---
license: cc-by-nc-4.0
tags:
- feature-extraction
- sentence-similarity
- mteb
language:
- multilingual
- af
- am
- ar
- as
- az
- be
- bg
- bn
- br
- bs
- ca
- cs
- cy
- da
- de
- el
- en
- eo
- es
- et
- eu
- fa
- fi
- fr
- fy
- ga
- gd
- gl
- gu
- ha
- he
- hi
- hr
- hu
- hy
- id
- is
- it
- ja
- jv
- ka
- kk
- km
- kn
- ko
- ku
- ky
- la
- lo
- lt
- lv
- mg
- mk
- ml
- mn
- mr
- ms
- my
- ne
- nl
- no
- om
- or
- pa
- pl
- ps
- pt
- ro
- ru
- sa
- sd
- si
- sk
- sl
- so
- sq
- sr
- su
- sv
- sw
- ta
- te
- th
- tl
- tr
- ug
- uk
- ur
- uz
- vi
- xh
- yi
- zh
inference: false
library_name: transformers
model-index:
- name: jina-embeddings-v3
results:
- dataset:
config: default
name: MTEB AFQMC (default)
revision: b44c3b011063adb25877c13823db83bb193913c4
split: validation
type: C-MTEB/AFQMC
metrics:
- type: cosine_pearson
value: 41.74237700998808
- type: cosine_spearman
value: 43.4726782647566
- type: euclidean_pearson
value: 42.244585459479964
- type: euclidean_spearman
value: 43.525070045169606
- type: main_score
value: 43.4726782647566
- type: manhattan_pearson
value: 42.04616728224863
- type: manhattan_spearman
value: 43.308828270754645
- type: pearson
value: 41.74237700998808
- type: spearman
value: 43.4726782647566
task:
type: STS
- dataset:
config: default
name: MTEB ATEC (default)
revision: 0f319b1142f28d00e055a6770f3f726ae9b7d865
split: test
type: C-MTEB/ATEC
metrics:
- type: cosine_pearson
value: 47.541497334563296
- type: cosine_spearman
value: 49.06268944206629
- type: euclidean_pearson
value: 51.838926748581635
- type: euclidean_spearman
value: 48.930697157135356
- type: main_score
value: 49.06268944206629
- type: manhattan_pearson
value: 51.835306769406365
- type: manhattan_spearman
value: 48.86135493444834
- type: pearson
value: 47.541497334563296
- type: spearman
value: 49.06268944206629
task:
type: STS
- dataset:
config: default
name: MTEB AllegroReviews (default)
revision: b89853e6de927b0e3bfa8ecc0e56fe4e02ceafc6
split: test
type: PL-MTEB/allegro-reviews
metrics:
- type: accuracy
value: 49.51292246520874
- type: f1
value: 44.14350234332397
- type: f1_weighted
value: 51.65508998354552
- type: main_score
value: 49.51292246520874
task:
type: Classification
- dataset:
config: default
name: MTEB AlloProfClusteringP2P (default)
revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b
split: test
type: lyon-nlp/alloprof
metrics:
- type: main_score
value: 63.883383458621665
- type: v_measure
value: 63.883383458621665
- type: v_measure_std
value: 2.693666879958465
task:
type: Clustering
- dataset:
config: default
name: MTEB AlloProfClusteringS2S (default)
revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b
split: test
type: lyon-nlp/alloprof
metrics:
- type: main_score
value: 46.85924588755251
- type: v_measure
value: 46.85924588755251
- type: v_measure_std
value: 2.1918258880872377
task:
type: Clustering
- dataset:
config: default
name: MTEB AlloprofReranking (default)
revision: e40c8a63ce02da43200eccb5b0846fcaa888f562
split: test
type: lyon-nlp/mteb-fr-reranking-alloprof-s2p
metrics:
- type: map
value: 66.39013753839347
- type: mrr
value: 67.68045617786551
- type: main_score
value: 66.39013753839347
task:
type: Reranking
- dataset:
config: default
name: MTEB AlloprofRetrieval (default)
revision: fcf295ea64c750f41fadbaa37b9b861558e1bfbd
split: test
type: lyon-nlp/alloprof
metrics:
- type: main_score
value: 54.284
- type: map_at_1
value: 37.047000000000004
- type: map_at_10
value: 48.53
- type: map_at_100
value: 49.357
- type: map_at_1000
value: 49.39
- type: map_at_20
value: 49.064
- type: map_at_3
value: 45.675
- type: map_at_5
value: 47.441
- type: mrr_at_1
value: 37.04663212435233
- type: mrr_at_10
value: 48.5300326232969
- type: mrr_at_100
value: 49.35708199037581
- type: mrr_at_1000
value: 49.39005824603193
- type: mrr_at_20
value: 49.06417416464799
- type: mrr_at_3
value: 45.67501439263105
- type: mrr_at_5
value: 47.44099021301103
- type: nauc_map_at_1000_diff1
value: 43.32474221868009
- type: nauc_map_at_1000_max
value: 39.407334029058575
- type: nauc_map_at_1000_std
value: -2.3728154448932606
- type: nauc_map_at_100_diff1
value: 43.32336300929909
- type: nauc_map_at_100_max
value: 39.432174777554835
- type: nauc_map_at_100_std
value: -2.356396922384349
- type: nauc_map_at_10_diff1
value: 43.1606520154482
- type: nauc_map_at_10_max
value: 39.33734650558226
- type: nauc_map_at_10_std
value: -2.5156222475075256
- type: nauc_map_at_1_diff1
value: 46.2178975214499
- type: nauc_map_at_1_max
value: 36.26173199049361
- type: nauc_map_at_1_std
value: -3.0897555582816443
- type: nauc_map_at_20_diff1
value: 43.272980702916456
- type: nauc_map_at_20_max
value: 39.4896977052276
- type: nauc_map_at_20_std
value: -2.3305501742917043
- type: nauc_map_at_3_diff1
value: 43.49525042967079
- type: nauc_map_at_3_max
value: 38.66352501824728
- type: nauc_map_at_3_std
value: -3.202794391620473
- type: nauc_map_at_5_diff1
value: 43.2266692546611
- type: nauc_map_at_5_max
value: 38.77368661115743
- type: nauc_map_at_5_std
value: -3.0897532130127954
- type: nauc_mrr_at_1000_diff1
value: 43.32474221868009
- type: nauc_mrr_at_1000_max
value: 39.407334029058575
- type: nauc_mrr_at_1000_std
value: -2.3728154448932606
- type: nauc_mrr_at_100_diff1
value: 43.32336300929909
- type: nauc_mrr_at_100_max
value: 39.432174777554835
- type: nauc_mrr_at_100_std
value: -2.356396922384349
- type: nauc_mrr_at_10_diff1
value: 43.1606520154482
- type: nauc_mrr_at_10_max
value: 39.33734650558226
- type: nauc_mrr_at_10_std
value: -2.5156222475075256
- type: nauc_mrr_at_1_diff1
value: 46.2178975214499
- type: nauc_mrr_at_1_max
value: 36.26173199049361
- type: nauc_mrr_at_1_std
value: -3.0897555582816443
- type: nauc_mrr_at_20_diff1
value: 43.272980702916456
- type: nauc_mrr_at_20_max
value: 39.4896977052276
- type: nauc_mrr_at_20_std
value: -2.3305501742917043
- type: nauc_mrr_at_3_diff1
value: 43.49525042967079
- type: nauc_mrr_at_3_max
value: 38.66352501824728
- type: nauc_mrr_at_3_std
value: -3.202794391620473
- type: nauc_mrr_at_5_diff1
value: 43.2266692546611
- type: nauc_mrr_at_5_max
value: 38.77368661115743
- type: nauc_mrr_at_5_std
value: -3.0897532130127954
- type: nauc_ndcg_at_1000_diff1
value: 43.01903168202974
- type: nauc_ndcg_at_1000_max
value: 40.75496622942232
- type: nauc_ndcg_at_1000_std
value: -1.3150412981845496
- type: nauc_ndcg_at_100_diff1
value: 42.98016493758145
- type: nauc_ndcg_at_100_max
value: 41.55869635162325
- type: nauc_ndcg_at_100_std
value: -0.5355252976886055
- type: nauc_ndcg_at_10_diff1
value: 42.218755211347506
- type: nauc_ndcg_at_10_max
value: 41.305042275175765
- type: nauc_ndcg_at_10_std
value: -1.4034484444573714
- type: nauc_ndcg_at_1_diff1
value: 46.2178975214499
- type: nauc_ndcg_at_1_max
value: 36.26173199049361
- type: nauc_ndcg_at_1_std
value: -3.0897555582816443
- type: nauc_ndcg_at_20_diff1
value: 42.66574440095576
- type: nauc_ndcg_at_20_max
value: 42.014620115124515
- type: nauc_ndcg_at_20_std
value: -0.5176162553751498
- type: nauc_ndcg_at_3_diff1
value: 42.837450505106055
- type: nauc_ndcg_at_3_max
value: 39.525369733082414
- type: nauc_ndcg_at_3_std
value: -3.1605948245795155
- type: nauc_ndcg_at_5_diff1
value: 42.37951815451173
- type: nauc_ndcg_at_5_max
value: 39.78840132935179
- type: nauc_ndcg_at_5_std
value: -2.936898430768135
- type: nauc_precision_at_1000_diff1
value: 49.69224988612385
- type: nauc_precision_at_1000_max
value: 79.57897547128005
- type: nauc_precision_at_1000_std
value: 45.040371354764645
- type: nauc_precision_at_100_diff1
value: 42.70597486048422
- type: nauc_precision_at_100_max
value: 65.74628759606188
- type: nauc_precision_at_100_std
value: 25.49157745244855
- type: nauc_precision_at_10_diff1
value: 38.565609931689345
- type: nauc_precision_at_10_max
value: 50.0239696180852
- type: nauc_precision_at_10_std
value: 3.976354829503967
- type: nauc_precision_at_1_diff1
value: 46.2178975214499
- type: nauc_precision_at_1_max
value: 36.26173199049361
- type: nauc_precision_at_1_std
value: -3.0897555582816443
- type: nauc_precision_at_20_diff1
value: 40.4134718566864
- type: nauc_precision_at_20_max
value: 57.121778108665374
- type: nauc_precision_at_20_std
value: 11.46021975428544
- type: nauc_precision_at_3_diff1
value: 40.90538379461529
- type: nauc_precision_at_3_max
value: 42.18393248057992
- type: nauc_precision_at_3_std
value: -3.005249943837297
- type: nauc_precision_at_5_diff1
value: 39.60162965860782
- type: nauc_precision_at_5_max
value: 43.28317158174058
- type: nauc_precision_at_5_std
value: -2.3469094487738054
- type: nauc_recall_at_1000_diff1
value: 49.69224988612252
- type: nauc_recall_at_1000_max
value: 79.57897547127862
- type: nauc_recall_at_1000_std
value: 45.04037135476256
- type: nauc_recall_at_100_diff1
value: 42.70597486048432
- type: nauc_recall_at_100_max
value: 65.74628759606213
- type: nauc_recall_at_100_std
value: 25.491577452448727
- type: nauc_recall_at_10_diff1
value: 38.56560993168935
- type: nauc_recall_at_10_max
value: 50.02396961808522
- type: nauc_recall_at_10_std
value: 3.9763548295040314
- type: nauc_recall_at_1_diff1
value: 46.2178975214499
- type: nauc_recall_at_1_max
value: 36.26173199049361
- type: nauc_recall_at_1_std
value: -3.0897555582816443
- type: nauc_recall_at_20_diff1
value: 40.41347185668637
- type: nauc_recall_at_20_max
value: 57.12177810866533
- type: nauc_recall_at_20_std
value: 11.460219754285431
- type: nauc_recall_at_3_diff1
value: 40.90538379461527
- type: nauc_recall_at_3_max
value: 42.18393248057989
- type: nauc_recall_at_3_std
value: -3.005249943837297
- type: nauc_recall_at_5_diff1
value: 39.601629658607784
- type: nauc_recall_at_5_max
value: 43.28317158174053
- type: nauc_recall_at_5_std
value: -2.3469094487738054
- type: ndcg_at_1
value: 37.047000000000004
- type: ndcg_at_10
value: 54.284
- type: ndcg_at_100
value: 58.34
- type: ndcg_at_1000
value: 59.303
- type: ndcg_at_20
value: 56.235
- type: ndcg_at_3
value: 48.503
- type: ndcg_at_5
value: 51.686
- type: precision_at_1
value: 37.047000000000004
- type: precision_at_10
value: 7.237
- type: precision_at_100
value: 0.914
- type: precision_at_1000
value: 0.099
- type: precision_at_20
value: 4.005
- type: precision_at_3
value: 18.898
- type: precision_at_5
value: 12.884
- type: recall_at_1
value: 37.047000000000004
- type: recall_at_10
value: 72.366
- type: recall_at_100
value: 91.408
- type: recall_at_1000
value: 99.136
- type: recall_at_20
value: 80.095
- type: recall_at_3
value: 56.693000000000005
- type: recall_at_5
value: 64.42099999999999
task:
type: Retrieval
- dataset:
config: en
name: MTEB AmazonCounterfactualClassification (en)
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
split: test
type: mteb/amazon_counterfactual
metrics:
- type: accuracy
value: 89.49253731343283
- type: ap
value: 61.88098616359918
- type: ap_weighted
value: 61.88098616359918
- type: f1
value: 84.76516623679144
- type: f1_weighted
value: 89.92745276292968
- type: main_score
value: 89.49253731343283
task:
type: Classification
- dataset:
config: de
name: MTEB AmazonCounterfactualClassification (de)
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
split: test
type: mteb/amazon_counterfactual
metrics:
- type: accuracy
value: 89.61456102783727
- type: ap
value: 93.11816566733742
- type: ap_weighted
value: 93.11816566733742
- type: f1
value: 88.27635757733722
- type: f1_weighted
value: 89.82581568285453
- type: main_score
value: 89.61456102783727
task:
type: Classification
- dataset:
config: default
name: MTEB AmazonPolarityClassification (default)
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
split: test
type: mteb/amazon_polarity
metrics:
- type: accuracy
value: 95.3825
- type: ap
value: 93.393033869502
- type: ap_weighted
value: 93.393033869502
- type: f1
value: 95.38109007966307
- type: f1_weighted
value: 95.38109007966305
- type: main_score
value: 95.3825
task:
type: Classification
- dataset:
config: en
name: MTEB AmazonReviewsClassification (en)
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
split: test
type: mteb/amazon_reviews_multi
metrics:
- type: accuracy
value: 49.768
- type: f1
value: 48.95084821944411
- type: f1_weighted
value: 48.9508482194441
- type: main_score
value: 49.768
task:
type: Classification
- dataset:
config: de
