |
| value: 79.583 | |
| - type: mrr_at_5 | |
| value: 80.146 | |
| - type: ndcg_at_1 | |
| value: 59.62499999999999 | |
| - type: ndcg_at_10 | |
| value: 46.304 | |
| - type: ndcg_at_100 | |
| value: 51.23 | |
| - type: ndcg_at_1000 | |
| value: 58.048 | |
| - type: ndcg_at_3 | |
| value: 51.541000000000004 | |
| - type: ndcg_at_5 | |
| value: 48.635 | |
| - type: precision_at_1 | |
| value: 73.25 | |
| - type: precision_at_10 | |
| value: 36.375 | |
| - type: precision_at_100 | |
| value: 11.53 | |
| - type: precision_at_1000 | |
| value: 2.23 | |
| - type: precision_at_3 | |
| value: 55.583000000000006 | |
| - type: precision_at_5 | |
| value: 47.15 | |
| - type: recall_at_1 | |
| value: 9.728 | |
| - type: recall_at_10 | |
| value: 28.793999999999997 | |
| - type: recall_at_100 | |
| value: 57.885 | |
| - type: recall_at_1000 | |
| value: 78.759 | |
| - type: recall_at_3 | |
| value: 17.79 | |
| - type: recall_at_5 | |
| value: 21.733 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/emotion | |
| name: MTEB EmotionClassification | |
| config: default | |
| split: test | |
| revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 | |
| metrics: | |
| - type: accuracy | |
| value: 46.775 | |
| - type: f1 | |
| value: 41.89794273264891 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: mteb/fever | |
| name: MTEB FEVER | |
| config: default | |
| split: test | |
| revision: bea83ef9e8fb933d90a2f1d5515737465d613e12 | |
| metrics: | |
| - type: map_at_1 | |
| value: 85.378 | |
| - type: map_at_10 | |
| value: 91.51 | |
| - type: map_at_100 | |
| value: 91.666 | |
| - type: map_at_1000 | |
| value: 91.676 | |
| - type: map_at_3 | |
| value: 90.757 | |
| - type: map_at_5 | |
| value: 91.277 | |
| - type: mrr_at_1 | |
| value: 91.839 | |
| - type: mrr_at_10 | |
| value: 95.49 | |
| - type: mrr_at_100 | |
| value: 95.493 | |
| - type: mrr_at_1000 | |
| value: 95.493 | |
| - type: mrr_at_3 | |
| value: 95.345 | |
| - type: mrr_at_5 | |
| value: 95.47200000000001 | |
| - type: ndcg_at_1 | |
| value: 91.839 | |
| - type: ndcg_at_10 | |
| value: 93.806 | |
| - type: ndcg_at_100 | |
| value: 94.255 | |
| - type: ndcg_at_1000 | |
| value: 94.399 | |
| - type: ndcg_at_3 | |
| value: 93.027 | |
| - type: ndcg_at_5 | |
| value: 93.51 | |
| - type: precision_at_1 | |
| value: 91.839 | |
| - type: precision_at_10 | |
| value: 10.93 | |
| - type: precision_at_100 | |
| value: 1.1400000000000001 | |
| - type: precision_at_1000 | |
| value: 0.117 | |
| - type: precision_at_3 | |
| value: 34.873 | |
| - type: precision_at_5 | |
| value: 21.44 | |
| - type: recall_at_1 | |
| value: 85.378 | |
| - type: recall_at_10 | |
| value: 96.814 | |
| - type: recall_at_100 | |
| value: 98.386 | |
| - type: recall_at_1000 | |
| value: 99.21600000000001 | |
| - type: recall_at_3 | |
| value: 94.643 | |
| - type: recall_at_5 | |
| value: 95.976 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: mteb/fiqa | |
| name: MTEB FiQA2018 | |
| config: default | |
| split: test | |
| revision: 27a168819829fe9bcd655c2df245fb19452e8e06 | |
| metrics: | |
| - type: map_at_1 | |
| value: 32.190000000000005 | |
| - type: map_at_10 | |
| value: 53.605000000000004 | |
| - type: map_at_100 | |
| value: 55.550999999999995 | |
| - type: map_at_1000 | |
| value: 55.665 | |
| - type: map_at_3 | |
| value: 46.62 | |
| - type: map_at_5 | |
| value: 50.517999999999994 | |
| - type: mrr_at_1 | |
| value: 60.34 | |
| - type: mrr_at_10 | |
| value: 70.775 | |
| - type: mrr_at_100 | |
| value: 71.238 | |
| - type: mrr_at_1000 | |
| value: 71.244 | |
| - type: mrr_at_3 | |
| value: 68.72399999999999 | |
| - type: mrr_at_5 | |
| value: 69.959 | |
| - type: ndcg_at_1 | |
| value: 60.34 | |
| - type: ndcg_at_10 | |
| value: 63.226000000000006 | |
| - type: ndcg_at_100 | |
| value: 68.60300000000001 | |
| - type: ndcg_at_1000 | |
| value: 69.901 | |
| - type: ndcg_at_3 | |
| value: 58.048 | |
| - type: ndcg_at_5 | |
| value: 59.789 | |
| - type: precision_at_1 | |
| value: 60.34 | |
| - type: precision_at_10 | |
| value: 17.130000000000003 | |
| - type: precision_at_100 | |
| value: 2.29 | |
| - type: precision_at_1000 | |
| value: 0.256 | |
| - type: precision_at_3 | |
| value: 38.323 | |
| - type: precision_at_5 | |
| value: 27.87 | |
| - type: recall_at_1 | |
| value: 32.190000000000005 | |
| - type: recall_at_10 | |
| value: 73.041 | |
| - type: recall_at_100 | |
| value: 91.31 | |
| - type: recall_at_1000 | |
| value: 98.104 | |
| - type: recall_at_3 | |
| value: 53.70399999999999 | |
| - type: recall_at_5 | |
| value: 62.358999999999995 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: mteb/hotpotqa | |
| name: MTEB HotpotQA | |
| config: default | |
| split: test | |
| revision: ab518f4d6fcca38d87c25209f94beba119d02014 | |
| metrics: | |
| - type: map_at_1 | |
| value: 43.511 | |
| - type: map_at_10 | |
| value: 58.15 | |
| - type: map_at_100 | |
| value: 58.95399999999999 | |
| - type: map_at_1000 | |
| value: 59.018 | |
| - type: map_at_3 | |
| value: 55.31700000000001 | |
| - type: map_at_5 | |
| value: 57.04900000000001 | |
| - type: mrr_at_1 | |
| value: 87.022 | |
| - type: mrr_at_10 | |
| value: 91.32000000000001 | |
| - type: mrr_at_100 | |
| value: 91.401 | |
| - type: mrr_at_1000 | |
| value: 91.403 | |
| - type: mrr_at_3 | |
