Sentence Similarity
sentence-transformers
PyTorch
Transformers
English
t5
text-embedding
embeddings
information-retrieval
beir
text-classification
language-model
text-clustering
text-semantic-similarity
text-evaluation
prompt-retrieval
text-reranking
feature-extraction
English
Sentence Similarity
natural_questions
ms_marco
fever
hotpot_qa
mteb
Eval Results
Inference Endpoints
| pipeline_tag: sentence-similarity | |
| tags: | |
| - text-embedding | |
| - embeddings | |
| - information-retrieval | |
| - beir | |
| - text-classification | |
| - language-model | |
| - text-clustering | |
| - text-semantic-similarity | |
| - text-evaluation | |
| - prompt-retrieval | |
| - text-reranking | |
| - sentence-transformers | |
| - feature-extraction | |
| - sentence-similarity | |
| - transformers | |
| - t5 | |
| - English | |
| - Sentence Similarity | |
| - natural_questions | |
| - ms_marco | |
| - fever | |
| - hotpot_qa | |
| - mteb | |
| language: en | |
| inference: false | |
| license: apache-2.0 | |
| model-index: | |
| - name: INSTRUCTOR | |
| results: | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/amazon_counterfactual | |
| name: MTEB AmazonCounterfactualClassification (en) | |
| config: en | |
| split: test | |
| revision: e8379541af4e31359cca9fbcf4b00f2671dba205 | |
| metrics: | |
| - type: accuracy | |
| value: 88.13432835820896 | |
| - type: ap | |
| value: 59.298209334395665 | |
| - type: f1 | |
| value: 83.31769058643586 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/amazon_polarity | |
| name: MTEB AmazonPolarityClassification | |
| config: default | |
| split: test | |
| revision: e2d317d38cd51312af73b3d32a06d1a08b442046 | |
| metrics: | |
| - type: accuracy | |
| value: 91.526375 | |
| - type: ap | |
| value: 88.16327709705504 | |
| - type: f1 | |
| value: 91.51095801287843 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/amazon_reviews_multi | |
| name: MTEB AmazonReviewsClassification (en) | |
| config: en | |
| split: test | |
| revision: 1399c76144fd37290681b995c656ef9b2e06e26d | |
| metrics: | |
| - type: accuracy | |
| value: 47.856 | |
| - type: f1 | |
| value: 45.41490917650942 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: arguana | |
| name: MTEB ArguAna | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 31.223 | |
| - type: map_at_10 | |
| value: 47.947 | |
| - type: map_at_100 | |
| value: 48.742000000000004 | |
| - type: map_at_1000 | |
| value: 48.745 | |
| - type: map_at_3 | |
| value: 43.137 | |
| - type: map_at_5 | |
| value: 45.992 | |
| - type: mrr_at_1 | |
| value: 32.432 | |
| - type: mrr_at_10 | |
| value: 48.4 | |
| - type: mrr_at_100 | |
| value: 49.202 | |
| - type: mrr_at_1000 | |
| value: 49.205 | |
| - type: mrr_at_3 | |
| value: 43.551 | |
| - type: mrr_at_5 | |
| value: 46.467999999999996 | |
| - type: ndcg_at_1 | |
| value: 31.223 | |
| - type: ndcg_at_10 | |
| value: 57.045 | |
| - type: ndcg_at_100 | |
| value: 60.175 | |
| - type: ndcg_at_1000 | |
| value: 60.233000000000004 | |
| - type: ndcg_at_3 | |
| value: 47.171 | |
| - type: ndcg_at_5 | |
| value: 52.322 | |
| - type: precision_at_1 | |
| value: 31.223 | |
| - type: precision_at_10 | |
| value: 8.599 | |
| - type: precision_at_100 | |
| value: 0.991 | |
| - type: precision_at_1000 | |
| value: 0.1 | |
| - type: precision_at_3 | |
| value: 19.63 | |
| - type: precision_at_5 | |
| value: 14.282 | |
| - type: recall_at_1 | |
| value: 31.223 | |
| - type: recall_at_10 | |
| value: 85.989 | |
| - type: recall_at_100 | |
| value: 99.075 | |
| - type: recall_at_1000 | |
| value: 99.502 | |
| - type: recall_at_3 | |
| value: 58.89 | |
| - type: recall_at_5 | |
| value: 71.408 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/arxiv-clustering-p2p | |
| name: MTEB ArxivClusteringP2P | |
| config: default | |
| split: test | |
| revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d | |
| metrics: | |
| - type: v_measure | |
| value: 43.1621946393635 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/arxiv-clustering-s2s | |
| name: MTEB ArxivClusteringS2S | |
| config: default | |
| split: test | |
| revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 | |
| metrics: | |
| - type: v_measure | |
| value: 32.56417132407894 | |
| - task: | |
| type: Reranking | |
| dataset: | |
| type: mteb/askubuntudupquestions-reranking | |
| name: MTEB AskUbuntuDupQuestions | |
| config: default | |
| split: test | |
| revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 | |
| metrics: | |
| - type: map | |
| value: 64.29539304390207 | |
| - type: mrr | |
| value: 76.44484017060196 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/biosses-sts | |
| name: MTEB BIOSSES | |
| config: default | |
| split: test | |
| revision: d3fb88f8f02e40887cd149695127462bbcf29b4a | |
| metrics: | |
| - type: cos_sim_spearman | |
| value: 84.38746499431112 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/banking77 | |
| name: MTEB Banking77Classification | |
| config: default | |
| split: test | |
| revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 | |
| metrics: | |
| - type: accuracy | |
| value: 78.51298701298701 | |
| - type: f1 | |
| value: 77.49041754069235 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/biorxiv-clustering-p2p | |
| name: MTEB BiorxivClusteringP2P | |
| config: default | |
| split: test | |
| revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 | |
| metrics: | |
| - type: v_measure | |
| value: 37.61848554098577 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/biorxiv-clustering-s2s | |
| name: MTEB BiorxivClusteringS2S | |
| config: default | |
| split: test | |
| revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 | |
| metrics: | |
| - type: v_measure | |
| value: 31.32623280148178 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackAndroidRetrieval | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 35.803000000000004 | |
| - type: map_at_10 | |
| value: 48.848 | |
| - type: map_at_100 | |
| value: 50.5 | |
| - type: map_at_1000 | |
| value: 50.602999999999994 | |
| - type: map_at_3 | |
| value: 45.111000000000004 | |
| - type: map_at_5 | |
| value: 47.202 | |
| - type: mrr_at_1 | |
| value: 44.635000000000005 | |
| - type: mrr_at_10 | |
| value: 55.593 | |
| - type: mrr_at_100 | |
| value: 56.169999999999995 | |
| - type: mrr_at_1000 | |
| value: 56.19499999999999 | |
| - type: mrr_at_3 | |
| value: 53.361999999999995 | |
| - type: mrr_at_5 | |
| value: 54.806999999999995 | |
| - type: ndcg_at_1 | |
| value: 44.635000000000005 | |
| - type: ndcg_at_10 | |
| value: 55.899 | |
| - type: ndcg_at_100 | |
| value: 60.958 | |
| - type: ndcg_at_1000 | |
| value: 62.302 | |
| - type: ndcg_at_3 | |
| value: 51.051 | |
| - type: ndcg_at_5 | |
| value: 53.351000000000006 | |
| - type: precision_at_1 | |
| value: 44.635000000000005 | |
| - type: precision_at_10 | |
| value: 10.786999999999999 | |
| - type: precision_at_100 | |
| value: 1.6580000000000001 | |
| - type: precision_at_1000 | |
| value: 0.213 | |
| - type: precision_at_3 | |
| value: 24.893 | |
| - type: precision_at_5 | |
| value: 17.740000000000002 | |
| - type: recall_at_1 | |
| value: 35.803000000000004 | |
| - type: recall_at_10 | |
| value: 68.657 | |
| - type: recall_at_100 | |
| value: 89.77199999999999 | |
| - type: recall_at_1000 | |
| value: 97.67 | |
| - type: recall_at_3 | |
| value: 54.066 | |
| - type: recall_at_5 | |
| value: 60.788 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackEnglishRetrieval | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 33.706 | |
| - type: map_at_10 | |
| value: 44.896 | |
| - type: map_at_100 | |
| value: 46.299 | |
| - type: map_at_1000 | |
| value: 46.44 | |
| - type: map_at_3 | |
| value: 41.721000000000004 | |
| - type: map_at_5 | |
| value: 43.486000000000004 | |
| - type: mrr_at_1 | |
| value: 41.592 | |
| - type: mrr_at_10 | |
| value: 50.529 | |
| - type: mrr_at_100 | |
| value: 51.22 | |
| - type: mrr_at_1000 | |
| value: 51.258 | |
| - type: mrr_at_3 | |
| value: 48.205999999999996 | |
| - type: mrr_at_5 | |
| value: 49.528 | |
| - type: ndcg_at_1 | |
| value: 41.592 | |
| - type: ndcg_at_10 | |
| value: 50.77199999999999 | |
| - type: ndcg_at_100 | |
| value: 55.383 | |
| - type: ndcg_at_1000 | |
| value: 57.288 | |
| - type: ndcg_at_3 | |
| value: 46.324 | |
| - type: ndcg_at_5 | |
| value: 48.346000000000004 | |
