metadata
tags:
- mteb
model-index:
- name: e5-mistral-7b-instruct
results:
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en)
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
- type: accuracy
value: 78.68656716417911
- type: ap
value: 41.71522322900398
- type: f1
value: 72.37207703532552
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (de)
config: de
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
- type: accuracy
value: 74.04710920770879
- type: ap
value: 83.42622221864045
- type: f1
value: 72.14388257905772
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en-ext)
config: en-ext
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
- type: accuracy
value: 77.93103448275862
- type: ap
value: 26.039284760509513
- type: f1
value: 64.81092954450712
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (ja)
config: ja
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
- type: accuracy
value: 77.21627408993577
- type: ap
value: 24.876490553983036
- type: f1
value: 63.8773359684989
- task:
type: Classification
dataset:
type: mteb/amazon_polarity
name: MTEB AmazonPolarityClassification
config: default
split: test
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
metrics:
- type: accuracy
value: 95.90679999999999
- type: ap
value: 94.32357863164454
- type: f1
value: 95.90485634708557
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (en)
config: en
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy
value: 55.786
- type: f1
value: 55.31211995815146
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (de)
config: de
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy
value: 53.26
- type: f1
value: 52.156230111544986
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (es)
config: es
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy
value: 50.33
- type: f1
value: 49.195023008878145
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (fr)
config: fr
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy
value: 49.3
- type: f1
value: 48.434470184108
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (ja)
config: ja
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy
value: 48.68599999999999
- type: f1
value: 47.62681775202072
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (zh)
config: zh
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy
value: 46.238
- type: f1
value: 45.014030559653705
- task:
type: Retrieval
dataset:
type: arguana
name: MTEB ArguAna
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 36.486000000000004
- type: map_at_10
value: 53.076
- type: map_at_100
value: 53.657999999999994
- type: map_at_1000
value: 53.659
- type: map_at_3
value: 48.234
- type: map_at_5
value: 51.121
- type: mrr_at_1
value: 37.269000000000005
- type: mrr_at_10
value: 53.335
- type: mrr_at_100
value: 53.916
- type: mrr_at_1000
value: 53.918
- type: mrr_at_3
value: 48.518
- type: mrr_at_5
value: 51.406
- type: ndcg_at_1
value: 36.486000000000004
- type: ndcg_at_10
value: 61.882000000000005
- type: ndcg_at_100
value: 64.165
- type: ndcg_at_1000
value: 64.203
- type: ndcg_at_3
value: 52.049
- type: ndcg_at_5
value: 57.199
- type: precision_at_1
value: 36.486000000000004
- type: precision_at_10
value: 8.982999999999999
- type: precision_at_100
value: 0.9939999999999999
- type: precision_at_1000
value: 0.1
- type: precision_at_3
value: 21.029
- type: precision_at_5
value: 15.092
- type: recall_at_1
value: 36.486000000000004
- type: recall_at_10
value: 89.82900000000001
- type: recall_at_100
value: 99.36
- type: recall_at_1000
value: 99.644
- type: recall_at_3
value: 63.087
- type: recall_at_5
value: 75.46199999999999
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-p2p
name: MTEB ArxivClusteringP2P
config: default
split: test
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
metrics:
- type: v_measure
value: 50.45119266859667
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-s2s
name: MTEB ArxivClusteringS2S
config: default
split: test
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
metrics:
- type: v_measure
value: 45.4958298992051
- task:
type: Reranking
dataset:
type: mteb/askubuntudupquestions-reranking
name: MTEB AskUbuntuDupQuestions
config: default
split: test
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
metrics:
- type: map
value: 66.98177472838887
- type: mrr
value: 79.91854636591478
- task:
type: STS
dataset:
type: mteb/biosses-sts
name: MTEB BIOSSES
config: default
split: test
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
metrics:
- type: cos_sim_pearson
value: 87.67086498650698
- type: cos_sim_spearman
value: 85.54773239564638
- type: euclidean_pearson
value: 86.48229161588425
- type: euclidean_spearman
value: 85.54773239564638
- type: manhattan_pearson
value: 86.67533327742343
- type: manhattan_spearman
value: 85.76099026691983
- 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: 99.5615866388309
- type: f1
value: 99.49895615866389
- type: precision
value: 99.46764091858039
- type: recall
value: 99.5615866388309
- 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: 99.19656614571869
- type: f1
value: 99.08650671362535
- type: precision
value: 99.0314769975787
- type: recall
value: 99.19656614571869
- 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: 98.0256321440942
- type: f1
value: 97.83743216718624
- type: precision
value: 97.74390947927492
- type: recall
value: 98.0256321440942
- 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: 99.26276987888363
- type: f1
value: 99.22766368264
- type: precision
value: 99.21011058451816
- type: recall
value: 99.26276987888363
- task:
type: Classification
dataset:
type: mteb/banking77
name: MTEB Banking77Classification
config: default
split: test
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
metrics:
- type: accuracy
value: 88.22727272727272
- type: f1
value: 88.17411732496673
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-p2p
name: MTEB BiorxivClusteringP2P
config: default
split: test
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
metrics:
- type: v_measure
value: 43.530637846246975
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-s2s
name: MTEB BiorxivClusteringS2S
config: default
split: test
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
metrics:
- type: v_measure
value: 40.23505728593893
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 27.162333333333333
- type: map_at_10
value: 37.22291666666667
- type: map_at_100
value: 38.56733333333333
- type: map_at_1000
value: 38.684250000000006
- type: map_at_3
value: 34.22858333333333
- type: map_at_5
value: 35.852500000000006
- type: mrr_at_1
value: 32.459833333333336
- type: mrr_at_10
value: 41.65358333333333
- type: mrr_at_100
value: 42.566916666666664
- type: mrr_at_1000
value: 42.61766666666667
- type: mrr_at_3
value: 39.210499999999996
- type: mrr_at_5
value: 40.582166666666666
- type: ndcg_at_1
value: 32.459833333333336
- type: ndcg_at_10
value: 42.96758333333333
- type: ndcg_at_100
value: 48.5065
- type: ndcg_at_1000
value: 50.556583333333336
- type: ndcg_at_3
value: 38.004416666666664
- type: ndcg_at_5
value: 40.25916666666667
- type: precision_at_1
value: 32.459833333333336
- type: precision_at_10
value: 7.664583333333333
- type: precision_at_100
value: 1.2349999999999999
- type: precision_at_1000
value: 0.15966666666666668
- type: precision_at_3
value: 17.731166666666663
- type: precision_at_5
value: 12.575333333333335
- type: recall_at_1
value: 27.162333333333333
- type: recall_at_10
value: 55.44158333333334
- type: recall_at_100
value: 79.56966666666666
- type: recall_at_1000
value: 93.45224999999999
- type: recall_at_3
value: 41.433083333333336
- type: recall_at_5
value: 47.31108333333333
- task:
type: Retrieval
dataset:
type: climate-fever
name: MTEB ClimateFEVER
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 16.539
- type: map_at_10
value: 28.494999999999997
- type: map_at_100
value: 30.568
- type: map_at_1000
value: 30.741000000000003
- type: map_at_3
value: 23.846999999999998
- type: map_at_5
value: 26.275
- type: mrr_at_1
value: 37.394
- type: mrr_at_10
value: 50.068
- type: mrr_at_100
value: 50.727
- type: mrr_at_1000
value: 50.751000000000005
- type: mrr_at_3
value: 46.938
- type: mrr_at_5
value: 48.818
- type: ndcg_at_1
value: 37.394
- type: ndcg_at_10
value: 38.349
- type: ndcg_at_100
value: 45.512
- type: ndcg_at_1000
value: 48.321
- type: ndcg_at_3
value: 32.172
- type: ndcg_at_5
value: 34.265
- type: precision_at_1
value: 37.394
- type: precision_at_10
value: 11.927999999999999
- type: precision_at_100
value: 1.966
- type: precision_at_1000
value: 0.25
- type: precision_at_3
value: 24.126
- type: precision_at_5
value: 18.306
- type: recall_at_1
value: 16.539
- type: recall_at_10
value: 44.504
- type: recall_at_100
value: 68.605
- type: recall_at_1000
value: 84.1
- type: recall_at_3
value: 29.008
- type: recall_at_5
value: 35.58
- task:
type: Retrieval
dataset:
type: dbpedia-entity
name: MTEB DBPedia
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 10.183