| value: 90.77 | |
| - type: mrr_at_5 | |
| value: 91.156 | |
| - type: ndcg_at_1 | |
| value: 87.022 | |
| - type: ndcg_at_10 | |
| value: 68.183 | |
| - type: ndcg_at_100 | |
| value: 70.781 | |
| - type: ndcg_at_1000 | |
| value: 72.009 | |
| - type: ndcg_at_3 | |
| value: 64.334 | |
| - type: ndcg_at_5 | |
| value: 66.449 | |
| - type: precision_at_1 | |
| value: 87.022 | |
| - type: precision_at_10 | |
| value: 13.406 | |
| - type: precision_at_100 | |
| value: 1.542 | |
| - type: precision_at_1000 | |
| value: 0.17099999999999999 | |
| - type: precision_at_3 | |
| value: 39.023 | |
| - type: precision_at_5 | |
| value: 25.080000000000002 | |
| - type: recall_at_1 | |
| value: 43.511 | |
| - type: recall_at_10 | |
| value: 67.02900000000001 | |
| - type: recall_at_100 | |
| value: 77.11 | |
| - type: recall_at_1000 | |
| value: 85.294 | |
| - type: recall_at_3 | |
| value: 58.535000000000004 | |
| - type: recall_at_5 | |
| value: 62.70099999999999 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/imdb | |
| name: MTEB ImdbClassification | |
| config: default | |
| split: test | |
| revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 | |
| metrics: | |
| - type: accuracy | |
| value: 92.0996 | |
| - type: ap | |
| value: 87.86206089096373 | |
| - type: f1 | |
| value: 92.07554547510763 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: mteb/msmarco | |
| name: MTEB MSMARCO | |
| config: default | |
| split: dev | |
| revision: c5a29a104738b98a9e76336939199e264163d4a0 | |
| metrics: | |
| - type: map_at_1 | |
| value: 23.179 | |
| - type: map_at_10 | |
| value: 35.86 | |
| - type: map_at_100 | |
| value: 37.025999999999996 | |
| - type: map_at_1000 | |
| value: 37.068 | |
| - type: map_at_3 | |
| value: 31.921 | |
| - type: map_at_5 | |
| value: 34.172000000000004 | |
| - type: mrr_at_1 | |
| value: 23.926 | |
| - type: mrr_at_10 | |
| value: 36.525999999999996 | |
| - type: mrr_at_100 | |
| value: 37.627 | |
| - type: mrr_at_1000 | |
| value: 37.665 | |
| - type: mrr_at_3 | |
| value: 32.653 | |
| - type: mrr_at_5 | |
| value: 34.897 | |
| - type: ndcg_at_1 | |
| value: 23.910999999999998 | |
| - type: ndcg_at_10 | |
| value: 42.927 | |
| - type: ndcg_at_100 | |
| value: 48.464 | |
| - type: ndcg_at_1000 | |
| value: 49.533 | |
| - type: ndcg_at_3 | |
| value: 34.910000000000004 | |
| - type: ndcg_at_5 | |
| value: 38.937 | |
| - type: precision_at_1 | |
| value: 23.910999999999998 | |
| - type: precision_at_10 | |
| value: 6.758 | |
| - type: precision_at_100 | |
| value: 0.9520000000000001 | |
| - type: precision_at_1000 | |
| value: 0.104 | |
| - type: precision_at_3 | |
| value: 14.838000000000001 | |
| - type: precision_at_5 | |
| value: 10.934000000000001 | |
| - type: recall_at_1 | |
| value: 23.179 | |
| - type: recall_at_10 | |
| value: 64.622 | |
| - type: recall_at_100 | |
| value: 90.135 | |
| - type: recall_at_1000 | |
| value: 98.301 | |
| - type: recall_at_3 | |
| value: 42.836999999999996 | |
| - type: recall_at_5 | |
| value: 52.512 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/mtop_domain | |
| name: MTEB MTOPDomainClassification (en) | |
| config: en | |
| split: test | |
| revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf | |
| metrics: | |
| - type: accuracy | |
| value: 96.59598723210215 | |
| - type: f1 | |
| value: 96.41913500001952 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/mtop_intent | |
| name: MTEB MTOPIntentClassification (en) | |
| config: en | |
| split: test | |
| revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba | |
| metrics: | |
| - type: accuracy | |
| value: 82.89557683538533 | |
| - type: f1 | |
| value: 63.379319722356264 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/amazon_massive_intent | |
| name: MTEB MassiveIntentClassification (en) | |
| config: en | |
| split: test | |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 | |
| metrics: | |
| - type: accuracy | |
| value: 78.93745796906524 | |
| - type: f1 | |
| value: 75.71616541785902 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/amazon_massive_scenario | |
| name: MTEB MassiveScenarioClassification (en) | |
| config: en | |
| split: test | |
| revision: 7d571f92784cd94a019292a1f45445077d0ef634 | |
| metrics: | |
| - type: accuracy | |
| value: 81.41223940820443 | |
| - type: f1 | |
| value: 81.2877893719078 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/medrxiv-clustering-p2p | |
| name: MTEB MedrxivClusteringP2P | |
| config: default | |
| split: test | |
| revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 | |
| metrics: | |
| - type: v_measure | |
| value: 35.03682528325662 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/medrxiv-clustering-s2s | |
| name: MTEB MedrxivClusteringS2S | |
| config: default | |
| split: test | |
| revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 | |
| metrics: | |
| - type: v_measure | |
| value: 32.942529406124 | |
| - task: | |
| type: Reranking | |
| dataset: | |
| type: mteb/mind_small | |
| name: MTEB MindSmallReranking | |
| config: default | |
| split: test | |
| revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 | |
| metrics: | |
| - type: map | |
| value: 31.459949660460317 | |
| - type: mrr | |
| value: 32.70509582031616 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: mteb/nfcorpus | |
