winberta-base / README.md

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	---
	tags:
	- mteb
	model-index:
	- name: winberta
	results:
	- task:
	type: Clustering
	dataset:
	type: PL-MTEB/8tags-clustering
	name: MTEB 8TagsClustering
	config: default
	split: test
	revision: None
	metrics:
	- type: v_measure
	value: 4.6762575299584555
	- task:
	type: STS
	dataset:
	type: C-MTEB/AFQMC
	name: MTEB AFQMC
	config: default
	split: validation
	revision: None
	metrics:
	- type: cos_sim_pearson
	value: 39.92944665836267
	- type: cos_sim_spearman
	value: 44.25208147787637
	- type: euclidean_pearson
	value: 42.772842908404925
	- type: euclidean_spearman
	value: 44.25208147787637
	- type: manhattan_pearson
	value: 42.600565541302124
	- type: manhattan_spearman
	value: 44.10077657065955
	- task:
	type: STS
	dataset:
	type: C-MTEB/ATEC
	name: MTEB ATEC
	config: default
	split: test
	revision: None
	metrics:
	- type: cos_sim_pearson
	value: 40.99236789888241
	- type: cos_sim_spearman
	value: 48.23930486989189
	- type: euclidean_pearson
	value: 48.58722571676781
	- type: euclidean_spearman
	value: 48.23930486989189
	- type: manhattan_pearson
	value: 48.46099247089918
	- type: manhattan_spearman
	value: 48.146434253428446
	- task:
	type: Classification
	dataset:
	type: PL-MTEB/allegro-reviews
	name: MTEB AllegroReviews
	config: default
	split: test
	revision: None
	metrics:
	- type: accuracy
	value: 24.890656063618295
	- type: f1
	value: 22.302214664290936
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_counterfactual
	name: MTEB AmazonCounterfactualClassification (en)
	config: en
	split: test
	revision: e8379541af4e31359cca9fbcf4b00f2671dba205
	metrics:
	- type: accuracy
	value: 69.91044776119402
	- type: ap
	value: 31.66723912472561
	- type: f1
	value: 63.421139457970746
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_counterfactual
	name: MTEB AmazonCounterfactualClassification (de)
	config: de
	split: test
	revision: e8379541af4e31359cca9fbcf4b00f2671dba205
	metrics:
	- type: accuracy
	value: 54.111349036402565
	- type: ap
	value: 71.1991959997261
	- type: f1
	value: 51.56958434326653
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_counterfactual
	name: MTEB AmazonCounterfactualClassification (en-ext)
	config: en-ext
	split: test
	revision: e8379541af4e31359cca9fbcf4b00f2671dba205
	metrics:
	- type: accuracy
	value: 70.38230884557721
	- type: ap
	value: 19.909214544678782
	- type: f1
	value: 57.875461279657294
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_counterfactual
	name: MTEB AmazonCounterfactualClassification (ja)
	config: ja
	split: test
	revision: e8379541af4e31359cca9fbcf4b00f2671dba205
	metrics:
	- type: accuracy
	value: 53.9507494646681
	- type: ap
	value: 11.599932987437649
	- type: f1
	value: 43.985879202841346
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_polarity
	name: MTEB AmazonPolarityClassification
	config: default
	split: test
	revision: e2d317d38cd51312af73b3d32a06d1a08b442046
	metrics:
	- type: accuracy
	value: 72.94987499999999
	- type: ap
	value: 67.05052265683933
	- type: f1
	value: 72.74508057235695
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_reviews_multi
	name: MTEB AmazonReviewsClassification (zh)
	config: zh
	split: test
	revision: 1399c76144fd37290681b995c656ef9b2e06e26d
	metrics:
	- type: accuracy
	value: 39.681999999999995
	- type: f1
	value: 37.89870143785791
	- task:
	type: Classification
	dataset:
	type: DDSC/angry-tweets
	name: MTEB AngryTweetsClassification
	config: default
	split: test
	revision: 20b0e6081892e78179356fada741b7afa381443d
	metrics:
	- type: accuracy
	value: 46.170009551098374
	- type: f1
	value: 45.00796485732147
	- task:
	type: Clustering
	dataset:
	type: mteb/arxiv-clustering-p2p
	name: MTEB ArxivClusteringP2P
	config: default
	split: test
	revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
	metrics:
	- type: v_measure
	value: 33.69909330263927
	- task:
	type: Clustering
	dataset:
	type: mteb/arxiv-clustering-s2s
	name: MTEB ArxivClusteringS2S
	config: default
	split: test
	revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
	metrics:
	- type: v_measure
	value: 23.04252711340139
	- task:
	type: Reranking
	dataset:
	type: mteb/askubuntudupquestions-reranking
	name: MTEB AskUbuntuDupQuestions
	config: default
	split: test
	revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
	metrics:
	- type: map
	value: 53.987091172373944
	- type: mrr
	value: 67.65840038693224
	- task:
	type: STS
	dataset:
	type: C-MTEB/BQ
	name: MTEB BQ
	config: default
	split: test
	revision: None
	metrics:
	- type: cos_sim_pearson
	value: 54.56093256747345
	- type: cos_sim_spearman
	value: 56.27367976851523
	- type: euclidean_pearson
	value: 55.38528627937832
	- type: euclidean_spearman
	value: 56.27367284031196
	- type: manhattan_pearson
	value: 55.30402898692059
	- type: manhattan_spearman
	value: 56.19811385550433
	- task:
	type: BitextMining
	dataset:
	type: mteb/bucc-bitext-mining
	name: MTEB BUCC (de-en)
	config: de-en
	split: test
	revision: d51519689f32196a32af33b075a01d0e7c51e252
	metrics:
	- type: accuracy
	value: 9.384133611691023
	- type: f1
	value: 9.25678496868476
	- type: precision
	value: 9.204791728800078
	- type: recall
	value: 9.384133611691023
	- task:
	type: BitextMining
	dataset:
	type: mteb/bucc-bitext-mining
	name: MTEB BUCC (fr-en)
	config: fr-en
	split: test
	revision: d51519689f32196a32af33b075a01d0e7c51e252
	metrics:
	- type: accuracy
	value: 17.719568567026194
	- type: f1
	value: 17.413603345806735
	- type: precision
	value: 17.284183459067894
	- type: recall
	value: 17.719568567026194
	- task:
	type: BitextMining
	dataset:
	type: mteb/bucc-bitext-mining
	name: MTEB BUCC (ru-en)
	config: ru-en
	split: test
	revision: d51519689f32196a32af33b075a01d0e7c51e252
	metrics:
	- type: accuracy
	value: 52.70523034291652
	- type: f1
	value: 51.97355963514606
	- type: precision
	value: 51.642562994485395
	- type: recall
	value: 52.70523034291652
	- task:
	type: BitextMining
	dataset:
	type: mteb/bucc-bitext-mining
	name: MTEB BUCC (zh-en)
	config: zh-en
	split: test
	revision: d51519689f32196a32af33b075a01d0e7c51e252
	metrics:
	- type: accuracy
	value: 89.0995260663507
	- type: f1
	value: 88.70458135860979
	- type: precision
	value: 88.5202738283307
	- type: recall
	value: 89.0995260663507
	- task:
	type: Classification
	dataset:
	type: mteb/banking77
	name: MTEB Banking77Classification
	config: default
	split: test
	revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
	metrics:
	- type: accuracy
	value: 64.12337662337661
	- type: f1
	value: 62.35908261257942
	- task:
	type: Clustering
	dataset:
	type: mteb/biorxiv-clustering-p2p
	name: MTEB BiorxivClusteringP2P
	config: default
	split: test
	revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
	metrics:
	- type: v_measure
	value: 32.70437969303962
	- task:
	type: Clustering
	dataset:
	type: mteb/biorxiv-clustering-s2s
	name: MTEB BiorxivClusteringS2S
	config: default
	split: test
	revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
	metrics:
	- type: v_measure
	value: 23.27850834359782
	- task:
	type: Clustering
	dataset:
	type: slvnwhrl/blurbs-clustering-p2p
	name: MTEB BlurbsClusteringP2P
	config: default
	split: test
	revision: a2dd5b02a77de3466a3eaa98ae586b5610314496
	metrics:
	- type: v_measure
	value: 17.471535040494018
	- task:
	type: Clustering
	dataset:
	type: slvnwhrl/blurbs-clustering-s2s
	name: MTEB BlurbsClusteringS2S
	config: default
	split: test
	revision: 9bfff9a7f8f6dc6ffc9da71c48dd48b68696471d
	metrics:
	- type: v_measure
	value: 7.957798776861661
	- task:
	type: Classification
	dataset:
	type: PL-MTEB/cbd
	name: MTEB CBD
	config: default
	split: test
	revision: None
	metrics:
	- type: accuracy
	value: 53.78000000000001
	- type: ap
	value: 16.030265142358818
	- type: f1
	value: 46.39936854646567
	- task:
	type: PairClassification
	dataset:
	type: PL-MTEB/cdsce-pairclassification
	name: MTEB CDSC-E
	config: default
	split: test
	revision: None
	metrics:
	- type: cos_sim_accuracy
	value: 82.69999999999999
	- type: cos_sim_ap
	value: 43.50726455006939
	- type: cos_sim_f1
	value: 55.21472392638037
	- type: cos_sim_precision
	value: 45.1505016722408
	- type: cos_sim_recall
	value: 71.05263157894737
	- type: dot_accuracy
	value: 82.69999999999999
	- type: dot_ap
	value: 43.50726455006939
	- type: dot_f1
	value: 55.21472392638037
	- type: dot_precision
	value: 45.1505016722408
	- type: dot_recall
	value: 71.05263157894737
	- type: euclidean_accuracy
	value: 82.69999999999999
	- type: euclidean_ap
	value: 43.50726455006939
	- type: euclidean_f1
	value: 55.21472392638037
	- type: euclidean_precision
	value: 45.1505016722408
	- type: euclidean_recall
	value: 71.05263157894737
	- type: manhattan_accuracy
	value: 83.1
	- type: manhattan_ap
	value: 43.95534719205733
	- type: manhattan_f1
	value: 55.34351145038169
	- type: manhattan_precision
	value: 43.41317365269461
	- type: manhattan_recall
	value: 76.31578947368422
	- type: max_accuracy
	value: 83.1
	- type: max_ap
	value: 43.95534719205733
	- type: max_f1
	value: 55.34351145038169
	- task:
	type: Clustering
	dataset:
	type: C-MTEB/CLSClusteringP2P
	name: MTEB CLSClusteringP2P
	config: default
	split: test
	revision: None
	metrics:
	- type: v_measure
	value: 42.20892953002924
	- task:
	type: Clustering
	dataset:
	type: C-MTEB/CLSClusteringS2S
	name: MTEB CLSClusteringS2S
	config: default
	split: test
	revision: None
	metrics:
	- type: v_measure
	value: 40.33286164241634
	- task:
	type: Reranking
	dataset:
	type: C-MTEB/CMedQAv1-reranking
	name: MTEB CMedQAv1
	config: default
	split: test
	revision: None
	metrics:
	- type: map
	value: 76.47170720756812
	- type: mrr
	value: 79.89289682539682
	- task:
	type: Reranking
	dataset:
	type: C-MTEB/CMedQAv2-reranking
	name: MTEB CMedQAv2
	config: default
	split: test
	revision: None
	metrics:
	- type: map
	value: 77.43675520157939
	- type: mrr
	value: 81.11420634920636
	- task:
	type: Retrieval
	dataset:
	type: C-MTEB/CmedqaRetrieval
	name: MTEB CmedqaRetrieval
	config: default
	split: dev
	revision: None
	metrics:
	- type: map_at_1
	value: 17.308
	- type: map_at_10
	value: 26.144000000000002
	- type: map_at_100
	value: 27.864
	- type: map_at_1000
	value: 28.032
	- type: map_at_3
	value: 23.058999999999997
	- type: map_at_5
	value: 24.724
	- type: mrr_at_1
	value: 27.206999999999997
	- type: mrr_at_10
	value: 34.287
	- type: mrr_at_100
	value: 35.375
	- type: mrr_at_1000
	value: 35.449999999999996
	- type: mrr_at_3
	value: 31.912000000000003
	- type: mrr_at_5
	value: 33.222
	- type: ndcg_at_1
	value: 27.206999999999997
	- type: ndcg_at_10
	value: 31.789
	- type: ndcg_at_100
	value: 39.251000000000005
	- type: ndcg_at_1000
	value: 42.536
	- type: ndcg_at_3
	value: 27.503
	- type: ndcg_at_5
	value: 29.226999999999997
	- type: precision_at_1
	value: 27.206999999999997
	- type: precision_at_10
	value: 7.3069999999999995
	- type: precision_at_100
	value: 1.345
	- type: precision_at_1000
	value: 0.17700000000000002
	- type: precision_at_3
	value: 15.854
	- type: precision_at_5
	value: 11.593
	- type: recall_at_1
	value: 17.308
	- type: recall_at_10
	value: 40.474
	- type: recall_at_100
	value: 71.897
	- type: recall_at_1000
	value: 94.375
	- type: recall_at_3
	value: 27.563
	- type: recall_at_5
	value: 32.944
	- task:
	type: PairClassification
	dataset:
	type: C-MTEB/CMNLI
	name: MTEB Cmnli
	config: default
	split: validation
	revision: None
	metrics:
	- type: cos_sim_accuracy
	value: 76.11545399879735
	- type: cos_sim_ap
	value: 84.09842598179311
	- type: cos_sim_f1
	value: 77.66760077602932
	- type: cos_sim_precision
	value: 72.04559088182364
	- type: cos_sim_recall
	value: 84.24129062426935
	- type: dot_accuracy
	value: 76.11545399879735
	- type: dot_ap
	value: 84.11185112340806
	- type: dot_f1
	value: 77.66760077602932
	- type: dot_precision
	value: 72.04559088182364
	- type: dot_recall
	value: 84.24129062426935
	- type: euclidean_accuracy
	value: 76.11545399879735
	- type: euclidean_ap
	value: 84.09842259671359
	- type: euclidean_f1
	value: 77.66760077602932
	- type: euclidean_precision
	value: 72.04559088182364
	- type: euclidean_recall
	value: 84.24129062426935
	- type: manhattan_accuracy
	value: 76.12748045700542
	- type: manhattan_ap
	value: 84.07246090513767
	- type: manhattan_f1
	value: 77.41864555848726
	- type: manhattan_precision
	value: 73.064951234696
	- type: manhattan_recall
	value: 82.3240589198036
	- type: max_accuracy
	value: 76.12748045700542
	- type: max_ap
	value: 84.11185112340806
	- type: max_f1
	value: 77.66760077602932
	- task:
	type: Retrieval
	dataset:
	type: C-MTEB/CovidRetrieval
	name: MTEB CovidRetrieval
	config: default
	split: dev
	revision: None
	metrics:
	- type: map_at_1
	value: 53.266999999999996
	- type: map_at_10
	value: 61.807
	- type: map_at_100
	value: 62.342
	- type: map_at_1000
	value: 62.36000000000001
	- type: map_at_3
	value: 59.255
	- type: map_at_5
	value: 60.757000000000005
	- type: mrr_at_1
	value: 53.21399999999999
	- type: mrr_at_10
	value: 61.760999999999996
	- type: mrr_at_100
	value: 62.283
	- type: mrr_at_1000
	value: 62.300999999999995
	- type: mrr_at_3
	value: 59.272999999999996
	- type: mrr_at_5
	value: 60.727
	- type: ndcg_at_1
	value: 53.319
	- type: ndcg_at_10
	value: 66.334
	- type: ndcg_at_100
	value: 69.128
	- type: ndcg_at_1000
	value: 69.651
	- type: ndcg_at_3
	value: 61.105
	- type: ndcg_at_5
	value: 63.806
	- type: precision_at_1
	value: 53.319
	- type: precision_at_10
	value: 8.145
	- type: precision_at_100
	value: 0.9530000000000001
	- type: precision_at_1000
	value: 0.099
	- type: precision_at_3
	value: 22.234
	- type: precision_at_5
	value: 14.668000000000001
	- type: recall_at_1
	value: 53.266999999999996
	- type: recall_at_10
	value: 80.717
	- type: recall_at_100
	value: 94.204
	- type: recall_at_1000
	value: 98.419
	- type: recall_at_3
	value: 66.359
	- type: recall_at_5
	value: 72.94500000000001
	- task:
	type: Classification
	dataset:
	type: DDSC/dkhate
	name: MTEB DKHateClassification
	config: default
	split: test
	revision: 59d12749a3c91a186063c7d729ec392fda94681c
	metrics:
	- type: accuracy
	value: 55.89665653495442
	- type: ap
	value: 13.442306681200666
	- type: f1
	value: 45.52792790494033
	- task:
	type: Classification
	dataset:
	type: AI-Sweden/SuperLim
	name: MTEB DalajClassification
	config: default
	split: test
	revision: 7ebf0b4caa7b2ae39698a889de782c09e6f5ee56
	metrics:
	- type: accuracy
	value: 49.77477477477478
	- type: ap
	value: 49.891019810950006
	- type: f1
	value: 49.271004191082156
	- task:
	type: Classification
	dataset:
	type: danish_political_comments
	name: MTEB DanishPoliticalCommentsClassification
	config: default
	split: train
	revision: edbb03726c04a0efab14fc8c3b8b79e4d420e5a1
	metrics:
	- type: accuracy
	value: 28.334721065778517
	- type: f1
	value: 25.604541019064698
	- task:
	type: Retrieval
	dataset:
	type: C-MTEB/DuRetrieval
	name: MTEB DuRetrieval
	config: default
	split: dev
	revision: None
	metrics:
	- type: map_at_1
	value: 21.575
	- type: map_at_10
	value: 65.302
	- type: map_at_100
	value: 68.85
	- type: map_at_1000
	value: 68.94200000000001
	- type: map_at_3
	value: 44.824000000000005
	- type: map_at_5
	value: 56.303000000000004
	- type: mrr_at_1
	value: 77.9
	- type: mrr_at_10
	value: 84.612
	- type: mrr_at_100
	value: 84.774
	- type: mrr_at_1000
	value: 84.78099999999999
	- type: mrr_at_3
	value: 84.05
	- type: mrr_at_5
	value: 84.42699999999999
	- type: ndcg_at_1
	value: 77.9
	- type: ndcg_at_10
	value: 75.247
	- type: ndcg_at_100
	value: 80.252
	- type: ndcg_at_1000
	value: 81.21000000000001
	- type: ndcg_at_3
	value: 73.664
	- type: ndcg_at_5
	value: 72.36200000000001
	- type: precision_at_1
	value: 77.9
	- type: precision_at_10
	value: 36.875
	- type: precision_at_100
	value: 4.607
	- type: precision_at_1000
	value: 0.483
	- type: precision_at_3
	value: 66.567
	- type: precision_at_5
	value: 55.97
	- type: recall_at_1
	value: 21.575
	- type: recall_at_10
	value: 77.268
	- type: recall_at_100
	value: 92.706
	- type: recall_at_1000
	value: 97.721
	- type: recall_at_3
	value: 48.42
	- type: recall_at_5
	value: 62.92
	- task:
	type: Retrieval
	dataset:
	type: C-MTEB/EcomRetrieval
	name: MTEB EcomRetrieval
	config: default
	split: dev
	revision: None
	metrics:
	- type: map_at_1
	value: 41.199999999999996
	- type: map_at_10
	value: 52.12
	- type: map_at_100
	value: 52.878
	- type: map_at_1000
	value: 52.898
	- type: map_at_3
	value: 49.6
	- type: map_at_5
	value: 51.23
	- type: mrr_at_1
	value: 41.199999999999996
	- type: mrr_at_10
	value: 52.12
	- type: mrr_at_100
	value: 52.878
	- type: mrr_at_1000
	value: 52.898
	- type: mrr_at_3
	value: 49.6
	- type: mrr_at_5
	value: 51.23
	- type: ndcg_at_1
	value: 41.199999999999996
	- type: ndcg_at_10
	value: 57.321
	- type: ndcg_at_100
	value: 61.019
	- type: ndcg_at_1000
	value: 61.638000000000005
	- type: ndcg_at_3
	value: 52.20399999999999
	- type: ndcg_at_5
	value: 55.177
	- type: precision_at_1
	value: 41.199999999999996
	- type: precision_at_10
	value: 7.359999999999999
	- type: precision_at_100
	value: 0.909
	- type: precision_at_1000
	value: 0.096
	- type: precision_at_3
	value: 19.900000000000002
	- type: precision_at_5
	value: 13.4
	- type: recall_at_1
	value: 41.199999999999996
	- type: recall_at_10
	value: 73.6
	- type: recall_at_100
	value: 90.9
	- type: recall_at_1000
	value: 95.89999999999999
	- type: recall_at_3
	value: 59.699999999999996
	- type: recall_at_5
	value: 67.0
	- task:
	type: Classification
	dataset:
	type: mteb/emotion
	name: MTEB EmotionClassification
	config: default
	split: test
	revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
	metrics:
	- type: accuracy
	value: 31.514999999999997
	- type: f1
	value: 26.58222460337632
	- task:
	type: Classification
	dataset:
	type: C-MTEB/IFlyTek-classification
	name: MTEB IFlyTek
	config: default
	split: validation
	revision: None
	metrics:
	- type: accuracy
	value: 47.00269334359369
	- type: f1
	value: 35.35096851514498
	- task:
	type: Classification
	dataset:
	type: mteb/imdb
	name: MTEB ImdbClassification
	config: default
	split: test
	revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
	metrics:
	- type: accuracy
	value: 65.1704
	- type: ap
	value: 59.97217670850408
	- type: f1
	value: 64.92509757731281
	- task:
	type: Classification
	dataset:
	type: C-MTEB/JDReview-classification
	name: MTEB JDReview
	config: default
	split: test
	revision: None
	metrics:
	- type: accuracy
	value: 77.33583489681051
	- type: ap