name: MTEB AmazonReviewsClassification (de)
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
split: test
type: mteb/amazon_reviews_multi
metrics:
- type: accuracy
value: 48.071999999999996
- type: f1
value: 47.24171107487612
- type: f1_weighted
value: 47.24171107487612
- type: main_score
value: 48.071999999999996
task:
type: Classification
- dataset:
config: es
name: MTEB AmazonReviewsClassification (es)
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
split: test
type: mteb/amazon_reviews_multi
metrics:
- type: accuracy
value: 48.102000000000004
- type: f1
value: 47.27193805278696
- type: f1_weighted
value: 47.27193805278696
- type: main_score
value: 48.102000000000004
task:
type: Classification
- dataset:
config: fr
name: MTEB AmazonReviewsClassification (fr)
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
split: test
type: mteb/amazon_reviews_multi
metrics:
- type: accuracy
value: 47.30800000000001
- type: f1
value: 46.41683358017851
- type: f1_weighted
value: 46.41683358017851
- type: main_score
value: 47.30800000000001
task:
type: Classification
- dataset:
config: zh
name: MTEB AmazonReviewsClassification (zh)
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
split: test
type: mteb/amazon_reviews_multi
metrics:
- type: accuracy
value: 44.944
- type: f1
value: 44.223824487744395
- type: f1_weighted
value: 44.22382448774439
- type: main_score
value: 44.944
task:
type: Classification
- dataset:
config: default
name: MTEB ArguAna (default)
revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
split: test
type: mteb/arguana
metrics:
- type: map_at_1
value: 29.232000000000003
- type: map_at_10
value: 45.117000000000004
- type: map_at_100
value: 45.977000000000004
- type: map_at_1000
value: 45.98
- type: map_at_20
value: 45.815
- type: map_at_3
value: 39.912
- type: map_at_5
value: 42.693
- type: mrr_at_1
value: 29.659000000000002
- type: mrr_at_10
value: 45.253
- type: mrr_at_100
value: 46.125
- type: mrr_at_1000
value: 46.129
- type: mrr_at_20
value: 45.964
- type: mrr_at_3
value: 40.043
- type: mrr_at_5
value: 42.870000000000005
- type: ndcg_at_1
value: 29.232000000000003
- type: ndcg_at_10
value: 54.327999999999996
- type: ndcg_at_100
value: 57.86
- type: ndcg_at_1000
value: 57.935
- type: ndcg_at_20
value: 56.794
- type: ndcg_at_3
value: 43.516
- type: ndcg_at_5
value: 48.512
- type: precision_at_1
value: 29.232000000000003
- type: precision_at_10
value: 8.393
- type: precision_at_100
value: 0.991
- type: precision_at_1000
value: 0.1
- type: precision_at_20
value: 4.676
- type: precision_at_3
value: 17.994
- type: precision_at_5
value: 13.215
- type: recall_at_1
value: 29.232000000000003
- type: recall_at_10
value: 83.926
- type: recall_at_100
value: 99.075
- type: recall_at_1000
value: 99.644
- type: recall_at_20
value: 93.528
- type: recall_at_3
value: 53.983000000000004
- type: recall_at_5
value: 66.074
- type: main_score
value: 54.327999999999996
task:
type: Retrieval
- dataset:
config: default
name: MTEB ArxivClusteringP2P (default)
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
split: test
type: mteb/arxiv-clustering-p2p
metrics:
- type: main_score
value: 46.6636824632419
- type: v_measure
value: 46.6636824632419
- type: v_measure_std
value: 13.817129140714963
task:
type: Clustering
- dataset:
config: default
name: MTEB ArxivClusteringS2S (default)
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
split: test
type: mteb/arxiv-clustering-s2s
metrics:
- type: main_score
value: 39.271141892800024
- type: v_measure
value: 39.271141892800024
- type: v_measure_std
value: 14.276782483454827
task:
type: Clustering
- dataset:
config: default
name: MTEB AskUbuntuDupQuestions (default)
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
split: test
type: mteb/askubuntudupquestions-reranking
metrics:
- type: map
value: 65.04363277324629
- type: mrr
value: 78.2372598162072
- type: main_score
value: 65.04363277324629
task:
type: Reranking
- dataset:
config: default
name: MTEB MindSmallReranking (default)
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
split: test
type: mteb/mind_small
metrics:
- type: map
value: 30.83
- type: main_score
value: 30.83
task:
type: Reranking
- dataset:
config: default
name: MTEB BIOSSES (default)
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
split: test
type: mteb/biosses-sts
metrics:
- type: cosine_pearson
value: 88.80382082011027
- type: cosine_spearman
value: 88.68876782169106
- type: euclidean_pearson
value: 87.00802890147176
- type: euclidean_spearman
value: 87.43211268192712
- type: main_score
value: 88.68876782169106
- type: manhattan_pearson
value: 87.14062537179474
- type: manhattan_spearman
value: 87.59115245033443
- type: pearson
value: 88.80382082011027
- type: spearman
value: 88.68876782169106
task:
type: STS
- dataset:
config: default
name: MTEB BQ (default)
revision: e3dda5e115e487b39ec7e618c0c6a29137052a55
split: test
type: C-MTEB/BQ
metrics:
- type: cosine_pearson
value: 61.588006604878196
- type: cosine_spearman
value: 63.20615427154465
- type: euclidean_pearson
value: 61.818547092516496
- type: euclidean_spearman
value: 63.21558009151778
- type: main_score
value: 63.20615427154465
- type: manhattan_pearson
value: 61.665588158487616
- type: manhattan_spearman
value: 63.051544488238584
- type: pearson
value: 61.588006604878196
- type: spearman
value: 63.20615427154465
task:
type: STS
- dataset:
config: default
name: MTEB BSARDRetrieval (default)
revision: 5effa1b9b5fa3b0f9e12523e6e43e5f86a6e6d59
split: test
type: maastrichtlawtech/bsard
metrics:
- type: main_score
value: 64.414
- type: map_at_1
value: 14.865
- type: map_at_10
value: 21.605
- type: map_at_100
value: 22.762
- type: map_at_1000
value: 22.854
- type: map_at_20
value: 22.259999999999998
- type: map_at_3
value: 20.119999999999997
- type: map_at_5
value: 20.931
- type: mrr_at_1
value: 14.864864864864865
- type: mrr_at_10
value: 21.605176605176606
- type: mrr_at_100
value: 22.7622306460065
- type: mrr_at_1000
value: 22.85383406410312
- type: mrr_at_20
value: 22.259528463088845
- type: mrr_at_3
value: 20.12012012012012
- type: mrr_at_5
value: 20.930930930930934
- type: nauc_map_at_1000_diff1
value: 17.486265968689338
- type: nauc_map_at_1000_max
value: 22.736799291688836
- type: nauc_map_at_1000_std
value: 9.831687441977147
- type: nauc_map_at_100_diff1
value: 17.50754492049086
- type: nauc_map_at_100_max
value: 22.77693662806787
- type: nauc_map_at_100_std
value: 9.853899509675395
- type: nauc_map_at_10_diff1
value: 17.42133968580952
- type: nauc_map_at_10_max
value: 22.45861793882279
- type: nauc_map_at_10_std
value: 8.964888472915938
- type: nauc_map_at_1_diff1
value: 19.433947086968093
- type: nauc_map_at_1_max
value: 24.75657047550517
- type: nauc_map_at_1_std
value: 15.122329157218505
- type: nauc_map_at_20_diff1
value: 17.429856756008785
- type: nauc_map_at_20_max
value: 22.438850987431017
- type: nauc_map_at_20_std
value: 9.172746012213558
- type: nauc_map_at_3_diff1
value: 18.218182689678475
- type: nauc_map_at_3_max
value: 23.57169444088667
- type: nauc_map_at_3_std
value: 10.464473559366356
- type: nauc_map_at_5_diff1
value: 18.6075342519133
- type: nauc_map_at_5_max
value: 23.308845973576673
- type: nauc_map_at_5_std
value: 9.364009996445652
- type: nauc_mrr_at_1000_diff1
value: 17.486265968689338
- type: nauc_mrr_at_1000_max
value: 22.736799291688836
- type: nauc_mrr_at_1000_std
value: 9.831687441977147
- type: nauc_mrr_at_100_diff1
value: 17.50754492049086
- type: nauc_mrr_at_100_max
value: 22.77693662806787
- type: nauc_mrr_at_100_std
value: 9.853899509675395
- type: nauc_mrr_at_10_diff1
value: 17.42133968580952
- type: nauc_mrr_at_10_max
value: 22.45861793882279
- type: nauc_mrr_at_10_std
value: 8.964888472915938
- type: nauc_mrr_at_1_diff1
value: 19.433947086968093
- type: nauc_mrr_at_1_max
value: 24.75657047550517
- type: nauc_mrr_at_1_std
value: 15.122329157218505
- type: nauc_mrr_at_20_diff1
value: 17.429856756008785
- type: nauc_mrr_at_20_max
value: 22.438850987431017
- type: nauc_mrr_at_20_std
value: 9.172746012213558
- type: nauc_mrr_at_3_diff1
value: 18.218182689678475
- type: nauc_mrr_at_3_max
value: 23.57169444088667
- type: nauc_mrr_at_3_std
value: 10.464473559366356
- type: nauc_mrr_at_5_diff1
value: 18.6075342519133
- type: nauc_mrr_at_5_max
value: 23.308845973576673
- type: nauc_mrr_at_5_std
value: 9.364009996445652
- type: nauc_ndcg_at_1000_diff1
value: 16.327871824135745
- type: nauc_ndcg_at_1000_max
value: 23.308241052911495
- type: nauc_ndcg_at_1000_std
value: 11.50905911184097
- type: nauc_ndcg_at_100_diff1
value: 16.676226744692773
- type: nauc_ndcg_at_100_max
value: 24.323253721240974
- type: nauc_ndcg_at_100_std
value: 11.952612443651557
- type: nauc_ndcg_at_10_diff1
value: 16.030325121764594
- type: nauc_ndcg_at_10_max
value: 21.306799242079542
- type: nauc_ndcg_at_10_std
value: 6.63359364302513
- type: nauc_ndcg_at_1_diff1
value: 19.433947086968093
- type: nauc_ndcg_at_1_max
value: 24.75657047550517
- type: nauc_ndcg_at_1_std
value: 15.122329157218505
- type: nauc_ndcg_at_20_diff1
value: 16.013173605999857
- type: nauc_ndcg_at_20_max
value: 21.607217260736576
- type: nauc_ndcg_at_20_std
value: 7.319482417138996
- type: nauc_ndcg_at_3_diff1
value: 17.97958548328493
- type: nauc_ndcg_at_3_max
value: 23.58346522810145
- type: nauc_ndcg_at_3_std
value: 9.392582854708314
- type: nauc_ndcg_at_5_diff1
value: 18.734733324685287
- type: nauc_ndcg_at_5_max
value: 23.273244317623742
- type: nauc_ndcg_at_5_std
value: 7.638611545253834
- type: nauc_precision_at_1000_diff1
value: 7.919843339380295
- type: nauc_precision_at_1000_max
value: 31.575386234270486
- type: nauc_precision_at_1000_std
value: 39.332224386769404
- type: nauc_precision_at_100_diff1
value: 15.018050960000052
- type: nauc_precision_at_100_max
value: 34.98209513759861
- type: nauc_precision_at_100_std
value: 26.970034484359022
- type: nauc_precision_at_10_diff1
value: 12.102191084210922
- type: nauc_precision_at_10_max
value: 18.112541150340675
- type: nauc_precision_at_10_std
value: 0.7358784689406018
- type: nauc_precision_at_1_diff1
value: 19.433947086968093
- type: nauc_precision_at_1_max
value: 24.75657047550517
- type: nauc_precision_at_1_std
value: 15.122329157218505
- type: nauc_precision_at_20_diff1
value: 12.018814361204328
- type: nauc_precision_at_20_max
value: 19.75123746049928
- type: nauc_precision_at_20_std
value: 3.012204650582264
- type: nauc_precision_at_3_diff1
value: 17.41375604940955
- type: nauc_precision_at_3_max
value: 23.699834627021037
- type: nauc_precision_at_3_std
value: 6.793486779050103
- type: nauc_precision_at_5_diff1
value: 19.194631963780257
- type: nauc_precision_at_5_max
value: 23.31708702442155
- type: nauc_precision_at_5_std
value: 3.4591358279667332
- type: nauc_recall_at_1000_diff1
value: 7.919843339380378
- type: nauc_recall_at_1000_max
value: 31.57538623427063
- type: nauc_recall_at_1000_std
value: 39.332224386769546
- type: nauc_recall_at_100_diff1
value: 15.018050960000085
- type: nauc_recall_at_100_max
value: 34.9820951375986
- type: nauc_recall_at_100_std
value: 26.97003448435901
- type: nauc_recall_at_10_diff1
value: 12.102191084210837
- type: nauc_recall_at_10_max
value: 18.112541150340594
- type: nauc_recall_at_10_std
value: 0.7358784689405188
- type: nauc_recall_at_1_diff1
value: 19.433947086968093
- type: nauc_recall_at_1_max
value: 24.75657047550517
- type: nauc_recall_at_1_std
value: 15.122329157218505
- type: nauc_recall_at_20_diff1
value: 12.01881436120429
- type: nauc_recall_at_20_max
value: 19.751237460499222
- type: nauc_recall_at_20_std
value: 3.0122046505822135
- type: nauc_recall_at_3_diff1
value: 17.413756049409503
- type: nauc_recall_at_3_max
value: 23.699834627020998
- type: nauc_recall_at_3_std
value: 6.793486779050083
- type: nauc_recall_at_5_diff1
value: 19.194631963780203
- type: nauc_recall_at_5_max
value: 23.3170870244215
- type: nauc_recall_at_5_std
value: 3.459135827966664
- type: ndcg_at_1
value: 14.865
- type: ndcg_at_10
value: 24.764
- type: ndcg_at_100
value: 30.861
- type: ndcg_at_1000
value: 33.628
- type: ndcg_at_20
value: 27.078000000000003
- type: ndcg_at_3
value: 21.675
- type: ndcg_at_5
value: 23.148
- type: precision_at_1
value: 14.865
- type: precision_at_10
value: 3.4680000000000004