- type: map_at_10
value: 23.958
- type: map_at_100
value: 34.354
- type: map_at_1000
value: 36.442
- type: map_at_3
value: 16.345000000000002
- type: map_at_5
value: 19.647000000000002
- type: mrr_at_1
value: 74.25
- type: mrr_at_10
value: 80.976
- type: mrr_at_100
value: 81.256
- type: mrr_at_1000
value: 81.262
- type: mrr_at_3
value: 79.958
- type: mrr_at_5
value: 80.37100000000001
- type: ndcg_at_1
value: 62
- type: ndcg_at_10
value: 48.894999999999996
- type: ndcg_at_100
value: 53.867
- type: ndcg_at_1000
value: 61.304
- type: ndcg_at_3
value: 53.688
- type: ndcg_at_5
value: 50.900999999999996
- type: precision_at_1
value: 74.25
- type: precision_at_10
value: 39.525
- type: precision_at_100
value: 12.323
- type: precision_at_1000
value: 2.539
- type: precision_at_3
value: 57.49999999999999
- type: precision_at_5
value: 49.1
- type: recall_at_1
value: 10.183
- type: recall_at_10
value: 29.296
- type: recall_at_100
value: 60.394999999999996
- type: recall_at_1000
value: 83.12
- type: recall_at_3
value: 17.495
- type: recall_at_5
value: 22.235
- task:
type: Classification
dataset:
type: mteb/emotion
name: MTEB EmotionClassification
config: default
split: test
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
metrics:
- type: accuracy
value: 49.765
- type: f1
value: 45.93242203574485
- task:
type: Retrieval
dataset:
type: fever
name: MTEB FEVER
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 75.138
- type: map_at_10
value: 84.21300000000001
- type: map_at_100
value: 84.43
- type: map_at_1000
value: 84.441
- type: map_at_3
value: 83.071
- type: map_at_5
value: 83.853
- type: mrr_at_1
value: 80.948
- type: mrr_at_10
value: 88.175
- type: mrr_at_100
value: 88.24
- type: mrr_at_1000
value: 88.241
- type: mrr_at_3
value: 87.516
- type: mrr_at_5
value: 87.997
- type: ndcg_at_1
value: 80.948
- type: ndcg_at_10
value: 87.84100000000001
- type: ndcg_at_100
value: 88.576
- type: ndcg_at_1000
value: 88.75699999999999
- type: ndcg_at_3
value: 86.176
- type: ndcg_at_5
value: 87.214
- type: precision_at_1
value: 80.948
- type: precision_at_10
value: 10.632
- type: precision_at_100
value: 1.123
- type: precision_at_1000
value: 0.11499999999999999
- type: precision_at_3
value: 33.193
- type: precision_at_5
value: 20.663
- type: recall_at_1
value: 75.138
- type: recall_at_10
value: 94.89699999999999
- type: recall_at_100
value: 97.751
- type: recall_at_1000
value: 98.833
- type: recall_at_3
value: 90.455
- type: recall_at_5
value: 93.085
- task:
type: Retrieval
dataset:
type: fiqa
name: MTEB FiQA2018
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 29.45
- type: map_at_10
value: 48.596000000000004
- type: map_at_100
value: 50.70400000000001
- type: map_at_1000
value: 50.83800000000001
- type: map_at_3
value: 42.795
- type: map_at_5
value: 46.085
- type: mrr_at_1
value: 56.172999999999995
- type: mrr_at_10
value: 64.35300000000001
- type: mrr_at_100
value: 64.947
- type: mrr_at_1000
value: 64.967
- type: mrr_at_3
value: 62.653999999999996
- type: mrr_at_5
value: 63.534
- type: ndcg_at_1
value: 56.172999999999995
- type: ndcg_at_10
value: 56.593
- type: ndcg_at_100
value: 62.942
- type: ndcg_at_1000
value: 64.801
- type: ndcg_at_3
value: 53.024
- type: ndcg_at_5
value: 53.986999999999995
- type: precision_at_1
value: 56.172999999999995
- type: precision_at_10
value: 15.494
- type: precision_at_100
value: 2.222
- type: precision_at_1000
value: 0.254
- type: precision_at_3
value: 35.185
- type: precision_at_5
value: 25.556
- type: recall_at_1
value: 29.45
- type: recall_at_10
value: 62.882000000000005
- type: recall_at_100
value: 85.56099999999999
- type: recall_at_1000
value: 96.539
- type: recall_at_3
value: 47.911
- type: recall_at_5
value: 54.52
- task:
type: Retrieval
dataset:
type: hotpotqa
name: MTEB HotpotQA
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 39.581
- type: map_at_10
value: 68.401
- type: map_at_100
value: 69.207
- type: map_at_1000
value: 69.25200000000001
- type: map_at_3
value: 64.689
- type: map_at_5
value: 67.158
- type: mrr_at_1
value: 79.163
- type: mrr_at_10
value: 85.22999999999999
- type: mrr_at_100
value: 85.386
- type: mrr_at_1000
value: 85.39099999999999
- type: mrr_at_3
value: 84.432
- type: mrr_at_5
value: 84.952
- type: ndcg_at_1
value: 79.163
- type: ndcg_at_10
value: 75.721
- type: ndcg_at_100
value: 78.411
- type: ndcg_at_1000
value: 79.23599999999999
- type: ndcg_at_3
value: 70.68799999999999
- type: ndcg_at_5
value: 73.694
- type: precision_at_1
value: 79.163
- type: precision_at_10
value: 16.134
- type: precision_at_100
value: 1.821
- type: precision_at_1000
value: 0.193
- type: precision_at_3
value: 46.446
- type: precision_at_5
value: 30.242
- type: recall_at_1
value: 39.581
- type: recall_at_10
value: 80.66799999999999
- type: recall_at_100
value: 91.033
- type: recall_at_1000
value: 96.408
- type: recall_at_3
value: 69.669
- type: recall_at_5
value: 75.604
- task:
type: Classification
dataset:
type: mteb/imdb
name: MTEB ImdbClassification
config: default
split: test
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
metrics:
- type: accuracy
value: 94.78120000000001
- type: ap
value: 92.52931921594387
- type: f1
value: 94.77902110732532
- task:
type: Retrieval
dataset:
type: msmarco
name: MTEB MSMARCO
config: default
split: dev
revision: None
metrics:
- type: map_at_1
value: 23.363999999999997
- type: map_at_10
value: 36.022
- type: map_at_100
value: 37.229
- type: map_at_1000
value: 37.274
- type: map_at_3
value: 32.131
- type: map_at_5
value: 34.391
- type: mrr_at_1
value: 24.069
- type: mrr_at_10
value: 36.620000000000005
- type: mrr_at_100
value: 37.769999999999996
- type: mrr_at_1000
value: 37.809
- type: mrr_at_3
value: 32.846
- type: mrr_at_5
value: 35.02
- type: ndcg_at_1
value: 24.069
- type: ndcg_at_10
value: 43.056
- type: ndcg_at_100
value: 48.754
- type: ndcg_at_1000
value: 49.829
- type: ndcg_at_3
value: 35.167
- type: ndcg_at_5
value: 39.168
- type: precision_at_1
value: 24.069
- type: precision_at_10
value: 6.762
- type: precision_at_100
value: 0.96
- type: precision_at_1000
value: 0.105
- type: precision_at_3
value: 14.957
- type: precision_at_5
value: 11.023
- type: recall_at_1
value: 23.363999999999997
- type: recall_at_10
value: 64.696
- type: recall_at_100
value: 90.795
- type: recall_at_1000
value: 98.892
- type: recall_at_3
value: 43.247
- type: recall_at_5
value: 52.86300000000001
- task:
type: Classification
dataset:
type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (en)
config: en
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config: az
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
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value: 67.00403496973773
- type: f1
value: 65.97477215779143
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (bn)
config: bn
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
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value: 68.04976462676531
- type: f1
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- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
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config: cy
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
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value: 61.882985877605925
- type: f1
value: 59.995293199988794
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (da)
config: da
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
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value: 76.75857431069267
- type: f1
value: 76.52031675299841
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (de)
config: de
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
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value: 79.03496973772697
- type: f1
value: 79.25548063175344
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (el)
config: el
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
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value: 72.96570275722931
- type: f1
value: 72.19110435289122
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (en)
config: en
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 82.38735709482178
- type: f1
value: 82.34495627619785
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (es)
config: es
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
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value: 78.83994620040352
- type: f1
value: 78.91526355393667
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (fa)
config: fa
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
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value: 76.7350369872226
- type: f1
value: 75.919437344927
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (fi)
config: fi
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
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value: 71.21721587088096
- type: f1
value: 70.82973286243262
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (fr)
config: fr
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