	value: 39.86267586660359
	- type: f1
	value: 71.07975139386433
	- task:
	type: STS
	dataset:
	type: C-MTEB/LCQMC
	name: MTEB LCQMC
	config: default
	split: test
	revision: None
	metrics:
	- type: cos_sim_pearson
	value: 68.22943962011342
	- type: cos_sim_spearman
	value: 74.09285052519111
	- type: euclidean_pearson
	value: 72.99465307442854
	- type: euclidean_spearman
	value: 74.09285052519111
	- type: manhattan_pearson
	value: 73.00139084439715
	- type: manhattan_spearman
	value: 74.07472412844967
	- task:
	type: Classification
	dataset:
	type: DDSC/lcc
	name: MTEB LccSentimentClassification
	config: default
	split: test
	revision: de7ba3406ee55ea2cc52a0a41408fa6aede6d3c6
	metrics:
	- type: accuracy
	value: 42.266666666666666
	- type: f1
	value: 40.963628523464294
	- task:
	type: Reranking
	dataset:
	type: C-MTEB/Mmarco-reranking
	name: MTEB MMarcoReranking
	config: default
	split: dev
	revision: None
	metrics:
	- type: map
	value: 24.311577701296468
	- type: mrr
	value: 23.545238095238094
	- task:
	type: Retrieval
	dataset:
	type: C-MTEB/MMarcoRetrieval
	name: MTEB MMarcoRetrieval
	config: default
	split: dev
	revision: None
	metrics:
	- type: map_at_1
	value: 55.757
	- type: map_at_10
	value: 64.866
	- type: map_at_100
	value: 65.398
	- type: map_at_1000
	value: 65.41900000000001
	- type: map_at_3
	value: 62.634
	- type: map_at_5
	value: 63.993
	- type: mrr_at_1
	value: 57.794000000000004
	- type: mrr_at_10
	value: 65.661
	- type: mrr_at_100
	value: 66.137
	- type: mrr_at_1000
	value: 66.156
	- type: mrr_at_3
	value: 63.625
	- type: mrr_at_5
	value: 64.863
	- type: ndcg_at_1
	value: 57.794000000000004
	- type: ndcg_at_10
	value: 69.107
	- type: ndcg_at_100
	value: 71.56700000000001
	- type: ndcg_at_1000
	value: 72.146
	- type: ndcg_at_3
	value: 64.756
	- type: ndcg_at_5
	value: 67.094
	- type: precision_at_1
	value: 57.794000000000004
	- type: precision_at_10
	value: 8.656
	- type: precision_at_100
	value: 0.989
	- type: precision_at_1000
	value: 0.104
	- type: precision_at_3
	value: 24.623
	- type: precision_at_5
	value: 15.991
	- type: recall_at_1
	value: 55.757
	- type: recall_at_10
	value: 81.55799999999999
	- type: recall_at_100
	value: 92.826
	- type: recall_at_1000
	value: 97.38900000000001
	- type: recall_at_3
	value: 69.903
	- type: recall_at_5
	value: 75.497
	- task:
	type: Classification
	dataset:
	type: mteb/mtop_domain
	name: MTEB MTOPDomainClassification (en)
	config: en
	split: test
	revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
	metrics:
	- type: accuracy
	value: 81.20611035111718
	- type: f1
	value: 80.7763576575655
	- task:
	type: Classification
	dataset:
	type: mteb/mtop_domain
	name: MTEB MTOPDomainClassification (de)
	config: de
	split: test
	revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
	metrics:
	- type: accuracy
	value: 57.22175260636799
	- type: f1
	value: 53.81709852420842
	- task:
	type: Classification
	dataset:
	type: mteb/mtop_domain
	name: MTEB MTOPDomainClassification (es)
	config: es
	split: test
	revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
	metrics:
	- type: accuracy
	value: 58.40226817878585
	- type: f1
	value: 57.10362737664957
	- task:
	type: Classification
	dataset:
	type: mteb/mtop_domain
	name: MTEB MTOPDomainClassification (fr)
	config: fr
	split: test
	revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
	metrics:
	- type: accuracy
	value: 54.97337926714688
	- type: f1
	value: 54.14308620410437
	- task:
	type: Classification
	dataset:
	type: mteb/mtop_domain
	name: MTEB MTOPDomainClassification (hi)
	config: hi
	split: test
	revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
	metrics:
	- type: accuracy
	value: 64.16636787378988
	- type: f1
	value: 61.67057141912039
	- task:
	type: Classification
	dataset:
	type: mteb/mtop_domain
	name: MTEB MTOPDomainClassification (th)
	config: th
	split: test
	revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
	metrics:
	- type: accuracy
	value: 70.47377938517178
	- type: f1
	value: 70.31854571152071
	- task:
	type: Classification
	dataset:
	type: mteb/mtop_intent
	name: MTEB MTOPIntentClassification (en)
	config: en
	split: test
	revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
	metrics:
	- type: accuracy
	value: 51.56406748746011
	- type: f1
	value: 35.39870036930897
	- task:
	type: Classification
	dataset:
	type: mteb/mtop_intent
	name: MTEB MTOPIntentClassification (de)
	config: de
	split: test
	revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
	metrics:
	- type: accuracy
	value: 32.17807833192449
	- type: f1
	value: 19.018762850873046
	- task:
	type: Classification
	dataset:
	type: mteb/mtop_intent
	name: MTEB MTOPIntentClassification (es)
	config: es
	split: test
	revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
	metrics:
	- type: accuracy
	value: 33.89593062041361
	- type: f1
	value: 20.385240649662023
	- task:
	type: Classification
	dataset:
	type: mteb/mtop_intent
	name: MTEB MTOPIntentClassification (fr)
	config: fr
	split: test
	revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
	metrics:
	- type: accuracy
	value: 26.689633573441906
	- type: f1
	value: 19.339198990825825
	- task:
	type: Classification
	dataset:
	type: mteb/mtop_intent
	name: MTEB MTOPIntentClassification (hi)
	config: hi
	split: test
	revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
	metrics:
	- type: accuracy
	value: 38.2717820007171
	- type: f1
	value: 20.92023255890095
	- task:
	type: Classification
	dataset:
	type: mteb/mtop_intent
	name: MTEB MTOPIntentClassification (th)
	config: th
	split: test
	revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
	metrics:
	- type: accuracy
	value: 42.72694394213382
	- type: f1
	value: 30.207341681902918
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_massive_intent
	name: MTEB MassiveIntentClassification (af)
	config: af
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 33.496973772696705
	- type: f1
	value: 30.700367642324967
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_massive_intent
	name: MTEB MassiveIntentClassification (am)
	config: am
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 19.559515803631474
	- type: f1
	value: 16.655700010020094
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_massive_intent
	name: MTEB MassiveIntentClassification (ar)
	config: ar
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 26.46267652992602
	- type: f1
	value: 23.470618969045958
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_massive_intent
	name: MTEB MassiveIntentClassification (az)
	config: az
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 31.577000672494947
	- type: f1
	value: 29.663054588730454
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_massive_intent
	name: MTEB MassiveIntentClassification (bn)
	config: bn
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 27.985877605917953
	- type: f1
	value: 25.140738617026408
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_massive_intent
	name: MTEB MassiveIntentClassification (cy)
	config: cy
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 28.261600537995967
	- type: f1
	value: 25.406976600356344
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_massive_intent
	name: MTEB MassiveIntentClassification (da)
	config: da
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 40.373234700739744
	- type: f1
	value: 36.84775969220266
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_massive_intent
	name: MTEB MassiveIntentClassification (de)
	config: de
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 34.20309347679893
	- type: f1
	value: 29.937516367091355
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_massive_intent
	name: MTEB MassiveIntentClassification (el)
	config: el
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 26.01546738399462
	- type: f1
	value: 23.974936009024375
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_massive_intent
	name: MTEB MassiveIntentClassification (en)
	config: en
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 60.48419636852724
	- type: f1
	value: 57.07615823930852
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_massive_intent
	name: MTEB MassiveIntentClassification (es)
	config: es
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 36.368527236045736
	- type: f1
	value: 35.28610128351216
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_massive_intent
	name: MTEB MassiveIntentClassification (fa)
	config: fa
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 48.913920645595155
	- type: f1
	value: 45.10811063972933
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_massive_intent
	name: MTEB MassiveIntentClassification (fi)
	config: fi
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 30.114324142568925
	- type: f1
	value: 27.789916812631493
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_massive_intent
	name: MTEB MassiveIntentClassification (fr)
	config: fr
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 37.53194351042367
	- type: f1
	value: 35.77870968876826
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_massive_intent
	name: MTEB MassiveIntentClassification (he)
	config: he
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 24.858776059179558
	- type: f1