- type: precision_at_100
value: 0.644
- type: precision_at_1000
value: 0.087
- type: precision_at_20
value: 2.185
- type: precision_at_3
value: 8.709
- type: precision_at_5
value: 5.946
- type: recall_at_1
value: 14.865
- type: recall_at_10
value: 34.685
- type: recall_at_100
value: 64.414
- type: recall_at_1000
value: 86.937
- type: recall_at_20
value: 43.694
- type: recall_at_3
value: 26.125999999999998
- type: recall_at_5
value: 29.73
task:
type: Retrieval
- dataset:
config: default
name: MTEB Banking77Classification (default)
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
split: test
type: mteb/banking77
metrics:
- type: accuracy
value: 84.08116883116882
- type: f1
value: 84.05587055990273
- type: f1_weighted
value: 84.05587055990274
- type: main_score
value: 84.08116883116882
task:
type: Classification
- dataset:
config: default
name: MTEB BiorxivClusteringP2P (default)
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
split: test
type: mteb/biorxiv-clustering-p2p
metrics:
- type: main_score
value: 38.1941007822277
- type: v_measure
value: 38.1941007822277
- type: v_measure_std
value: 0.7502113547288178
task:
type: Clustering
- dataset:
config: default
name: MTEB BiorxivClusteringS2S (default)
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
split: test
type: mteb/biorxiv-clustering-s2s
metrics:
- type: main_score
value: 34.42075599178318
- type: v_measure
value: 34.42075599178318
- type: v_measure_std
value: 0.600256720497283
task:
type: Clustering
- dataset:
config: default
name: MTEB BlurbsClusteringP2P (default)
revision: a2dd5b02a77de3466a3eaa98ae586b5610314496
split: test
type: slvnwhrl/blurbs-clustering-p2p
metrics:
- type: main_score
value: 41.634627363047265
- type: v_measure
value: 41.634627363047265
- type: v_measure_std
value: 9.726923191225307
task:
type: Clustering
- dataset:
config: default
name: MTEB BlurbsClusteringS2S (default)
revision: 22793b6a6465bf00120ad525e38c51210858132c
split: test
type: slvnwhrl/blurbs-clustering-s2s
metrics:
- type: main_score
value: 20.996468295584197
- type: v_measure
value: 20.996468295584197
- type: v_measure_std
value: 9.225766688272197
task:
type: Clustering
- dataset:
config: default
name: MTEB CBD (default)
revision: 36ddb419bcffe6a5374c3891957912892916f28d
split: test
type: PL-MTEB/cbd
metrics:
- type: accuracy
value: 69.99
- type: ap
value: 22.57826353116948
- type: ap_weighted
value: 22.57826353116948
- type: f1
value: 59.04574955548393
- type: f1_weighted
value: 74.36235022309789
- type: main_score
value: 69.99
task:
type: Classification
- dataset:
config: default
name: MTEB CDSC-E (default)
revision: 0a3d4aa409b22f80eb22cbf59b492637637b536d
split: test
type: PL-MTEB/cdsce-pairclassification
metrics:
- type: cosine_accuracy
value: 88.7
- type: cosine_accuracy_threshold
value: 97.37848043441772
- type: cosine_ap
value: 73.0405088928302
- type: cosine_f1
value: 63.52201257861635
- type: cosine_f1_threshold
value: 96.98888063430786
- type: cosine_precision
value: 78.90625
- type: cosine_recall
value: 53.1578947368421
- type: dot_accuracy
value: 84.89999999999999
- type: dot_accuracy_threshold
value: 43603.09753417969
- type: dot_ap
value: 56.98157569085279
- type: dot_f1
value: 57.606490872210955
- type: dot_f1_threshold
value: 40406.23779296875
- type: dot_precision
value: 46.864686468646866
- type: dot_recall
value: 74.73684210526315
- type: euclidean_accuracy
value: 88.5
- type: euclidean_accuracy_threshold
value: 498.0483055114746
- type: euclidean_ap
value: 72.97328234816734
- type: euclidean_f1
value: 63.722397476340696
- type: euclidean_f1_threshold
value: 508.6186408996582
- type: euclidean_precision
value: 79.52755905511812
- type: euclidean_recall
value: 53.1578947368421
- type: main_score
value: 73.0405088928302
- type: manhattan_accuracy
value: 88.6
- type: manhattan_accuracy_threshold
value: 12233.079528808594
- type: manhattan_ap
value: 72.92148503992615
- type: manhattan_f1
value: 63.69426751592356
- type: manhattan_f1_threshold
value: 12392.754364013672
- type: manhattan_precision
value: 80.64516129032258
- type: manhattan_recall
value: 52.63157894736842
- type: max_accuracy
value: 88.7
- type: max_ap
value: 73.0405088928302
- type: max_f1
value: 63.722397476340696
- type: max_precision
value: 80.64516129032258
- type: max_recall
value: 74.73684210526315
- type: similarity_accuracy
value: 88.7
- type: similarity_accuracy_threshold
value: 97.37848043441772
- type: similarity_ap
value: 73.0405088928302
- type: similarity_f1
value: 63.52201257861635
- type: similarity_f1_threshold
value: 96.98888063430786
- type: similarity_precision
value: 78.90625
- type: similarity_recall
value: 53.1578947368421
task:
type: PairClassification
- dataset:
config: default
name: MTEB CDSC-R (default)
revision: 1cd6abbb00df7d14be3dbd76a7dcc64b3a79a7cd
split: test
type: PL-MTEB/cdscr-sts
metrics:
- type: cosine_pearson
value: 92.97492495289738
- type: cosine_spearman
value: 92.63248098608472
- type: euclidean_pearson
value: 92.04712487782031
- type: euclidean_spearman
value: 92.19679486755008
- type: main_score
value: 92.63248098608472
- type: manhattan_pearson
value: 92.0101187740438
- type: manhattan_spearman
value: 92.20926859332754
- type: pearson
value: 92.97492495289738
- type: spearman
value: 92.63248098608472
task:
type: STS
- dataset:
config: default
name: MTEB CLSClusteringP2P (default)
revision: 4b6227591c6c1a73bc76b1055f3b7f3588e72476
split: test
type: C-MTEB/CLSClusteringP2P
metrics:
- type: main_score
value: 39.96377851800628
- type: v_measure
value: 39.96377851800628
- type: v_measure_std
value: 0.9793033243093288
task:
type: Clustering
- dataset:
config: default
name: MTEB CLSClusteringS2S (default)
revision: e458b3f5414b62b7f9f83499ac1f5497ae2e869f
split: test
type: C-MTEB/CLSClusteringS2S
metrics:
- type: main_score
value: 38.788850224595784
- type: v_measure
value: 38.788850224595784
- type: v_measure_std
value: 1.0712604145916924
task:
type: Clustering
- dataset:
config: default
name: MTEB CMedQAv1-reranking (default)
revision: 8d7f1e942507dac42dc58017c1a001c3717da7df
split: test
type: C-MTEB/CMedQAv1-reranking
metrics:
- type: map
value: 77.95952507806115
- type: mrr
value: 80.8643253968254
- type: main_score
value: 77.95952507806115
task:
type: Reranking
- dataset:
config: default
name: MTEB CMedQAv2-reranking (default)
revision: 23d186750531a14a0357ca22cd92d712fd512ea0
split: test
type: C-MTEB/CMedQAv2-reranking
metrics:
- type: map
value: 78.21522500165045
- type: mrr
value: 81.28194444444443
- type: main_score
value: 78.21522500165045
task:
type: Reranking
- dataset:
config: default
name: MTEB CQADupstackAndroidRetrieval (default)
revision: f46a197baaae43b4f621051089b82a364682dfeb
split: test
type: mteb/cqadupstack-android
metrics:
- type: map_at_1
value: 33.377
- type: map_at_10
value: 46.371
- type: map_at_100
value: 47.829
- type: map_at_1000
value: 47.94
- type: map_at_20
value: 47.205000000000005
- type: map_at_3
value: 42.782
- type: map_at_5
value: 44.86
- type: mrr_at_1
value: 41.345
- type: mrr_at_10
value: 52.187
- type: mrr_at_100
value: 52.893
- type: mrr_at_1000
value: 52.929
- type: mrr_at_20
value: 52.637
- type: mrr_at_3
value: 49.714000000000006
- type: mrr_at_5
value: 51.373000000000005
- type: ndcg_at_1
value: 41.345
- type: ndcg_at_10
value: 52.946000000000005
- type: ndcg_at_100
value: 57.92699999999999
- type: ndcg_at_1000
value: 59.609
- type: ndcg_at_20
value: 54.900999999999996
- type: ndcg_at_3
value: 48.357
- type: ndcg_at_5
value: 50.739000000000004
- type: precision_at_1
value: 41.345
- type: precision_at_10
value: 10.186
- type: precision_at_100
value: 1.554
- type: precision_at_1000
value: 0.2
- type: precision_at_20
value: 5.959
- type: precision_at_3
value: 23.796
- type: precision_at_5
value: 17.024
- type: recall_at_1
value: 33.377
- type: recall_at_10
value: 65.067
- type: recall_at_100
value: 86.04899999999999
- type: recall_at_1000
value: 96.54899999999999
- type: recall_at_20
value: 72.071
- type: recall_at_3
value: 51.349999999999994
- type: recall_at_5
value: 58.41
- type: main_score
value: 52.946000000000005
task:
type: Retrieval
- dataset:
config: default
name: MTEB CQADupstackEnglishRetrieval (default)
revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
split: test
type: mteb/cqadupstack-english
metrics:
- type: map_at_1
value: 31.097
- type: map_at_10
value: 42.183
- type: map_at_100
value: 43.580999999999996
- type: map_at_1000
value: 43.718
- type: map_at_20
value: 42.921
- type: map_at_3
value: 38.963
- type: map_at_5
value: 40.815
- type: mrr_at_1
value: 39.745000000000005
- type: mrr_at_10
value: 48.736000000000004
- type: mrr_at_100
value: 49.405
- type: mrr_at_1000
value: 49.452
- type: mrr_at_20
value: 49.118
- type: mrr_at_3
value: 46.497
- type: mrr_at_5
value: 47.827999999999996
- type: ndcg_at_1
value: 39.745000000000005
- type: ndcg_at_10
value: 48.248000000000005
- type: ndcg_at_100
value: 52.956
- type: ndcg_at_1000
value: 54.99699999999999
- type: ndcg_at_20
value: 50.01
- type: ndcg_at_3
value: 43.946000000000005
- type: ndcg_at_5
value: 46.038000000000004
- type: precision_at_1
value: 39.745000000000005
- type: precision_at_10
value: 9.229
- type: precision_at_100
value: 1.5070000000000001
- type: precision_at_1000
value: 0.199
- type: precision_at_20
value: 5.489999999999999
- type: precision_at_3
value: 21.38
- type: precision_at_5
value: 15.274
- type: recall_at_1
value: 31.097
- type: recall_at_10
value: 58.617
- type: recall_at_100
value: 78.55199999999999
- type: recall_at_1000
value: 91.13900000000001
- type: recall_at_20
value: 64.92
- type: recall_at_3
value: 45.672000000000004
- type: recall_at_5
value: 51.669
- type: main_score
value: 48.248000000000005
task:
type: Retrieval
- dataset:
config: default
name: MTEB CQADupstackGamingRetrieval (default)
revision: 4885aa143210c98657558c04aaf3dc47cfb54340
split: test
type: mteb/cqadupstack-gaming
metrics:
- type: map_at_1
value: 39.745000000000005
- type: map_at_10
value: 52.063
- type: map_at_100
value: 53.077
- type: map_at_1000
value: 53.13
- type: map_at_20
value: 52.66
- type: map_at_3
value: 48.662
- type: map_at_5
value: 50.507000000000005
- type: mrr_at_1
value: 45.391999999999996
- type: mrr_at_10
value: 55.528
- type: mrr_at_100
value: 56.16100000000001
- type: mrr_at_1000
value: 56.192
- type: mrr_at_20
value: 55.923
- type: mrr_at_3
value: 52.93600000000001
- type: mrr_at_5
value: 54.435
- type: ndcg_at_1
value: 45.391999999999996
- type: ndcg_at_10
value: 58.019
- type: ndcg_at_100
value: 61.936
- type: ndcg_at_1000
value: 63.015
- type: ndcg_at_20
value: 59.691
- type: ndcg_at_3
value: 52.294
- type: ndcg_at_5
value: 55.017
- type: precision_at_1
value: 45.391999999999996
- type: precision_at_10
value: 9.386
- type: precision_at_100
value: 1.232
- type: precision_at_1000
value: 0.136
- type: precision_at_20
value: 5.223
- type: precision_at_3
value: 23.177
- type: precision_at_5
value: 15.9
- type: recall_at_1
value: 39.745000000000005
- type: recall_at_10
value: 72.08099999999999
- type: recall_at_100
value: 88.85300000000001
- type: recall_at_1000
value: 96.569
- type: recall_at_20
value: 78.203
- type: recall_at_3
value: 56.957
- type: recall_at_5
value: 63.63100000000001
- type: main_score
value: 58.019
task:
type: Retrieval
- dataset:
config: default
name: MTEB CQADupstackGisRetrieval (default)
revision: 5003b3064772da1887988e05400cf3806fe491f2
split: test
type: mteb/cqadupstack-gis
metrics:
- type: map_at_1
value: 26.651999999999997
- type: map_at_10
value: 35.799
- type: map_at_100
value: 36.846000000000004
- type: map_at_1000
value: 36.931000000000004
- type: map_at_20
value: 36.341
- type: map_at_3
value: 32.999
- type: map_at_5
value: 34.597
- type: mrr_at_1
value: 28.814
- type: mrr_at_10
value: 37.869
- type: mrr_at_100
value: 38.728
- type: mrr_at_1000
value: 38.795
- type: mrr_at_20
value: 38.317
- type: mrr_at_3
value: 35.235
- type: mrr_at_5
value: 36.738
- type: ndcg_at_1
value: 28.814
- type: ndcg_at_10
value: 41.028
- type: ndcg_at_100
value: 46.162
- type: ndcg_at_1000
value: 48.15
- type: ndcg_at_20
value: 42.824
- type: ndcg_at_3
value: 35.621
- type: ndcg_at_5
value: 38.277
- type: precision_at_1
value: 28.814
- type: precision_at_10
value: 6.361999999999999