| name: MTEB NFCorpus | |
| config: default | |
| split: test | |
| revision: ec0fa4fe99da2ff19ca1214b7966684033a58814 | |
| metrics: | |
| - type: map_at_1 | |
| value: 6.497 | |
| - type: map_at_10 | |
| value: 13.843 | |
| - type: map_at_100 | |
| value: 17.713 | |
| - type: map_at_1000 | |
| value: 19.241 | |
| - type: map_at_3 | |
| value: 10.096 | |
| - type: map_at_5 | |
| value: 11.85 | |
| - type: mrr_at_1 | |
| value: 48.916 | |
| - type: mrr_at_10 | |
| value: 57.764 | |
| - type: mrr_at_100 | |
| value: 58.251 | |
| - type: mrr_at_1000 | |
| value: 58.282999999999994 | |
| - type: mrr_at_3 | |
| value: 55.623999999999995 | |
| - type: mrr_at_5 | |
| value: 57.018 | |
| - type: ndcg_at_1 | |
| value: 46.594 | |
| - type: ndcg_at_10 | |
| value: 36.945 | |
| - type: ndcg_at_100 | |
| value: 34.06 | |
| - type: ndcg_at_1000 | |
| value: 43.05 | |
| - type: ndcg_at_3 | |
| value: 41.738 | |
| - type: ndcg_at_5 | |
| value: 39.330999999999996 | |
| - type: precision_at_1 | |
| value: 48.916 | |
| - type: precision_at_10 | |
| value: 27.43 | |
| - type: precision_at_100 | |
| value: 8.616 | |
| - type: precision_at_1000 | |
| value: 2.155 | |
| - type: precision_at_3 | |
| value: 39.112 | |
| - type: precision_at_5 | |
| value: 33.808 | |
| - type: recall_at_1 | |
| value: 6.497 | |
| - type: recall_at_10 | |
| value: 18.163 | |
| - type: recall_at_100 | |
| value: 34.566 | |
| - type: recall_at_1000 | |
| value: 67.15 | |
| - type: recall_at_3 | |
| value: 11.100999999999999 | |
| - type: recall_at_5 | |
| value: 14.205000000000002 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: mteb/nq | |
| name: MTEB NQ | |
| config: default | |
| split: test | |
| revision: b774495ed302d8c44a3a7ea25c90dbce03968f31 | |
| metrics: | |
| - type: map_at_1 | |
| value: 31.916 | |
| - type: map_at_10 | |
| value: 48.123 | |
| - type: map_at_100 | |
| value: 49.103 | |
| - type: map_at_1000 | |
| value: 49.131 | |
| - type: map_at_3 | |
| value: 43.711 | |
| - type: map_at_5 | |
| value: 46.323 | |
| - type: mrr_at_1 | |
| value: 36.181999999999995 | |
| - type: mrr_at_10 | |
| value: 50.617999999999995 | |
| - type: mrr_at_100 | |
| value: 51.329 | |
| - type: mrr_at_1000 | |
| value: 51.348000000000006 | |
| - type: mrr_at_3 | |
| value: 47.010999999999996 | |
| - type: mrr_at_5 | |
| value: 49.175000000000004 | |
| - type: ndcg_at_1 | |
| value: 36.181999999999995 | |
| - type: ndcg_at_10 | |
| value: 56.077999999999996 | |
| - type: ndcg_at_100 | |
| value: 60.037 | |
| - type: ndcg_at_1000 | |
| value: 60.63499999999999 | |
| - type: ndcg_at_3 | |
| value: 47.859 | |
| - type: ndcg_at_5 | |
| value: 52.178999999999995 | |
| - type: precision_at_1 | |
| value: 36.181999999999995 | |
| - type: precision_at_10 | |
| value: 9.284 | |
| - type: precision_at_100 | |
| value: 1.149 | |
| - type: precision_at_1000 | |
| value: 0.121 | |
| - type: precision_at_3 | |
| value: 22.006999999999998 | |
| - type: precision_at_5 | |
| value: 15.695 | |
| - type: recall_at_1 | |
| value: 31.916 | |
| - type: recall_at_10 | |
| value: 77.771 | |
| - type: recall_at_100 | |
| value: 94.602 | |
| - type: recall_at_1000 | |
| value: 98.967 | |
| - type: recall_at_3 | |
| value: 56.528 | |
| - type: recall_at_5 | |
| value: 66.527 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: mteb/quora | |
| name: MTEB QuoraRetrieval | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 71.486 | |
| - type: map_at_10 | |
| value: 85.978 | |
| - type: map_at_100 | |
| value: 86.587 | |
| - type: map_at_1000 | |
| value: 86.598 | |
| - type: map_at_3 | |
| value: 83.04899999999999 | |
| - type: map_at_5 | |
| value: 84.857 | |
| - type: mrr_at_1 | |
| value: 82.32000000000001 | |
| - type: mrr_at_10 | |
| value: 88.64 | |
| - type: mrr_at_100 | |
| value: 88.702 | |
| - type: mrr_at_1000 | |
| value: 88.702 | |
| - type: mrr_at_3 | |
| value: 87.735 | |
| - type: mrr_at_5 | |
| value: 88.36 | |
| - type: ndcg_at_1 | |
| value: 82.34 | |
| - type: ndcg_at_10 | |
| value: 89.67 | |
| - type: ndcg_at_100 | |
| value: 90.642 | |
| - type: ndcg_at_1000 | |
| value: 90.688 | |
| - type: ndcg_at_3 | |
| value: 86.932 | |
| - type: ndcg_at_5 | |
| value: 88.408 | |
| - type: precision_at_1 | |
| value: 82.34 | |
| - type: precision_at_10 | |
| value: 13.675999999999998 | |
| - type: precision_at_100 | |
| value: 1.544 | |
| - type: precision_at_1000 | |
| value: 0.157 | |
| - type: precision_at_3 | |
| value: 38.24 | |
| - type: precision_at_5 | |
| value: 25.068 | |
| - type: recall_at_1 | |
| value: 71.486 | |
| - type: recall_at_10 | |
| value: 96.844 | |
| - type: recall_at_100 | |
| value: 99.843 | |
| - type: recall_at_1000 | |
| value: 99.996 | |
| - type: recall_at_3 | |
| value: 88.92099999999999 | |
| - type: recall_at_5 | |
| value: 93.215 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/reddit-clustering | |
| name: MTEB RedditClustering | |
| config: default | |
| split: test | |
| revision: 24640382cdbf8abc73003fb0fa6d111a705499eb | |
| metrics: | |
| - type: v_measure | |
| value: 59.75758437908334 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/reddit-clustering-p2p | |
| name: MTEB RedditClusteringP2P | |
| config: default | |
| split: test | |