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value: 78.59784801613988
- type: f1
value: 78.47383161087423
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (he)
config: he
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
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value: 69.64021519838602
- type: f1
value: 68.45118053027653
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (hi)
config: hi
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
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value: 73.51042367182245
- type: f1
value: 72.90013022879003
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (hu)
config: hu
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
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value: 74.0551445864156
- type: f1
value: 73.45871761713292
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (hy)
config: hy
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 59.54606590450571
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value: 57.72711794953869
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (id)
config: id
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 77.40753194351042
- type: f1
value: 76.8157455506521
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (is)
config: is
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
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value: 66.58372562205783
- type: f1
value: 65.2654868709758
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (it)
config: it
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 78.39273705447208
- type: f1
value: 78.3592956594837
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (ja)
config: ja
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
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value: 79.62004034969739
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value: 79.78673754501855
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (jv)
config: jv
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
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value: 64.29051782111634
- type: f1
value: 63.12502587609454
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (ka)
config: ka
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
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value: 57.51849361129791
- type: f1
value: 56.32320906403241
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (km)
config: km
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
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value: 52.41761936785474
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value: 49.113762010098306
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (kn)
config: kn
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
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value: 58.547410894418284
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value: 56.87580674198118
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (ko)
config: ko
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 78.89038332212507
- type: f1
value: 79.09210140529848
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (lv)
config: lv
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
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value: 63.503698722259585
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value: 61.45718858568352
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (ml)
config: ml
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
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value: 54.02824478816408
- type: f1
value: 52.732738981386504
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (mn)
config: mn
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 54.23671822461331
- type: f1
value: 52.688080372545286
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (ms)
config: ms
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
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value: 75.5312710154674
- type: f1
value: 74.59368478550698
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (my)
config: my
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
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value: 52.192333557498316
- type: f1
value: 50.18302290152229
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (nb)
config: nb
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
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value: 75.6960322797579
- type: f1
value: 75.25331182714856
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (nl)
config: nl
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
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value: 78.47679892400808
- type: f1
value: 78.24044732352424
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (pl)
config: pl
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
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value: 77.36718224613315
- type: f1
value: 77.2714452985389
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (pt)
config: pt
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 77.96234028244788
- type: f1
value: 78.21282127011372
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (ro)
config: ro
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
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value: 73.19435104236717
- type: f1
value: 73.1963711292812
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (ru)
config: ru
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 80.52118359112306
- type: f1
value: 80.4179964390288
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (sl)
config: sl
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 73.65837256220577
- type: f1
value: 73.07156989634905
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (sq)
config: sq
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
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value: 64.02824478816409
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value: 62.972399027713664
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (sv)
config: sv
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 78.87020847343645
- type: f1
value: 78.224240866849
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (sw)
config: sw
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
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value: 64.6570275722932
- type: f1
value: 63.274871811412545
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (ta)
config: ta
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 57.760591795561524
- type: f1
value: 56.73711528075771
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (te)
config: te
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 57.26967047747142
- type: f1
value: 55.74735330863165
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (th)
config: th
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 72.46133154001345
- type: f1
value: 71.9644168952811
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (tl)
config: tl
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 73.70880968392737
- type: f1
value: 73.61543141070884
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (tr)
config: tr
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 75.0437121721587
- type: f1
value: 74.83359868879921
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (ur)
config: ur
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 67.05110961667788
- type: f1
value: 66.25869819274315
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (vi)
config: vi
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 75.52118359112306
- type: f1
value: 75.92098546052303
- 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: 79.92938802958977
- type: f1
value: 79.79833572573796
- 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: 76.86617350369872
- type: f1
value: 77.42645654909516
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-p2p
name: MTEB MedrxivClusteringP2P
config: default
split: test
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
metrics:
- type: v_measure
value: 38.192667527616315
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-s2s
name: MTEB MedrxivClusteringS2S
config: default
split: test
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
metrics:
- type: v_measure
value: 37.44738902946689
- task:
type: Reranking
dataset:
type: mteb/mind_small
name: MTEB MindSmallReranking
config: default
split: test
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
metrics:
- type: map
value: 32.59661273103955
- type: mrr
value: 33.82024242497473
- task:
type: Retrieval
dataset:
type: nfcorpus
name: MTEB NFCorpus
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 5.471
- type: map_at_10
value: 14.142
- type: map_at_100
value: 18.179000000000002
- type: map_at_1000
value: 19.772000000000002
- type: map_at_3
value: 9.716
- type: map_at_5
value: 11.763
- type: mrr_at_1
value: 51.393
- type: mrr_at_10