	value: 24.016121696621195
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_massive_intent
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	config: hi
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 39.14256893073302
	- type: f1
	value: 35.82510556127162
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_massive_intent
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	config: hu
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 31.97041022192334
	- type: f1
	value: 29.964722488737355
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_massive_intent
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	config: hy
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 31.355077336919972
	- type: f1
	value: 27.175518791441
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_massive_intent
	name: MTEB MassiveIntentClassification (id)
	config: id
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 37.03765971755212
	- type: f1
	value: 35.94269966729341
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_massive_intent
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	config: is
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 28.6079354404842
	- type: f1
	value: 25.780613738124625
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_massive_intent
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	config: it
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 37.85810356422326
	- type: f1
	value: 35.910057289042975
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_massive_intent
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	config: ja
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 47.901815736381984
	- type: f1
	value: 44.49582926460981
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_massive_intent
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	config: jv
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 29.078681909885677
	- type: f1
	value: 27.191374864489585
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_massive_intent
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	config: ka
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 25.770006724949564
	- type: f1
	value: 23.628483056948564
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_massive_intent
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	config: km
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 23.661735036987224
	- type: f1
	value: 20.66379761523298
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_massive_intent
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	config: kn
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 21.267652992602553
	- type: f1
	value: 18.69704378377225
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_massive_intent
	name: MTEB MassiveIntentClassification (ko)
	config: ko
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 40.42367182246133
	- type: f1
	value: 37.08072704015134
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_massive_intent
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	config: lv
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 30.12777404169469
	- type: f1
	value: 28.12098399487521
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_massive_intent
	name: MTEB MassiveIntentClassification (ml)
	config: ml
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 25.89105581708137
	- type: f1
	value: 23.62828321219826
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_massive_intent
	name: MTEB MassiveIntentClassification (mn)
	config: mn
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 27.713517148621385
	- type: f1
	value: 26.39822334010705
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_massive_intent
	name: MTEB MassiveIntentClassification (ms)
	config: ms
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 33.03631472763954
	- type: f1
	value: 32.08618313202589
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_massive_intent
	name: MTEB MassiveIntentClassification (my)
	config: my
	split: test
	revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
	metrics:
	- type: accuracy
	value: 24.193006052454603
	- type: f1
	value: 20.242784930454743
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_massive_intent
	name: MTEB MassiveIntentClassification (nb)
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	value: 45.16139878950908
	- type: f1
	value: 40.874809080044805
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_massive_scenario
	name: MTEB MassiveScenarioClassification (sw)
	config: sw
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 36.0221923335575
	- type: f1
	value: 31.880593511438942
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_massive_scenario
	name: MTEB MassiveScenarioClassification (ta)
	config: ta
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 37.80766644250168
	- type: f1
	value: 35.80909783577956
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_massive_scenario
	name: MTEB MassiveScenarioClassification (te)
	config: te
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 34.5965030262273
	- type: f1
	value: 33.552796756090274
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_massive_scenario
	name: MTEB MassiveScenarioClassification (th)
	config: th
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 57.38399462004035
	- type: f1
	value: 53.92067950173084
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_massive_scenario
	name: MTEB MassiveScenarioClassification (tl)
	config: tl
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 39.36112979152656
	- type: f1
	value: 35.73348460761388
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_massive_scenario
	name: MTEB MassiveScenarioClassification (tr)
	config: tr
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 36.163416274377944
	- type: f1
	value: 35.36946437302125
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_massive_scenario
	name: MTEB MassiveScenarioClassification (ur)
	config: ur
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 36.425689307330195
	- type: f1
	value: 35.72323238273122
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_massive_scenario
	name: MTEB MassiveScenarioClassification (vi)
	config: vi
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 47.04438466711499
	- type: f1
	value: 46.775815838841666
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_massive_scenario
	name: MTEB MassiveScenarioClassification (zh-CN)
	config: zh-CN
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 75.69266980497646
	- type: f1
	value: 75.03810873420112
	- task:
	type: Classification
	dataset:
	type: mteb/amazon_massive_scenario
	name: MTEB MassiveScenarioClassification (zh-TW)
	config: zh-TW
	split: test
	revision: 7d571f92784cd94a019292a1f45445077d0ef634
	metrics:
	- type: accuracy
	value: 71.96032279757902
	- type: f1
	value: 71.05327209484685
	- task:
	type: Retrieval
	dataset:
	type: C-MTEB/MedicalRetrieval
	name: MTEB MedicalRetrieval
	config: default
	split: dev
	revision: None
	metrics:
	- type: map_at_1
	value: 41.3
	- type: map_at_10
	value: 46.753
	- type: map_at_100
	value: 47.344
	- type: map_at_1000
	value: 47.410000000000004
	- type: map_at_3
	value: 45.533
	- type: map_at_5
	value: 46.248
	- type: mrr_at_1
	value: 41.5
	- type: mrr_at_10
	value: 46.853
	- type: mrr_at_100
	value: 47.443999999999996
	- type: mrr_at_1000
	value: 47.510000000000005
	- type: mrr_at_3
	value: 45.633
	- type: mrr_at_5
	value: 46.348
	- type: ndcg_at_1
	value: 41.3
	- type: ndcg_at_10
	value: 49.283
	- type: ndcg_at_100
	value: 52.602000000000004
	- type: ndcg_at_1000
	value: 54.556000000000004
	- type: ndcg_at_3
	value: 46.793
	- type: ndcg_at_5
	value: 48.075
	- type: precision_at_1
	value: 41.3
	- type: precision_at_10
	value: 5.72
	- type: precision_at_100
	value: 0.738
	- type: precision_at_1000
	value: 0.09
	- type: precision_at_3
	value: 16.8
	- type: precision_at_5
	value: 10.7
	- type: recall_at_1
	value: 41.3
	- type: recall_at_10
	value: 57.199999999999996
	- type: recall_at_100
	value: 73.8
	- type: recall_at_1000
	value: 89.60000000000001
	- type: recall_at_3
	value: 50.4
	- type: recall_at_5
	value: 53.5
	- task:
	type: Clustering
	dataset:
	type: mteb/medrxiv-clustering-p2p
	name: MTEB MedrxivClusteringP2P
	config: default
	split: test
	revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
	metrics:
	- type: v_measure
	value: 31.936450521634473
	- task:
	type: Clustering
	dataset:
	type: mteb/medrxiv-clustering-s2s
	name: MTEB MedrxivClusteringS2S
	config: default
	split: test
	revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
	metrics:
	- type: v_measure
	value: 28.047583673034808
	- task:
	type: Classification
	dataset:
	type: C-MTEB/MultilingualSentiment-classification
	name: MTEB MultilingualSentiment
	config: default
	split: validation
	revision: None
	metrics:
	- type: accuracy
	value: 69.17
	- type: f1
	value: 68.72937085716812
	- task:
	type: Classification
	dataset:
	type: ScandEval/norec-mini
	name: MTEB NoRecClassification
	config: default
	split: test
	revision: 07b99ab3363c2e7f8f87015b01c21f4d9b917ce3
	metrics:
	- type: accuracy
	value: 43.5302734375
	- type: f1
	value: 40.85343331953274
	- task:
	type: Classification