| - type: precision_at_1 | |
| value: 41.592 | |
| - type: precision_at_10 | |
| value: 9.516 | |
| - type: precision_at_100 | |
| value: 1.541 | |
| - type: precision_at_1000 | |
| value: 0.2 | |
| - type: precision_at_3 | |
| value: 22.399 | |
| - type: precision_at_5 | |
| value: 15.770999999999999 | |
| - type: recall_at_1 | |
| value: 33.706 | |
| - type: recall_at_10 | |
| value: 61.353 | |
| - type: recall_at_100 | |
| value: 80.182 | |
| - type: recall_at_1000 | |
| value: 91.896 | |
| - type: recall_at_3 | |
| value: 48.204 | |
| - type: recall_at_5 | |
| value: 53.89699999999999 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackGamingRetrieval | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 44.424 | |
| - type: map_at_10 | |
| value: 57.169000000000004 | |
| - type: map_at_100 | |
| value: 58.202 | |
| - type: map_at_1000 | |
| value: 58.242000000000004 | |
| - type: map_at_3 | |
| value: 53.825 | |
| - type: map_at_5 | |
| value: 55.714 | |
| - type: mrr_at_1 | |
| value: 50.470000000000006 | |
| - type: mrr_at_10 | |
| value: 60.489000000000004 | |
| - type: mrr_at_100 | |
| value: 61.096 | |
| - type: mrr_at_1000 | |
| value: 61.112 | |
| - type: mrr_at_3 | |
| value: 58.192 | |
| - type: mrr_at_5 | |
| value: 59.611999999999995 | |
| - type: ndcg_at_1 | |
| value: 50.470000000000006 | |
| - type: ndcg_at_10 | |
| value: 63.071999999999996 | |
| - type: ndcg_at_100 | |
| value: 66.964 | |
| - type: ndcg_at_1000 | |
| value: 67.659 | |
| - type: ndcg_at_3 | |
| value: 57.74399999999999 | |
| - type: ndcg_at_5 | |
| value: 60.367000000000004 | |
| - type: precision_at_1 | |
| value: 50.470000000000006 | |
| - type: precision_at_10 | |
| value: 10.019 | |
| - type: precision_at_100 | |
| value: 1.29 | |
| - type: precision_at_1000 | |
| value: 0.13899999999999998 | |
| - type: precision_at_3 | |
| value: 25.558999999999997 | |
| - type: precision_at_5 | |
| value: 17.467 | |
| - type: recall_at_1 | |
| value: 44.424 | |
| - type: recall_at_10 | |
| value: 77.02 | |
| - type: recall_at_100 | |
| value: 93.738 | |
| - type: recall_at_1000 | |
| value: 98.451 | |
| - type: recall_at_3 | |
| value: 62.888 | |
| - type: recall_at_5 | |
| value: 69.138 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackGisRetrieval | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 26.294 | |
| - type: map_at_10 | |
| value: 34.503 | |
| - type: map_at_100 | |
| value: 35.641 | |
| - type: map_at_1000 | |
| value: 35.724000000000004 | |
| - type: map_at_3 | |
| value: 31.753999999999998 | |
| - type: map_at_5 | |
| value: 33.190999999999995 | |
| - type: mrr_at_1 | |
| value: 28.362 | |
| - type: mrr_at_10 | |
| value: 36.53 | |
| - type: mrr_at_100 | |
| value: 37.541000000000004 | |
| - type: mrr_at_1000 | |
| value: 37.602000000000004 | |
| - type: mrr_at_3 | |
| value: 33.917 | |
| - type: mrr_at_5 | |
| value: 35.358000000000004 | |
| - type: ndcg_at_1 | |
| value: 28.362 | |
| - type: ndcg_at_10 | |
| value: 39.513999999999996 | |
| - type: ndcg_at_100 | |
| value: 44.815 | |
| - type: ndcg_at_1000 | |
| value: 46.839 | |
| - type: ndcg_at_3 | |
| value: 34.02 | |
| - type: ndcg_at_5 | |
| value: 36.522 | |
| - type: precision_at_1 | |
| value: 28.362 | |
| - type: precision_at_10 | |
| value: 6.101999999999999 | |
| - type: precision_at_100 | |
| value: 0.9129999999999999 | |
| - type: precision_at_1000 | |
| value: 0.11399999999999999 | |
| - type: precision_at_3 | |
| value: 14.161999999999999 | |
| - type: precision_at_5 | |
| value: 9.966 | |
| - type: recall_at_1 | |
| value: 26.294 | |
| - type: recall_at_10 | |
| value: 53.098 | |
| - type: recall_at_100 | |
| value: 76.877 | |
| - type: recall_at_1000 | |
| value: 91.834 | |
| - type: recall_at_3 | |
| value: 38.266 | |
| - type: recall_at_5 | |
| value: 44.287 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackMathematicaRetrieval | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 16.407 | |
| - type: map_at_10 | |
| value: 25.185999999999996 | |
| - type: map_at_100 | |
| value: 26.533 | |
| - type: map_at_1000 | |
| value: 26.657999999999998 | |
| - type: map_at_3 | |
| value: 22.201999999999998 | |
| - type: map_at_5 | |
| value: 23.923 | |
| - type: mrr_at_1 | |
| value: 20.522000000000002 | |
| - type: mrr_at_10 | |
| value: 29.522 | |
| - type: mrr_at_100 | |
| value: 30.644 | |
| - type: mrr_at_1000 | |
| value: 30.713 | |
| - type: mrr_at_3 | |
| value: 26.679000000000002 | |
| - type: mrr_at_5 | |
| value: 28.483000000000004 | |
| - type: ndcg_at_1 | |
| value: 20.522000000000002 | |
| - type: ndcg_at_10 | |
| value: 30.656 | |
| - type: ndcg_at_100 | |
| value: 36.864999999999995 | |
| - type: ndcg_at_1000 | |
| value: 39.675 | |
| - type: ndcg_at_3 | |
| value: 25.319000000000003 | |
| - type: ndcg_at_5 | |
| value: 27.992 | |
| - type: precision_at_1 | |
| value: 20.522000000000002 | |
| - type: precision_at_10 | |
| value: 5.795999999999999 | |
| - type: precision_at_100 | |
| value: 1.027 | |
| - type: precision_at_1000 | |
| value: 0.13999999999999999 | |
| - type: precision_at_3 | |
| value: 12.396 | |
| - type: precision_at_5 | |
| value: 9.328 | |
| - type: recall_at_1 | |
| value: 16.407 | |
| - type: recall_at_10 | |
| value: 43.164 | |
| - type: recall_at_100 | |
| value: 69.695 | |
| - type: recall_at_1000 | |
| value: 89.41900000000001 | |
| - type: recall_at_3 | |
| value: 28.634999999999998 | |
| - type: recall_at_5 | |
| value: 35.308 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackPhysicsRetrieval | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 30.473 | |
| - type: map_at_10 | |
| value: 41.676 | |
| - type: map_at_100 | |
| value: 43.120999999999995 | |
| - type: map_at_1000 | |
| value: 43.230000000000004 | |
| - type: map_at_3 | |
| value: 38.306000000000004 | |
| - type: map_at_5 | |
| value: 40.355999999999995 | |
| - type: mrr_at_1 | |
| value: 37.536 | |
| - type: mrr_at_10 | |
| value: 47.643 | |
| - type: mrr_at_100 | |
| value: 48.508 | |
| - type: mrr_at_1000 | |
| value: 48.551 | |
| - type: mrr_at_3 | |
| value: 45.348 | |
| - type: mrr_at_5 | |
| value: 46.744 | |
| - type: ndcg_at_1 | |
| value: 37.536 | |
| - type: ndcg_at_10 | |
| value: 47.823 | |
| - type: ndcg_at_100 | |
| value: 53.395 | |
| - type: ndcg_at_1000 | |
| value: 55.271 | |
| - type: ndcg_at_3 | |
| value: 42.768 | |
| - type: ndcg_at_5 | |
| value: 45.373000000000005 | |
| - type: precision_at_1 | |
| value: 37.536 | |
| - type: precision_at_10 | |
| value: 8.681 | |
| - type: precision_at_100 | |
| value: 1.34 | |
| - type: precision_at_1000 | |
| value: 0.165 | |
| - type: precision_at_3 | |
| value: 20.468 | |
| - type: precision_at_5 | |
| value: 14.495 | |
| - type: recall_at_1 | |
| value: 30.473 | |
| - type: recall_at_10 | |
| value: 60.092999999999996 | |
| - type: recall_at_100 | |
| value: 82.733 | |
| - type: recall_at_1000 | |
| value: 94.875 | |
| - type: recall_at_3 | |
| value: 45.734 | |
| - type: recall_at_5 | |
| value: 52.691 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackProgrammersRetrieval | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 29.976000000000003 | |
| - type: map_at_10 | |
| value: 41.097 | |
| - type: map_at_100 | |
| value: 42.547000000000004 | |
| - type: map_at_1000 | |
| value: 42.659000000000006 | |
| - type: map_at_3 | |
| value: 37.251 | |
| - type: map_at_5 | |
| value: 39.493 | |
| - type: mrr_at_1 | |
| value: 37.557 | |
| - type: mrr_at_10 | |
| value: 46.605000000000004 | |
| - type: mrr_at_100 | |
| value: 47.487 | |
| - type: mrr_at_1000 | |
| value: 47.54 | |
| - type: mrr_at_3 | |
| value: 43.721 | |
| - type: mrr_at_5 | |
| value: 45.411 | |
| - type: ndcg_at_1 | |
| value: 37.557 | |
| - type: ndcg_at_10 | |
| value: 47.449000000000005 | |
| - type: ndcg_at_100 | |
| value: 53.052 | |
| - type: ndcg_at_1000 | |
| value: 55.010999999999996 | |
| - type: ndcg_at_3 | |
| value: 41.439 | |
| - type: ndcg_at_5 | |
| value: 44.292 | |
| - type: precision_at_1 | |
| value: 37.557 | |
| - type: precision_at_10 | |
| value: 8.847 | |
| - type: precision_at_100 | |
| value: 1.357 | |
| - type: precision_at_1000 | |
| value: 0.16999999999999998 | |
| - type: precision_at_3 | |
| value: 20.091 | |
| - type: precision_at_5 | |
| value: 14.384 | |
| - type: recall_at_1 | |
| value: 29.976000000000003 | |
| - type: recall_at_10 | |
| value: 60.99099999999999 | |