| revision: 282350215ef01743dc01b456c7f5241fa8937f16 | |
| metrics: | |
| - type: v_measure | |
| value: 68.03497914092789 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: mteb/scidocs | |
| name: MTEB SCIDOCS | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 5.808 | |
| - type: map_at_10 | |
| value: 16.059 | |
| - type: map_at_100 | |
| value: 19.048000000000002 | |
| - type: map_at_1000 | |
| value: 19.43 | |
| - type: map_at_3 | |
| value: 10.953 | |
| - type: map_at_5 | |
| value: 13.363 | |
| - type: mrr_at_1 | |
| value: 28.7 | |
| - type: mrr_at_10 | |
| value: 42.436 | |
| - type: mrr_at_100 | |
| value: 43.599 | |
| - type: mrr_at_1000 | |
| value: 43.62 | |
| - type: mrr_at_3 | |
| value: 38.45 | |
| - type: mrr_at_5 | |
| value: 40.89 | |
| - type: ndcg_at_1 | |
| value: 28.7 | |
| - type: ndcg_at_10 | |
| value: 26.346000000000004 | |
| - type: ndcg_at_100 | |
| value: 36.758 | |
| - type: ndcg_at_1000 | |
| value: 42.113 | |
| - type: ndcg_at_3 | |
| value: 24.254 | |
| - type: ndcg_at_5 | |
| value: 21.506 | |
| - type: precision_at_1 | |
| value: 28.7 | |
| - type: precision_at_10 | |
| value: 13.969999999999999 | |
| - type: precision_at_100 | |
| value: 2.881 | |
| - type: precision_at_1000 | |
| value: 0.414 | |
| - type: precision_at_3 | |
| value: 22.933 | |
| - type: precision_at_5 | |
| value: 19.220000000000002 | |
| - type: recall_at_1 | |
| value: 5.808 | |
| - type: recall_at_10 | |
| value: 28.310000000000002 | |
| - type: recall_at_100 | |
| value: 58.475 | |
| - type: recall_at_1000 | |
| value: 84.072 | |
| - type: recall_at_3 | |
| value: 13.957 | |
| - type: recall_at_5 | |
| value: 19.515 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/sickr-sts | |
| name: MTEB SICK-R | |
| config: default | |
| split: test | |
| revision: a6ea5a8cab320b040a23452cc28066d9beae2cee | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 82.39274129958557 | |
| - type: cos_sim_spearman | |
| value: 79.78021235170053 | |
| - type: euclidean_pearson | |
| value: 79.35335401300166 | |
| - type: euclidean_spearman | |
| value: 79.7271870968275 | |
| - type: manhattan_pearson | |
| value: 79.35256263340601 | |
| - type: manhattan_spearman | |
| value: 79.76036386976321 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/sts12-sts | |
| name: MTEB STS12 | |
| config: default | |
| split: test | |
| revision: a0d554a64d88156834ff5ae9920b964011b16384 | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 83.99130429246708 | |
| - type: cos_sim_spearman | |
| value: 73.88322811171203 | |
| - type: euclidean_pearson | |
| value: 80.7569419170376 | |
| - type: euclidean_spearman | |
| value: 73.82542155409597 | |
| - type: manhattan_pearson | |
| value: 80.79468183847625 | |
| - type: manhattan_spearman | |
| value: 73.87027144047784 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/sts13-sts | |
| name: MTEB STS13 | |
| config: default | |
| split: test | |
| revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 84.88548789489907 | |
| - type: cos_sim_spearman | |
| value: 85.07535893847255 | |
| - type: euclidean_pearson | |
| value: 84.6637222061494 | |
| - type: euclidean_spearman | |
| value: 85.14200626702456 | |
| - type: manhattan_pearson | |
| value: 84.75327892344734 | |
| - type: manhattan_spearman | |
| value: 85.24406181838596 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/sts14-sts | |
| name: MTEB STS14 | |
| config: default | |
| split: test | |
| revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 82.88140039325008 | |
| - type: cos_sim_spearman | |
| value: 79.61211268112362 | |
| - type: euclidean_pearson | |
| value: 81.29639728816458 | |
| - type: euclidean_spearman | |
| value: 79.51284578041442 | |
| - type: manhattan_pearson | |
| value: 81.3381797137111 | |
| - type: manhattan_spearman | |
| value: 79.55683684039808 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/sts15-sts | |
| name: MTEB STS15 | |
| config: default | |
| split: test | |
| revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 85.16716737270485 | |
| - type: cos_sim_spearman | |
| value: 86.14823841857738 | |
| - type: euclidean_pearson | |
| value: 85.36325733440725 | |
| - type: euclidean_spearman | |
| value: 86.04919691402029 | |
| - type: manhattan_pearson | |
| value: 85.3147511385052 | |
| - type: manhattan_spearman | |
| value: 86.00676205857764 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/sts16-sts | |
| name: MTEB STS16 | |
| config: default | |
| split: test | |
| revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 80.34266645861588 | |
| - type: cos_sim_spearman | |
| value: 81.59914035005882 | |
| - type: euclidean_pearson | |
| value: 81.15053076245988 | |
| - type: euclidean_spearman | |
| value: 81.52776915798489 | |
| - type: manhattan_pearson | |
| value: 81.1819647418673 | |
| - type: manhattan_spearman | |
| value: 81.57479527353556 | |
| - 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: 89.38263326821439 | |
| - type: cos_sim_spearman | |
| value: 89.10946308202642 | |
| - type: euclidean_pearson | |
| value: 88.87831312540068 | |
| - type: euclidean_spearman | |
| value: 89.03615865973664 | |
| - type: manhattan_pearson | |
| value: 88.79835539970384 | |
| - type: manhattan_spearman | |