	dataset:
	type: NbAiLab/norwegian_parliament
	name: MTEB NorwegianParliament
	config: default
	split: test
	revision: f7393532774c66312378d30b197610b43d751972
	metrics:
	- type: accuracy
	value: 54.900000000000006
	- type: ap
	value: 52.72583551130585
	- type: f1
	value: 54.72449827992906
	- task:
	type: PairClassification
	dataset:
	type: C-MTEB/OCNLI
	name: MTEB Ocnli
	config: default
	split: validation
	revision: None
	metrics:
	- type: cos_sim_accuracy
	value: 70.27612344342177
	- type: cos_sim_ap
	value: 73.44116481862304
	- type: cos_sim_f1
	value: 72.28607918263091
	- type: cos_sim_precision
	value: 60.556348074179745
	- type: cos_sim_recall
	value: 89.65153115100317
	- type: dot_accuracy
	value: 70.27612344342177
	- type: dot_ap
	value: 73.44116481862304
	- type: dot_f1
	value: 72.28607918263091
	- type: dot_precision
	value: 60.556348074179745
	- type: dot_recall
	value: 89.65153115100317
	- type: euclidean_accuracy
	value: 70.27612344342177
	- type: euclidean_ap
	value: 73.44116481862304
	- type: euclidean_f1
	value: 72.28607918263091
	- type: euclidean_precision
	value: 60.556348074179745
	- type: euclidean_recall
	value: 89.65153115100317
	- type: manhattan_accuracy
	value: 70.38440714672441
	- type: manhattan_ap
	value: 73.46922542436253
	- type: manhattan_f1
	value: 72.38838318162117
	- type: manhattan_precision
	value: 61.39705882352941
	- type: manhattan_recall
	value: 88.17317845828934
	- type: max_accuracy
	value: 70.38440714672441
	- type: max_ap
	value: 73.46922542436253
	- type: max_f1
	value: 72.38838318162117
	- task:
	type: Classification
	dataset:
	type: C-MTEB/OnlineShopping-classification
	name: MTEB OnlineShopping
	config: default
	split: test
	revision: None
	metrics:
	- type: accuracy
	value: 89.79000000000002
	- type: ap
	value: 87.04275277120101
	- type: f1
	value: 89.77446550482388
	- task:
	type: Classification
	dataset:
	type: laugustyniak/abusive-clauses-pl
	name: MTEB PAC
	config: default
	split: test
	revision: None
	metrics:
	- type: accuracy
	value: 57.138719953663475
	- type: ap
	value: 72.7490265036156
	- type: f1
	value: 55.67596841902006
	- task:
	type: STS
	dataset:
	type: C-MTEB/PAWSX
	name: MTEB PAWSX
	config: default
	split: test
	revision: None
	metrics:
	- type: cos_sim_pearson
	value: 11.928849138540556
	- type: cos_sim_spearman
	value: 12.182908575820269
	- type: euclidean_pearson
	value: 14.455528347393356
	- type: euclidean_spearman
	value: 12.182908575820269
	- type: manhattan_pearson
	value: 14.506141564058982
	- type: manhattan_spearman
	value: 12.25397844569351
	- task:
	type: PairClassification
	dataset:
	type: PL-MTEB/ppc-pairclassification
	name: MTEB PPC
	config: default
	split: test
	revision: None
	metrics:
	- type: cos_sim_accuracy
	value: 67.0
	- type: cos_sim_ap
	value: 70.19022218012687
	- type: cos_sim_f1
	value: 75.44529262086515
	- type: cos_sim_precision
	value: 61.2603305785124
	- type: cos_sim_recall
	value: 98.17880794701986
	- type: dot_accuracy
	value: 67.0
	- type: dot_ap
	value: 70.19022218012687
	- type: dot_f1
	value: 75.44529262086515
	- type: dot_precision
	value: 61.2603305785124
	- type: dot_recall
	value: 98.17880794701986
	- type: euclidean_accuracy
	value: 67.0
	- type: euclidean_ap
	value: 70.19022218012687
	- type: euclidean_f1
	value: 75.44529262086515
	- type: euclidean_precision
	value: 61.2603305785124
	- type: euclidean_recall
	value: 98.17880794701986
	- type: manhattan_accuracy
	value: 66.7
	- type: manhattan_ap
	value: 70.20851258919818
	- type: manhattan_f1
	value: 75.40574282147317
	- type: manhattan_precision
	value: 60.52104208416834
	- type: manhattan_recall
	value: 100.0
	- type: max_accuracy
	value: 67.0
	- type: max_ap
	value: 70.20851258919818
	- type: max_f1
	value: 75.44529262086515
	- task:
	type: PairClassification
	dataset:
	type: PL-MTEB/psc-pairclassification
	name: MTEB PSC
	config: default
	split: test
	revision: None
	metrics:
	- type: cos_sim_accuracy
	value: 83.20964749536178
	- type: cos_sim_ap
	value: 77.83239751517948
	- type: cos_sim_f1
	value: 70.17045454545455
	- type: cos_sim_precision
	value: 65.69148936170212
	- type: cos_sim_recall
	value: 75.3048780487805
	- type: dot_accuracy
	value: 83.20964749536178
	- type: dot_ap
	value: 77.83239751517948
	- type: dot_f1
	value: 70.17045454545455
	- type: dot_precision
	value: 65.69148936170212
	- type: dot_recall
	value: 75.3048780487805
	- type: euclidean_accuracy
	value: 83.20964749536178
	- type: euclidean_ap
	value: 77.83239751517948
	- type: euclidean_f1
	value: 70.17045454545455
	- type: euclidean_precision
	value: 65.69148936170212
	- type: euclidean_recall
	value: 75.3048780487805
	- type: manhattan_accuracy
	value: 82.74582560296847
	- type: manhattan_ap
	value: 77.71434418573791
	- type: manhattan_f1
	value: 69.89720998531571
	- type: manhattan_precision
	value: 67.42209631728045
	- type: manhattan_recall
	value: 72.5609756097561
	- type: max_accuracy
	value: 83.20964749536178
	- type: max_ap
	value: 77.83239751517948
	- type: max_f1
	value: 70.17045454545455
	- task:
	type: Classification
	dataset:
	type: PL-MTEB/polemo2_in
	name: MTEB PolEmo2.0-IN
	config: default
	split: test
	revision: None
	metrics:
	- type: accuracy
	value: 40.96952908587258
	- type: f1
	value: 40.34996985581621
	- task:
	type: Classification
	dataset:
	type: PL-MTEB/polemo2_out
	name: MTEB PolEmo2.0-OUT
	config: default
	split: test
	revision: None
	metrics:
	- type: accuracy
	value: 17.57085020242915
	- type: f1
	value: 13.699227854176883
	- task:
	type: STS
	dataset:
	type: C-MTEB/QBQTC
	name: MTEB QBQTC
	config: default
	split: test
	revision: None
	metrics:
	- type: cos_sim_pearson
	value: 28.3302552745107
	- type: cos_sim_spearman
	value: 29.935415470590353
	- type: euclidean_pearson
	value: 28.406125326818536
	- type: euclidean_spearman
	value: 29.935394196825893
	- type: manhattan_pearson
	value: 28.535226539445524
	- type: manhattan_spearman
	value: 30.110291572017182
	- task:
	type: Clustering
	dataset:
	type: mteb/reddit-clustering
	name: MTEB RedditClustering
	config: default
	split: test
	revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
	metrics:
	- type: v_measure
	value: 30.831283224792134
	- task:
	type: Clustering
	dataset:
	type: mteb/reddit-clustering-p2p
	name: MTEB RedditClusteringP2P
	config: default
	split: test
	revision: 282350215ef01743dc01b456c7f5241fa8937f16
	metrics:
	- type: v_measure
	value: 46.29339268141013
	- task:
	type: PairClassification
	dataset:
	type: PL-MTEB/sicke-pl-pairclassification
	name: MTEB SICK-E-PL
	config: default
	split: test
	revision: None
	metrics:
	- type: cos_sim_accuracy
	value: 73.11455360782715
	- type: cos_sim_ap
	value: 46.51191750197438
	- type: cos_sim_f1
	value: 53.48066298342542
	- type: cos_sim_precision
	value: 43.682310469314075
	- type: cos_sim_recall
	value: 68.94586894586895
	- type: dot_accuracy
	value: 73.11455360782715
	- type: dot_ap
	value: 46.511775041787075
	- type: dot_f1
	value: 53.48066298342542
	- type: dot_precision
	value: 43.682310469314075
	- type: dot_recall
	value: 68.94586894586895
	- type: euclidean_accuracy
	value: 73.11455360782715
	- type: euclidean_ap
	value: 46.51191750197438
	- type: euclidean_f1
	value: 53.48066298342542
	- type: euclidean_precision
	value: 43.682310469314075
	- type: euclidean_recall
	value: 68.94586894586895
	- type: manhattan_accuracy
	value: 73.11455360782715
	- type: manhattan_ap
	value: 46.514972647839905
	- type: manhattan_f1
	value: 53.430821147356575
	- type: manhattan_precision
	value: 44.1449814126394
	- type: manhattan_recall
	value: 67.66381766381767
	- type: max_accuracy
	value: 73.11455360782715
	- type: max_ap
	value: 46.514972647839905
	- type: max_f1
	value: 53.48066298342542
	- task:
	type: STS
	dataset:
	type: mteb/sts22-crosslingual-sts
	name: MTEB STS22 (zh)
	config: zh
	split: test
	revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
	metrics:
	- type: cos_sim_pearson
	value: 65.06521909332356
	- type: cos_sim_spearman
	value: 66.05535986394263
	- type: euclidean_pearson
	value: 65.77030042276493
	- type: euclidean_spearman
	value: 66.05535986394263
	- type: manhattan_pearson
	value: 65.91869122430603
	- type: manhattan_spearman
	value: 66.15477943325074
	- task:
	type: STS
	dataset:
	type: C-MTEB/STSB
	name: MTEB STSB
	config: default
	split: test
	revision: None
	metrics:
	- type: cos_sim_pearson
	value: 79.77776864632986
	- type: cos_sim_spearman
	value: 80.54295891407341
	- type: euclidean_pearson
	value: 80.15310049503712
	- type: euclidean_spearman
	value: 80.54295891407341
	- type: manhattan_pearson
	value: 80.16703044389185
	- type: manhattan_spearman
	value: 80.61034669195091
	- task:
	type: Classification
	dataset:
	type: ScandEval/scala-da
	name: MTEB ScalaDaClassification
	config: default
	split: test
	revision: 1de08520a7b361e92ffa2a2201ebd41942c54675
	metrics:
	- type: accuracy
	value: 50.1123046875
	- type: ap
	value: 50.05839950666221
	- type: f1
	value: 49.75320900875982
	- task:
	type: Classification
	dataset:
	type: ScandEval/scala-sv
	name: MTEB ScalaSvClassification
	config: default
	split: test
	revision: 1b48e3dcb02872335ff985ff938a054a4ed99008
	metrics:
	- type: accuracy
	value: 49.8193359375
	- type: ap
	value: 49.91266630748165