| - type: recall_at_100 | |
| value: 84.245 | |
| - type: recall_at_1000 | |
| value: 96.97200000000001 | |
| - type: recall_at_3 | |
| value: 43.794 | |
| - type: recall_at_5 | |
| value: 51.778999999999996 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackRetrieval | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 28.099166666666665 | |
| - type: map_at_10 | |
| value: 38.1365 | |
| - type: map_at_100 | |
| value: 39.44491666666667 | |
| - type: map_at_1000 | |
| value: 39.55858333333334 | |
| - type: map_at_3 | |
| value: 35.03641666666666 | |
| - type: map_at_5 | |
| value: 36.79833333333334 | |
| - type: mrr_at_1 | |
| value: 33.39966666666667 | |
| - type: mrr_at_10 | |
| value: 42.42583333333333 | |
| - type: mrr_at_100 | |
| value: 43.28575 | |
| - type: mrr_at_1000 | |
| value: 43.33741666666667 | |
| - type: mrr_at_3 | |
| value: 39.94975 | |
| - type: mrr_at_5 | |
| value: 41.41633333333334 | |
| - type: ndcg_at_1 | |
| value: 33.39966666666667 | |
| - type: ndcg_at_10 | |
| value: 43.81741666666667 | |
| - type: ndcg_at_100 | |
| value: 49.08166666666667 | |
| - type: ndcg_at_1000 | |
| value: 51.121166666666674 | |
| - type: ndcg_at_3 | |
| value: 38.73575 | |
| - type: ndcg_at_5 | |
| value: 41.18158333333333 | |
| - type: precision_at_1 | |
| value: 33.39966666666667 | |
| - type: precision_at_10 | |
| value: 7.738916666666667 | |
| - type: precision_at_100 | |
| value: 1.2265833333333331 | |
| - type: precision_at_1000 | |
| value: 0.15983333333333336 | |
| - type: precision_at_3 | |
| value: 17.967416666666665 | |
| - type: precision_at_5 | |
| value: 12.78675 | |
| - type: recall_at_1 | |
| value: 28.099166666666665 | |
| - type: recall_at_10 | |
| value: 56.27049999999999 | |
| - type: recall_at_100 | |
| value: 78.93291666666667 | |
| - type: recall_at_1000 | |
| value: 92.81608333333334 | |
| - type: recall_at_3 | |
| value: 42.09775 | |
| - type: recall_at_5 | |
| value: 48.42533333333334 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackStatsRetrieval | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 23.663 | |
| - type: map_at_10 | |
| value: 30.377 | |
| - type: map_at_100 | |
| value: 31.426 | |
| - type: map_at_1000 | |
| value: 31.519000000000002 | |
| - type: map_at_3 | |
| value: 28.069 | |
| - type: map_at_5 | |
| value: 29.256999999999998 | |
| - type: mrr_at_1 | |
| value: 26.687 | |
| - type: mrr_at_10 | |
| value: 33.107 | |
| - type: mrr_at_100 | |
| value: 34.055 | |
| - type: mrr_at_1000 | |
| value: 34.117999999999995 | |
| - type: mrr_at_3 | |
| value: 31.058000000000003 | |
| - type: mrr_at_5 | |
| value: 32.14 | |
| - type: ndcg_at_1 | |
| value: 26.687 | |
| - type: ndcg_at_10 | |
| value: 34.615 | |
| - type: ndcg_at_100 | |
| value: 39.776 | |
| - type: ndcg_at_1000 | |
| value: 42.05 | |
| - type: ndcg_at_3 | |
| value: 30.322 | |
| - type: ndcg_at_5 | |
| value: 32.157000000000004 | |
| - type: precision_at_1 | |
| value: 26.687 | |
| - type: precision_at_10 | |
| value: 5.491 | |
| - type: precision_at_100 | |
| value: 0.877 | |
| - type: precision_at_1000 | |
| value: 0.11499999999999999 | |
| - type: precision_at_3 | |
| value: 13.139000000000001 | |
| - type: precision_at_5 | |
| value: 9.049 | |
| - type: recall_at_1 | |
| value: 23.663 | |
| - type: recall_at_10 | |
| value: 45.035 | |
| - type: recall_at_100 | |
| value: 68.554 | |
| - type: recall_at_1000 | |
| value: 85.077 | |
| - type: recall_at_3 | |
| value: 32.982 | |
| - type: recall_at_5 | |
| value: 37.688 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackTexRetrieval | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 17.403 | |
| - type: map_at_10 | |
| value: 25.197000000000003 | |
| - type: map_at_100 | |
| value: 26.355 | |
| - type: map_at_1000 | |
| value: 26.487 | |
| - type: map_at_3 | |
| value: 22.733 | |
| - type: map_at_5 | |
| value: 24.114 | |
| - type: mrr_at_1 | |
| value: 21.37 | |
| - type: mrr_at_10 | |
| value: 29.091 | |
| - type: mrr_at_100 | |
| value: 30.018 | |
| - type: mrr_at_1000 | |
| value: 30.096 | |
| - type: mrr_at_3 | |
| value: 26.887 | |
| - type: mrr_at_5 | |
| value: 28.157 | |
| - type: ndcg_at_1 | |
| value: 21.37 | |
| - type: ndcg_at_10 | |
| value: 30.026000000000003 | |
| - type: ndcg_at_100 | |
| value: 35.416 | |
| - type: ndcg_at_1000 | |
| value: 38.45 | |
| - type: ndcg_at_3 | |
| value: 25.764 | |
| - type: ndcg_at_5 | |
| value: 27.742 | |
| - type: precision_at_1 | |
| value: 21.37 | |
| - type: precision_at_10 | |
| value: 5.609 | |
| - type: precision_at_100 | |
| value: 0.9860000000000001 | |
| - type: precision_at_1000 | |
| value: 0.14300000000000002 | |
| - type: precision_at_3 | |
| value: 12.423 | |
| - type: precision_at_5 | |
| value: 9.009 | |
| - type: recall_at_1 | |
| value: 17.403 | |
| - type: recall_at_10 | |
| value: 40.573 | |
| - type: recall_at_100 | |
| value: 64.818 | |
| - type: recall_at_1000 | |
| value: 86.53699999999999 | |
| - type: recall_at_3 | |
| value: 28.493000000000002 | |
| - type: recall_at_5 | |
| value: 33.660000000000004 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackUnixRetrieval | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 28.639 | |
| - type: map_at_10 | |
| value: 38.951 | |
| - type: map_at_100 | |
| value: 40.238 | |
| - type: map_at_1000 | |
| value: 40.327 | |
| - type: map_at_3 | |
| value: 35.842 | |
| - type: map_at_5 | |
| value: 37.617 | |
| - type: mrr_at_1 | |
| value: 33.769 | |
| - type: mrr_at_10 | |
| value: 43.088 | |
| - type: mrr_at_100 | |
| value: 44.03 | |
| - type: mrr_at_1000 | |
| value: 44.072 | |
| - type: mrr_at_3 | |
| value: 40.656 | |
| - type: mrr_at_5 | |
| value: 42.138999999999996 | |
| - type: ndcg_at_1 | |
| value: 33.769 | |
| - type: ndcg_at_10 | |
| value: 44.676 | |
| - type: ndcg_at_100 | |
| value: 50.416000000000004 | |
| - type: ndcg_at_1000 | |
| value: 52.227999999999994 | |
| - type: ndcg_at_3 | |
| value: 39.494 | |
| - type: ndcg_at_5 | |
| value: 42.013 | |
| - type: precision_at_1 | |
| value: 33.769 | |
| - type: precision_at_10 | |
| value: 7.668 | |
| - type: precision_at_100 | |
| value: 1.18 | |
| - type: precision_at_1000 | |
| value: 0.145 | |
| - type: precision_at_3 | |
| value: 18.221 | |
| - type: precision_at_5 | |
| value: 12.966 | |
| - type: recall_at_1 | |
| value: 28.639 | |
| - type: recall_at_10 | |
| value: 57.687999999999995 | |
| - type: recall_at_100 | |
| value: 82.541 | |
| - type: recall_at_1000 | |
| value: 94.896 | |
| - type: recall_at_3 | |
| value: 43.651 | |
| - type: recall_at_5 | |
| value: 49.925999999999995 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackWebmastersRetrieval | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 29.57 | |
| - type: map_at_10 | |
| value: 40.004 | |
| - type: map_at_100 | |
| value: 41.75 | |
| - type: map_at_1000 | |
| value: 41.97 | |
| - type: map_at_3 | |
| value: 36.788 | |
| - type: map_at_5 | |
| value: 38.671 | |
| - type: mrr_at_1 | |
| value: 35.375 | |
| - type: mrr_at_10 | |
| value: 45.121 | |
| - type: mrr_at_100 | |
| value: 45.994 | |
| - type: mrr_at_1000 | |
| value: 46.04 | |
| - type: mrr_at_3 | |
| value: 42.227 | |
| - type: mrr_at_5 | |
| value: 43.995 | |
| - type: ndcg_at_1 | |
| value: 35.375 | |
| - type: ndcg_at_10 | |
| value: 46.392 | |
| - type: ndcg_at_100 | |
| value: 52.196 | |
| - type: ndcg_at_1000 | |
| value: 54.274 | |
| - type: ndcg_at_3 | |
| value: 41.163 | |
| - type: ndcg_at_5 | |
| value: 43.813 | |
| - type: precision_at_1 | |
| value: 35.375 | |
| - type: precision_at_10 | |
| value: 8.676 | |
| - type: precision_at_100 | |
| value: 1.678 | |
| - type: precision_at_1000 | |
| value: 0.253 | |
| - type: precision_at_3 | |
| value: 19.104 | |
| - type: precision_at_5 | |
| value: 13.913 | |
| - type: recall_at_1 | |
| value: 29.57 | |
| - type: recall_at_10 | |
| value: 58.779 | |
| - type: recall_at_100 | |
| value: 83.337 | |
| - type: recall_at_1000 | |
| value: 95.979 | |
| - type: recall_at_3 | |
| value: 44.005 | |
| - type: recall_at_5 | |
| value: 50.975 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: BeIR/cqadupstack | |
| name: MTEB CQADupstackWordpressRetrieval | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 20.832 | |
| - type: map_at_10 | |
| value: 29.733999999999998 | |
| - type: map_at_100 | |
| value: 30.727 | |
| - type: map_at_1000 | |
| value: 30.843999999999998 | |