| value: 88.9766156339753 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/sts22-crosslingual-sts | |
| name: MTEB STS22 (en) | |
| config: en | |
| split: test | |
| revision: eea2b4fe26a775864c896887d910b76a8098ad3f | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 70.1574915581685 | |
| - type: cos_sim_spearman | |
| value: 70.59144980004054 | |
| - type: euclidean_pearson | |
| value: 71.43246306918755 | |
| - type: euclidean_spearman | |
| value: 70.5544189562984 | |
| - type: manhattan_pearson | |
| value: 71.4071414609503 | |
| - type: manhattan_spearman | |
| value: 70.31799126163712 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/stsbenchmark-sts | |
| name: MTEB STSBenchmark | |
| config: default | |
| split: test | |
| revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 83.36215796635351 | |
| - type: cos_sim_spearman | |
| value: 83.07276756467208 | |
| - type: euclidean_pearson | |
| value: 83.06690453635584 | |
| - type: euclidean_spearman | |
| value: 82.9635366303289 | |
| - type: manhattan_pearson | |
| value: 83.04994049700815 | |
| - type: manhattan_spearman | |
| value: 82.98120125356036 | |
| - task: | |
| type: Reranking | |
| dataset: | |
| type: mteb/scidocs-reranking | |
| name: MTEB SciDocsRR | |
| config: default | |
| split: test | |
| revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab | |
| metrics: | |
| - type: map | |
| value: 86.92530011616722 | |
| - type: mrr | |
| value: 96.21826793395421 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: mteb/scifact | |
| name: MTEB SciFact | |
| config: default | |
| split: test | |
| revision: 0228b52cf27578f30900b9e5271d331663a030d7 | |
| metrics: | |
| - type: map_at_1 | |
| value: 65.75 | |
| - type: map_at_10 | |
| value: 77.701 | |
| - type: map_at_100 | |
| value: 78.005 | |
| - type: map_at_1000 | |
| value: 78.006 | |
| - type: map_at_3 | |
| value: 75.48 | |
| - type: map_at_5 | |
| value: 76.927 | |
| - type: mrr_at_1 | |
| value: 68.333 | |
| - type: mrr_at_10 | |
| value: 78.511 | |
| - type: mrr_at_100 | |
| value: 78.704 | |
| - type: mrr_at_1000 | |
| value: 78.704 | |
| - type: mrr_at_3 | |
| value: 77 | |
| - type: mrr_at_5 | |
| value: 78.083 | |
| - type: ndcg_at_1 | |
| value: 68.333 | |
| - type: ndcg_at_10 | |
| value: 82.42699999999999 | |
| - type: ndcg_at_100 | |
| value: 83.486 | |
| - type: ndcg_at_1000 | |
| value: 83.511 | |
| - type: ndcg_at_3 | |
| value: 78.96300000000001 | |
| - type: ndcg_at_5 | |
| value: 81.028 | |
| - type: precision_at_1 | |
| value: 68.333 | |
| - type: precision_at_10 | |
| value: 10.667 | |
| - type: precision_at_100 | |
| value: 1.127 | |
| - type: precision_at_1000 | |
| value: 0.11299999999999999 | |
| - type: precision_at_3 | |
| value: 31.333 | |
| - type: precision_at_5 | |
| value: 20.133000000000003 | |
| - type: recall_at_1 | |
| value: 65.75 | |
| - type: recall_at_10 | |
| value: 95.578 | |
| - type: recall_at_100 | |
| value: 99.833 | |
| - type: recall_at_1000 | |
| value: 100 | |
| - type: recall_at_3 | |
| value: 86.506 | |
| - type: recall_at_5 | |
| value: 91.75 | |
| - task: | |
| type: PairClassification | |
| dataset: | |
| type: mteb/sprintduplicatequestions-pairclassification | |
| name: MTEB SprintDuplicateQuestions | |
| config: default | |
| split: test | |
| revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 | |
| metrics: | |
| - type: cos_sim_accuracy | |
| value: 99.75247524752476 | |
| - type: cos_sim_ap | |
| value: 94.16065078045173 | |
| - type: cos_sim_f1 | |
| value: 87.22986247544205 | |
| - type: cos_sim_precision | |
| value: 85.71428571428571 | |
| - type: cos_sim_recall | |
| value: 88.8 | |
| - type: dot_accuracy | |
| value: 99.74554455445545 | |
| - type: dot_ap | |
| value: 93.90633887037264 | |
| - type: dot_f1 | |
| value: 86.9873417721519 | |
| - type: dot_precision | |
| value: 88.1025641025641 | |
| - type: dot_recall | |
| value: 85.9 | |
| - type: euclidean_accuracy | |
| value: 99.75247524752476 | |
| - type: euclidean_ap | |
| value: 94.17466319018055 | |
| - type: euclidean_f1 | |
| value: 87.3405299313052 | |
| - type: euclidean_precision | |
| value: 85.74181117533719 | |
| - type: euclidean_recall | |
| value: 89 | |
| - type: manhattan_accuracy | |
| value: 99.75445544554455 | |
| - type: manhattan_ap | |
| value: 94.27688371923577 | |
| - type: manhattan_f1 | |
| value: 87.74002954209749 | |
| - type: manhattan_precision | |
| value: 86.42095053346266 | |
| - type: manhattan_recall | |
| value: 89.1 | |
| - type: max_accuracy | |
| value: 99.75445544554455 | |
| - type: max_ap | |
| value: 94.27688371923577 | |
| - type: max_f1 | |
| value: 87.74002954209749 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/stackexchange-clustering | |
| name: MTEB StackExchangeClustering | |
| config: default | |
| split: test | |
| revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 | |
| metrics: | |
| - type: v_measure | |
| value: 71.26500637517056 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/stackexchange-clustering-p2p | |
| name: MTEB StackExchangeClusteringP2P | |
| config: default | |
| split: test | |
| revision: 815ca46b2622cec33ccafc3735d572c266efdb44 | |
| metrics: | |
| - type: v_measure | |
| value: 39.17507906280528 | |
| - task: | |
| type: Reranking | |
| dataset: | |