value: 58.814
- type: mrr_at_100
value: 59.330000000000005
- type: mrr_at_1000
value: 59.35
- type: mrr_at_3
value: 56.398
- type: mrr_at_5
value: 58.038999999999994
- type: ndcg_at_1
value: 49.69
- type: ndcg_at_10
value: 38.615
- type: ndcg_at_100
value: 35.268
- type: ndcg_at_1000
value: 43.745
- type: ndcg_at_3
value: 43.187
- type: ndcg_at_5
value: 41.528999999999996
- type: precision_at_1
value: 51.083999999999996
- type: precision_at_10
value: 29.474
- type: precision_at_100
value: 9.167
- type: precision_at_1000
value: 2.2089999999999996
- type: precision_at_3
value: 40.351
- type: precision_at_5
value: 36.285000000000004
- type: recall_at_1
value: 5.471
- type: recall_at_10
value: 19.242
- type: recall_at_100
value: 37.14
- type: recall_at_1000
value: 68.35900000000001
- type: recall_at_3
value: 10.896
- type: recall_at_5
value: 14.75
- task:
type: Retrieval
dataset:
type: nq
name: MTEB NQ
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 39.499
- type: map_at_10
value: 55.862
- type: map_at_100
value: 56.667
- type: map_at_1000
value: 56.684999999999995
- type: map_at_3
value: 51.534
- type: map_at_5
value: 54.2
- type: mrr_at_1
value: 44.351
- type: mrr_at_10
value: 58.567
- type: mrr_at_100
value: 59.099000000000004
- type: mrr_at_1000
value: 59.109
- type: mrr_at_3
value: 55.218999999999994
- type: mrr_at_5
value: 57.391999999999996
- type: ndcg_at_1
value: 44.322
- type: ndcg_at_10
value: 63.535
- type: ndcg_at_100
value: 66.654
- type: ndcg_at_1000
value: 66.991
- type: ndcg_at_3
value: 55.701
- type: ndcg_at_5
value: 60.06700000000001
- type: precision_at_1
value: 44.322
- type: precision_at_10
value: 10.026
- type: precision_at_100
value: 1.18
- type: precision_at_1000
value: 0.121
- type: precision_at_3
value: 24.865000000000002
- type: precision_at_5
value: 17.48
- type: recall_at_1
value: 39.499
- type: recall_at_10
value: 84.053
- type: recall_at_100
value: 97.11
- type: recall_at_1000
value: 99.493
- type: recall_at_3
value: 64.091
- type: recall_at_5
value: 74.063
- task:
type: Retrieval
dataset:
type: quora
name: MTEB QuoraRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 71.911
- type: map_at_10
value: 86.087
- type: map_at_100
value: 86.701
- type: map_at_1000
value: 86.715
- type: map_at_3
value: 83.231
- type: map_at_5
value: 85.051
- type: mrr_at_1
value: 82.75
- type: mrr_at_10
value: 88.759
- type: mrr_at_100
value: 88.844
- type: mrr_at_1000
value: 88.844
- type: mrr_at_3
value: 87.935
- type: mrr_at_5
value: 88.504
- type: ndcg_at_1
value: 82.75
- type: ndcg_at_10
value: 89.605
- type: ndcg_at_100
value: 90.664
- type: ndcg_at_1000
value: 90.733
- type: ndcg_at_3
value: 87.03
- type: ndcg_at_5
value: 88.473
- type: precision_at_1
value: 82.75
- type: precision_at_10
value: 13.575000000000001
- type: precision_at_100
value: 1.539
- type: precision_at_1000
value: 0.157
- type: precision_at_3
value: 38.153
- type: precision_at_5
value: 25.008000000000003
- type: recall_at_1
value: 71.911
- type: recall_at_10
value: 96.261
- type: recall_at_100
value: 99.72800000000001
- type: recall_at_1000
value: 99.993
- type: recall_at_3
value: 88.762
- type: recall_at_5
value: 92.949
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering
name: MTEB RedditClustering
config: default
split: test
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
metrics:
- type: v_measure
value: 57.711581165572376
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering-p2p
name: MTEB RedditClusteringP2P
config: default
split: test
revision: 282350215ef01743dc01b456c7f5241fa8937f16
metrics:
- type: v_measure
value: 66.48938885750297
- task:
type: Retrieval
dataset:
type: scidocs
name: MTEB SCIDOCS
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 3.7379999999999995
- type: map_at_10
value: 9.261
- type: map_at_100
value: 11.001
- type: map_at_1000
value: 11.262
- type: map_at_3
value: 6.816
- type: map_at_5
value: 8
- type: mrr_at_1
value: 18.4
- type: mrr_at_10
value: 28.755999999999997
- type: mrr_at_100
value: 29.892000000000003
- type: mrr_at_1000
value: 29.961
- type: mrr_at_3
value: 25.467000000000002
- type: mrr_at_5
value: 27.332
- type: ndcg_at_1
value: 18.4
- type: ndcg_at_10
value: 16.296
- type: ndcg_at_100
value: 23.52
- type: ndcg_at_1000
value: 28.504
- type: ndcg_at_3
value: 15.485
- type: ndcg_at_5
value: 13.471
- type: precision_at_1
value: 18.4
- type: precision_at_10
value: 8.469999999999999
- type: precision_at_100
value: 1.8950000000000002
- type: precision_at_1000
value: 0.309
- type: precision_at_3
value: 14.6
- type: precision_at_5
value: 11.84
- type: recall_at_1
value: 3.7379999999999995
- type: recall_at_10
value: 17.185
- type: recall_at_100
value: 38.397
- type: recall_at_1000
value: 62.798
- type: recall_at_3
value: 8.896999999999998
- type: recall_at_5
value: 12.021999999999998
- task:
type: STS
dataset:
type: mteb/sickr-sts
name: MTEB SICK-R
config: default
split: test
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
metrics:
- type: cos_sim_pearson
value: 86.43977757480083
- type: cos_sim_spearman
value: 82.64182475199533
- type: euclidean_pearson
value: 83.71756009999591
- type: euclidean_spearman
value: 82.64182331395057
- type: manhattan_pearson
value: 83.8028936913025
- type: manhattan_spearman
value: 82.71024597804252
- task:
type: STS
dataset:
type: mteb/sts12-sts
name: MTEB STS12
config: default
split: test
revision: a0d554a64d88156834ff5ae9920b964011b16384
metrics:
- type: cos_sim_pearson
value: 86.85653060698912
- type: cos_sim_spearman
value: 79.65598885228324
- type: euclidean_pearson
value: 83.1205137628455
- type: euclidean_spearman
value: 79.65629387709038
- type: manhattan_pearson
value: 83.71108853545837
- type: manhattan_spearman
value: 80.25617619716708
- task:
type: STS
dataset:
type: mteb/sts13-sts
name: MTEB STS13
config: default
split: test
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
metrics:
- type: cos_sim_pearson
value: 88.22921688565664
- type: cos_sim_spearman
value: 88.42662103041957
- type: euclidean_pearson
value: 87.91679798473325
- type: euclidean_spearman
value: 88.42662103041957
- type: manhattan_pearson
value: 88.16927537961303
- type: manhattan_spearman
value: 88.81581680062541
- task:
type: STS
dataset:
type: mteb/sts14-sts
name: MTEB STS14
config: default
split: test
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
metrics:
- type: cos_sim_pearson
value: 86.77261424554293
- type: cos_sim_spearman
value: 84.53930146434155
- type: euclidean_pearson
value: 85.67420491389697
- type: euclidean_spearman
value: 84.53929771783851
- type: manhattan_pearson
value: 85.74306784515618
- type: manhattan_spearman
value: 84.7399304675314
- task:
type: STS
dataset:
type: mteb/sts15-sts
name: MTEB STS15
config: default
split: test
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
metrics:
- type: cos_sim_pearson
value: 89.86138395166455
- type: cos_sim_spearman
value: 90.42577823022054
- type: euclidean_pearson
value: 89.8787763797515
- type: euclidean_spearman
value: 90.42577823022054
- type: manhattan_pearson
value: 89.9592937492158
- type: manhattan_spearman
value: 90.63535505335524
- task:
type: STS
dataset:
type: mteb/sts16-sts
name: MTEB STS16
config: default
split: test
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
metrics:
- type: cos_sim_pearson
value: 86.5176674585941
- type: cos_sim_spearman
value: 87.6842917085397
- type: euclidean_pearson
value: 86.70213081520711
- type: euclidean_spearman
value: 87.6842917085397
- type: manhattan_pearson
value: 86.83702628983627
- type: manhattan_spearman
value: 87.87791000374443
- task:
type: STS
dataset:
type: mteb/sts17-crosslingual-sts
name: MTEB STS17 (en-en)
config: en-en
split: test
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
metrics:
- type: cos_sim_pearson
value: 91.6934766230911
- type: cos_sim_spearman
value: 91.76610452580849
- type: euclidean_pearson
value: 91.84972362904293
- type: euclidean_spearman
value: 91.76610452580849
- type: manhattan_pearson
value: 91.72471134652476
- type: manhattan_spearman
value: 91.57332965544492
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (en)
config: en
split: test
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
metrics:
- type: cos_sim_pearson
value: 67.53254210885925
- type: cos_sim_spearman
value: 66.97079949935386
- type: euclidean_pearson
value: 68.19500839554337
- type: euclidean_spearman
value: 66.97079949935386
- type: manhattan_pearson
value: 68.39083341409233
- type: manhattan_spearman
value: 67.09308082453076
- task:
type: STS
dataset:
type: mteb/stsbenchmark-sts
name: MTEB STSBenchmark
config: default
split: test
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
metrics:
- type: cos_sim_pearson
value: 87.68273341294419
- type: cos_sim_spearman
value: 88.59927164210958
- type: euclidean_pearson
value: 88.10745681818025
- type: euclidean_spearman
value: 88.59927164210958
- type: manhattan_pearson
value: 88.25166703784649
- type: manhattan_spearman
value: 88.85343247873482
- task:
type: Reranking
dataset:
type: mteb/scidocs-reranking
name: MTEB SciDocsRR
config: default
split: test
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
metrics:
- type: map
value: 86.3340463345719
- type: mrr
value: 96.5182611506141
- task:
type: Retrieval
dataset:
type: scifact
name: MTEB SciFact
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 60.967000000000006
- type: map_at_10
value: 71.873
- type: map_at_100
value: 72.271
- type: map_at_1000
value: 72.292
- type: map_at_3
value: 69.006
- type: map_at_5
value: 70.856
- type: mrr_at_1
value: 63.666999999999994
- type: mrr_at_10
value: 72.929
- type: mrr_at_100
value: 73.26
- type: mrr_at_1000
value: 73.282
- type: mrr_at_3
value: 71.111
- type: mrr_at_5
value: 72.328
- type: ndcg_at_1
value: 63.666999999999994
- type: ndcg_at_10
value: 76.414
- type: ndcg_at_100
value: 78.152
- type: ndcg_at_1000
value: 78.604
- type: ndcg_at_3
value: 71.841
- type: ndcg_at_5
value: 74.435
- type: precision_at_1
value: 63.666999999999994
- type: precision_at_10
value: 10.067
- type: precision_at_100
value: 1.097
- type: precision_at_1000
value: 0.11299999999999999
- type: precision_at_3
value: 27.667
- type: precision_at_5
value: 18.467
- type: recall_at_1
value: 60.967000000000006
- type: recall_at_10
value: 88.922
- type: recall_at_100
value: 96.667
- type: recall_at_1000
value: 100
- type: recall_at_3
value: 77.228
- type: recall_at_5
value: 83.428
- task:
type: PairClassification
dataset:
type: mteb/sprintduplicatequestions-pairclassification
name: MTEB SprintDuplicateQuestions
config: default
split: test
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
metrics:
- type: cos_sim_accuracy
value: 99.82277227722773
- type: cos_sim_ap
value: 95.66279851444406
- type: cos_sim_f1
value: 90.9367088607595
- type: cos_sim_precision
value: 92.1025641025641
- type: cos_sim_recall
value: 89.8
- type: dot_accuracy
value: 99.82277227722773
- type: dot_ap
value: 95.66279851444406
- type: dot_f1
value: 90.9367088607595
- type: dot_precision
value: 92.1025641025641
- type: dot_recall
value: 89.8
- type: euclidean_accuracy
value: 99.82277227722773
- type: euclidean_ap
value: 95.66279851444406
- type: euclidean_f1
value: 90.9367088607595
- type: euclidean_precision
value: 92.1025641025641
- type: euclidean_recall
value: 89.8
- type: manhattan_accuracy
value: 99.82673267326733
- type: manhattan_ap
value: 95.86094873177069
- type: manhattan_f1
value: 91.26788357178096
- type: manhattan_precision
value: 90.06815968841285
- type: manhattan_recall
value: 92.5
- type: max_accuracy
value: 99.82673267326733
- type: max_ap
value: 95.86094873177069
- type: max_f1
value: 91.26788357178096
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering
name: MTEB StackExchangeClustering
config: default
split: test
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
metrics:
- type: v_measure
value: 73.09533925852372
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering-p2p
name: MTEB StackExchangeClusteringP2P
config: default
split: test
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
metrics:
- type: v_measure
value: 45.90745648090035
- task:
type: Reranking
dataset:
type: mteb/stackoverflowdupquestions-reranking
name: MTEB StackOverflowDupQuestions
config: default
split: test
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
metrics:
- type: map
value: 54.91147686504404
- type: mrr
value: 56.03900082760377
- task:
type: Summarization
dataset:
type: mteb/summeval
name: MTEB SummEval
config: default
split: test
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
metrics:
- type: cos_sim_pearson
value: 31.46908662038217
- type: cos_sim_spearman
value: 31.40325730367437
- type: dot_pearson
value: 31.469083969291894
- type: dot_spearman
value: 31.40325730367437
- task:
type: Retrieval
dataset:
type: trec-covid
name: MTEB TRECCOVID
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 0.243
- type: map_at_10
value: 2.278
- type: map_at_100
value: 14.221
- type: map_at_1000
value: 33.474
- type: map_at_3
value: 0.7270000000000001
- type: map_at_5
value: 1.183
- type: mrr_at_1
value: 94
- type: mrr_at_10
value: 97
- type: mrr_at_100
value: 97
- type: mrr_at_1000
value: 97
- type: mrr_at_3
value: 97
- type: mrr_at_5
value: 97
- type: ndcg_at_1
value: 90
- type: ndcg_at_10
value: 87.249
- type: ndcg_at_100
value: 67.876
- type: ndcg_at_1000
value: 59.205
- type: ndcg_at_3
value: 90.12299999999999
- type: ndcg_at_5
value: 89.126
- type: precision_at_1
value: 94
- type: precision_at_10
value: 90.8
- type: precision_at_100
value: 69.28
- type: precision_at_1000
value: 25.85
- type: precision_at_3
value: 94.667
- type: precision_at_5
value: 92.80000000000001
- type: recall_at_1
value: 0.243
- type: recall_at_10
value: 2.392
- type: recall_at_100
value: 16.982
- type: recall_at_1000
value: 55.214
- type: recall_at_3
value: 0.745
- type: recall_at_5
value: 1.2229999999999999
- 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: 70.5
- type: f1
value: 67.05501804646966
- type: precision
value: 65.73261904761904
- type: recall
value: 70.5
- 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: 75.14450867052022
- type: f1
value: 70.98265895953759
- type: precision
value: 69.26782273603082
- type: recall
value: 75.14450867052022
- 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: 33.170731707317074
- type: f1
value: 29.92876500193573
- type: precision
value: 28.669145894755648
- type: recall
value: 33.170731707317074
- 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: 95.5
- type: f1
value: 94.13333333333333
- type: precision
value: 93.46666666666667
- type: recall
value: 95.5
- 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: 99.6
- type: f1
value: 99.46666666666665
- type: precision
value: 99.4
- type: recall
value: 99.6
- 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: 97.2
- type: f1
value: 96.39999999999999
- type: precision
value: 96
- type: recall
value: 97.2
- 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: 94.5
- type: f1
value: 92.99666666666667
- type: precision
value: 92.31666666666666
- type: recall
value: 94.5
- 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: 85.82089552238806
- type: f1
value: 81.59203980099502
- type: precision
value: 79.60199004975124
- type: recall
value: 85.82089552238806
- 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: 79.5
- type: f1
value: 75.11246031746032
- type: precision
value: 73.38734126984127
- type: recall
value: 79.5
- 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: 44.390243902439025
- type: f1
value: 38.48896631823461
- type: precision
value: 36.57220286488579
- type: recall
value: 44.390243902439025
- 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: 90.2
- type: f1
value: 87.57333333333334
- type: precision
value: 86.34166666666665
- type: recall
value: 90.2
- 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: 88.82138517618469
- type: f1
value: 85.98651854423423
- type: precision
value: 84.79257073424753
- type: recall
value: 88.82138517618469
- 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: 77.04347826086956
- type: f1
value: 72.32108147606868
- type: precision
value: 70.37207357859532
- type: recall
value: 77.04347826086956
- 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: 53.04347826086957
- type: f1
value: 46.88868184955141
- type: precision
value: 44.71730105643149
- type: recall
value: 53.04347826086957
- 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: 68
- type: f1
value: 62.891813186813195
- type: precision
value: 61.037906162464985
- type: recall
value: 68
- 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: 86.3
- type: f1
value: 82.82000000000001
- type: precision
value: 81.25690476190475
- type: recall
value: 86.3
- 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: 68.87816646562122
- type: f1
value: 63.53054933272062
- type: precision
value: 61.47807816331196
- type: recall
value: 68.87816646562122
- 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: 74.4
- type: f1
value: 68.99388888888889
- type: precision
value: 66.81035714285713
- type: recall
value: 74.4
- 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: 90.5
- type: f1
value: 87.93666666666667
- type: precision
value: 86.825
- type: recall
value: 90.5
- 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: 90.7
- type: f1
value: 88.09
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value: 90.7
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type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
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config: pms-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 60.340702947845806
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value: 67.61904761904762
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type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
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config: gle-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 77.9