| - type: map_at_3 | |
| value: 26.834999999999997 | |
| - type: map_at_5 | |
| value: 28.555999999999997 | |
| - type: mrr_at_1 | |
| value: 22.921 | |
| - type: mrr_at_10 | |
| value: 31.791999999999998 | |
| - type: mrr_at_100 | |
| value: 32.666000000000004 | |
| - type: mrr_at_1000 | |
| value: 32.751999999999995 | |
| - type: mrr_at_3 | |
| value: 29.144 | |
| - type: mrr_at_5 | |
| value: 30.622 | |
| - type: ndcg_at_1 | |
| value: 22.921 | |
| - type: ndcg_at_10 | |
| value: 34.915 | |
| - type: ndcg_at_100 | |
| value: 39.744 | |
| - type: ndcg_at_1000 | |
| value: 42.407000000000004 | |
| - type: ndcg_at_3 | |
| value: 29.421000000000003 | |
| - type: ndcg_at_5 | |
| value: 32.211 | |
| - type: precision_at_1 | |
| value: 22.921 | |
| - type: precision_at_10 | |
| value: 5.675 | |
| - type: precision_at_100 | |
| value: 0.872 | |
| - type: precision_at_1000 | |
| value: 0.121 | |
| - type: precision_at_3 | |
| value: 12.753999999999998 | |
| - type: precision_at_5 | |
| value: 9.353 | |
| - type: recall_at_1 | |
| value: 20.832 | |
| - type: recall_at_10 | |
| value: 48.795 | |
| - type: recall_at_100 | |
| value: 70.703 | |
| - type: recall_at_1000 | |
| value: 90.187 | |
| - type: recall_at_3 | |
| value: 34.455000000000005 | |
| - type: recall_at_5 | |
| value: 40.967 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: climate-fever | |
| name: MTEB ClimateFEVER | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 10.334 | |
| - type: map_at_10 | |
| value: 19.009999999999998 | |
| - type: map_at_100 | |
| value: 21.129 | |
| - type: map_at_1000 | |
| value: 21.328 | |
| - type: map_at_3 | |
| value: 15.152 | |
| - type: map_at_5 | |
| value: 17.084 | |
| - type: mrr_at_1 | |
| value: 23.453 | |
| - type: mrr_at_10 | |
| value: 36.099 | |
| - type: mrr_at_100 | |
| value: 37.069 | |
| - type: mrr_at_1000 | |
| value: 37.104 | |
| - type: mrr_at_3 | |
| value: 32.096000000000004 | |
| - type: mrr_at_5 | |
| value: 34.451 | |
| - type: ndcg_at_1 | |
| value: 23.453 | |
| - type: ndcg_at_10 | |
| value: 27.739000000000004 | |
| - type: ndcg_at_100 | |
| value: 35.836 | |
| - type: ndcg_at_1000 | |
| value: 39.242 | |
| - type: ndcg_at_3 | |
| value: 21.263 | |
| - type: ndcg_at_5 | |
| value: 23.677 | |
| - type: precision_at_1 | |
| value: 23.453 | |
| - type: precision_at_10 | |
| value: 9.199 | |
| - type: precision_at_100 | |
| value: 1.791 | |
| - type: precision_at_1000 | |
| value: 0.242 | |
| - type: precision_at_3 | |
| value: 16.2 | |
| - type: precision_at_5 | |
| value: 13.147 | |
| - type: recall_at_1 | |
| value: 10.334 | |
| - type: recall_at_10 | |
| value: 35.177 | |
| - type: recall_at_100 | |
| value: 63.009 | |
| - type: recall_at_1000 | |
| value: 81.938 | |
| - type: recall_at_3 | |
| value: 19.914 | |
| - type: recall_at_5 | |
| value: 26.077 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: dbpedia-entity | |
| name: MTEB DBPedia | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 8.212 | |
| - type: map_at_10 | |
| value: 17.386 | |
| - type: map_at_100 | |
| value: 24.234 | |
| - type: map_at_1000 | |
| value: 25.724999999999998 | |
| - type: map_at_3 | |
| value: 12.727 | |
| - type: map_at_5 | |
| value: 14.785 | |
| - type: mrr_at_1 | |
| value: 59.25 | |
| - type: mrr_at_10 | |
| value: 68.687 | |
| - type: mrr_at_100 | |
| value: 69.133 | |
| - type: mrr_at_1000 | |
| value: 69.14099999999999 | |
| - type: mrr_at_3 | |
| value: 66.917 | |
| - type: mrr_at_5 | |
| value: 67.742 | |
| - type: ndcg_at_1 | |
| value: 48.625 | |
| - type: ndcg_at_10 | |
| value: 36.675999999999995 | |
| - type: ndcg_at_100 | |
| value: 41.543 | |
| - type: ndcg_at_1000 | |
| value: 49.241 | |
| - type: ndcg_at_3 | |
| value: 41.373 | |
| - type: ndcg_at_5 | |
| value: 38.707 | |
| - type: precision_at_1 | |
| value: 59.25 | |
| - type: precision_at_10 | |
| value: 28.525 | |
| - type: precision_at_100 | |
| value: 9.027000000000001 | |
| - type: precision_at_1000 | |
| value: 1.8339999999999999 | |
| - type: precision_at_3 | |
| value: 44.833 | |
| - type: precision_at_5 | |
| value: 37.35 | |
| - type: recall_at_1 | |
| value: 8.212 | |
| - type: recall_at_10 | |
| value: 23.188 | |
| - type: recall_at_100 | |
| value: 48.613 | |
| - type: recall_at_1000 | |
| value: 73.093 | |
| - type: recall_at_3 | |
| value: 14.419 | |
| - type: recall_at_5 | |
| value: 17.798 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/emotion | |
| name: MTEB EmotionClassification | |
| config: default | |
| split: test | |
| revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 | |
| metrics: | |
| - type: accuracy | |
| value: 52.725 | |
| - type: f1 | |
| value: 46.50743309855908 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: fever | |
| name: MTEB FEVER | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 55.086 | |
| - type: map_at_10 | |
| value: 66.914 | |
| - type: map_at_100 | |
| value: 67.321 | |
| - type: map_at_1000 | |
| value: 67.341 | |
| - type: map_at_3 | |
| value: 64.75800000000001 | |
| - type: map_at_5 | |
| value: 66.189 | |
| - type: mrr_at_1 | |
| value: 59.28600000000001 | |
| - type: mrr_at_10 | |
| value: 71.005 | |
| - type: mrr_at_100 | |
| value: 71.304 | |
| - type: mrr_at_1000 | |
| value: 71.313 | |
| - type: mrr_at_3 | |
| value: 69.037 | |
| - type: mrr_at_5 | |
| value: 70.35 | |
| - type: ndcg_at_1 | |
| value: 59.28600000000001 | |
| - type: ndcg_at_10 | |
| value: 72.695 | |
| - type: ndcg_at_100 | |
| value: 74.432 | |
| - type: ndcg_at_1000 | |
| value: 74.868 | |
| - type: ndcg_at_3 | |
| value: 68.72200000000001 | |
| - type: ndcg_at_5 | |
| value: 71.081 | |
| - type: precision_at_1 | |
| value: 59.28600000000001 | |
| - type: precision_at_10 | |
| value: 9.499 | |
| - type: precision_at_100 | |
| value: 1.052 | |
| - type: precision_at_1000 | |
| value: 0.11100000000000002 | |
| - type: precision_at_3 | |
| value: 27.503 | |
| - type: precision_at_5 | |
| value: 17.854999999999997 | |
| - type: recall_at_1 | |
| value: 55.086 | |
| - type: recall_at_10 | |
| value: 86.453 | |
| - type: recall_at_100 | |
| value: 94.028 | |
| - type: recall_at_1000 | |
| value: 97.052 | |
| - type: recall_at_3 | |
| value: 75.821 | |
| - type: recall_at_5 | |
| value: 81.6 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: fiqa | |
| name: MTEB FiQA2018 | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 22.262999999999998 | |
| - type: map_at_10 | |
| value: 37.488 | |
| - type: map_at_100 | |
| value: 39.498 | |
| - type: map_at_1000 | |
| value: 39.687 | |
| - type: map_at_3 | |
| value: 32.529 | |
| - type: map_at_5 | |
| value: 35.455 | |
| - type: mrr_at_1 | |
| value: 44.907000000000004 | |
| - type: mrr_at_10 | |
| value: 53.239000000000004 | |
| - type: mrr_at_100 | |
| value: 54.086 | |
| - type: mrr_at_1000 | |
| value: 54.122 | |
| - type: mrr_at_3 | |
| value: 51.235 | |
| - type: mrr_at_5 | |
| value: 52.415 | |
| - type: ndcg_at_1 | |
| value: 44.907000000000004 | |
| - type: ndcg_at_10 | |
| value: 45.446 | |
| - type: ndcg_at_100 | |
| value: 52.429 | |
| - type: ndcg_at_1000 | |
| value: 55.169000000000004 | |
| - type: ndcg_at_3 | |
| value: 41.882000000000005 | |
| - type: ndcg_at_5 | |
| value: 43.178 | |
| - type: precision_at_1 | |
| value: 44.907000000000004 | |
| - type: precision_at_10 | |
| value: 12.931999999999999 | |
| - type: precision_at_100 | |
| value: 2.025 | |
| - type: precision_at_1000 | |
| value: 0.248 | |
| - type: precision_at_3 | |
| value: 28.652 | |
| - type: precision_at_5 | |
| value: 21.204 | |
| - type: recall_at_1 | |
| value: 22.262999999999998 | |
| - type: recall_at_10 | |
| value: 52.447 | |
| - type: recall_at_100 | |
| value: 78.045 | |
| - type: recall_at_1000 | |
| value: 94.419 | |
| - type: recall_at_3 | |
| value: 38.064 | |
| - type: recall_at_5 | |
| value: 44.769 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: hotpotqa | |
| name: MTEB HotpotQA | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 32.519 | |
| - type: map_at_10 | |
| value: 45.831 | |
| - type: map_at_100 | |
| value: 46.815 | |
| - type: map_at_1000 | |
| value: 46.899 | |
| - type: map_at_3 | |
| value: 42.836 | |
| - type: map_at_5 | |
| value: 44.65 | |
| - type: mrr_at_1 | |
| value: 65.037 | |
| - type: mrr_at_10 | |
| value: 72.16 | |
| - type: mrr_at_100 | |
| value: 72.51100000000001 | |