| type: mteb/stackoverflowdupquestions-reranking | |
| name: MTEB StackOverflowDupQuestions | |
| config: default | |
| split: test | |
| revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 | |
| metrics: | |
| - type: map | |
| value: 52.4848744828509 | |
| - type: mrr | |
| value: 53.33678168236992 | |
| - task: | |
| type: Summarization | |
| dataset: | |
| type: mteb/summeval | |
| name: MTEB SummEval | |
| config: default | |
| split: test | |
| revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 30.599864323827887 | |
| - type: cos_sim_spearman | |
| value: 30.91116204665598 | |
| - type: dot_pearson | |
| value: 30.82637894269936 | |
| - type: dot_spearman | |
| value: 30.957573868416066 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: mteb/trec-covid | |
| name: MTEB TRECCOVID | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 0.23600000000000002 | |
| - type: map_at_10 | |
| value: 1.892 | |
| - type: map_at_100 | |
| value: 11.586 | |
| - type: map_at_1000 | |
| value: 27.761999999999997 | |
| - type: map_at_3 | |
| value: 0.653 | |
| - type: map_at_5 | |
| value: 1.028 | |
| - type: mrr_at_1 | |
| value: 88 | |
| - type: mrr_at_10 | |
| value: 94 | |
| - type: mrr_at_100 | |
| value: 94 | |
| - type: mrr_at_1000 | |
| value: 94 | |
| - type: mrr_at_3 | |
| value: 94 | |
| - type: mrr_at_5 | |
| value: 94 | |
| - type: ndcg_at_1 | |
| value: 82 | |
| - type: ndcg_at_10 | |
| value: 77.48899999999999 | |
| - type: ndcg_at_100 | |
| value: 60.141 | |
| - type: ndcg_at_1000 | |
| value: 54.228 | |
| - type: ndcg_at_3 | |
| value: 82.358 | |
| - type: ndcg_at_5 | |
| value: 80.449 | |
| - type: precision_at_1 | |
| value: 88 | |
| - type: precision_at_10 | |
| value: 82.19999999999999 | |
| - type: precision_at_100 | |
| value: 61.760000000000005 | |
| - type: precision_at_1000 | |
| value: 23.684 | |
| - type: precision_at_3 | |
| value: 88 | |
| - type: precision_at_5 | |
| value: 85.6 | |
| - type: recall_at_1 | |
| value: 0.23600000000000002 | |
| - type: recall_at_10 | |
| value: 2.117 | |
| - type: recall_at_100 | |
| value: 14.985000000000001 | |
| - type: recall_at_1000 | |
| value: 51.107 | |
| - type: recall_at_3 | |
| value: 0.688 | |
| - type: recall_at_5 | |
| value: 1.1039999999999999 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: mteb/touche2020 | |
| name: MTEB Touche2020 | |
| config: default | |
| split: test | |
| revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f | |
| metrics: | |
| - type: map_at_1 | |
| value: 2.3040000000000003 | |
| - type: map_at_10 | |
| value: 9.025 | |
| - type: map_at_100 | |
| value: 15.312999999999999 | |
| - type: map_at_1000 | |
| value: 16.954 | |
| - type: map_at_3 | |
| value: 4.981 | |
| - type: map_at_5 | |
| value: 6.32 | |
| - type: mrr_at_1 | |
| value: 24.490000000000002 | |
| - type: mrr_at_10 | |
| value: 39.835 | |
| - type: mrr_at_100 | |
| value: 40.8 | |
| - type: mrr_at_1000 | |
| value: 40.8 | |
| - type: mrr_at_3 | |
| value: 35.034 | |
| - type: mrr_at_5 | |
| value: 37.687 | |
| - type: ndcg_at_1 | |
| value: 22.448999999999998 | |
| - type: ndcg_at_10 | |
| value: 22.545 | |
| - type: ndcg_at_100 | |
| value: 35.931999999999995 | |
| - type: ndcg_at_1000 | |
| value: 47.665 | |
| - type: ndcg_at_3 | |
| value: 23.311 | |
| - type: ndcg_at_5 | |
| value: 22.421 | |
| - type: precision_at_1 | |
| value: 24.490000000000002 | |
| - type: precision_at_10 | |
| value: 20.408 | |
| - type: precision_at_100 | |
| value: 7.815999999999999 | |
| - type: precision_at_1000 | |
| value: 1.553 | |
| - type: precision_at_3 | |
| value: 25.169999999999998 | |
| - type: precision_at_5 | |
| value: 23.265 | |
| - type: recall_at_1 | |
| value: 2.3040000000000003 | |
| - type: recall_at_10 | |
| value: 15.693999999999999 | |
| - type: recall_at_100 | |
| value: 48.917 | |
| - type: recall_at_1000 | |
| value: 84.964 | |
| - type: recall_at_3 | |
| value: 6.026 | |
| - type: recall_at_5 | |
| value: 9.066 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/toxic_conversations_50k | |
| name: MTEB ToxicConversationsClassification | |
| config: default | |
| split: test | |
| revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c | |
| metrics: | |
| - type: accuracy | |
| value: 82.6074 | |
| - type: ap | |
| value: 23.187467098602013 | |
| - type: f1 | |
| value: 65.36829506379657 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/tweet_sentiment_extraction | |
| name: MTEB TweetSentimentExtractionClassification | |
| config: default | |
| split: test | |
| revision: d604517c81ca91fe16a244d1248fc021f9ecee7a | |
| metrics: | |
| - type: accuracy | |
| value: 63.16355404640635 | |
| - type: f1 | |
| value: 63.534725639863346 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/twentynewsgroups-clustering | |
| name: MTEB TwentyNewsgroupsClustering | |
| config: default | |
| split: test | |
| revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 | |
| metrics: | |
| - type: v_measure | |
| value: 50.91004094411276 | |
| - task: | |
| type: PairClassification | |
| dataset: | |
| type: mteb/twittersemeval2015-pairclassification | |
| name: MTEB TwitterSemEval2015 | |
| config: default | |
| split: test | |
| revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 | |
| metrics: | |
| - type: cos_sim_accuracy | |