	- type: f1
	value: 49.56571584707715
	- task:
	type: PairClassification
	dataset:
	type: mteb/sprintduplicatequestions-pairclassification
	name: MTEB SprintDuplicateQuestions
	config: default
	split: test
	revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
	metrics:
	- type: cos_sim_accuracy
	value: 99.71188118811881
	- type: cos_sim_ap
	value: 90.71339192859018
	- type: cos_sim_f1
	value: 85.26740665993945
	- type: cos_sim_precision
	value: 86.0488798370672
	- type: cos_sim_recall
	value: 84.5
	- type: dot_accuracy
	value: 99.71188118811881
	- type: dot_ap
	value: 90.71339192859018
	- type: dot_f1
	value: 85.26740665993945
	- type: dot_precision
	value: 86.0488798370672
	- type: dot_recall
	value: 84.5
	- type: euclidean_accuracy
	value: 99.71188118811881
	- type: euclidean_ap
	value: 90.71339192859018
	- type: euclidean_f1
	value: 85.26740665993945
	- type: euclidean_precision
	value: 86.0488798370672
	- type: euclidean_recall
	value: 84.5
	- type: manhattan_accuracy
	value: 99.71881188118812
	- type: manhattan_ap
	value: 91.25511397395691
	- type: manhattan_f1
	value: 85.48548548548548
	- type: manhattan_precision
	value: 85.57114228456913
	- type: manhattan_recall
	value: 85.39999999999999
	- type: max_accuracy
	value: 99.71881188118812
	- type: max_ap
	value: 91.25511397395691
	- type: max_f1
	value: 85.48548548548548
	- task:
	type: Clustering
	dataset:
	type: mteb/stackexchange-clustering
	name: MTEB StackExchangeClustering
	config: default
	split: test
	revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
	metrics:
	- type: v_measure
	value: 39.44467533846411
	- task:
	type: Clustering
	dataset:
	type: mteb/stackexchange-clustering-p2p
	name: MTEB StackExchangeClusteringP2P
	config: default
	split: test
	revision: 815ca46b2622cec33ccafc3735d572c266efdb44
	metrics:
	- type: v_measure
	value: 32.60878918655969
	- task:
	type: Classification
	dataset:
	type: ScandEval/swerec-mini
	name: MTEB SweRecClassification
	config: default
	split: test
	revision: 3c62f26bafdc4c4e1c16401ad4b32f0a94b46612
	metrics:
	- type: accuracy
	value: 62.9736328125
	- type: f1
	value: 55.59659753835253
	- task:
	type: Reranking
	dataset:
	type: C-MTEB/T2Reranking
	name: MTEB T2Reranking
	config: default
	split: dev
	revision: None
	metrics:
	- type: map
	value: 67.18460327564007
	- type: mrr
	value: 77.58419442026417
	- task:
	type: Retrieval
	dataset:
	type: C-MTEB/T2Retrieval
	name: MTEB T2Retrieval
	config: default
	split: dev
	revision: None
	metrics:
	- type: map_at_1
	value: 24.196
	- type: map_at_10
	value: 66.633
	- type: map_at_100
	value: 70.417
	- type: map_at_1000
	value: 70.54
	- type: map_at_3
	value: 47.166999999999994
	- type: map_at_5
	value: 57.711
	- type: mrr_at_1
	value: 83.947
	- type: mrr_at_10
	value: 87.47500000000001
	- type: mrr_at_100
	value: 87.62100000000001
	- type: mrr_at_1000
	value: 87.628
	- type: mrr_at_3
	value: 86.813
	- type: mrr_at_5
	value: 87.202
	- type: ndcg_at_1
	value: 83.943
	- type: ndcg_at_10
	value: 75.936
	- type: ndcg_at_100
	value: 80.73700000000001
	- type: ndcg_at_1000
	value: 81.989
	- type: ndcg_at_3
	value: 78.417
	- type: ndcg_at_5
	value: 76.301
	- type: precision_at_1
	value: 83.943
	- type: precision_at_10
	value: 37.984
	- type: precision_at_100
	value: 4.772
	- type: precision_at_1000
	value: 0.507
	- type: precision_at_3
	value: 68.911
	- type: precision_at_5
	value: 57.267
	- type: recall_at_1
	value: 24.196
	- type: recall_at_10
	value: 74.67099999999999
	- type: recall_at_100
	value: 90.18599999999999
	- type: recall_at_1000
	value: 96.54700000000001
	- type: recall_at_3
	value: 49.217
	- type: recall_at_5
	value: 61.765
	- task:
	type: Classification
	dataset:
	type: C-MTEB/TNews-classification
	name: MTEB TNews
	config: default
	split: validation
	revision: None
	metrics:
	- type: accuracy
	value: 49.769
	- type: f1
	value: 48.06519294990893
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (sqi-eng)
	config: sqi-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 20.4
	- type: f1
	value: 15.828455908556528
	- type: precision
	value: 14.818339585714199
	- type: recall
	value: 20.4
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (fry-eng)
	config: fry-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 26.589595375722542
	- type: f1
	value: 19.027433709514636
	- type: precision
	value: 17.053635189473336
	- type: recall
	value: 26.589595375722542
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (kur-eng)
	config: kur-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 8.780487804878048
	- type: f1
	value: 6.111094140071713
	- type: precision
	value: 5.623318968152088
	- type: recall
	value: 8.780487804878048
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (tur-eng)
	config: tur-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 12.4
	- type: f1
	value: 9.377654588051435
	- type: precision
	value: 8.787308104062777
	- type: recall
	value: 12.4
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (deu-eng)
	config: deu-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 23.0
	- type: f1
	value: 20.202147869674185
	- type: precision
	value: 19.391492475731603
	- type: recall
	value: 23.0
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (nld-eng)
	config: nld-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 34.1
	- type: f1
	value: 29.410775916893563
	- type: precision
	value: 28.070429087454624
	- type: recall
	value: 34.1
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (ron-eng)
	config: ron-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 20.599999999999998
	- type: f1
	value: 17.35632359863931
	- type: precision
	value: 16.518293570846236
	- type: recall
	value: 20.599999999999998
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (ang-eng)
	config: ang-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 20.8955223880597
	- type: f1
	value: 13.264176317293085
	- type: precision
	value: 11.76782203505206
	- type: recall
	value: 20.8955223880597
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (ido-eng)
	config: ido-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 15.6
	- type: f1
	value: 11.7763376390295
	- type: precision
	value: 10.914347870755636
	- type: recall
	value: 15.6
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (jav-eng)
	config: jav-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 10.24390243902439
	- type: f1
	value: 6.743976890318354
	- type: precision
	value: 6.10895202358617
	- type: recall
	value: 10.24390243902439
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (isl-eng)
	config: isl-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 9.700000000000001
	- type: f1
	value: 7.491822942738051
	- type: precision
	value: 7.074516864427855
	- type: recall
	value: 9.700000000000001
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (slv-eng)
	config: slv-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 14.094775212636696
	- type: f1
	value: 10.166440808088712
	- type: precision
	value: 9.417657228214015
	- type: recall
	value: 14.094775212636696
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (cym-eng)
	config: cym-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 8.521739130434783
	- type: f1
	value: 5.637620426566197
	- type: precision
	value: 5.181579047619263
	- type: recall
	value: 8.521739130434783
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (kaz-eng)
	config: kaz-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 21.913043478260867
	- type: f1
	value: 16.97458403110577
	- type: precision
	value: 15.775659428291005
	- type: recall
	value: 21.913043478260867
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (est-eng)
	config: est-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 7.8
	- type: f1
	value: 5.450419697471649
	- type: precision
	value: 5.062362215300643
	- type: recall
	value: 7.8
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (heb-eng)
	config: heb-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 34.4
	- type: f1
	value: 30.260987068487072
	- type: precision
	value: 28.893481007908996
	- type: recall
	value: 34.4
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (gla-eng)
	config: gla-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 4.2219541616405305
	- type: f1
	value: 2.684516189451713
	- type: precision
	value: 2.463954323534627
	- type: recall
	value: 4.2219541616405305
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (mar-eng)
	config: mar-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 33.300000000000004
	- type: f1
	value: 28.55938229523907
	- type: precision
	value: 27.10483987488783
	- type: recall
	value: 33.300000000000004
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (lat-eng)
	config: lat-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 11.200000000000001
	- type: f1
	value: 7.868244347487681
	- type: precision
	value: 7.121914265161029
	- type: recall
	value: 11.200000000000001
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (bel-eng)
	config: bel-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 29.799999999999997
	- type: f1
	value: 24.34143569640063
	- type: precision
	value: 22.947270794132873
	- type: recall
	value: 29.799999999999997
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (pms-eng)