- type: precision_at_100
value: 0.9450000000000001
- type: precision_at_1000
value: 0.11399999999999999
- type: precision_at_20
value: 3.6159999999999997
- type: precision_at_3
value: 15.140999999999998
- type: precision_at_5
value: 10.712000000000002
- type: recall_at_1
value: 26.651999999999997
- type: recall_at_10
value: 55.038
- type: recall_at_100
value: 78.806
- type: recall_at_1000
value: 93.485
- type: recall_at_20
value: 61.742
- type: recall_at_3
value: 40.682
- type: recall_at_5
value: 46.855000000000004
- type: main_score
value: 41.028
task:
type: Retrieval
- dataset:
config: default
name: MTEB CQADupstackMathematicaRetrieval (default)
revision: 90fceea13679c63fe563ded68f3b6f06e50061de
split: test
type: mteb/cqadupstack-mathematica
metrics:
- type: map_at_1
value: 17.627000000000002
- type: map_at_10
value: 26.436999999999998
- type: map_at_100
value: 27.85
- type: map_at_1000
value: 27.955999999999996
- type: map_at_20
value: 27.233
- type: map_at_3
value: 23.777
- type: map_at_5
value: 25.122
- type: mrr_at_1
value: 22.387999999999998
- type: mrr_at_10
value: 31.589
- type: mrr_at_100
value: 32.641999999999996
- type: mrr_at_1000
value: 32.696999999999996
- type: mrr_at_20
value: 32.201
- type: mrr_at_3
value: 28.98
- type: mrr_at_5
value: 30.342000000000002
- type: ndcg_at_1
value: 22.387999999999998
- type: ndcg_at_10
value: 32.129999999999995
- type: ndcg_at_100
value: 38.562999999999995
- type: ndcg_at_1000
value: 40.903
- type: ndcg_at_20
value: 34.652
- type: ndcg_at_3
value: 27.26
- type: ndcg_at_5
value: 29.235
- type: precision_at_1
value: 22.387999999999998
- type: precision_at_10
value: 5.970000000000001
- type: precision_at_100
value: 1.068
- type: precision_at_1000
value: 0.13899999999999998
- type: precision_at_20
value: 3.6999999999999997
- type: precision_at_3
value: 13.267000000000001
- type: precision_at_5
value: 9.403
- type: recall_at_1
value: 17.627000000000002
- type: recall_at_10
value: 44.71
- type: recall_at_100
value: 72.426
- type: recall_at_1000
value: 88.64699999999999
- type: recall_at_20
value: 53.65
- type: recall_at_3
value: 30.989
- type: recall_at_5
value: 36.237
- type: main_score
value: 32.129999999999995
task:
type: Retrieval
- dataset:
config: default
name: MTEB CQADupstackPhysicsRetrieval (default)
revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
split: test
type: mteb/cqadupstack-physics
metrics:
- type: map_at_1
value: 30.891000000000002
- type: map_at_10
value: 41.519
- type: map_at_100
value: 42.896
- type: map_at_1000
value: 42.992999999999995
- type: map_at_20
value: 42.287
- type: map_at_3
value: 37.822
- type: map_at_5
value: 39.976
- type: mrr_at_1
value: 37.921
- type: mrr_at_10
value: 47.260999999999996
- type: mrr_at_100
value: 48.044
- type: mrr_at_1000
value: 48.08
- type: mrr_at_20
value: 47.699999999999996
- type: mrr_at_3
value: 44.513999999999996
- type: mrr_at_5
value: 46.064
- type: ndcg_at_1
value: 37.921
- type: ndcg_at_10
value: 47.806
- type: ndcg_at_100
value: 53.274
- type: ndcg_at_1000
value: 55.021
- type: ndcg_at_20
value: 49.973
- type: ndcg_at_3
value: 42.046
- type: ndcg_at_5
value: 44.835
- type: precision_at_1
value: 37.921
- type: precision_at_10
value: 8.767999999999999
- type: precision_at_100
value: 1.353
- type: precision_at_1000
value: 0.168
- type: precision_at_20
value: 5.135
- type: precision_at_3
value: 20.051
- type: precision_at_5
value: 14.398
- type: recall_at_1
value: 30.891000000000002
- type: recall_at_10
value: 60.897999999999996
- type: recall_at_100
value: 83.541
- type: recall_at_1000
value: 94.825
- type: recall_at_20
value: 68.356
- type: recall_at_3
value: 44.65
- type: recall_at_5
value: 51.919000000000004
- type: main_score
value: 47.806
task:
type: Retrieval
- dataset:
config: default
name: MTEB CQADupstackProgrammersRetrieval (default)
revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
split: test
type: mteb/cqadupstack-programmers
metrics:
- type: map_at_1
value: 27.654
- type: map_at_10
value: 38.025999999999996
- type: map_at_100
value: 39.425
- type: map_at_1000
value: 39.528
- type: map_at_20
value: 38.838
- type: map_at_3
value: 34.745
- type: map_at_5
value: 36.537
- type: mrr_at_1
value: 34.018
- type: mrr_at_10
value: 43.314
- type: mrr_at_100
value: 44.283
- type: mrr_at_1000
value: 44.327
- type: mrr_at_20
value: 43.929
- type: mrr_at_3
value: 40.868
- type: mrr_at_5
value: 42.317
- type: ndcg_at_1
value: 34.018
- type: ndcg_at_10
value: 43.887
- type: ndcg_at_100
value: 49.791000000000004
- type: ndcg_at_1000
value: 51.834
- type: ndcg_at_20
value: 46.376
- type: ndcg_at_3
value: 38.769999999999996
- type: ndcg_at_5
value: 41.144
- type: precision_at_1
value: 34.018
- type: precision_at_10
value: 8.001999999999999
- type: precision_at_100
value: 1.2630000000000001
- type: precision_at_1000
value: 0.16
- type: precision_at_20
value: 4.737
- type: precision_at_3
value: 18.417
- type: precision_at_5
value: 13.150999999999998
- type: recall_at_1
value: 27.654
- type: recall_at_10
value: 56.111
- type: recall_at_100
value: 81.136
- type: recall_at_1000
value: 94.788
- type: recall_at_20
value: 65.068
- type: recall_at_3
value: 41.713
- type: recall_at_5
value: 48.106
- type: main_score
value: 43.887
task:
type: Retrieval
- dataset:
config: default
name: MTEB CQADupstackRetrieval (default)
revision: CQADupstackRetrieval_is_a_combined_dataset
split: test
type: CQADupstackRetrieval_is_a_combined_dataset
metrics:
- type: main_score
value: 42.58858333333333
- type: ndcg_at_10
value: 42.58858333333333
task:
type: Retrieval
- dataset:
config: default
name: MTEB CQADupstackStatsRetrieval (default)
revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
split: test
type: mteb/cqadupstack-stats
metrics:
- type: map_at_1
value: 24.501
- type: map_at_10
value: 32.814
- type: map_at_100
value: 33.754
- type: map_at_1000
value: 33.859
- type: map_at_20
value: 33.324
- type: map_at_3
value: 30.758000000000003
- type: map_at_5
value: 31.936999999999998
- type: mrr_at_1
value: 27.761000000000003
- type: mrr_at_10
value: 35.662
- type: mrr_at_100
value: 36.443999999999996
- type: mrr_at_1000
value: 36.516999999999996
- type: mrr_at_20
value: 36.085
- type: mrr_at_3
value: 33.742
- type: mrr_at_5
value: 34.931
- type: ndcg_at_1
value: 27.761000000000003
- type: ndcg_at_10
value: 37.208000000000006
- type: ndcg_at_100
value: 41.839
- type: ndcg_at_1000
value: 44.421
- type: ndcg_at_20
value: 38.917
- type: ndcg_at_3
value: 33.544000000000004
- type: ndcg_at_5
value: 35.374
- type: precision_at_1
value: 27.761000000000003
- type: precision_at_10
value: 5.92
- type: precision_at_100
value: 0.899
- type: precision_at_1000
value: 0.12
- type: precision_at_20
value: 3.4130000000000003
- type: precision_at_3
value: 15.031
- type: precision_at_5
value: 10.306999999999999
- type: recall_at_1
value: 24.501
- type: recall_at_10
value: 47.579
- type: recall_at_100
value: 69.045
- type: recall_at_1000
value: 88.032
- type: recall_at_20
value: 54.125
- type: recall_at_3
value: 37.202
- type: recall_at_5
value: 41.927
- type: main_score
value: 37.208000000000006
task:
type: Retrieval
- dataset:
config: default
name: MTEB CQADupstackTexRetrieval (default)
revision: 46989137a86843e03a6195de44b09deda022eec7
split: test
type: mteb/cqadupstack-tex
metrics:
- type: map_at_1
value: 18.29
- type: map_at_10
value: 26.183
- type: map_at_100
value: 27.351999999999997
- type: map_at_1000
value: 27.483999999999998
- type: map_at_20
value: 26.798
- type: map_at_3
value: 23.629
- type: map_at_5
value: 24.937
- type: mrr_at_1
value: 22.299
- type: mrr_at_10
value: 30.189
- type: mrr_at_100
value: 31.098
- type: mrr_at_1000
value: 31.177
- type: mrr_at_20
value: 30.697000000000003
- type: mrr_at_3
value: 27.862
- type: mrr_at_5
value: 29.066
- type: ndcg_at_1
value: 22.299
- type: ndcg_at_10
value: 31.202
- type: ndcg_at_100
value: 36.617
- type: ndcg_at_1000
value: 39.544000000000004
- type: ndcg_at_20
value: 33.177
- type: ndcg_at_3
value: 26.639000000000003
- type: ndcg_at_5
value: 28.526
- type: precision_at_1
value: 22.299
- type: precision_at_10
value: 5.8020000000000005
- type: precision_at_100
value: 1.0070000000000001
- type: precision_at_1000
value: 0.14400000000000002
- type: precision_at_20
value: 3.505
- type: precision_at_3
value: 12.698
- type: precision_at_5
value: 9.174
- type: recall_at_1
value: 18.29
- type: recall_at_10
value: 42.254999999999995
- type: recall_at_100
value: 66.60000000000001
- type: recall_at_1000
value: 87.31400000000001
- type: recall_at_20
value: 49.572
- type: recall_at_3
value: 29.342000000000002
- type: recall_at_5
value: 34.221000000000004
- type: main_score
value: 31.202
task:
type: Retrieval
- dataset:
config: default
name: MTEB CQADupstackUnixRetrieval (default)
revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
split: test
type: mteb/cqadupstack-unix
metrics:
- type: map_at_1
value: 27.722
- type: map_at_10
value: 37.698
- type: map_at_100
value: 38.899
- type: map_at_1000
value: 38.998
- type: map_at_20
value: 38.381
- type: map_at_3
value: 34.244
- type: map_at_5
value: 36.295
- type: mrr_at_1
value: 32.183
- type: mrr_at_10
value: 41.429
- type: mrr_at_100
value: 42.308
- type: mrr_at_1000
value: 42.358000000000004
- type: mrr_at_20
value: 41.957
- type: mrr_at_3
value: 38.401999999999994
- type: mrr_at_5
value: 40.294999999999995
- type: ndcg_at_1
value: 32.183
- type: ndcg_at_10
value: 43.519000000000005
- type: ndcg_at_100
value: 48.786
- type: ndcg_at_1000
value: 50.861999999999995
- type: ndcg_at_20
value: 45.654
- type: ndcg_at_3
value: 37.521
- type: ndcg_at_5
value: 40.615
- type: precision_at_1
value: 32.183
- type: precision_at_10
value: 7.603
- type: precision_at_100
value: 1.135
- type: precision_at_1000
value: 0.14200000000000002
- type: precision_at_20
value: 4.408
- type: precision_at_3
value: 17.071
- type: precision_at_5
value: 12.668
- type: recall_at_1
value: 27.722
- type: recall_at_10
value: 57.230000000000004
- type: recall_at_100
value: 79.97999999999999
- type: recall_at_1000
value: 94.217
- type: recall_at_20
value: 64.864
- type: recall_at_3
value: 41.215
- type: recall_at_5
value: 48.774
- type: main_score
value: 43.519000000000005
task:
type: Retrieval
- dataset:
config: default
name: MTEB CQADupstackWebmastersRetrieval (default)
revision: 160c094312a0e1facb97e55eeddb698c0abe3571
split: test
type: mteb/cqadupstack-webmasters
metrics:
- type: map_at_1
value: 25.852999999999998
- type: map_at_10
value: 35.394999999999996
- type: map_at_100
value: 37.291999999999994
- type: map_at_1000
value: 37.495
- type: map_at_20
value: 36.372
- type: map_at_3
value: 32.336
- type: map_at_5
value: 34.159
- type: mrr_at_1
value: 31.818
- type: mrr_at_10
value: 40.677
- type: mrr_at_100
value: 41.728
- type: mrr_at_1000
value: 41.778
- type: mrr_at_20
value: 41.301
- type: mrr_at_3
value: 38.208
- type: mrr_at_5
value: 39.592
- type: ndcg_at_1
value: 31.818
- type: ndcg_at_10
value: 41.559000000000005
- type: ndcg_at_100
value: 48.012
- type: ndcg_at_1000
value: 50.234
- type: ndcg_at_20
value: 44.15
- type: ndcg_at_3
value: 36.918
- type: ndcg_at_5
value: 39.227000000000004
- type: precision_at_1
value: 31.818
- type: precision_at_10
value: 8.043
- type: precision_at_100
value: 1.625
- type: precision_at_1000
value: 0.245
- type: precision_at_20
value: 5.2170000000000005
- type: precision_at_3
value: 17.655
- type: precision_at_5
value: 12.845999999999998
- type: recall_at_1
value: 25.852999999999998
- type: recall_at_10
value: 53.093
- type: recall_at_100
value: 81.05799999999999
- type: recall_at_1000
value: 94.657
- type: recall_at_20
value: 62.748000000000005
- type: recall_at_3
value: 39.300000000000004
- type: recall_at_5
value: 45.754
- type: main_score
value: 41.559000000000005
task:
type: Retrieval
- dataset:
config: default
name: MTEB CQADupstackWordpressRetrieval (default)
revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
split: test
type: mteb/cqadupstack-wordpress
metrics:
- type: map_at_1
value: 19.23
- type: map_at_10
value: 28.128999999999998
- type: map_at_100
value: 29.195
- type: map_at_1000
value: 29.310000000000002
- type: map_at_20
value: 28.713
- type: map_at_3
value: 25.191000000000003
- type: map_at_5
value: 26.69
- type: mrr_at_1