| value: 86.55301901412649 | |
| - type: cos_sim_ap | |
| value: 75.25312618556728 | |
| - type: cos_sim_f1 | |
| value: 68.76561719140429 | |
| - type: cos_sim_precision | |
| value: 65.3061224489796 | |
| - type: cos_sim_recall | |
| value: 72.61213720316623 | |
| - type: dot_accuracy | |
| value: 86.29671574178936 | |
| - type: dot_ap | |
| value: 75.11910195501207 | |
| - type: dot_f1 | |
| value: 68.44048376830045 | |
| - type: dot_precision | |
| value: 66.12546125461255 | |
| - type: dot_recall | |
| value: 70.92348284960423 | |
| - type: euclidean_accuracy | |
| value: 86.5828217202122 | |
| - type: euclidean_ap | |
| value: 75.22986344900924 | |
| - type: euclidean_f1 | |
| value: 68.81267797449549 | |
| - type: euclidean_precision | |
| value: 64.8238861674831 | |
| - type: euclidean_recall | |
| value: 73.3245382585752 | |
| - type: manhattan_accuracy | |
| value: 86.61262442629791 | |
| - type: manhattan_ap | |
| value: 75.24401608557328 | |
| - type: manhattan_f1 | |
| value: 68.80473982483257 | |
| - type: manhattan_precision | |
| value: 67.21187720181177 | |
| - type: manhattan_recall | |
| value: 70.47493403693932 | |
| - type: max_accuracy | |
| value: 86.61262442629791 | |
| - type: max_ap | |
| value: 75.25312618556728 | |
| - type: max_f1 | |
| value: 68.81267797449549 | |
| - task: | |
| type: PairClassification | |
| dataset: | |
| type: mteb/twitterurlcorpus-pairclassification | |
| name: MTEB TwitterURLCorpus | |
| config: default | |
| split: test | |
| revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf | |
| metrics: | |
| - type: cos_sim_accuracy | |
| value: 88.10688089416696 | |
| - type: cos_sim_ap | |
| value: 84.17862178779863 | |
| - type: cos_sim_f1 | |
| value: 76.17305208781748 | |
| - type: cos_sim_precision | |
| value: 71.31246641590543 | |
| - type: cos_sim_recall | |
| value: 81.74468740375731 | |
| - type: dot_accuracy | |
| value: 88.1844995536927 | |
| - type: dot_ap | |
| value: 84.33816725235876 | |
| - type: dot_f1 | |
| value: 76.43554032918746 | |
| - type: dot_precision | |
| value: 74.01557767200346 | |
| - type: dot_recall | |
| value: 79.0190945488143 | |
| - type: euclidean_accuracy | |
| value: 88.07001203089223 | |
| - type: euclidean_ap | |
| value: 84.12267000814985 | |
| - type: euclidean_f1 | |
| value: 76.12232600180778 | |
| - type: euclidean_precision | |
| value: 74.50604541433205 | |
| - type: euclidean_recall | |
| value: 77.81028641823221 | |
| - type: manhattan_accuracy | |
| value: 88.06419063142779 | |
| - type: manhattan_ap | |
| value: 84.11648917164187 | |
| - type: manhattan_f1 | |
| value: 76.20579953925474 | |
| - type: manhattan_precision | |
| value: 72.56772755762935 | |
| - type: manhattan_recall | |
| value: 80.22790267939637 | |
| - type: max_accuracy | |
| value: 88.1844995536927 | |
| - type: max_ap | |
| value: 84.33816725235876 | |
| - type: max_f1 | |
| value: 76.43554032918746 | |
| <!-- **English** | [中文](./README_zh.md) --> | |
| # gte-large-en-v1.5 | |
| We introduce `gte-v1.5` series, upgraded `gte` embeddings that support the context length of up to **8192**, while further enhancing model performance. | |
| The models are built upon the `transformer++` encoder [backbone](https://huggingface.co/Alibaba-NLP/new-impl) (BERT + RoPE + GLU). | |
| The `gte-v1.5` series achieve state-of-the-art scores on the MTEB benchmark within the same model size category and prodvide competitive on the LoCo long-context retrieval tests (refer to [Evaluation](#evaluation)). | |
| We also present the [`gte-Qwen1.5-7B-instruct`](https://huggingface.co/Alibaba-NLP/gte-Qwen1.5-7B-instruct), | |
| a SOTA instruction-tuned multi-lingual embedding model that ranked 2nd in MTEB and 1st in C-MTEB. | |
| <!-- Provide a longer summary of what this model is. --> | |
| - **Developed by:** Institute for Intelligent Computing, Alibaba Group | |
| - **Model type:** Text Embeddings | |
| - **Paper:** Coming soon. | |
| <!-- - **Demo [optional]:** [More Information Needed] --> | |
| ### Model list | |
| | Models | Language | Model Size | Max Seq. Length | Dimension | MTEB-en | LoCo | | |
| |:-----: | :-----: |:-----: |:-----: |:-----: | :-----: | :-----: | | |
| |[`gte-Qwen1.5-7B-instruct`](https://huggingface.co/Alibaba-NLP/gte-Qwen1.5-7B-instruct)| Multiple | 7720 | 32768 | 4096 | 67.34 | 87.57 | | |
| |[`gte-large-en-v1.5`](https://huggingface.co/Alibaba-NLP/gte-large-en-v1.5) | English | 434 | 8192 | 1024 | 65.39 | 86.71 | | |
| |[`gte-base-en-v1.5`](https://huggingface.co/Alibaba-NLP/gte-base-en-v1.5) | English | 137 | 8192 | 768 | 64.11 | 87.44 | | |
| ## How to Get Started with the Model | |
| Use the code below to get started with the model. | |
| ```python | |
| # Requires transformers>=4.36.0 | |
| import torch.nn.functional as F | |
| from transformers import AutoModel, AutoTokenizer | |
| input_texts = [ | |
| "what is the capital of China?", | |
| "how to implement quick sort in python?", | |
| "Beijing", | |
| "sorting algorithms" | |
| ] | |
| model_path = 'Alibaba-NLP/gte-large-en-v1.5' | |
| tokenizer = AutoTokenizer.from_pretrained(model_path) | |
| model = AutoModel.from_pretrained(model_path, trust_remote_code=True) | |
| # Tokenize the input texts | |
| batch_dict = tokenizer(input_texts, max_length=8192, padding=True, truncation=True, return_tensors='pt') | |