	config: pms-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 12.95238095238095
	- type: f1
	value: 9.269868736708247
	- type: precision
	value: 8.408018250035058
	- type: recall
	value: 12.95238095238095
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (gle-eng)
	config: gle-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 6.0
	- type: f1
	value: 3.647551182853867
	- type: precision
	value: 3.2680275654986537
	- type: recall
	value: 6.0
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (pes-eng)
	config: pes-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 57.099999999999994
	- type: f1
	value: 51.06459207459208
	- type: precision
	value: 48.901510822510815
	- type: recall
	value: 57.099999999999994
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (nob-eng)
	config: nob-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 32.4
	- type: f1
	value: 27.89405452374492
	- type: precision
	value: 26.51932166043579
	- type: recall
	value: 32.4
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (bul-eng)
	config: bul-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 47.4
	- type: f1
	value: 42.17928673178673
	- type: precision
	value: 40.436673759871375
	- type: recall
	value: 47.4
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (cbk-eng)
	config: cbk-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 14.000000000000002
	- type: f1
	value: 10.949295388694702
	- type: precision
	value: 10.259331172194964
	- type: recall
	value: 14.000000000000002
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (hun-eng)
	config: hun-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 18.2
	- type: f1
	value: 14.773692094643707
	- type: precision
	value: 13.903416806571641
	- type: recall
	value: 18.2
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (uig-eng)
	config: uig-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 4.5
	- type: f1
	value: 2.64568935010746
	- type: precision
	value: 2.4019067331153896
	- type: recall
	value: 4.5
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (rus-eng)
	config: rus-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 65.8
	- type: f1
	value: 60.679131295533736
	- type: precision
	value: 58.812619047619044
	- type: recall
	value: 65.8
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (spa-eng)
	config: spa-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 32.9
	- type: f1
	value: 28.186653736628603
	- type: precision
	value: 26.8010262685625
	- type: recall
	value: 32.9
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (hye-eng)
	config: hye-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 25.60646900269542
	- type: f1
	value: 23.12611992122878
	- type: precision
	value: 22.426345061728544
	- type: recall
	value: 25.60646900269542
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (tel-eng)
	config: tel-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 29.48717948717949
	- type: f1
	value: 23.68695247318436
	- type: precision
	value: 22.09868834868835
	- type: recall
	value: 29.48717948717949
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (afr-eng)
	config: afr-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 16.400000000000002
	- type: f1
	value: 13.221122174926522
	- type: precision
	value: 12.33469931277381
	- type: recall
	value: 16.400000000000002
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (mon-eng)
	config: mon-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 29.772727272727273
	- type: f1
	value: 24.851015943121205
	- type: precision
	value: 23.526050931889745
	- type: recall
	value: 29.772727272727273
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (arz-eng)
	config: arz-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 13.626834381551362
	- type: f1
	value: 11.419087551163022
	- type: precision
	value: 10.700808625336927
	- type: recall
	value: 13.626834381551362
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (hrv-eng)
	config: hrv-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 13.4
	- type: f1
	value: 10.050831111434281
	- type: precision
	value: 9.371874912594967
	- type: recall
	value: 13.4
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (nov-eng)
	config: nov-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 31.1284046692607
	- type: f1
	value: 25.220003329410517
	- type: precision
	value: 23.700114736106954
	- type: recall
	value: 31.1284046692607
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (gsw-eng)
	config: gsw-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 17.94871794871795
	- type: f1
	value: 11.687818354485021
	- type: precision
	value: 10.603332951114169
	- type: recall
	value: 17.94871794871795
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (nds-eng)
	config: nds-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 18.9
	- type: f1
	value: 14.988123337504142
	- type: precision
	value: 14.116226418627315
	- type: recall
	value: 18.9
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (ukr-eng)
	config: ukr-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 44.800000000000004
	- type: f1
	value: 39.7999924337166
	- type: precision
	value: 38.31692251705409
	- type: recall
	value: 44.800000000000004
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (uzb-eng)
	config: uzb-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 5.607476635514018
	- type: f1
	value: 3.5310597299663247
	- type: precision
	value: 3.2762993077737717
	- type: recall
	value: 5.607476635514018
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (lit-eng)
	config: lit-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
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	value: 11.462450592885375
	- type: f1
	value: 7.1683505686002045
	- type: precision
	value: 6.267734051287927
	- type: recall
	value: 11.462450592885375
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (xho-eng)
	config: xho-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 11.267605633802818
	- type: f1
	value: 8.034434678244908
	- type: precision
	value: 7.4930465143804
	- type: recall
	value: 11.267605633802818
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (orv-eng)
	config: orv-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 5.029940119760479
	- type: f1
	value: 3.1094915169923047
	- type: precision
	value: 2.708633372048006
	- type: recall
	value: 5.029940119760479
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (ind-eng)
	config: ind-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 36.7
	- type: f1
	value: 32.12717818306083
	- type: precision
	value: 30.816954398121375
	- type: recall
	value: 36.7
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (tuk-eng)
	config: tuk-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 6.896551724137931
	- type: f1
	value: 4.022988505747127
	- type: precision
	value: 3.3913545619534733
	- type: recall
	value: 6.896551724137931
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (max-eng)
	config: max-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 19.366197183098592
	- type: f1
	value: 13.728751930776578
	- type: precision
	value: 12.40776989741364
	- type: recall
	value: 19.366197183098592
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (swh-eng)
	config: swh-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 9.743589743589745
	- type: f1
	value: 6.368220492881125
	- type: precision
	value: 5.755926465392591
	- type: recall
	value: 9.743589743589745
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (hin-eng)
	config: hin-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 55.2
	- type: f1
	value: 49.45361290600652
	- type: precision
	value: 47.434083591084736
	- type: recall
	value: 55.2
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (dsb-eng)
	config: dsb-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 6.6805845511482245
	- type: f1
	value: 4.493424007014965
	- type: precision
	value: 4.131033519879768
	- type: recall
	value: 6.6805845511482245
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (ber-eng)
	config: ber-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 4.5
	- type: f1
	value: 2.488223360284137
	- type: precision
	value: 2.1928034718812546
	- type: recall
	value: 4.5
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (tam-eng)
	config: tam-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 31.921824104234524
	- type: f1
	value: 26.717853265084536
	- type: precision
	value: 25.08341519742171
	- type: recall
	value: 31.921824104234524
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (slk-eng)
	config: slk-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 17.4
	- type: f1
	value: 14.049848881932899
	- type: precision
	value: 13.225483025465493
	- type: recall
	value: 17.4
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (tgl-eng)
	config: tgl-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 7.9
	- type: f1
	value: 5.764422668778745
	- type: precision
	value: 5.318704596860335
	- type: recall
	value: 7.9
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (ast-eng)
	config: ast-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 23.62204724409449
	- type: f1
	value: 17.735908011498562
	- type: precision
	value: 16.31534545023977
	- type: recall