value: 21.257
- type: mrr_at_10
value: 30.253999999999998
- type: mrr_at_100
value: 31.195
- type: mrr_at_1000
value: 31.270999999999997
- type: mrr_at_20
value: 30.747999999999998
- type: mrr_at_3
value: 27.633999999999997
- type: mrr_at_5
value: 28.937
- type: ndcg_at_1
value: 21.257
- type: ndcg_at_10
value: 33.511
- type: ndcg_at_100
value: 38.733000000000004
- type: ndcg_at_1000
value: 41.489
- type: ndcg_at_20
value: 35.476
- type: ndcg_at_3
value: 27.845
- type: ndcg_at_5
value: 30.264999999999997
- type: precision_at_1
value: 21.257
- type: precision_at_10
value: 5.619
- type: precision_at_100
value: 0.893
- type: precision_at_1000
value: 0.124
- type: precision_at_20
value: 3.29
- type: precision_at_3
value: 12.508
- type: precision_at_5
value: 8.946
- type: recall_at_1
value: 19.23
- type: recall_at_10
value: 48.185
- type: recall_at_100
value: 71.932
- type: recall_at_1000
value: 92.587
- type: recall_at_20
value: 55.533
- type: recall_at_3
value: 32.865
- type: recall_at_5
value: 38.577
- type: main_score
value: 33.511
task:
type: Retrieval
- dataset:
config: default
name: MTEB ClimateFEVER (default)
revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
split: test
type: mteb/climate-fever
metrics:
- type: map_at_1
value: 19.594
- type: map_at_10
value: 32.519
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revision: cd540c506dae1cf9e9a59c3e06f42030d54e7301
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type: C-MTEB/CmedqaRetrieval
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task:
type: Retrieval
- dataset:
config: default
name: MTEB Cmnli (default)
revision: None
split: validation
type: C-MTEB/CMNLI
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task:
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task:
type: Retrieval
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config: default
name: MTEB EmotionClassification (default)
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
split: test
type: mteb/emotion
metrics:
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value: 74.83537255312045
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task:
type: Classification
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config: default
name: MTEB FEVER (default)
revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
split: test
type: mteb/fever
metrics:
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value: 85.762
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value: 85.954
- type: map_at_1000
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value: 85.887
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value: 84.854
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value: 85.408
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value: 90.432
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value: 90.244
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value: 98.18
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value: 95.707
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value: 90.853
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task:
type: Retrieval
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config: default
name: MTEB FiQA2018 (default)
revision: 27a168819829fe9bcd655c2df245fb19452e8e06
split: test
type: mteb/fiqa
metrics:
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task:
type: Retrieval
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config: default
name: MTEB GeoreviewClassification (default)
revision: 3765c0d1de6b7d264bc459433c45e5a75513839c
split: test
type: ai-forever/georeview-classification
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task:
type: Classification
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config: default
name: MTEB GeoreviewClusteringP2P (default)
revision: 97a313c8fc85b47f13f33e7e9a95c1ad888c7fec
split: test
type: ai-forever/georeview-clustering-p2p
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task:
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config: default
name: MTEB GerDaLIR (default)
revision: 0bb47f1d73827e96964edb84dfe552f62f4fd5eb
split: test
type: jinaai/ger_da_lir
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task:
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config: default
name: MTEB GermanDPR (default)
revision: 5129d02422a66be600ac89cd3e8531b4f97d347d
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task:
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name: MTEB GermanQuAD-Retrieval (default)
revision: f5c87ae5a2e7a5106606314eef45255f03151bb3
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type: mteb/germanquad-retrieval
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task:
type: Retrieval
- dataset:
config: default
name: MTEB GermanSTSBenchmark (default)
revision: e36907544d44c3a247898ed81540310442329e20
split: test
type: jinaai/german-STSbenchmark
metrics:
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task:
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config: default
name: MTEB HALClusteringS2S (default)
revision: e06ebbbb123f8144bef1a5d18796f3dec9ae2915
split: test
type: lyon-nlp/clustering-hal-s2s
metrics:
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value: 27.477557517301303
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task:
type: Clustering
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config: default
name: MTEB HeadlineClassification (default)
revision: 2fe05ee6b5832cda29f2ef7aaad7b7fe6a3609eb
split: test
type: ai-forever/headline-classification
metrics:
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task:
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config: default
name: MTEB HotpotQA (default)
revision: ab518f4d6fcca38d87c25209f94beba119d02014
split: test
type: mteb/hotpotqa
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value: 56.989000000000004
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task:
type: Retrieval
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config: default
name: MTEB IFlyTek (default)
revision: 421605374b29664c5fc098418fe20ada9bd55f8a
split: validation
type: C-MTEB/IFlyTek-classification
metrics:
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value: 33.929325579581636
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value: 43.03952025643197
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value: 41.67756829549827
task:
type: Classification
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config: default
name: MTEB ImdbClassification (default)
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
split: test
type: mteb/imdb
metrics:
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value: 91.90440000000001
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value: 88.78663714603425
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task:
type: Classification
- dataset:
config: default
name: MTEB InappropriatenessClassification (default)
revision: 601651fdc45ef243751676e62dd7a19f491c0285
split: test
type: ai-forever/inappropriateness-classification
metrics:
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value: 61.0498046875
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task:
type: Classification
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config: default
name: MTEB JDReview (default)
revision: b7c64bd89eb87f8ded463478346f76731f07bf8b
split: test
type: C-MTEB/JDReview-classification
metrics:
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task:
type: Classification
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config: default
name: MTEB KinopoiskClassification (default)
revision: 5911f26666ac11af46cb9c6849d0dc80a378af24
split: test
type: ai-forever/kinopoisk-sentiment-classification
metrics:
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task:
type: Classification
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config: default
name: MTEB LCQMC (default)
revision: 17f9b096f80380fce5ed12a9be8be7784b337daf
split: test
type: C-MTEB/LCQMC
metrics:
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value: 67.74375505907872
- type: cosine_spearman
value: 75.94582231399434
- type: euclidean_pearson
value: 74.52501692443582
- type: euclidean_spearman
value: 75.88428434746646
- type: main_score
value: 75.94582231399434
- type: manhattan_pearson
value: 74.55015441749529
- type: manhattan_spearman
value: 75.83288262176175
- type: pearson
value: 67.74375505907872
- type: spearman
value: 75.94582231399434
task:
type: STS
- dataset:
config: default
name: MTEB LEMBNarrativeQARetrieval (default)
revision: 6e346642246bfb4928c560ee08640dc84d074e8c
split: test
type: dwzhu/LongEmbed
metrics:
- type: map_at_1
value: 23.093
- type: map_at_10
value: 30.227999999999998
- type: map_at_100
value: 31.423000000000002
- type: map_at_1000
value: 31.533
- type: map_at_20
value: 30.835
- type: map_at_3
value: 27.983999999999998
- type: map_at_5
value: 29.253
- type: mrr_at_1
value: 23.093
- type: mrr_at_10
value: 30.227999999999998
- type: mrr_at_100
value: 31.423000000000002
- type: mrr_at_1000
value: 31.533
- type: mrr_at_20
value: 30.835
- type: mrr_at_3
value: 27.983999999999998
- type: mrr_at_5
value: 29.253
- type: ndcg_at_1
value: 23.093
- type: ndcg_at_10
value: 34.297
- type: ndcg_at_100
value: 41.049
- type: ndcg_at_1000
value: 43.566
- type: ndcg_at_20
value: 36.52
- type: ndcg_at_3
value: 29.629
- type: ndcg_at_5
value: 31.926
- type: precision_at_1
value: 23.093
- type: precision_at_10
value: 4.735
- type: precision_at_100
value: 0.8109999999999999
- type: precision_at_1000
value: 0.1
- type: precision_at_20
value: 2.8080000000000003
- type: precision_at_3
value: 11.468
- type: precision_at_5
value: 8.001
- type: recall_at_1
value: 23.093
- type: recall_at_10
value: 47.354
- type: recall_at_100
value: 81.147
- type: recall_at_1000
value: 100.0
- type: recall_at_20
value: 56.16799999999999
- type: recall_at_3
value: 34.405
- type: recall_at_5
value: 40.004
- type: main_score
value: 34.297
task:
type: Retrieval
- dataset:
config: default
name: MTEB LEMBNeedleRetrieval (default)
revision: 6e346642246bfb4928c560ee08640dc84d074e8c
split: test_256
type: dwzhu/LongEmbed
metrics:
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value: 64.0
- type: map_at_10
value: 77.083
- type: map_at_100
value: 77.265
- type: map_at_1000
value: 77.265
- type: map_at_20
value: 77.265
- type: map_at_3
value: 76.333
- type: map_at_5
value: 76.833
- type: mrr_at_1
value: 64.0
- type: mrr_at_10
value: 77.083
- type: mrr_at_100
value: 77.265
- type: mrr_at_1000
value: 77.265
- type: mrr_at_20
value: 77.265
- type: mrr_at_3
value: 76.333
- type: mrr_at_5
value: 76.833
- type: ndcg_at_1
value: 64.0
- type: ndcg_at_10
value: 82.325
- type: ndcg_at_100
value: 82.883
- type: ndcg_at_1000
value: 82.883
- type: ndcg_at_20
value: 82.883
- type: ndcg_at_3
value: 80.833
- type: ndcg_at_5
value: 81.694
- type: precision_at_1
value: 64.0
- type: precision_at_10
value: 9.8
- type: precision_at_100
value: 1.0
- type: precision_at_1000
value: 0.1
- type: precision_at_20
value: 5.0
- type: precision_at_3
value: 31.333
- type: precision_at_5
value: 19.2
- type: recall_at_1
value: 64.0
- type: recall_at_10
value: 98.0
- type: recall_at_100
value: 100.0
- type: recall_at_1000
value: 100.0
- type: recall_at_20
value: 100.0
- type: recall_at_3
value: 94.0
- type: recall_at_5
value: 96.0
- type: main_score
value: 64.0
task:
type: Retrieval
- dataset:
config: default
name: MTEB LEMBPasskeyRetrieval (default)
revision: 6e346642246bfb4928c560ee08640dc84d074e8c
split: test_256
type: dwzhu/LongEmbed
metrics:
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value: 100.0
- type: map_at_10
value: 100.0
- type: map_at_100
value: 100.0
- type: map_at_1000
value: 100.0
- type: map_at_20
value: 100.0
- type: map_at_3
value: 100.0
- type: map_at_5
value: 100.0
- type: mrr_at_1
value: 100.0
- type: mrr_at_10
value: 100.0
- type: mrr_at_100
value: 100.0
- type: mrr_at_1000
value: 100.0
- type: mrr_at_20
value: 100.0
- type: mrr_at_3
value: 100.0
- type: mrr_at_5
value: 100.0
- type: ndcg_at_1
value: 100.0
- type: ndcg_at_10
value: 100.0
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value: 100.0
- type: ndcg_at_1000
value: 100.0
- type: ndcg_at_20
value: 100.0
- type: ndcg_at_3