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value: 77.9
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type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (pes-eng)
config: pes-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 91.8
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value: 91.8
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type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
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config: nob-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 97.6
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value: 97.6
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type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
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config: bul-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 95.39999999999999
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value: 95.39999999999999
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type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
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config: cbk-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 85
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value: 85
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type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (hun-eng)
config: hun-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 91.60000000000001
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type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (uig-eng)
config: uig-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 44.3
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value: 44.3
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type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
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config: rus-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 95.19999999999999
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value: 95.19999999999999
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type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (spa-eng)
config: spa-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 99.1
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value: 98.8
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value: 99.1
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type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
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config: hye-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 69.6765498652291
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type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
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config: tel-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 50
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value: 50
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type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
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config: afr-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 89.7
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value: 87.19023809523809
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value: 86.12595238095237
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value: 89.7
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type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (mon-eng)
config: mon-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 42.72727272727273
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value: 37.78789518562245
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value: 36.24208471267295
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value: 42.72727272727273
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type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
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config: arz-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 75.26205450733752
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value: 70.72842833849123
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value: 68.93256464011182
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value: 75.26205450733752
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type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
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config: hrv-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 95.19999999999999
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value: 93.42
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value: 95.19999999999999
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type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (nov-eng)
config: nov-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 76.26459143968872
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value: 72.40190419178747
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value: 70.84954604409856
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value: 76.26459143968872
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (gsw-eng)
config: gsw-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 59.82905982905983
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value: 59.82905982905983
- 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: 81.69999999999999
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value: 75.64833333333334
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value: 81.69999999999999
- 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: 95.5
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value: 94.45
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value: 95.5
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (uzb-eng)
config: uzb-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 58.41121495327103
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value: 52.73495974430554
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value: 50.717067200712066
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value: 58.41121495327103
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (lit-eng)
config: lit-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 73.3
- type: f1
value: 69.20371794871795
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value: 67.6597557997558
- type: recall
value: 73.3
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (ina-eng)
config: ina-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy
value: 96.5
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value: 95.51666666666667
- type: precision
value: 95.05
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value: 96.5
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (lfn-eng)
config: lfn-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy
value: 78.4
- type: f1
value: 73.88856643356644
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value: 72.01373015873016
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value: 78.4
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (zsm-eng)
config: zsm-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy
value: 95.3
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value: 94.09666666666668
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- type: recall
value: 95.3
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (ita-eng)
config: ita-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 93.7
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value: 91.94
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value: 93.7
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (cmn-eng)
config: cmn-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy
value: 96.8
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value: 95.89999999999999
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value: 96.8
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (lvs-eng)
config: lvs-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 70.5
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value: 66.00635642135641
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value: 64.36345238095238
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value: 70.5
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (glg-eng)
config: glg-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy
value: 92.4
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value: 90.44388888888889
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value: 89.5767857142857
- type: recall
value: 92.4
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (ceb-eng)
config: ceb-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 48
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value: 48
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (bre-eng)
config: bre-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 16.7
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value: 14.198431372549017
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value: 16.7