	value: 23.62204724409449
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (mkd-eng)
	config: mkd-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 19.400000000000002
	- type: f1
	value: 16.688139723374675
	- type: precision
	value: 16.0446811984312
	- type: recall
	value: 19.400000000000002
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (khm-eng)
	config: khm-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 19.390581717451525
	- type: f1
	value: 15.330085364864166
	- type: precision
	value: 14.23910323480727
	- type: recall
	value: 19.390581717451525
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (ces-eng)
	config: ces-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 14.899999999999999
	- type: f1
	value: 11.89041342121772
	- type: precision
	value: 11.273006536745667
	- type: recall
	value: 14.899999999999999
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (tzl-eng)
	config: tzl-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 24.03846153846154
	- type: f1
	value: 20.606022267206477
	- type: precision
	value: 19.935897435897438
	- type: recall
	value: 24.03846153846154
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (urd-eng)
	config: urd-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 29.599999999999998
	- type: f1
	value: 24.793469753676277
	- type: precision
	value: 23.43004941257573
	- type: recall
	value: 29.599999999999998
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (ara-eng)
	config: ara-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 24.6
	- type: f1
	value: 19.561599234099237
	- type: precision
	value: 18.231733884473016
	- type: recall
	value: 24.6
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (kor-eng)
	config: kor-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 53.800000000000004
	- type: f1
	value: 48.1892730115302
	- type: precision
	value: 46.16164682539682
	- type: recall
	value: 53.800000000000004
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (yid-eng)
	config: yid-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 3.6556603773584904
	- type: f1
	value: 2.2631181434426764
	- type: precision
	value: 2.082608234687079
	- type: recall
	value: 3.6556603773584904
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (fin-eng)
	config: fin-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 16.0
	- type: f1
	value: 13.533088016975684
	- type: precision
	value: 12.965331925224502
	- type: recall
	value: 16.0
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (tha-eng)
	config: tha-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 65.69343065693431
	- type: f1
	value: 60.208146297669686
	- type: precision
	value: 58.18983631939836
	- type: recall
	value: 65.69343065693431
	- task:
	type: BitextMining
	dataset:
	type: mteb/tatoeba-bitext-mining
	name: MTEB Tatoeba (wuu-eng)
	config: wuu-eng
	split: test
	revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
	metrics:
	- type: accuracy
	value: 78.2
	- type: f1
	value: 73.25492063492062
	- type: precision
	value: 71.14833333333334
	- type: recall
	value: 78.2
	- task:
	type: Clustering
	dataset:
	type: slvnwhrl/tenkgnad-clustering-p2p
	name: MTEB TenKGnadClusteringP2P
	config: default
	split: test
	revision: 5c59e41555244b7e45c9a6be2d720ab4bafae558
	metrics:
	- type: v_measure
	value: 29.791089429037896
	- task:
	type: Clustering
	dataset:
	type: slvnwhrl/tenkgnad-clustering-s2s
	name: MTEB TenKGnadClusteringS2S
	config: default
	split: test
	revision: 6cddbe003f12b9b140aec477b583ac4191f01786
	metrics:
	- type: v_measure
	value: 11.270010272065322
	- task:
	type: Clustering
	dataset:
	type: C-MTEB/ThuNewsClusteringP2P
	name: MTEB ThuNewsClusteringP2P
	config: default
	split: test
	revision: None
	metrics:
	- type: v_measure
	value: 55.805739403705914
	- task:
	type: Clustering
	dataset:
	type: C-MTEB/ThuNewsClusteringS2S
	name: MTEB ThuNewsClusteringS2S
	config: default
	split: test
	revision: None
	metrics:
	- type: v_measure
	value: 50.50265410416623
	- task:
	type: Classification
	dataset:
	type: mteb/toxic_conversations_50k
	name: MTEB ToxicConversationsClassification
	config: default
	split: test
	revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
	metrics:
	- type: accuracy
	value: 65.6482
	- type: ap
	value: 11.625197643165249
	- type: f1
	value: 50.23643212069197
	- task:
	type: Classification
	dataset:
	type: mteb/tweet_sentiment_extraction
	name: MTEB TweetSentimentExtractionClassification
	config: default
	split: test
	revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
	metrics:
	- type: accuracy
	value: 57.41086587436334
	- type: f1
	value: 57.58586420979367
	- task:
	type: Clustering
	dataset:
	type: mteb/twentynewsgroups-clustering
	name: MTEB TwentyNewsgroupsClustering
	config: default
	split: test
	revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
	metrics:
	- type: v_measure
	value: 26.543120146469633
	- task:
	type: PairClassification
	dataset:
	type: mteb/twittersemeval2015-pairclassification
	name: MTEB TwitterSemEval2015
	config: default
	split: test
	revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
	metrics:
	- type: cos_sim_accuracy
	value: 81.49848006198962
	- type: cos_sim_ap
	value: 58.06838035805121
	- type: cos_sim_f1
	value: 55.897019598747534
	- type: cos_sim_precision
	value: 49.86550796606662
	- type: cos_sim_recall
	value: 63.58839050131926
	- type: dot_accuracy
	value: 81.49848006198962
	- type: dot_ap
	value: 58.06837481847699
	- type: dot_f1
	value: 55.897019598747534
	- type: dot_precision
	value: 49.86550796606662
	- type: dot_recall
	value: 63.58839050131926
	- type: euclidean_accuracy
	value: 81.49848006198962
	- type: euclidean_ap
	value: 58.06838167667462
	- type: euclidean_f1
	value: 55.897019598747534
	- type: euclidean_precision
	value: 49.86550796606662
	- type: euclidean_recall
	value: 63.58839050131926
	- type: manhattan_accuracy
	value: 81.43291410860107
	- type: manhattan_ap
	value: 57.83294460595276
	- type: manhattan_f1
	value: 55.628827131417815
	- type: manhattan_precision
	value: 50.233943002977455
	- type: manhattan_recall
	value: 62.321899736147756
	- type: max_accuracy
	value: 81.49848006198962
	- type: max_ap
	value: 58.06838167667462
	- type: max_f1
	value: 55.897019598747534
	- task:
	type: PairClassification
	dataset:
	type: mteb/twitterurlcorpus-pairclassification
	name: MTEB TwitterURLCorpus
	config: default
	split: test
	revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
	metrics:
	- type: cos_sim_accuracy
	value: 87.24725423991929
	- type: cos_sim_ap
	value: 82.09462792672173
	- type: cos_sim_f1
	value: 74.30311032863851
	- type: cos_sim_precision
	value: 70.95124684785654
	- type: cos_sim_recall
	value: 77.98737295965506
	- type: dot_accuracy
	value: 87.24725423991929
	- type: dot_ap
	value: 82.0946313711965
	- type: dot_f1
	value: 74.30311032863851
	- type: dot_precision
	value: 70.95124684785654
	- type: dot_recall
	value: 77.98737295965506
	- type: euclidean_accuracy
	value: 87.24725423991929
	- type: euclidean_ap
	value: 82.09462900001712
	- type: euclidean_f1
	value: 74.30311032863851
	- type: euclidean_precision
	value: 70.95124684785654
	- type: euclidean_recall
	value: 77.98737295965506
	- type: manhattan_accuracy
	value: 87.30934916753988
	- type: manhattan_ap
	value: 82.22847590036976
	- type: manhattan_f1
	value: 74.5143604081188
	- type: manhattan_precision
	value: 70.50779907922765
	- type: manhattan_recall
	value: 79.00369571912535
	- type: max_accuracy
	value: 87.30934916753988
	- type: max_ap
	value: 82.22847590036976
	- type: max_f1
	value: 74.5143604081188
	- task:
	type: Retrieval
	dataset:
	type: C-MTEB/VideoRetrieval
	name: MTEB VideoRetrieval
	config: default
	split: dev
	revision: None
	metrics:
	- type: map_at_1
	value: 44.800000000000004
	- type: map_at_10
	value: 54.806
	- type: map_at_100
	value: 55.477
	- type: map_at_1000
	value: 55.498999999999995
	- type: map_at_3
	value: 52.333
	- type: map_at_5
	value: 53.933
	- type: mrr_at_1
	value: 44.800000000000004
	- type: mrr_at_10
	value: 54.806
	- type: mrr_at_100
	value: 55.477
	- type: mrr_at_1000
	value: 55.498999999999995
	- type: mrr_at_3
	value: 52.333
	- type: mrr_at_5
	value: 53.933
	- type: ndcg_at_1
	value: 44.800000000000004
	- type: ndcg_at_10
	value: 59.75899999999999
	- type: ndcg_at_100
	value: 63.171
	- type: ndcg_at_1000
	value: 63.818
	- type: ndcg_at_3
	value: 54.790000000000006
	- type: ndcg_at_5
	value: 57.652
	- type: precision_at_1
	value: 44.800000000000004
	- type: precision_at_10
	value: 7.53
	- type: precision_at_100
	value: 0.9159999999999999
	- type: precision_at_1000
	value: 0.097
	- type: precision_at_3
	value: 20.633000000000003
	- type: precision_at_5
	value: 13.76
	- type: recall_at_1
	value: 44.800000000000004
	- type: recall_at_10
	value: 75.3
	- type: recall_at_100
	value: 91.60000000000001
	- type: recall_at_1000
	value: 96.8
	- type: recall_at_3
	value: 61.9
	- type: recall_at_5
	value: 68.8
	- task:
	type: Classification
	dataset:
	type: C-MTEB/waimai-classification
	name: MTEB Waimai
	config: default
	split: test
	revision: None
	metrics:
	- type: accuracy
	value: 84.33999999999999
	- type: ap
	value: 65.75892461630445
	- type: f1
	value: 82.55845192469975
	---

	---
	license: apache-2.0
	---