value: 100.0
- type: ndcg_at_5
value: 100.0
- type: precision_at_1
value: 100.0
- type: precision_at_10
value: 10.0
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value: 1.0
- type: precision_at_1000
value: 0.1
- type: precision_at_20
value: 5.0
- type: precision_at_3
value: 33.333
- type: precision_at_5
value: 20.0
- type: recall_at_1
value: 100.0
- type: recall_at_10
value: 100.0
- type: recall_at_100
value: 100.0
- type: recall_at_1000
value: 100.0
- type: recall_at_20
value: 100.0
- type: recall_at_3
value: 100.0
- type: recall_at_5
value: 100.0
- type: main_score
value: 100.0
task:
type: Retrieval
- dataset:
config: default
name: MTEB LEMBQMSumRetrieval (default)
revision: 6e346642246bfb4928c560ee08640dc84d074e8c
split: test
type: dwzhu/LongEmbed
metrics:
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value: 24.361
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- type: map_at_100
value: 35.104
- type: map_at_1000
value: 35.127
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- type: mrr_at_1
value: 24.361
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value: 33.641
- type: mrr_at_100
value: 35.104
- type: mrr_at_1000
value: 35.127
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- type: mrr_at_3
value: 30.255
- type: mrr_at_5
value: 32.079
- type: ndcg_at_1
value: 24.361
- type: ndcg_at_10
value: 39.337
- type: ndcg_at_100
value: 47.384
- type: ndcg_at_1000
value: 47.75
- type: ndcg_at_20
value: 42.077999999999996
- type: ndcg_at_3
value: 32.235
- type: ndcg_at_5
value: 35.524
- type: precision_at_1
value: 24.361
- type: precision_at_10
value: 5.783
- type: precision_at_100
value: 0.975
- type: precision_at_1000
value: 0.1
- type: precision_at_20
value: 3.435
- type: precision_at_3
value: 12.661
- type: precision_at_5
value: 9.193999999999999
- type: recall_at_1
value: 24.361
- type: recall_at_10
value: 57.826
- type: recall_at_100
value: 97.51100000000001
- type: recall_at_1000
value: 100.0
- type: recall_at_20
value: 68.697
- type: recall_at_3
value: 37.983
- type: recall_at_5
value: 45.972
- type: main_score
value: 39.337
task:
type: Retrieval
- dataset:
config: default
name: MTEB LEMBSummScreenFDRetrieval (default)
revision: 6e346642246bfb4928c560ee08640dc84d074e8c
split: validation
type: dwzhu/LongEmbed
metrics:
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value: 84.821
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value: 90.11200000000001
- type: map_at_100
value: 90.158
- type: map_at_1000
value: 90.158
- type: map_at_20
value: 90.137
- type: map_at_3
value: 89.385
- type: map_at_5
value: 89.876
- type: mrr_at_1
value: 84.821
- type: mrr_at_10
value: 90.11200000000001
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value: 90.158
- type: mrr_at_1000
value: 90.158
- type: mrr_at_20
value: 90.137
- type: mrr_at_3
value: 89.385
- type: mrr_at_5
value: 89.876
- type: ndcg_at_1
value: 84.821
- type: ndcg_at_10
value: 92.334
- type: ndcg_at_100
value: 92.535
- type: ndcg_at_1000
value: 92.535
- type: ndcg_at_20
value: 92.414
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- type: ndcg_at_5
value: 91.758
- type: precision_at_1
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- type: precision_at_10
value: 9.911
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value: 1.0
- type: precision_at_1000
value: 0.1
- type: precision_at_20
value: 4.97
- type: precision_at_3
value: 31.746000000000002
- type: precision_at_5
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- type: recall_at_1
value: 84.821
- type: recall_at_10
value: 99.107
- type: recall_at_100
value: 100.0
- type: recall_at_1000
value: 100.0
- type: recall_at_20
value: 99.405
- type: recall_at_3
value: 95.238
- type: recall_at_5
value: 97.321
- type: main_score
value: 92.334
task:
type: Retrieval
- dataset:
config: default
name: MTEB LEMBWikimQARetrieval (default)
revision: 6e346642246bfb4928c560ee08640dc84d074e8c
split: test
type: dwzhu/LongEmbed
metrics:
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value: 53.667
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- type: precision_at_100
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- type: recall_at_1
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- type: recall_at_100
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- type: recall_at_1000
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value: 86.0
- type: recall_at_3
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- type: recall_at_5
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task:
type: Retrieval
- dataset:
config: deu-deu
name: MTEB MLQARetrieval (deu-deu)
revision: 397ed406c1a7902140303e7faf60fff35b58d285
split: test
type: facebook/mlqa
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revision: 397ed406c1a7902140303e7faf60fff35b58d285
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task:
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name: MTEB MLQARetrieval (deu-eng)
revision: 397ed406c1a7902140303e7faf60fff35b58d285
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task:
type: Retrieval
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config: eng-eng
name: MTEB MLQARetrieval (eng-eng)
revision: 397ed406c1a7902140303e7faf60fff35b58d285
split: test
type: facebook/mlqa
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task:
type: Retrieval
- dataset:
config: de
name: MTEB MLSUMClusteringP2P (de)
revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7
split: test
type: reciTAL/mlsum
metrics:
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task:
type: Clustering
- dataset:
config: fr
name: MTEB MLSUMClusteringP2P (fr)
revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7
split: test
type: reciTAL/mlsum
metrics:
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task:
type: Clustering
- dataset:
config: ru
name: MTEB MLSUMClusteringP2P (ru)
revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7
split: test
type: reciTAL/mlsum
metrics:
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task:
type: Clustering
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config: es
name: MTEB MLSUMClusteringP2P (es)
revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7
split: test
type: reciTAL/mlsum
metrics:
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task:
type: Clustering
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config: de
name: MTEB MLSUMClusteringS2S (de)
revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7
split: test
type: reciTAL/mlsum
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task:
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config: fr
name: MTEB MLSUMClusteringS2S (fr)
revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7
split: test
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task:
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config: ru
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revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7
split: test
type: reciTAL/mlsum
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task:
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config: es
name: MTEB MLSUMClusteringS2S (es)
revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7
split: test
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task:
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config: default
name: MTEB MMarcoReranking (default)
revision: 8e0c766dbe9e16e1d221116a3f36795fbade07f6
split: dev
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task:
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name: MTEB MMarcoRetrieval (default)
revision: 539bbde593d947e2a124ba72651aafc09eb33fc2
split: dev
type: C-MTEB/MMarcoRetrieval
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- type: recall_at_1
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value: 96.99
- type: recall_at_1000
value: 98.958
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value: 93.21199999999999
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value: 80.84599999999999
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value: 85.732
task:
type: Retrieval
- dataset:
config: default
name: MTEB MSMARCO (default)
revision: c5a29a104738b98a9e76336939199e264163d4a0
split: dev
type: mteb/msmarco
metrics:
- type: map_at_1
value: 21.861
- type: map_at_10
value: 34.008
- type: map_at_100
value: 35.174
- type: map_at_1000
value: 35.224
- type: map_at_20
value: 34.705999999999996
- type: map_at_3
value: 30.209000000000003
- type: map_at_5
value: 32.351
- type: mrr_at_1
value: 22.493
- type: mrr_at_10
value: 34.583999999999996
- type: mrr_at_100
value: 35.691
- type: mrr_at_1000
value: 35.736000000000004
- type: mrr_at_20
value: 35.257
- type: mrr_at_3
value: 30.85
- type: mrr_at_5
value: 32.962
- type: ndcg_at_1
value: 22.493
- type: ndcg_at_10
value: 40.815
- type: ndcg_at_100
value: 46.483999999999995
- type: ndcg_at_1000
value: 47.73
- type: ndcg_at_20
value: 43.302
- type: ndcg_at_3
value: 33.056000000000004
- type: ndcg_at_5
value: 36.879
- type: precision_at_1
value: 22.493
- type: precision_at_10
value: 6.465999999999999
- type: precision_at_100
value: 0.932
- type: precision_at_1000
value: 0.104
- type: precision_at_20
value: 3.752
- type: precision_at_3
value: 14.069
- type: precision_at_5
value: 10.384
- type: recall_at_1
value: 21.861
- type: recall_at_10
value: 61.781
- type: recall_at_100
value: 88.095
- type: recall_at_1000
value: 97.625
- type: recall_at_20
value: 71.44500000000001
- type: recall_at_3
value: 40.653
- type: recall_at_5
value: 49.841
- type: main_score
value: 40.815
task:
type: Retrieval
- dataset:
config: en
name: MTEB MTOPDomainClassification (en)
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
split: test
type: mteb/mtop_domain
metrics:
- type: accuracy
value: 97.4874601003192
- type: f1
value: 97.19067544931094
- type: f1_weighted
value: 97.49331776181019
- type: main_score
value: 97.4874601003192
task:
type: Classification
- dataset:
config: de
name: MTEB MTOPDomainClassification (de)
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
split: test
type: mteb/mtop_domain
metrics:
- type: accuracy
value: 96.89489997182305
- type: f1
value: 96.51138586512977
- type: f1_weighted
value: 96.89723065967186
- type: main_score
value: 96.89489997182305
task:
type: Classification
- dataset:
config: es
name: MTEB MTOPDomainClassification (es)
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
split: test
type: mteb/mtop_domain
metrics:
- type: accuracy
value: 97.17144763175452
- type: f1
value: 96.81785681878274
- type: f1_weighted
value: 97.1778974586874
- type: main_score
value: 97.17144763175452
task:
type: Classification
- dataset:
config: fr
name: MTEB MTOPDomainClassification (fr)
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
split: test
type: mteb/mtop_domain
metrics:
- type: accuracy
value: 96.30128405887879
- type: f1
value: 95.94555923088487
- type: f1_weighted
value: 96.30399416794926
- type: main_score
value: 96.30128405887879
task:
type: Classification
- dataset:
config: en
name: MTEB MTOPIntentClassification (en)
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
split: test
type: mteb/mtop_intent
metrics:
- type: accuracy
value: 84.53488372093022
- type: f1
value: 61.77995074251401
- type: f1_weighted
value: 86.8005170485101
- type: main_score
value: 84.53488372093022
task:
type: Classification
- dataset:
config: de
name: MTEB MTOPIntentClassification (de)
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
split: test
type: mteb/mtop_intent
metrics:
- type: accuracy
value: 80.79459002535924
- type: f1
value: 56.08938302001448
- type: f1_weighted
value: 83.66582131948252
- type: main_score
value: 80.79459002535924
task:
type: Classification
- dataset:
config: es
name: MTEB MTOPIntentClassification (es)
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
split: test
type: mteb/mtop_intent
metrics:
- type: accuracy
value: 84.7765176784523
- type: f1
value: 61.39860057885528
- type: f1_weighted
value: 86.94881745670745
- type: main_score
value: 84.7765176784523
task:
type: Classification
- dataset:
config: fr
name: MTEB MTOPIntentClassification (fr)
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
split: test
type: mteb/mtop_intent
metrics:
- type: accuracy
