metadata
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
- 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:
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revision: None
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split: dev
revision: None
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revision: None
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dataset:
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dataset:
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dataset:
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dataset:
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dataset:
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dataset:
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dataset:
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dataset:
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dataset:
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dataset:
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dataset:
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dataset:
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- task:
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dataset:
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dataset:
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dataset:
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dataset:
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metrics:
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metrics:
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dataset:
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metrics:
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metrics:
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metrics:
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dataset:
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metrics:
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metrics:
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dataset:
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metrics:
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metrics:
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dataset:
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split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
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config: zh-CN
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
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dataset:
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config: zh-TW
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
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value: 71.96032279757902
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dataset:
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name: MTEB MedicalRetrieval
config: default
split: dev
revision: None
metrics:
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value: 41.3
- type: map_at_10
value: 46.753
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value: 47.344
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value: 45.533
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value: 0.09
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value: 41.3
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value: 73.8
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value: 89.60000000000001
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value: 50.4
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value: 53.5
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type: Clustering
dataset:
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config: default
split: test
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
metrics:
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value: 31.936450521634473
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dataset:
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config: default
split: test
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
metrics:
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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
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value: 40.85343331953274
- task:
type: Classification
dataset:
type: NbAiLab/norwegian_parliament
name: MTEB NorwegianParliament
config: default
split: test
revision: f7393532774c66312378d30b197610b43d751972
metrics:
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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
- 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
- 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
- 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
- type: max_accuracy
value: 67
- 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
- type: f1
value: 20.202147869674185
- type: precision
value: 19.391492475731603
- type: recall
value: 23
- 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
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type: BitextMining
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metrics:
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revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 33.300000000000004
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revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 29.799999999999997
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config: pms-eng
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revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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metrics:
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dataset:
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revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 57.099999999999994
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dataset:
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metrics:
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value: 32.4
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dataset:
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revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 47.4
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dataset:
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metrics:
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dataset:
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metrics:
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value: 18.2
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dataset:
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revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 4.5
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dataset:
type: mteb/tatoeba-bitext-mining
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config: rus-eng
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revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 65.8
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dataset:
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revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 32.9
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dataset:
type: mteb/tatoeba-bitext-mining
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config: hye-eng
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revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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dataset:
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config: tel-eng
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revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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dataset:
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config: afr-eng
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revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 16.400000000000002
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dataset:
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config: mon-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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dataset:
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config: arz-eng
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revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 13.626834381551362
- task:
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dataset:
type: mteb/tatoeba-bitext-mining
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config: hrv-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 13.4
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value: 13.4
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type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
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config: nov-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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dataset:
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config: gsw-eng
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revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 17.94871794871795
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dataset:
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config: nds-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 18.9
- task:
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dataset:
type: mteb/tatoeba-bitext-mining
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config: ukr-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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dataset:
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config: uzb-eng
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revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 5.607476635514018
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type: BitextMining
dataset:
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config: lit-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 11
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value: 11
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type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
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config: ina-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 27.700000000000003
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dataset:
type: mteb/tatoeba-bitext-mining
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config: lfn-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 12.1
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type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
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config: zsm-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 35.099999999999994
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dataset:
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config: ita-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 20.5
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dataset:
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config: cmn-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 89.3
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value: 89.3
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dataset:
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config: lvs-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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dataset:
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config: glg-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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dataset:
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config: ceb-eng
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revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 6.5
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type: BitextMining
dataset:
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config: bre-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 4.5
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value: 4.5
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dataset:
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config: ben-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 28.4
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value: 28.4
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type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
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config: swg-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 16.071428571428573
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type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
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config: arq-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 5.26893523600439
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value: 3.7779047220052937
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value: 5.26893523600439
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type: BitextMining
dataset:
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config: kab-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 1.3
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value: 1.3
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type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
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config: fra-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 24
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value: 19.96240217555452
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value: 24
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type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (por-eng)
config: por-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 33.6
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value: 28.597393691065413
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value: 33.6
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type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (tat-eng)
config: tat-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 4.5
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value: 4.5
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type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
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config: oci-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 8.7
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value: 6.688281884758027
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value: 8.7
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type: BitextMining
dataset:
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config: pol-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 17.4
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value: 14.513506869901672
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value: 17.4
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type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (war-eng)
config: war-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 6.6000000000000005
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value: 4.54242126134823
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value: 6.6000000000000005
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dataset:
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name: MTEB Tatoeba (aze-eng)
config: aze-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 11.799999999999999
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value: 7.820128737629438
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value: 11.799999999999999
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (vie-eng)
config: vie-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 55.50000000000001
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value: 49.56005716505717
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value: 55.50000000000001
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (nno-eng)
config: nno-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy
value: 16.900000000000002
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value: 13.80254156510093
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value: 13.026236549222661
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value: 16.900000000000002
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (cha-eng)
config: cha-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 14.5985401459854
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value: 9.10786699107867
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value: 7.985485722712
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value: 14.5985401459854
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (mhr-eng)
config: mhr-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy
value: 5.7
- type: f1
value: 3.5188978346475572
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value: 3.158298308588556
- type: recall
value: 5.7
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (dan-eng)
config: dan-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy
value: 30.5
- type: f1
value: 25.997416905156033
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value: 24.596070762988056
- type: recall
value: 30.5
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (ell-eng)
config: ell-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy
value: 11.700000000000001
- type: f1
value: 9.498482945625803
- type: precision
value: 8.987285930402825
- type: recall
value: 11.700000000000001
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (amh-eng)
config: amh-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy
value: 8.333333333333332
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value: 5.745982981006023
- type: precision
value: 5.401133186459273
- type: recall
value: 8.333333333333332
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (pam-eng)
config: pam-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy
value: 5
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value: 3.085855110083055
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value: 2.816700840061992
- type: recall
value: 5
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (hsb-eng)
config: hsb-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy
value: 8.902691511387163
- type: f1
value: 6.435632935092832
- type: precision
value: 5.983137847614094
- type: recall
value: 8.902691511387163
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (srp-eng)
config: srp-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy
value: 15.5
- type: f1
value: 12.91642697840956
- type: precision
value: 12.27655802325753
- type: recall
value: 15.5
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (epo-eng)
config: epo-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy
value: 10.6
- type: f1
value: 8.25444066151791
- type: precision
value: 7.838679485283888
- type: recall
value: 10.6
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (kzj-eng)
config: kzj-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy
value: 3.5000000000000004
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value: 2.339236097978308
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value: 2.223062696511718
- type: recall
value: 3.5000000000000004
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (awa-eng)
config: awa-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy
value: 22.51082251082251
- type: f1
value: 16.74832651150451
- type: precision
value: 15.469328651146835
- type: recall
value: 22.51082251082251
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (fao-eng)
config: fao-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy
value: 9.16030534351145
- type: f1
value: 6.340001193595815
- type: precision
value: 5.839561202156622
- type: recall
value: 9.16030534351145
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (mal-eng)
config: mal-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy
value: 42.066957787481805
- type: f1
value: 36.61324818401623
- type: precision
value: 34.71464471808596
- type: recall
value: 42.066957787481805
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (ile-eng)
config: ile-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy
value: 21.5
- type: f1
value: 17.235331398320522
- type: precision
value: 16.204611769215212
- type: recall
value: 21.5
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (bos-eng)
config: bos-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy
value: 22.598870056497177
- type: f1
value: 15.808069297141552
- type: precision
value: 14.216539784336394
- type: recall
value: 22.598870056497177
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (cor-eng)
config: cor-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy
value: 3.9
- type: f1
value: 1.9378227948724842
- type: precision
value: 1.7177968874340983
- type: recall
value: 3.9
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (cat-eng)
config: cat-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy
value: 20.200000000000003
- type: f1
value: 15.962850129692935
- type: precision
value: 14.831492566514589
- type: recall
value: 20.200000000000003
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (eus-eng)
config: eus-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy
value: 9.700000000000001
- type: f1
value: 7.3770897326135305
- type: precision
value: 6.927006519505818
- type: recall
value: 9.700000000000001
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (yue-eng)
config: yue-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy
value: 63.5
- type: f1
value: 58.353888888888896
- type: precision
value: 56.41114468864469
- type: recall
value: 63.5
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (swe-eng)
config: swe-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy
value: 26
- type: f1
value: 21.75037437399202
- type: precision
value: 20.57120606116242
- type: recall
value: 26
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (dtp-eng)
config: dtp-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy
value: 2.4
- type: f1
value: 1.7611348003539113
- type: precision
value: 1.6490144671379943
- type: recall
value: 2.4
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (kat-eng)
config: kat-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy
value: 38.605898123324394
- type: f1
value: 33.00341324278513
- type: precision
value: 31.243423531164034
- type: recall
value: 38.605898123324394
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (jpn-eng)
config: jpn-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy
value: 57.4
- type: f1
value: 52.341290679908326
- type: precision
value: 50.74419584500466
- type: recall
value: 57.4
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (csb-eng)
config: csb-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy
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
- type: f1
value: 13.533088016975684
- type: precision
value: 12.965331925224502
- type: recall
value: 16
- 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