| - type: mrr_at_1000 | |
| value: 72.53 | |
| - type: mrr_at_3 | |
| value: 70.682 | |
| - type: mrr_at_5 | |
| value: 71.54599999999999 | |
| - type: ndcg_at_1 | |
| value: 65.037 | |
| - type: ndcg_at_10 | |
| value: 55.17999999999999 | |
| - type: ndcg_at_100 | |
| value: 58.888 | |
| - type: ndcg_at_1000 | |
| value: 60.648 | |
| - type: ndcg_at_3 | |
| value: 50.501 | |
| - type: ndcg_at_5 | |
| value: 52.977 | |
| - type: precision_at_1 | |
| value: 65.037 | |
| - type: precision_at_10 | |
| value: 11.530999999999999 | |
| - type: precision_at_100 | |
| value: 1.4460000000000002 | |
| - type: precision_at_1000 | |
| value: 0.168 | |
| - type: precision_at_3 | |
| value: 31.483 | |
| - type: precision_at_5 | |
| value: 20.845 | |
| - type: recall_at_1 | |
| value: 32.519 | |
| - type: recall_at_10 | |
| value: 57.657000000000004 | |
| - type: recall_at_100 | |
| value: 72.30199999999999 | |
| - type: recall_at_1000 | |
| value: 84.024 | |
| - type: recall_at_3 | |
| value: 47.225 | |
| - type: recall_at_5 | |
| value: 52.113 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/imdb | |
| name: MTEB ImdbClassification | |
| config: default | |
| split: test | |
| revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 | |
| metrics: | |
| - type: accuracy | |
| value: 88.3168 | |
| - type: ap | |
| value: 83.80165516037135 | |
| - type: f1 | |
| value: 88.29942471066407 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: msmarco | |
| name: MTEB MSMARCO | |
| config: default | |
| split: dev | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 20.724999999999998 | |
| - type: map_at_10 | |
| value: 32.736 | |
| - type: map_at_100 | |
| value: 33.938 | |
| - type: map_at_1000 | |
| value: 33.991 | |
| - type: map_at_3 | |
| value: 28.788000000000004 | |
| - type: map_at_5 | |
| value: 31.016 | |
| - type: mrr_at_1 | |
| value: 21.361 | |
| - type: mrr_at_10 | |
| value: 33.323 | |
| - type: mrr_at_100 | |
| value: 34.471000000000004 | |
| - type: mrr_at_1000 | |
| value: 34.518 | |
| - type: mrr_at_3 | |
| value: 29.453000000000003 | |
| - type: mrr_at_5 | |
| value: 31.629 | |
| - type: ndcg_at_1 | |
| value: 21.361 | |
| - type: ndcg_at_10 | |
| value: 39.649 | |
| - type: ndcg_at_100 | |
| value: 45.481 | |
| - type: ndcg_at_1000 | |
| value: 46.775 | |
| - type: ndcg_at_3 | |
| value: 31.594 | |
| - type: ndcg_at_5 | |
| value: 35.543 | |
| - type: precision_at_1 | |
| value: 21.361 | |
| - type: precision_at_10 | |
| value: 6.3740000000000006 | |
| - type: precision_at_100 | |
| value: 0.931 | |
| - type: precision_at_1000 | |
| value: 0.104 | |
| - type: precision_at_3 | |
| value: 13.514999999999999 | |
| - type: precision_at_5 | |
| value: 10.100000000000001 | |
| - type: recall_at_1 | |
| value: 20.724999999999998 | |
| - type: recall_at_10 | |
| value: 61.034 | |
| - type: recall_at_100 | |
| value: 88.062 | |
| - type: recall_at_1000 | |
| value: 97.86399999999999 | |
| - type: recall_at_3 | |
| value: 39.072 | |
| - type: recall_at_5 | |
| value: 48.53 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/mtop_domain | |
| name: MTEB MTOPDomainClassification (en) | |
| config: en | |
| split: test | |
| revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf | |
| metrics: | |
| - type: accuracy | |
| value: 93.8919288645691 | |
| - type: f1 | |
| value: 93.57059586398059 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/mtop_intent | |
| name: MTEB MTOPIntentClassification (en) | |
| config: en | |
| split: test | |
| revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba | |
| metrics: | |
| - type: accuracy | |
| value: 67.97993616051072 | |
| - type: f1 | |
| value: 48.244319183606535 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/amazon_massive_intent | |
| name: MTEB MassiveIntentClassification (en) | |
| config: en | |
| split: test | |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 | |
| metrics: | |
| - type: accuracy | |
| value: 68.90047074646941 | |
| - type: f1 | |
| value: 66.48999056063725 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/amazon_massive_scenario | |
| name: MTEB MassiveScenarioClassification (en) | |
| config: en | |
| split: test | |
| revision: 7d571f92784cd94a019292a1f45445077d0ef634 | |
| metrics: | |
| - type: accuracy | |
| value: 73.34566240753195 | |
| - type: f1 | |
| value: 73.54164154290658 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/medrxiv-clustering-p2p | |
| name: MTEB MedrxivClusteringP2P | |
| config: default | |
| split: test | |
| revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 | |
| metrics: | |
| - type: v_measure | |
| value: 34.21866934757011 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/medrxiv-clustering-s2s | |
| name: MTEB MedrxivClusteringS2S | |
| config: default | |
| split: test | |
| revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 | |
| metrics: | |
| - type: v_measure | |
| value: 32.000936217235534 | |
| - task: | |
| type: Reranking | |
| dataset: | |
| type: mteb/mind_small | |
| name: MTEB MindSmallReranking | |
| config: default | |
| split: test | |
| revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 | |
| metrics: | |
| - type: map | |
| value: 31.68189362520352 | |
| - type: mrr | |
| value: 32.69603637784303 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: nfcorpus | |
| name: MTEB NFCorpus | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 6.078 | |
| - type: map_at_10 | |
| value: 12.671 | |
| - type: map_at_100 | |
| value: 16.291 | |
| - type: map_at_1000 | |
| value: 17.855999999999998 | |
| - type: map_at_3 | |
| value: 9.610000000000001 | |
| - type: map_at_5 | |
| value: 11.152 | |
| - type: mrr_at_1 | |
| value: 43.963 | |
| - type: mrr_at_10 | |
| value: 53.173 | |
| - type: mrr_at_100 | |
| value: 53.718999999999994 | |
| - type: mrr_at_1000 | |
| value: 53.756 | |
| - type: mrr_at_3 | |
| value: 50.980000000000004 | |
| - type: mrr_at_5 | |
| value: 52.42 | |
| - type: ndcg_at_1 | |
| value: 42.415000000000006 | |
| - type: ndcg_at_10 | |
| value: 34.086 | |
| - type: ndcg_at_100 | |
| value: 32.545 | |
| - type: ndcg_at_1000 | |
| value: 41.144999999999996 | |
| - type: ndcg_at_3 | |
| value: 39.434999999999995 | |
| - type: ndcg_at_5 | |
| value: 37.888 | |
| - type: precision_at_1 | |
| value: 43.653 | |
| - type: precision_at_10 | |
| value: 25.014999999999997 | |
| - type: precision_at_100 | |
| value: 8.594 | |
| - type: precision_at_1000 | |
| value: 2.169 | |
| - type: precision_at_3 | |
| value: 37.049 | |
| - type: precision_at_5 | |
| value: 33.065 | |
| - type: recall_at_1 | |
| value: 6.078 | |
| - type: recall_at_10 | |
| value: 16.17 | |
| - type: recall_at_100 | |
| value: 34.512 | |
| - type: recall_at_1000 | |
| value: 65.447 | |
| - type: recall_at_3 | |
| value: 10.706 | |
| - type: recall_at_5 | |
| value: 13.158 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: nq | |
| name: MTEB NQ | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 27.378000000000004 | |
| - type: map_at_10 | |
| value: 42.178 | |
| - type: map_at_100 | |
| value: 43.32 | |
| - type: map_at_1000 | |
| value: 43.358000000000004 | |
| - type: map_at_3 | |
| value: 37.474000000000004 | |
| - type: map_at_5 | |
| value: 40.333000000000006 | |
| - type: mrr_at_1 | |
| value: 30.823 | |
| - type: mrr_at_10 | |
| value: 44.626 | |
| - type: mrr_at_100 | |
| value: 45.494 | |
| - type: mrr_at_1000 | |
| value: 45.519 | |
| - type: mrr_at_3 | |
| value: 40.585 | |
| - type: mrr_at_5 | |
| value: 43.146 | |
| - type: ndcg_at_1 | |
| value: 30.794 | |
| - type: ndcg_at_10 | |
| value: 50.099000000000004 | |
| - type: ndcg_at_100 | |
| value: 54.900999999999996 | |
| - type: ndcg_at_1000 | |
| value: 55.69499999999999 | |
| - type: ndcg_at_3 | |
| value: 41.238 | |
| - type: ndcg_at_5 | |
| value: 46.081 | |
| - type: precision_at_1 | |
| value: 30.794 | |
| - type: precision_at_10 | |
| value: 8.549 | |
| - type: precision_at_100 | |
| value: 1.124 | |
| - type: precision_at_1000 | |
| value: 0.12 | |
| - type: precision_at_3 | |
| value: 18.926000000000002 | |
| - type: precision_at_5 | |
| value: 14.16 | |
| - type: recall_at_1 | |
| value: 27.378000000000004 | |
| - type: recall_at_10 | |
| value: 71.842 | |
| - type: recall_at_100 | |
| value: 92.565 | |
| - type: recall_at_1000 | |
| value: 98.402 | |
| - type: recall_at_3 | |
| value: 49.053999999999995 | |