value: 82.2079549013467
- type: f1
value: 59.90260478749016
- type: f1_weighted
value: 84.36861708593257
- type: main_score
value: 82.2079549013467
task:
type: Classification
- dataset:
config: eng
name: MTEB MasakhaNEWSClassification (eng)
revision: 18193f187b92da67168c655c9973a165ed9593dd
split: test
type: mteb/masakhanews
metrics:
- type: accuracy
value: 74.98945147679325
- type: f1
value: 74.3157483560261
- type: f1_weighted
value: 75.01179008904884
- type: main_score
value: 74.98945147679325
task:
type: Classification
- dataset:
config: fra
name: MTEB MasakhaNEWSClassification (fra)
revision: 18193f187b92da67168c655c9973a165ed9593dd
split: test
type: mteb/masakhanews
metrics:
- type: accuracy
value: 74.02843601895735
- type: f1
value: 70.40326349620732
- type: f1_weighted
value: 74.6596277063484
- type: main_score
value: 74.02843601895735
task:
type: Classification
- dataset:
config: amh
name: MTEB MasakhaNEWSClusteringP2P (amh)
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
split: test
type: masakhane/masakhanews
metrics:
- type: main_score
value: 69.45780291725053
- type: v_measure
value: 69.45780291725053
- type: v_measure_std
value: 36.54340055904091
task:
type: Clustering
- dataset:
config: eng
name: MTEB MasakhaNEWSClusteringP2P (eng)
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
split: test
type: masakhane/masakhanews
metrics:
- type: main_score
value: 64.88996119332239
- type: v_measure
value: 64.88996119332239
- type: v_measure_std
value: 30.017223408197268
task:
type: Clustering
- dataset:
config: fra
name: MTEB MasakhaNEWSClusteringP2P (fra)
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
split: test
type: masakhane/masakhanews
metrics:
- type: main_score
value: 42.362383958691666
- type: v_measure
value: 42.362383958691666
- type: v_measure_std
value: 37.61076788039063
task:
type: Clustering
- dataset:
config: hau
name: MTEB MasakhaNEWSClusteringP2P (hau)
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
split: test
type: masakhane/masakhanews
metrics:
- type: main_score
value: 43.29201252405562
- type: v_measure
value: 43.29201252405562
- type: v_measure_std
value: 34.31987945146255
task:
type: Clustering
- dataset:
config: ibo
name: MTEB MasakhaNEWSClusteringP2P (ibo)
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
split: test
type: masakhane/masakhanews
metrics:
- type: main_score
value: 33.59926542995238
- type: v_measure
value: 33.59926542995238
- type: v_measure_std
value: 35.70048601084112
task:
type: Clustering
- dataset:
config: lin
name: MTEB MasakhaNEWSClusteringP2P (lin)
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
split: test
type: masakhane/masakhanews
metrics:
- type: main_score
value: 67.58487601893106
- type: v_measure
value: 67.58487601893106
- type: v_measure_std
value: 35.16784970777931
task:
type: Clustering
- dataset:
config: lug
name: MTEB MasakhaNEWSClusteringP2P (lug)
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
split: test
type: masakhane/masakhanews
metrics:
- type: main_score
value: 50.01220872023533
- type: v_measure
value: 50.01220872023533
- type: v_measure_std
value: 41.87411574676182
task:
type: Clustering
- dataset:
config: orm
name: MTEB MasakhaNEWSClusteringP2P (orm)
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
split: test
type: masakhane/masakhanews
metrics:
- type: main_score
value: 29.007847502598317
- type: v_measure
value: 29.007847502598317
- type: v_measure_std
value: 38.374997395079994
task:
type: Clustering
- dataset:
config: pcm
name: MTEB MasakhaNEWSClusteringP2P (pcm)
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
split: test
type: masakhane/masakhanews
metrics:
- type: main_score
value: 79.13520228554611
- type: v_measure
value: 79.13520228554611
- type: v_measure_std
value: 18.501843848275183
task:
type: Clustering
- dataset:
config: run
name: MTEB MasakhaNEWSClusteringP2P (run)
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
split: test
type: masakhane/masakhanews
metrics:
- type: main_score
value: 60.317213909746656
- type: v_measure
value: 60.317213909746656
- type: v_measure_std
value: 36.500281823747386
task:
type: Clustering
- dataset:
config: sna
name: MTEB MasakhaNEWSClusteringP2P (sna)
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
split: test
type: masakhane/masakhanews
metrics:
- type: main_score
value: 59.395277358240946
- type: v_measure
value: 59.395277358240946
- type: v_measure_std
value: 37.500916816164654
task:
type: Clustering
- dataset:
config: som
name: MTEB MasakhaNEWSClusteringP2P (som)
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
split: test
type: masakhane/masakhanews
metrics:
- type: main_score
value: 38.18638688704302
- type: v_measure
value: 38.18638688704302
- type: v_measure_std
value: 35.453681137564466
task:
type: Clustering
- dataset:
config: swa
name: MTEB MasakhaNEWSClusteringP2P (swa)
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
split: test
type: masakhane/masakhanews
metrics:
- type: main_score
value: 29.49230755729658
- type: v_measure
value: 29.49230755729658
- type: v_measure_std
value: 28.284313285264645
task:
type: Clustering
- dataset:
config: tir
name: MTEB MasakhaNEWSClusteringP2P (tir)
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
split: test
type: masakhane/masakhanews
metrics:
- type: main_score
value: 60.632258622750115
- type: v_measure
value: 60.632258622750115
- type: v_measure_std
value: 34.429711214740564
task:
type: Clustering
- dataset:
config: xho
name: MTEB MasakhaNEWSClusteringP2P (xho)
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
split: test
type: masakhane/masakhanews
metrics:
- type: main_score
value: 41.76322918806381
- type: v_measure
value: 41.76322918806381
- type: v_measure_std
value: 36.43245296200775
task:
type: Clustering
- dataset:
config: yor
name: MTEB MasakhaNEWSClusteringP2P (yor)
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
split: test
type: masakhane/masakhanews
metrics:
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value: 33.17083910808645
- type: v_measure
value: 33.17083910808645
- type: v_measure_std
value: 34.87547994284835
task:
type: Clustering
- dataset:
config: amh
name: MTEB MasakhaNEWSClusteringS2S (amh)
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
split: test
type: masakhane/masakhanews
metrics:
- type: main_score
value: 60.95132147787602
- type: v_measure
value: 60.95132147787602
- type: v_measure_std
value: 37.330148394033365
task:
type: Clustering
- dataset:
config: eng
name: MTEB MasakhaNEWSClusteringS2S (eng)
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
split: test
type: masakhane/masakhanews
metrics:
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value: 60.974810831426595
- type: v_measure
value: 60.974810831426595
- type: v_measure_std
value: 24.934675467507827
task:
type: Clustering
- dataset:
config: fra
name: MTEB MasakhaNEWSClusteringS2S (fra)
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
split: test
type: masakhane/masakhanews
metrics:
- type: main_score
value: 44.479206673553335
- type: v_measure
value: 44.479206673553335
- type: v_measure_std
value: 32.58254804499339
task:
type: Clustering
- dataset:
config: hau
name: MTEB MasakhaNEWSClusteringS2S (hau)
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
split: test
type: masakhane/masakhanews
metrics:
- type: main_score
value: 26.4742082741682
- type: v_measure
value: 26.4742082741682
- type: v_measure_std
value: 22.344929192323097
task:
type: Clustering
- dataset:
config: ibo
name: MTEB MasakhaNEWSClusteringS2S (ibo)
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
split: test
type: masakhane/masakhanews
metrics:
- type: main_score
value: 38.906129911741985
- type: v_measure
value: 38.906129911741985
- type: v_measure_std
value: 34.785601792668444
task:
type: Clustering
- dataset:
config: lin
name: MTEB MasakhaNEWSClusteringS2S (lin)
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
split: test
type: masakhane/masakhanews
metrics:
- type: main_score
value: 62.60982020876592
- type: v_measure
value: 62.60982020876592
- type: v_measure_std
value: 40.7368955715045
task:
type: Clustering
- dataset:
config: lug
name: MTEB MasakhaNEWSClusteringS2S (lug)
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
split: test
type: masakhane/masakhanews
metrics:
- type: main_score
value: 42.70424106365967
- type: v_measure
value: 42.70424106365967
- type: v_measure_std
value: 46.80946241135087
task:
type: Clustering
- dataset:
config: orm
name: MTEB MasakhaNEWSClusteringS2S (orm)
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
split: test
type: masakhane/masakhanews
metrics:
- type: main_score
value: 28.609942199922322
- type: v_measure
value: 28.609942199922322
- type: v_measure_std
value: 38.46685040191088
task:
type: Clustering
- dataset:
config: pcm
name: MTEB MasakhaNEWSClusteringS2S (pcm)
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
split: test
type: masakhane/masakhanews
metrics:
- type: main_score
value: 76.83901348810822
- type: v_measure
value: 76.83901348810822
- type: v_measure_std
value: 17.57617141269189
task:
type: Clustering
- dataset:
config: run
name: MTEB MasakhaNEWSClusteringS2S (run)
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
split: test
type: masakhane/masakhanews
metrics:
- type: main_score
value: 46.89757547846193
- type: v_measure
value: 46.89757547846193
- type: v_measure_std
value: 44.58903590203438
task:
type: Clustering
- dataset:
config: sna
name: MTEB MasakhaNEWSClusteringS2S (sna)
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
split: test
type: masakhane/masakhanews
metrics:
- type: main_score
value: 55.37185207068829
- type: v_measure
value: 55.37185207068829
- type: v_measure_std
value: 36.944574863543004
task:
type: Clustering
- dataset:
config: som
name: MTEB MasakhaNEWSClusteringS2S (som)
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
split: test
type: masakhane/masakhanews
metrics:
- type: main_score
value: 37.44211021681754
- type: v_measure
value: 37.44211021681754
- type: v_measure_std
value: 33.41469994463241
task:
type: Clustering
- dataset:
config: swa
name: MTEB MasakhaNEWSClusteringS2S (swa)
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
split: test
type: masakhane/masakhanews
metrics:
- type: main_score
value: 26.020680621216062
- type: v_measure
value: 26.020680621216062
- type: v_measure_std
value: 25.480037522570413
task:
type: Clustering
- dataset:
config: tir
name: MTEB MasakhaNEWSClusteringS2S (tir)
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
split: test
type: masakhane/masakhanews
metrics:
- type: main_score
value: 63.74306846771303
- type: v_measure
value: 63.74306846771303
- type: v_measure_std
value: 32.19119631078685
task:
type: Clustering
- dataset:
config: xho
name: MTEB MasakhaNEWSClusteringS2S (xho)
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
split: test
type: masakhane/masakhanews
metrics:
- type: main_score
value: 24.580890519243777
- type: v_measure
value: 24.580890519243777
- type: v_measure_std
value: 37.941836363967106
task:
type: Clustering
- dataset:
config: yor
name: MTEB MasakhaNEWSClusteringS2S (yor)
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
split: test
type: masakhane/masakhanews
metrics:
- type: main_score
value: 43.63458888828314
- type: v_measure
value: 43.63458888828314
- type: v_measure_std
value: 31.28169350649098
task:
type: Clustering
- dataset:
config: pl
name: MTEB MassiveIntentClassification (pl)
revision: 4672e20407010da34463acc759c162ca9734bca6
split: test
type: mteb/amazon_massive_intent
metrics:
- type: accuracy
value: 75.37323470073974
- type: f1
value: 71.1836877753734
- type: f1_weighted
value: 75.72073213955457
- type: main_score
value: 75.37323470073974
task:
type: Classification
- dataset:
config: de
name: MTEB MassiveIntentClassification (de)
revision: 4672e20407010da34463acc759c162ca9734bca6
split: test
type: mteb/amazon_massive_intent
metrics:
- type: accuracy
value: 74.83523873570948
- type: f1
value: 70.72375821116886
- type: f1_weighted
value: 75.20800490010755
- type: main_score
value: 74.83523873570948
task:
type: Classification
- dataset:
config: es
name: MTEB MassiveIntentClassification (es)
revision: 4672e20407010da34463acc759c162ca9734bca6
split: test