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (ben-eng)
config: ben-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 85.7
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value: 80.10833333333332
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value: 85.7
- task:
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: 64.745670995671
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value: 62.916666666666664
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value: 69.64285714285714
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type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (arq-eng)
config: arq-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 54.665203073545555
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value: 48.55366630916923
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value: 46.35683318998357
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value: 54.665203073545555
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (kab-eng)
config: kab-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy
value: 4.8
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value: 3.808587223587223
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value: 3.5653174603174604
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value: 4.8
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (fra-eng)
config: fra-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy
value: 96.6
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value: 95.77333333333333
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value: 95.39166666666667
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value: 96.6
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (por-eng)
config: por-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy
value: 95.39999999999999
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value: 94.44
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value: 93.975
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value: 95.39999999999999
- task:
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: 42
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value: 37.024908424908425
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value: 35.365992063492065
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value: 42
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (oci-eng)
config: oci-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy
value: 66.7
- type: f1
value: 62.20460835058661
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value: 60.590134587634594
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value: 66.7
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (pol-eng)
config: pol-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 97.3
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value: 96.46666666666667
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value: 96.06666666666668
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value: 97.3
- task:
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: 47.3
- type: f1
value: 41.96905408317173
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value: 40.18741402116402
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value: 47.3
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (aze-eng)
config: aze-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 80.2
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value: 76.22690476190476
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value: 74.63539682539682
- type: recall
value: 80.2
- 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: 96
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value: 94.83333333333333
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value: 94.26666666666668
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value: 96
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (nno-eng)
config: nno-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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value: 89.7
- type: f1
value: 87.24333333333334
- type: precision
value: 86.17
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value: 89.7
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (cha-eng)
config: cha-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy
value: 50.36496350364964
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value: 44.795520780922246
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value: 43.09002433090024
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value: 50.36496350364964
- 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: 18.8
- type: f1
value: 16.242864357864356
- type: precision
value: 15.466596638655464
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value: 18.8
- 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: 95.19999999999999
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value: 93.92333333333333
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value: 93.30833333333332
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value: 95.19999999999999
- 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: 93.4
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value: 91.42333333333333
- type: precision
value: 90.50833333333334
- type: recall
value: 93.4
- 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: 26.190476190476193
- type: f1
value: 22.05208151636723
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value: 21.09292328042328
- type: recall
value: 26.190476190476193
- 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: 17.2
- type: f1
value: 14.021009731460952
- type: precision
value: 13.1389886698243
- type: recall
value: 17.2
- 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: 78.67494824016563
- type: f1
value: 74.24430641821947
- type: precision
value: 72.50747642051991
- type: recall
value: 78.67494824016563
- 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: 94.19999999999999
- type: f1
value: 92.54
- type: precision
value: 91.75833333333334
- type: recall
value: 94.19999999999999
- 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: 90.2
- type: f1
value: 87.78666666666666
- type: precision
value: 86.69833333333334
- type: recall
value: 90.2
- 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: 14.7
- type: f1
value: 12.19206214842218
- type: precision
value: 11.526261904761904
- type: recall
value: 14.7
- 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: 73.16017316017316
- type: f1
value: 67.44858316286889
- type: precision
value: 65.23809523809523
- type: recall
value: 73.16017316017316
- 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: 75.19083969465649
- type: f1
value: 70.33078880407125
- type: precision
value: 68.3969465648855
- type: recall
value: 75.19083969465649
- 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: 62.154294032023294
- type: f1
value: 55.86030821838681
- type: precision
value: 53.53509623160277
- type: recall
value: 62.154294032023294
- 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: 86.8
- type: f1
value: 83.9652380952381
- type: precision
value: 82.84242424242424
- type: recall
value: 86.8
- 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: 93.50282485875707
- type: f1
value: 91.54425612052731
- type: precision
value: 90.65442561205272
- type: recall
value: 93.50282485875707
- 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: 11.4
- type: f1
value: 9.189775870222714
- type: precision
value: 8.66189886502811
- type: recall
value: 11.4
- 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: 93.4
- type: f1
value: 91.88666666666666
- type: precision
value: 91.21444444444444
- type: recall
value: 93.4
- 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: 46
- type: f1
value: 40.51069226095542
- type: precision
value: 38.57804926010808
- type: recall
value: 46
- 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: 91
- type: f1
value: 89.11333333333333
- type: precision
value: 88.27000000000001
- type: recall
value: 91
- 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: 94.39999999999999
- type: f1
value: 92.95
- type: precision
value: 92.27000000000001
- type: recall
value: 94.39999999999999
- 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: 14.2
- type: f1
value: 11.73701698770113
- type: precision
value: 11.079207014736676
- type: recall
value: 14.2
- 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: 65.14745308310992
- type: f1
value: 59.665707393589415
- type: precision
value: 57.560853653346946
- type: recall
value: 65.14745308310992
- 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: 95.39999999999999
- type: f1
value: 94
- type: precision
value: 93.33333333333333
- type: recall
value: 95.39999999999999
- 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: 69.56521739130434
- type: f1
value: 62.92490118577074
- type: precision
value: 60.27009222661397
- type: recall
value: 69.56521739130434