| - type: recall_at_5 | |
| value: 60.207 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: quora | |
| name: MTEB QuoraRetrieval | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 70.557 | |
| - type: map_at_10 | |
| value: 84.729 | |
| - type: map_at_100 | |
| value: 85.369 | |
| - type: map_at_1000 | |
| value: 85.382 | |
| - type: map_at_3 | |
| value: 81.72 | |
| - type: map_at_5 | |
| value: 83.613 | |
| - type: mrr_at_1 | |
| value: 81.3 | |
| - type: mrr_at_10 | |
| value: 87.488 | |
| - type: mrr_at_100 | |
| value: 87.588 | |
| - type: mrr_at_1000 | |
| value: 87.589 | |
| - type: mrr_at_3 | |
| value: 86.53 | |
| - type: mrr_at_5 | |
| value: 87.18599999999999 | |
| - type: ndcg_at_1 | |
| value: 81.28999999999999 | |
| - type: ndcg_at_10 | |
| value: 88.442 | |
| - type: ndcg_at_100 | |
| value: 89.637 | |
| - type: ndcg_at_1000 | |
| value: 89.70700000000001 | |
| - type: ndcg_at_3 | |
| value: 85.55199999999999 | |
| - type: ndcg_at_5 | |
| value: 87.154 | |
| - type: precision_at_1 | |
| value: 81.28999999999999 | |
| - type: precision_at_10 | |
| value: 13.489999999999998 | |
| - type: precision_at_100 | |
| value: 1.54 | |
| - type: precision_at_1000 | |
| value: 0.157 | |
| - type: precision_at_3 | |
| value: 37.553 | |
| - type: precision_at_5 | |
| value: 24.708 | |
| - type: recall_at_1 | |
| value: 70.557 | |
| - type: recall_at_10 | |
| value: 95.645 | |
| - type: recall_at_100 | |
| value: 99.693 | |
| - type: recall_at_1000 | |
| value: 99.995 | |
| - type: recall_at_3 | |
| value: 87.359 | |
| - type: recall_at_5 | |
| value: 91.89699999999999 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/reddit-clustering | |
| name: MTEB RedditClustering | |
| config: default | |
| split: test | |
| revision: 24640382cdbf8abc73003fb0fa6d111a705499eb | |
| metrics: | |
| - type: v_measure | |
| value: 63.65060114776209 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/reddit-clustering-p2p | |
| name: MTEB RedditClusteringP2P | |
| config: default | |
| split: test | |
| revision: 282350215ef01743dc01b456c7f5241fa8937f16 | |
| metrics: | |
| - type: v_measure | |
| value: 64.63271250680617 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: scidocs | |
| name: MTEB SCIDOCS | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 4.263 | |
| - type: map_at_10 | |
| value: 10.801 | |
| - type: map_at_100 | |
| value: 12.888 | |
| - type: map_at_1000 | |
| value: 13.224 | |
| - type: map_at_3 | |
| value: 7.362 | |
| - type: map_at_5 | |
| value: 9.149000000000001 | |
| - type: mrr_at_1 | |
| value: 21 | |
| - type: mrr_at_10 | |
| value: 31.416 | |
| - type: mrr_at_100 | |
| value: 32.513 | |
| - type: mrr_at_1000 | |
| value: 32.58 | |
| - type: mrr_at_3 | |
| value: 28.116999999999997 | |
| - type: mrr_at_5 | |
| value: 29.976999999999997 | |
| - type: ndcg_at_1 | |
| value: 21 | |
| - type: ndcg_at_10 | |
| value: 18.551000000000002 | |
| - type: ndcg_at_100 | |
| value: 26.657999999999998 | |
| - type: ndcg_at_1000 | |
| value: 32.485 | |
| - type: ndcg_at_3 | |
| value: 16.834 | |
| - type: ndcg_at_5 | |
| value: 15.204999999999998 | |
| - type: precision_at_1 | |
| value: 21 | |
| - type: precision_at_10 | |
| value: 9.84 | |
| - type: precision_at_100 | |
| value: 2.16 | |
| - type: precision_at_1000 | |
| value: 0.35500000000000004 | |
| - type: precision_at_3 | |
| value: 15.667 | |
| - type: precision_at_5 | |
| value: 13.62 | |
| - type: recall_at_1 | |
| value: 4.263 | |
| - type: recall_at_10 | |
| value: 19.922 | |
| - type: recall_at_100 | |
| value: 43.808 | |
| - type: recall_at_1000 | |
| value: 72.14500000000001 | |
| - type: recall_at_3 | |
| value: 9.493 | |
| - type: recall_at_5 | |
| value: 13.767999999999999 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/sickr-sts | |
| name: MTEB SICK-R | |
| config: default | |
| split: test | |
| revision: a6ea5a8cab320b040a23452cc28066d9beae2cee | |
| metrics: | |
| - type: cos_sim_spearman | |
| value: 81.27446313317233 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/sts12-sts | |
| name: MTEB STS12 | |
| config: default | |
| split: test | |
| revision: a0d554a64d88156834ff5ae9920b964011b16384 | |
| metrics: | |
| - type: cos_sim_spearman | |
| value: 76.27963301217527 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/sts13-sts | |
| name: MTEB STS13 | |
| config: default | |
| split: test | |
| revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca | |
| metrics: | |
| - type: cos_sim_spearman | |
| value: 88.18495048450949 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/sts14-sts | |
| name: MTEB STS14 | |
| config: default | |
| split: test | |
| revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 | |
| metrics: | |
| - type: cos_sim_spearman | |
| value: 81.91982338692046 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/sts15-sts | |
| name: MTEB STS15 | |
| config: default | |
| split: test | |
| revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 | |
| metrics: | |
| - type: cos_sim_spearman | |
| value: 89.00896818385291 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/sts16-sts | |
| name: MTEB STS16 | |
| config: default | |
| split: test | |
| revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 | |
| metrics: | |
| - type: cos_sim_spearman | |
| value: 85.48814644586132 | |
| - 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_spearman | |
| value: 90.30116926966582 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/sts22-crosslingual-sts | |
| name: MTEB STS22 (en) | |
| config: en | |
| split: test | |
| revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 | |
| metrics: | |
| - type: cos_sim_spearman | |
| value: 67.74132963032342 | |
| - task: | |
| type: STS | |
| dataset: | |
| type: mteb/stsbenchmark-sts | |
| name: MTEB STSBenchmark | |
| config: default | |
| split: test | |
| revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 | |
| metrics: | |
| - type: cos_sim_spearman | |
| value: 86.87741355780479 | |
| - task: | |
| type: Reranking | |
| dataset: | |
| type: mteb/scidocs-reranking | |
| name: MTEB SciDocsRR | |
| config: default | |
| split: test | |
| revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab | |
| metrics: | |
| - type: map | |
| value: 82.0019012295875 | |
| - type: mrr | |
| value: 94.70267024188593 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: scifact | |
| name: MTEB SciFact | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 50.05 | |
| - type: map_at_10 | |
| value: 59.36 | |
| - type: map_at_100 | |
| value: 59.967999999999996 | |
| - type: map_at_1000 | |
| value: 60.023 | |
| - type: map_at_3 | |
| value: 56.515 | |
| - type: map_at_5 | |
| value: 58.272999999999996 | |
| - type: mrr_at_1 | |
| value: 53 | |
| - type: mrr_at_10 | |
| value: 61.102000000000004 | |
| - type: mrr_at_100 | |
| value: 61.476 | |
| - type: mrr_at_1000 | |
| value: 61.523 | |
| - type: mrr_at_3 | |
| value: 58.778 | |
| - type: mrr_at_5 | |
| value: 60.128 | |
| - type: ndcg_at_1 | |
| value: 53 | |
| - type: ndcg_at_10 | |
| value: 64.43100000000001 | |
| - type: ndcg_at_100 | |
| value: 66.73599999999999 | |
| - type: ndcg_at_1000 | |
| value: 68.027 | |
| - type: ndcg_at_3 | |
| value: 59.279 | |
| - type: ndcg_at_5 | |
| value: 61.888 | |
| - type: precision_at_1 | |
| value: 53 | |
| - type: precision_at_10 | |
| value: 8.767 | |
| - type: precision_at_100 | |
| value: 1.01 | |
| - type: precision_at_1000 | |
| value: 0.11100000000000002 | |
| - type: precision_at_3 | |
| value: 23.444000000000003 | |
| - type: precision_at_5 | |
| value: 15.667 | |
| - type: recall_at_1 | |
| value: 50.05 | |
| - type: recall_at_10 | |
| value: 78.511 | |
| - type: recall_at_100 | |
| value: 88.5 | |
| - type: recall_at_1000 | |
| value: 98.333 | |
| - type: recall_at_3 | |
| value: 64.117 | |
| - type: recall_at_5 | |
| value: 70.867 | |
| - task: | |
| type: PairClassification | |
| dataset: | |
| type: mteb/sprintduplicatequestions-pairclassification | |
| name: MTEB SprintDuplicateQuestions | |
| config: default | |
| split: test | |
| revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 | |
| metrics: | |
| - type: cos_sim_accuracy | |
| value: 99.72178217821782 | |
| - type: cos_sim_ap | |
| value: 93.0728601593541 | |
| - type: cos_sim_f1 | |
| value: 85.6727976766699 | |
| - type: cos_sim_precision | |