| outputs = model(**batch_dict) | |
| embeddings = outputs.last_hidden_state[:, 0] | |
| # (Optionally) normalize embeddings | |
| embeddings = F.normalize(embeddings, p=2, dim=1) | |
| scores = (embeddings[:1] @ embeddings[1:].T) * 100 | |
| print(scores.tolist()) | |
| ``` | |
| **It is recommended to install xformers and enable unpadding for acceleration, refer to [enable-unpadding-and-xformers](https://huggingface.co/Alibaba-NLP/new-impl#recommendation-enable-unpadding-and-acceleration-with-xformers).** | |
| Use with sentence-transformers: | |
| ```python | |
| # Requires sentence_transformers>=2.7.0 | |
| 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('Alibaba-NLP/gte-large-en-v1.5', trust_remote_code=True) | |
| embeddings = model.encode(sentences) | |
| print(cos_sim(embeddings[0], embeddings[1])) | |
| ``` | |
| Use with `transformers.js`: | |
| ```js | |
| // npm i @xenova/transformers | |
| import { pipeline, dot } from '@xenova/transformers'; | |
| // Create feature extraction pipeline | |
| const extractor = await pipeline('feature-extraction', 'Alibaba-NLP/gte-large-en-v1.5', { | |
| quantized: false, // Comment out this line to use the quantized version | |
| }); | |
| // Generate sentence embeddings | |
| const sentences = [ | |
| "what is the capital of China?", | |
| "how to implement quick sort in python?", | |
| "Beijing", | |
| "sorting algorithms" | |
| ] | |
| const output = await extractor(sentences, { normalize: true, pooling: 'cls' }); | |
| // Compute similarity scores | |
| const [source_embeddings, ...document_embeddings ] = output.tolist(); | |
| const similarities = document_embeddings.map(x => 100 * dot(source_embeddings, x)); | |
| console.log(similarities); // [41.86354093370361, 77.07076371259589, 37.02981979677899] | |
| ``` | |
| ## Training Details | |
| ### Training Data | |
| - Masked language modeling (MLM): `c4-en` | |
| - Weak-supervised contrastive (WSC) pre-training: [GTE](https://arxiv.org/pdf/2308.03281.pdf) pre-training data | |
| - Supervised contrastive fine-tuning: GTE(https://arxiv.org/pdf/2308.03281.pdf) fine-tuning data | |
| ### Training Procedure | |
| To enable the backbone model to support a context length of 8192, we adopted a multi-stage training strategy. | |
| The model first undergoes preliminary MLM pre-training on shorter lengths. | |
| And then, we resample the data, reducing the proportion of short texts, and continue the MLM pre-training. | |
| The entire training process is as follows: | |
| - MLM-512: lr 2e-4, mlm_probability 0.3, batch_size 4096, num_steps 300000, rope_base 10000 | |
| - MLM-2048: lr 5e-5, mlm_probability 0.3, batch_size 4096, num_steps 30000, rope_base 10000 | |
| - MLM-8192: lr 5e-5, mlm_probability 0.3, batch_size 1024, num_steps 30000, rope_base 160000 | |
| - WSC: max_len 512, lr 5e-5, batch_size 28672, num_steps 100000 | |
| - Fine-tuning: TODO | |
| ## Evaluation | |
| ### MTEB | |
| The results of other models are retrieved from [MTEB leaderboard](https://huggingface.co/spaces/mteb/leaderboard). | |
| The gte evaluation setting: `mteb==1.2.0, fp16 auto mix precision, max_length=8192`, and set ntk scaling factor to 2 (equivalent to rope_base * 2). | |
| | Model Name | Param Size (M) | Dimension | Sequence Length | Average (56) | Class. (12) | Clust. (11) | Pair Class. (3) | Reran. (4) | Retr. (15) | STS (10) | Summ. (1) | | |
| |:----:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:| | |
| | [**gte-large-en-v1.5**](https://huggingface.co/Alibaba-NLP/gte-large-en-v1.5) | 409 | 1024 | 8192 | **65.39** | 77.75 | 47.95 | 84.63 | 58.50 | 57.91 | 81.43 | 30.91 | | |
| | [mxbai-embed-large-v1](https://huggingface.co/mixedbread-ai/mxbai-embed-large-v1) | 335 | 1024 | 512 | 64.68 | 75.64 | 46.71 | 87.2 | 60.11 | 54.39 | 85 | 32.71 | | |
| | [multilingual-e5-large-instruct](https://huggingface.co/intfloat/multilingual-e5-large-instruct) | 560 | 1024 | 514 | 64.41 | 77.56 | 47.1 | 86.19 | 58.58 | 52.47 | 84.78 | 30.39 | | |
| | [bge-large-en-v1.5](https://huggingface.co/BAAI/bge-large-en-v1.5)| 335 | 1024 | 512 | 64.23 | 75.97 | 46.08 | 87.12 | 60.03 | 54.29 | 83.11 | 31.61 | | |
| | [**gte-base-en-v1.5**](https://huggingface.co/Alibaba-NLP/gte-base-en-v1.5) | 137 | 768 | 8192 | **64.11** | 77.17 | 46.82 | 85.33 | 57.66 | 54.09 | 81.97 | 31.17 | | |
| | [bge-base-en-v1.5](https://huggingface.co/BAAI/bge-base-en-v1.5)| 109 | 768 | 512 | 63.55 | 75.53 | 45.77 | 86.55 | 58.86 | 53.25 | 82.4 | 31.07 | | |
| ### LoCo | |
| | Model Name | Dimension | Sequence Length | Average (5) | QsmsumRetrieval | SummScreenRetrieval | QasperAbastractRetrieval | QasperTitleRetrieval | GovReportRetrieval | | |
| |:----:|:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:| | |
| | [gte-qwen1.5-7b](https://huggingface.co/Alibaba-NLP/gte-qwen1.5-7b) | 4096 | 32768 | 87.57 | 49.37 | 93.10 | 99.67 | 97.54 | 98.21 | | |
| | [gte-large-v1.5](https://huggingface.co/Alibaba-NLP/gte-large-v1.5) |1024 | 8192 | 86.71 | 44.55 | 92.61 | 99.82 | 97.81 | 98.74 | | |
| | [gte-base-v1.5](https://huggingface.co/Alibaba-NLP/gte-base-v1.5) | 768 | 8192 | 87.44 | 49.91 | 91.78 | 99.82 | 97.13 | 98.58 | | |
| ## 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} | |
| } | |
| ``` |