- 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: 40.140845070422536
- type: f1
value: 35.96411804158283
- type: precision
value: 34.89075869357559
- type: recall
value: 40.140845070422536
- 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: 65.86826347305389
- type: f1
value: 59.646248628284546
- type: precision
value: 57.22982606216139
- type: recall
value: 65.86826347305389
- 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: 94.89999999999999
- type: f1
value: 93.48333333333333
- type: precision
value: 92.83666666666667
- type: recall
value: 94.89999999999999
- 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: 47.783251231527096
- type: f1
value: 42.006447302013804
- type: precision
value: 40.12747105111637
- type: recall
value: 47.783251231527096
- 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: 69.71830985915493
- type: f1
value: 64.80266212660578
- type: precision
value: 63.08098591549296
- type: recall
value: 69.71830985915493
- 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: 67.94871794871796
- type: f1
value: 61.59912309912309
- type: precision
value: 59.17338217338218
- type: recall
value: 67.94871794871796
- 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: 96.39999999999999
- type: f1
value: 95.28333333333335
- type: precision
value: 94.75
- type: recall
value: 96.39999999999999
- 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: 70.14613778705638
- type: f1
value: 65.4349338900487
- type: precision
value: 63.57599255302805
- type: recall
value: 70.14613778705638
- 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: 9.2
- type: f1
value: 7.622184434339607
- type: precision
value: 7.287048159682417
- type: recall
value: 9.2
- 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: 77.85016286644951
- type: f1
value: 72.83387622149837
- type: precision
value: 70.58450959102424
- type: recall
value: 77.85016286644951
- 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: 90.8
- type: f1
value: 88.84333333333333
- type: precision
value: 87.96666666666665
- type: recall
value: 90.8
- 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: 94.6
- type: f1
value: 93.14
- type: precision
value: 92.49833333333333
- type: recall
value: 94.6
- 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: 84.25196850393701
- type: f1
value: 80.94488188976378
- type: precision
value: 79.65879265091863
- type: recall
value: 84.25196850393701
- 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: 89.5
- type: f1
value: 86.89666666666666
- type: precision
value: 85.7
- type: recall
value: 89.5
- 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: 42.797783933518005
- type: f1
value: 37.30617360155193
- type: precision
value: 35.34933825792552
- type: recall
value: 42.797783933518005
- 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: 96.1
- type: f1
value: 94.93333333333332
- type: precision
value: 94.38333333333333
- type: recall
value: 96.1
- 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: 54.807692307692314
- type: f1
value: 49.506903353057204
- type: precision
value: 47.54807692307693
- type: recall
value: 54.807692307692314
- 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: 87.1
- type: f1
value: 83.61857142857143
- type: precision
value: 81.975
- type: recall
value: 87.1
- 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: 91.10000000000001
- type: f1
value: 88.76333333333332
- type: precision
value: 87.67
- type: recall
value: 91.10000000000001
- 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: 93.10000000000001
- type: f1
value: 91.28999999999999
- type: precision
value: 90.44500000000001
- type: recall
value: 93.10000000000001
- 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: 39.97641509433962
- type: f1
value: 33.12271889998028
- type: precision
value: 30.95185381542554
- type: recall
value: 39.97641509433962
- 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: 92.60000000000001
- type: f1
value: 90.69
- type: precision
value: 89.84500000000001
- type: recall
value: 92.60000000000001
- 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: 95.07299270072993
- type: f1
value: 93.64355231143554
- type: precision
value: 92.94403892944038
- type: recall
value: 95.07299270072993
- 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: 91.9
- type: f1
value: 89.61333333333333
- type: precision
value: 88.53333333333333
- type: recall
value: 91.9
- task:
type: Retrieval
dataset:
type: webis-touche2020
name: MTEB Touche2020
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 2.519
- type: map_at_10
value: 10.31
- type: map_at_100
value: 16.027
- type: map_at_1000
value: 17.827
- type: map_at_3
value: 5.721
- type: map_at_5
value: 7.7829999999999995
- type: mrr_at_1
value: 34.694
- type: mrr_at_10
value: 52.642999999999994
- type: mrr_at_100
value: 53.366
- type: mrr_at_1000
value: 53.366
- type: mrr_at_3
value: 48.638999999999996
- type: mrr_at_5
value: 50.578
- type: ndcg_at_1
value: 31.633
- type: ndcg_at_10
value: 26.394000000000002
- type: ndcg_at_100
value: 36.41
- type: ndcg_at_1000
value: 49.206
- type: ndcg_at_3
value: 31.694
- type: ndcg_at_5
value: 29.529
- type: precision_at_1
value: 34.694
- type: precision_at_10
value: 23.469
- type: precision_at_100
value: 7.286
- type: precision_at_1000
value: 1.5610000000000002
- type: precision_at_3
value: 34.014
- type: precision_at_5
value: 29.796
- type: recall_at_1
value: 2.519
- type: recall_at_10
value: 17.091
- type: recall_at_100
value: 45.429
- type: recall_at_1000
value: 84.621
- type: recall_at_3
value: 7.208
- type: recall_at_5
value: 10.523
- task:
type: Classification
dataset:
type: mteb/toxic_conversations_50k
name: MTEB ToxicConversationsClassification
config: default
split: test
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
metrics:
- type: accuracy
value: 69.58659999999999
- type: ap
value: 14.735696532619
- type: f1
value: 54.23517220069903
- task:
type: Classification
dataset:
type: mteb/tweet_sentiment_extraction
name: MTEB TweetSentimentExtractionClassification
config: default
split: test
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
metrics:
- type: accuracy
value: 63.723825693265425
- type: f1
value: 64.02405729449103
- task:
type: Clustering
dataset:
type: mteb/twentynewsgroups-clustering
name: MTEB TwentyNewsgroupsClustering
config: default
split: test
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
metrics:
- type: v_measure
value: 54.310161547491006
- task:
type: PairClassification
dataset:
type: mteb/twittersemeval2015-pairclassification
name: MTEB TwitterSemEval2015
config: default
split: test
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
metrics:
- type: cos_sim_accuracy
value: 88.77630088812064
- type: cos_sim_ap
value: 81.61725457333809
- type: cos_sim_f1
value: 74.91373801916932
- type: cos_sim_precision
value: 72.63940520446097
- type: cos_sim_recall
value: 77.33509234828496
- type: dot_accuracy
value: 88.77630088812064
- type: dot_ap
value: 81.61725317476251
- type: dot_f1
value: 74.91373801916932
- type: dot_precision
value: 72.63940520446097
- type: dot_recall
value: 77.33509234828496
- type: euclidean_accuracy
value: 88.77630088812064
- type: euclidean_ap
value: 81.61724596869566
- type: euclidean_f1
value: 74.91373801916932
- type: euclidean_precision
value: 72.63940520446097
- type: euclidean_recall
value: 77.33509234828496
- type: manhattan_accuracy
value: 88.67497168742922
- type: manhattan_ap
value: 81.430251048948
- type: manhattan_f1
value: 74.79593118171543
- type: manhattan_precision
value: 71.3635274382938
- type: manhattan_recall
value: 78.57519788918206
- type: max_accuracy
value: 88.77630088812064
- type: max_ap
value: 81.61725457333809
- type: max_f1
value: 74.91373801916932
- task:
type: PairClassification
dataset:
type: mteb/twitterurlcorpus-pairclassification
name: MTEB TwitterURLCorpus
config: default
split: test
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
metrics:
- type: cos_sim_accuracy
value: 89.85136026700819
- type: cos_sim_ap
value: 87.74656687446567
- type: cos_sim_f1
value: 80.3221673073403
- type: cos_sim_precision
value: 76.56871640957633
- type: cos_sim_recall
value: 84.46258084385587
- type: dot_accuracy
value: 89.85136026700819
- type: dot_ap
value: 87.74656471395072
- type: dot_f1
value: 80.3221673073403
- type: dot_precision
value: 76.56871640957633
- type: dot_recall
value: 84.46258084385587
- type: euclidean_accuracy
value: 89.85136026700819
- type: euclidean_ap
value: 87.74656885754466
- type: euclidean_f1
value: 80.3221673073403
- type: euclidean_precision
value: 76.56871640957633
- type: euclidean_recall
value: 84.46258084385587
- type: manhattan_accuracy
value: 89.86300306593705
- type: manhattan_ap
value: 87.78807479093082
- type: manhattan_f1
value: 80.31663429471911
- type: manhattan_precision
value: 76.63472970137772
- type: manhattan_recall
value: 84.3701878657222
- type: max_accuracy
value: 89.86300306593705
- type: max_ap
value: 87.78807479093082
- type: max_f1
value: 80.3221673073403