| value: 83.02063789868667 | |
| - type: cos_sim_recall | |
| value: 88.5 | |
| - type: dot_accuracy | |
| value: 99.72178217821782 | |
| - type: dot_ap | |
| value: 93.07287396168348 | |
| - type: dot_f1 | |
| value: 85.6727976766699 | |
| - type: dot_precision | |
| value: 83.02063789868667 | |
| - type: dot_recall | |
| value: 88.5 | |
| - type: euclidean_accuracy | |
| value: 99.72178217821782 | |
| - type: euclidean_ap | |
| value: 93.07285657982895 | |
| - type: euclidean_f1 | |
| value: 85.6727976766699 | |
| - type: euclidean_precision | |
| value: 83.02063789868667 | |
| - type: euclidean_recall | |
| value: 88.5 | |
| - type: manhattan_accuracy | |
| value: 99.72475247524753 | |
| - type: manhattan_ap | |
| value: 93.02792973059809 | |
| - type: manhattan_f1 | |
| value: 85.7727737973388 | |
| - type: manhattan_precision | |
| value: 87.84067085953879 | |
| - type: manhattan_recall | |
| value: 83.8 | |
| - type: max_accuracy | |
| value: 99.72475247524753 | |
| - type: max_ap | |
| value: 93.07287396168348 | |
| - type: max_f1 | |
| value: 85.7727737973388 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/stackexchange-clustering | |
| name: MTEB StackExchangeClustering | |
| config: default | |
| split: test | |
| revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 | |
| metrics: | |
| - type: v_measure | |
| value: 68.77583615550819 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/stackexchange-clustering-p2p | |
| name: MTEB StackExchangeClusteringP2P | |
| config: default | |
| split: test | |
| revision: 815ca46b2622cec33ccafc3735d572c266efdb44 | |
| metrics: | |
| - type: v_measure | |
| value: 36.151636938606956 | |
| - task: | |
| type: Reranking | |
| dataset: | |
| type: mteb/stackoverflowdupquestions-reranking | |
| name: MTEB StackOverflowDupQuestions | |
| config: default | |
| split: test | |
| revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 | |
| metrics: | |
| - type: map | |
| value: 52.16607939471187 | |
| - type: mrr | |
| value: 52.95172046091163 | |
| - task: | |
| type: Summarization | |
| dataset: | |
| type: mteb/summeval | |
| name: MTEB SummEval | |
| config: default | |
| split: test | |
| revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c | |
| metrics: | |
| - type: cos_sim_pearson | |
| value: 31.314646669495666 | |
| - type: cos_sim_spearman | |
| value: 31.83562491439455 | |
| - type: dot_pearson | |
| value: 31.314590842874157 | |
| - type: dot_spearman | |
| value: 31.83363065810437 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: trec-covid | |
| name: MTEB TRECCOVID | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 0.198 | |
| - type: map_at_10 | |
| value: 1.3010000000000002 | |
| - type: map_at_100 | |
| value: 7.2139999999999995 | |
| - type: map_at_1000 | |
| value: 20.179 | |
| - type: map_at_3 | |
| value: 0.528 | |
| - type: map_at_5 | |
| value: 0.8019999999999999 | |
| - type: mrr_at_1 | |
| value: 72 | |
| - type: mrr_at_10 | |
| value: 83.39999999999999 | |
| - type: mrr_at_100 | |
| value: 83.39999999999999 | |
| - type: mrr_at_1000 | |
| value: 83.39999999999999 | |
| - type: mrr_at_3 | |
| value: 81.667 | |
| - type: mrr_at_5 | |
| value: 83.06700000000001 | |
| - type: ndcg_at_1 | |
| value: 66 | |
| - type: ndcg_at_10 | |
| value: 58.059000000000005 | |
| - type: ndcg_at_100 | |
| value: 44.316 | |
| - type: ndcg_at_1000 | |
| value: 43.147000000000006 | |
| - type: ndcg_at_3 | |
| value: 63.815999999999995 | |
| - type: ndcg_at_5 | |
| value: 63.005 | |
| - type: precision_at_1 | |
| value: 72 | |
| - type: precision_at_10 | |
| value: 61.4 | |
| - type: precision_at_100 | |
| value: 45.62 | |
| - type: precision_at_1000 | |
| value: 19.866 | |
| - type: precision_at_3 | |
| value: 70 | |
| - type: precision_at_5 | |
| value: 68.8 | |
| - type: recall_at_1 | |
| value: 0.198 | |
| - type: recall_at_10 | |
| value: 1.517 | |
| - type: recall_at_100 | |
| value: 10.587 | |
| - type: recall_at_1000 | |
| value: 41.233 | |
| - type: recall_at_3 | |
| value: 0.573 | |
| - type: recall_at_5 | |
| value: 0.907 | |
| - task: | |
| type: Retrieval | |
| dataset: | |
| type: webis-touche2020 | |
| name: MTEB Touche2020 | |
| config: default | |
| split: test | |
| revision: None | |
| metrics: | |
| - type: map_at_1 | |
| value: 1.894 | |
| - type: map_at_10 | |
| value: 8.488999999999999 | |
| - type: map_at_100 | |
| value: 14.445 | |
| - type: map_at_1000 | |
| value: 16.078 | |
| - type: map_at_3 | |
| value: 4.589 | |
| - type: map_at_5 | |
| value: 6.019 | |
| - type: mrr_at_1 | |
| value: 22.448999999999998 | |
| - type: mrr_at_10 | |
| value: 39.82 | |
| - type: mrr_at_100 | |
| value: 40.752 | |
| - type: mrr_at_1000 | |
| value: 40.771 | |
| - type: mrr_at_3 | |
| value: 34.354 | |
| - type: mrr_at_5 | |
| value: 37.721 | |
| - type: ndcg_at_1 | |
| value: 19.387999999999998 | |
| - type: ndcg_at_10 | |
| value: 21.563 | |
| - type: ndcg_at_100 | |
| value: 33.857 | |
| - type: ndcg_at_1000 | |
| value: 46.199 | |
| - type: ndcg_at_3 | |
| value: 22.296 | |
| - type: ndcg_at_5 | |
| value: 21.770999999999997 | |
| - type: precision_at_1 | |
| value: 22.448999999999998 | |
| - type: precision_at_10 | |
| value: 19.796 | |
| - type: precision_at_100 | |
| value: 7.142999999999999 | |
| - type: precision_at_1000 | |
| value: 1.541 | |
| - type: precision_at_3 | |
| value: 24.490000000000002 | |
| - type: precision_at_5 | |
| value: 22.448999999999998 | |
| - type: recall_at_1 | |
| value: 1.894 | |
| - type: recall_at_10 | |
| value: 14.931 | |
| - type: recall_at_100 | |
| value: 45.524 | |
| - type: recall_at_1000 | |
| value: 83.243 | |
| - type: recall_at_3 | |
| value: 5.712 | |
| - type: recall_at_5 | |
| value: 8.386000000000001 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/toxic_conversations_50k | |
| name: MTEB ToxicConversationsClassification | |
| config: default | |
| split: test | |
| revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c | |
| metrics: | |
| - type: accuracy | |
| value: 71.049 | |
| - type: ap | |
| value: 13.85116971310922 | |
| - type: f1 | |
| value: 54.37504302487686 | |
| - task: | |
| type: Classification | |
| dataset: | |
| type: mteb/tweet_sentiment_extraction | |
| name: MTEB TweetSentimentExtractionClassification | |
| config: default | |
| split: test | |
| revision: d604517c81ca91fe16a244d1248fc021f9ecee7a | |
| metrics: | |
| - type: accuracy | |
| value: 64.1312959818902 | |
| - type: f1 | |
| value: 64.11413877009383 | |
| - task: | |
| type: Clustering | |
| dataset: | |
| type: mteb/twentynewsgroups-clustering | |
| name: MTEB TwentyNewsgroupsClustering | |
| config: default | |
| split: test | |
| revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 | |
| metrics: | |
| - type: v_measure | |
| value: 54.13103431861502 | |
| - task: | |
| type: PairClassification | |
| dataset: | |
| type: mteb/twittersemeval2015-pairclassification | |
| name: MTEB TwitterSemEval2015 | |
| config: default | |
| split: test | |
| revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 | |
| metrics: | |
| - type: cos_sim_accuracy | |
| value: 87.327889372355 | |
| - type: cos_sim_ap | |
| value: 77.42059895975699 | |
| - type: cos_sim_f1 | |
| value: 71.02706903250873 | |
| - type: cos_sim_precision | |
| value: 69.75324344950394 | |
| - type: cos_sim_recall | |
| value: 72.34828496042216 | |
| - type: dot_accuracy | |
| value: 87.327889372355 | |
| - type: dot_ap | |
| value: 77.4209479346677 | |
| - type: dot_f1 | |
| value: 71.02706903250873 | |
| - type: dot_precision | |
| value: 69.75324344950394 | |
| - type: dot_recall | |
| value: 72.34828496042216 | |
| - type: euclidean_accuracy | |
| value: 87.327889372355 | |
| - type: euclidean_ap | |
| value: 77.42096495861037 | |
| - type: euclidean_f1 | |
| value: 71.02706903250873 | |
| - type: euclidean_precision | |
| value: 69.75324344950394 | |
| - type: euclidean_recall | |
| value: 72.34828496042216 | |
| - type: manhattan_accuracy | |
| value: 87.31000774870358 | |
| - type: manhattan_ap | |
| value: 77.38930750711619 | |
| - type: manhattan_f1 | |
| value: 71.07935314027831 | |
| - type: manhattan_precision | |
| value: 67.70957726295677 | |
| - type: manhattan_recall | |
| value: 74.80211081794195 | |
| - type: max_accuracy | |
| value: 87.327889372355 | |
| - type: max_ap | |
| value: 77.42096495861037 | |
| - type: max_f1 | |
| value: 71.07935314027831 | |
| - task: | |
| type: PairClassification | |
| dataset: | |
| type: mteb/twitterurlcorpus-pairclassification | |
| name: MTEB TwitterURLCorpus | |
| config: default | |
| split: test | |
| revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf | |
| metrics: | |
| - type: cos_sim_accuracy | |
| value: 89.58939729110878 | |
| - type: cos_sim_ap | |
| value: 87.17594155025475 | |
| - type: cos_sim_f1 | |
| value: 79.21146953405018 | |
| - type: cos_sim_precision | |
| value: 76.8918527109307 | |
| - type: cos_sim_recall | |
| value: 81.67539267015707 | |
| - type: dot_accuracy | |
| value: 89.58939729110878 | |
| - type: dot_ap | |
| value: 87.17593963273593 | |
| - type: dot_f1 | |
| value: 79.21146953405018 | |
| - type: dot_precision | |
| value: 76.8918527109307 | |
| - type: dot_recall | |
| value: 81.67539267015707 | |
| - type: euclidean_accuracy | |
| value: 89.58939729110878 | |
| - type: euclidean_ap | |
| value: 87.17592466925834 | |
| - type: euclidean_f1 | |
| value: 79.21146953405018 | |
| - type: euclidean_precision | |
| value: 76.8918527109307 | |
| - type: euclidean_recall | |
| value: 81.67539267015707 | |
| - type: manhattan_accuracy | |
| value: 89.62626615438352 | |
| - type: manhattan_ap | |
| value: 87.16589873161546 | |
| - type: manhattan_f1 | |
| value: 79.25143598295348 | |
| - type: manhattan_precision | |
| value: 76.39494177323712 | |
| - type: manhattan_recall | |
| value: 82.32984293193716 | |
| - type: max_accuracy | |
| value: 89.62626615438352 | |
| - type: max_ap | |
| value: 87.17594155025475 | |
| - type: max_f1 | |
| value: 79.25143598295348 | |
| duplicated_from: hkunlp/instructor-large | |
| # Same as hkunlp/instructor-large, except using a custom handler so it can be deployed with HF Inference Endpoints | |
| # hkunlp/instructor-large | |
| We introduce **Instructor**👨🏫, an instruction-finetuned text embedding model that can generate text embeddings tailored to any task (e.g., classification, retrieval, clustering, text evaluation, etc.) and domains (e.g., science, finance, etc.) ***by simply providing the task instruction, without any finetuning***. Instructor👨 achieves sota on 70 diverse embedding tasks ([MTEB leaderboard](https://huggingface.co/spaces/mteb/leaderboard))! | |
| The model is easy to use with **our customized** `sentence-transformer` library. For more details, check out [our paper](https://arxiv.org/abs/2212.09741) and [project page](https://instructor-embedding.github.io/)! | |
| **************************** **Updates** **************************** | |
| * 12/28: We released a new [checkpoint](https://huggingface.co/hkunlp/instructor-large) trained with hard negatives, which gives better performance. | |
| * 12/21: We released our [paper](https://arxiv.org/abs/2212.09741), [code](https://github.com/HKUNLP/instructor-embedding), [checkpoint](https://huggingface.co/hkunlp/instructor-large) and [project page](https://instructor-embedding.github.io/)! Check them out! | |
| ## Quick start | |
| <hr /> | |
| ## Installation | |
| ```bash | |
| pip install InstructorEmbedding | |
| ``` | |
| ## Compute your customized embeddings | |
| Then you can use the model like this to calculate domain-specific and task-aware embeddings: | |
| ```python | |
| from InstructorEmbedding import INSTRUCTOR | |
| model = INSTRUCTOR('hkunlp/instructor-large') | |
| sentence = "3D ActionSLAM: wearable person tracking in multi-floor environments" | |
| instruction = "Represent the Science title:" | |
| embeddings = model.encode([[instruction,sentence]]) | |
| print(embeddings) | |
| ``` | |
| ## Use cases | |
| <hr /> | |
| ## Calculate embeddings for your customized texts | |
| If you want to calculate customized embeddings for specific sentences, you may follow the unified template to write instructions: | |
| Represent the `domain` `text_type` for `task_objective`: | |
| * `domain` is optional, and it specifies the domain of the text, e.g., science, finance, medicine, etc. | |
| * `text_type` is required, and it specifies the encoding unit, e.g., sentence, document, paragraph, etc. | |
| * `task_objective` is optional, and it specifies the objective of embedding, e.g., retrieve a document, classify the sentence, etc. | |
| ## Calculate Sentence similarities | |
| You can further use the model to compute similarities between two groups of sentences, with **customized embeddings**. | |
| ```python | |
| from sklearn.metrics.pairwise import cosine_similarity | |
| sentences_a = [['Represent the Science sentence: ','Parton energy loss in QCD matter'], | |
| ['Represent the Financial statement: ','The Federal Reserve on Wednesday raised its benchmark interest rate.']] | |
| sentences_b = [['Represent the Science sentence: ','The Chiral Phase Transition in Dissipative Dynamics'], | |
| ['Represent the Financial statement: ','The funds rose less than 0.5 per cent on Friday']] | |
| embeddings_a = model.encode(sentences_a) | |
| embeddings_b = model.encode(sentences_b) | |
| similarities = cosine_similarity(embeddings_a,embeddings_b) | |
| print(similarities) | |
| ``` | |
| ## Information Retrieval | |
| You can also use **customized embeddings** for information retrieval. | |
| ```python | |
| import numpy as np | |
| from sklearn.metrics.pairwise import cosine_similarity | |
| query = [['Represent the Wikipedia question for retrieving supporting documents: ','where is the food stored in a yam plant']] | |
| corpus = [['Represent the Wikipedia document for retrieval: ','Capitalism has been dominant in the Western world since the end of feudalism, but most feel[who?] that the term "mixed economies" more precisely describes most contemporary economies, due to their containing both private-owned and state-owned enterprises. In capitalism, prices determine the demand-supply scale. For example, higher demand for certain goods and services lead to higher prices and lower demand for certain goods lead to lower prices.'], | |
| ['Represent the Wikipedia document for retrieval: ',"The disparate impact theory is especially controversial under the Fair Housing Act because the Act regulates many activities relating to housing, insurance, and mortgage loans—and some scholars have argued that the theory's use under the Fair Housing Act, combined with extensions of the Community Reinvestment Act, contributed to rise of sub-prime lending and the crash of the U.S. housing market and ensuing global economic recession"], | |
| ['Represent the Wikipedia document for retrieval: ','Disparate impact in United States labor law refers to practices in employment, housing, and other areas that adversely affect one group of people of a protected characteristic more than another, even though rules applied by employers or landlords are formally neutral. Although the protected classes vary by statute, most federal civil rights laws protect based on race, color, religion, national origin, and sex as protected traits, and some laws include disability status and other traits as well.']] | |
| query_embeddings = model.encode(query) | |
| corpus_embeddings = model.encode(corpus) | |
| similarities = cosine_similarity(query_embeddings,corpus_embeddings) | |
| retrieved_doc_id = np.argmax(similarities) | |
| print(retrieved_doc_id) | |
| ``` | |
| ## Clustering | |
| Use **customized embeddings** for clustering texts in groups. | |
| ```python | |
| import sklearn.cluster | |
| sentences = [['Represent the Medicine sentence for clustering: ','Dynamical Scalar Degree of Freedom in Horava-Lifshitz Gravity'], | |
| ['Represent the Medicine sentence for clustering: ','Comparison of Atmospheric Neutrino Flux Calculations at Low Energies'], | |
| ['Represent the Medicine sentence for clustering: ','Fermion Bags in the Massive Gross-Neveu Model'], | |
| ['Represent the Medicine sentence for clustering: ',"QCD corrections to Associated t-tbar-H production at the Tevatron"], | |
| ['Represent the Medicine sentence for clustering: ','A New Analysis of the R Measurements: Resonance Parameters of the Higher, Vector States of Charmonium']] | |
| embeddings = model.encode(sentences) | |
| clustering_model = sklearn.cluster.MiniBatchKMeans(n_clusters=2) | |
| clustering_model.fit(embeddings) | |
| cluster_assignment = clustering_model.labels_ | |
| print(cluster_assignment) | |
| ``` | |