type: mteb/amazon_massive_intent
metrics:
- type: accuracy
value: 75.31607262945528
- type: f1
value: 72.06063554897662
- type: f1_weighted
value: 75.72438161355252
- type: main_score
value: 75.31607262945528
task:
type: Classification
- dataset:
config: ru
name: MTEB MassiveIntentClassification (ru)
revision: 4672e20407010da34463acc759c162ca9734bca6
split: test
type: mteb/amazon_massive_intent
metrics:
- type: accuracy
value: 76.7955615332885
- type: f1
value: 73.08099648499756
- type: f1_weighted
value: 77.18482068239668
- type: main_score
value: 76.7955615332885
task:
type: Classification
- dataset:
config: en
name: MTEB MassiveIntentClassification (en)
revision: 4672e20407010da34463acc759c162ca9734bca6
split: test
type: mteb/amazon_massive_intent
metrics:
- type: accuracy
value: 77.60591795561534
- type: f1
value: 74.46676705370395
- type: f1_weighted
value: 77.69888062336614
- type: main_score
value: 77.60591795561534
task:
type: Classification
- dataset:
config: fr
name: MTEB MassiveIntentClassification (fr)
revision: 4672e20407010da34463acc759c162ca9734bca6
split: test
type: mteb/amazon_massive_intent
metrics:
- type: accuracy
value: 76.32145258910558
- type: f1
value: 72.89824154178328
- type: f1_weighted
value: 76.6539327979472
- type: main_score
value: 76.32145258910558
task:
type: Classification
- dataset:
config: zh-CN
name: MTEB MassiveIntentClassification (zh-CN)
revision: 4672e20407010da34463acc759c162ca9734bca6
split: test
type: mteb/amazon_massive_intent
metrics:
- type: accuracy
value: 73.21788836583724
- type: f1
value: 70.45594512246377
- type: f1_weighted
value: 73.67862536499393
- type: main_score
value: 73.21788836583724
task:
type: Classification
- dataset:
config: zh-CN
name: MTEB MassiveScenarioClassification (zh-CN)
revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
split: test
type: mteb/amazon_massive_scenario
metrics:
- type: accuracy
value: 80.82044384667114
- type: f1
value: 80.53217664465089
- type: f1_weighted
value: 80.94535087010512
- type: main_score
value: 80.82044384667114
task:
type: Classification
- dataset:
config: pl
name: MTEB MassiveScenarioClassification (pl)
revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
split: test
type: mteb/amazon_massive_scenario
metrics:
- type: accuracy
value: 82.1049092131809
- type: f1
value: 81.55343463694733
- type: f1_weighted
value: 82.33509098770782
- type: main_score
value: 82.1049092131809
task:
type: Classification
- dataset:
config: es
name: MTEB MassiveScenarioClassification (es)
revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
split: test
type: mteb/amazon_massive_scenario
metrics:
- type: accuracy
value: 82.58238063214526
- type: f1
value: 82.27974449333072
- type: f1_weighted
value: 82.81337569618209
- type: main_score
value: 82.58238063214526
task:
type: Classification
- dataset:
config: de
name: MTEB MassiveScenarioClassification (de)
revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
split: test
type: mteb/amazon_massive_scenario
metrics:
- type: accuracy
value: 83.97108271687962
- type: f1
value: 83.56285606936076
- type: f1_weighted
value: 84.10198745390771
- type: main_score
value: 83.97108271687962
task:
type: Classification
- dataset:
config: en
name: MTEB MassiveScenarioClassification (en)
revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
split: test
type: mteb/amazon_massive_scenario
metrics:
- type: accuracy
value: 84.71082716879623
- type: f1
value: 84.09447062371402
- type: f1_weighted
value: 84.73765765551342
- type: main_score
value: 84.71082716879623
task:
type: Classification
- dataset:
config: fr
name: MTEB MassiveScenarioClassification (fr)
revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
split: test
type: mteb/amazon_massive_scenario
metrics:
- type: accuracy
value: 83.093476798924
- type: f1
value: 82.72656900752943
- type: f1_weighted
value: 83.26606516503364
- type: main_score
value: 83.093476798924
task:
type: Classification
- dataset:
config: ru
name: MTEB MassiveScenarioClassification (ru)
revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
split: test
type: mteb/amazon_massive_scenario
metrics:
- type: accuracy
value: 84.05850706119705
- type: f1
value: 83.64234048881222
- type: f1_weighted
value: 84.17315768381876
- type: main_score
value: 84.05850706119705
task:
type: Classification
- dataset:
config: default
name: MTEB MedicalRetrieval (default)
revision: 2039188fb5800a9803ba5048df7b76e6fb151fc6
split: dev
type: C-MTEB/MedicalRetrieval
metrics:
- type: main_score
value: 56.635999999999996
- type: map_at_1
value: 48.699999999999996
- type: map_at_10
value: 53.991
- type: map_at_100
value: 54.449999999999996
- type: map_at_1000
value: 54.515
- type: map_at_20
value: 54.212
- type: map_at_3
value: 52.833
- type: map_at_5
value: 53.503
- type: mrr_at_1
value: 48.699999999999996
- type: mrr_at_10
value: 53.991309523809505
- type: mrr_at_100
value: 54.45008993448266
- type: mrr_at_1000
value: 54.515253990549795
- type: mrr_at_20
value: 54.21201762247036
- type: mrr_at_3
value: 52.8333333333333
- type: mrr_at_5
value: 53.50333333333328
- type: nauc_map_at_1000_diff1
value: 79.96867989401643
- type: nauc_map_at_1000_max
value: 69.75230895599029
- type: nauc_map_at_1000_std
value: 2.6418738289740213
- type: nauc_map_at_100_diff1
value: 79.95343709599133
- type: nauc_map_at_100_max
value: 69.751282671507
- type: nauc_map_at_100_std
value: 2.621719966106279
- type: nauc_map_at_10_diff1
value: 80.02875864565634
- type: nauc_map_at_10_max
value: 69.80948662290187
- type: nauc_map_at_10_std
value: 2.329151604733765
- type: nauc_map_at_1_diff1
value: 83.616940281383
- type: nauc_map_at_1_max
value: 69.08142651929452
- type: nauc_map_at_1_std
value: 1.9687791394035643
- type: nauc_map_at_20_diff1
value: 79.95555601275339
- type: nauc_map_at_20_max
value: 69.76604695002925
- type: nauc_map_at_20_std
value: 2.556184141901367
- type: nauc_map_at_3_diff1
value: 80.74790131023668
- type: nauc_map_at_3_max
value: 70.57797991892402
- type: nauc_map_at_3_std
value: 2.7115149849964117
- type: nauc_map_at_5_diff1
value: 80.31796539878381
- type: nauc_map_at_5_max
value: 69.93573796420061
- type: nauc_map_at_5_std
value: 2.0731614029506606
- type: nauc_mrr_at_1000_diff1
value: 79.96867999907981
- type: nauc_mrr_at_1000_max
value: 69.57395578976896
- type: nauc_mrr_at_1000_std
value: 2.46351945887829
- type: nauc_mrr_at_100_diff1
value: 79.95343709599133
- type: nauc_mrr_at_100_max
value: 69.57322054130803
- type: nauc_mrr_at_100_std
value: 2.4436578359073433
- type: nauc_mrr_at_10_diff1
value: 80.02875864565634
- type: nauc_mrr_at_10_max
value: 69.63292630937411
- type: nauc_mrr_at_10_std
value: 2.1525912912060012
- type: nauc_mrr_at_1_diff1
value: 83.616940281383
- type: nauc_mrr_at_1_max
value: 68.74717310480305
- type: nauc_mrr_at_1_std
value: 1.6345257249120868
- type: nauc_mrr_at_20_diff1
value: 79.95555601275339
- type: nauc_mrr_at_20_max
value: 69.58883608470444
- type: nauc_mrr_at_20_std
value: 2.378973276576547
- type: nauc_mrr_at_3_diff1
value: 80.74790131023668
- type: nauc_mrr_at_3_max
value: 70.40430475488604
- type: nauc_mrr_at_3_std
value: 2.5378398209583817
- type: nauc_mrr_at_5_diff1
value: 80.31796539878381
- type: nauc_mrr_at_5_max
value: 69.7605991748183
- type: nauc_mrr_at_5_std
value: 1.898022613568352
- type: nauc_ndcg_at_1000_diff1
value: 78.35504059321225
- type: nauc_ndcg_at_1000_max
value: 69.06752522437093
- type: nauc_ndcg_at_1000_std
value: 3.9624036886099265
- type: nauc_ndcg_at_100_diff1
value: 77.79729140249833
- type: nauc_ndcg_at_100_max
value: 68.93113791506029
- type: nauc_ndcg_at_100_std
value: 3.642178826886181
- type: nauc_ndcg_at_10_diff1
value: 78.160158293918
- type: nauc_ndcg_at_10_max
value: 69.28122202281361
- type: nauc_ndcg_at_10_std
value: 2.438976810940962
- type: nauc_ndcg_at_1_diff1
value: 83.616940281383
- type: nauc_ndcg_at_1_max
value: 69.08142651929452
- type: nauc_ndcg_at_1_std
value: 1.9687791394035643
- type: nauc_ndcg_at_20_diff1
value: 77.88514432874997
- type: nauc_ndcg_at_20_max
value: 69.06148818508873
- type: nauc_ndcg_at_20_std
value: 3.1800249272363676
- type: nauc_ndcg_at_3_diff1
value: 79.73510384405803
- type: nauc_ndcg_at_3_max
value: 70.78000695123832
- type: nauc_ndcg_at_3_std
value: 2.9041415468363274
- type: nauc_ndcg_at_5_diff1
value: 78.91872808866195
- type: nauc_ndcg_at_5_max
value: 69.61478429620091
- type: nauc_ndcg_at_5_std
value: 1.734699636301054
- type: nauc_precision_at_1000_diff1
value: 66.37858395390673
- type: nauc_precision_at_1000_max
value: 60.651659037598534
- type: nauc_precision_at_1000_std
value: 27.388353715469798
- type: nauc_precision_at_100_diff1
value: 66.34325807776025
- type: nauc_precision_at_100_max
value: 63.63855305621111
- type: nauc_precision_at_100_std
value: 10.641748149575351
- type: nauc_precision_at_10_diff1
value: 71.3784685491089
- type: nauc_precision_at_10_max
value: 67.05313695174542
- type: nauc_precision_at_10_std
value: 3.000406867930561
- type: nauc_precision_at_1_diff1
value: 83.616940281383
- type: nauc_precision_at_1_max
value: 69.08142651929452
- type: nauc_precision_at_1_std
value: 1.9687791394035643
- type: nauc_precision_at_20_diff1
value: 69.73407910977694
- type: nauc_precision_at_20_max
value: 65.77426240320742
- type: nauc_precision_at_20_std
value: 6.204416838482586
- type: nauc_precision_at_3_diff1
value: 76.63737537643107
- type: nauc_precision_at_3_max
value: 71.29710200719668
- type: nauc_precision_at_3_std
value: 3.47180961484546
- type: nauc_precision_at_5_diff1
value: 74.36945983536717
- type: nauc_precision_at_5_max
value: 68.33292218003061
- type: nauc_precision_at_5_std
value: 0.47128762620258075
- type: nauc_recall_at_1000_diff1
value: 66.37858395390681
- type: nauc_recall_at_1000_max
value: 60.65165903759889
- type: nauc_recall_at_1000_std
value: 27.388353715469822
- type: nauc_recall_at_100_diff1
value: 66.34325807776025
- type: nauc_recall_at_100_max
value: 63.63855305621116
- type: nauc_recall_at_100_std
value: 10.641748149575351
- type: nauc_recall_at_10_diff1
value: 71.37846854910892
- type: nauc_recall_at_10_max
value: 67.05313695174546
- type: nauc_recall_at_10_std
value: 3.000406867930663
- type: nauc_recall_at_1_diff1
value: 83.616940281383
- type: nauc_recall_at_1_max
value: 69.08142651929452
- type: nauc_recall_at_1_std
value: 1.9687791394035643
- type: nauc_recall_at_20_diff1
value: 69.73407910977691
- type: nauc_recall_at_20_max
value: 65.77426240320746
- type: nauc_recall_at_20_std
value: 6.204416838482536
- type: nauc_recall_at_3_diff1
value: 76.63737537643112
- type: nauc_recall_at_3_max
value: 71.29710200719668
- type: nauc_recall_at_3_std
value: 3.471809614845442
- type: nauc_recall_at_5_diff1
value: 74.36945983536715
- type: nauc_recall_at_5_max
value: 68.33292218003065
- type: nauc_recall_at_5_std
value: 0.4712876262026442
- type: ndcg_at_1
value: 48.699999999999996
- type: ndcg_at_10
value: 56.635999999999996
- type: ndcg_at_100
value: 59.193
- type: ndcg_at_1000
value: 60.97
- type: ndcg_at_20
value: 57.426
- type: ndcg_at_3
value: 54.186
- type: ndcg_at_5
value: 55.407
- type: precision_at_1
value: 48.699999999999996
- type: precision_at_10
value: 6.5
- type: precision_at_100
value: 0.777
- type: precision_at_1000
value: 0.092
- type: precision_at_20
value: 3.405
- type: precision_at_3
value: 19.367
- type: precision_at_5
value: 12.22
- type: recall_at_1
value: 48.699999999999996
- type: recall_at_10
value: 65.0
- type: recall_at_100
value: 77.7
- type: recall_at_1000
value: 91.8
- type: recall_at_20
value: 68.10000000000001
- type: recall_at_3
value: 58.099999999999994
- type: recall_at_5
value: 61.1
task:
type: Retrieval
- dataset:
config: default
name: MTEB MedrxivClusteringP2P (default)
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
split: test
type: mteb/medrxiv-clustering-p2p
metrics:
- type: main_score
value: 34.80188561439236
- type: v_measure
value: 34.80188561439236
- type: v_measure_std
value: 1.5703148841573102
task:
type: Clustering
- dataset:
config: default
name: MTEB MedrxivClusteringS2S (default)
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
split: test
type: mteb/medrxiv-clustering-s2s
metrics:
- type: main_score
value: 32.42285513996236
- type: v_measure
value: 32.42285513996236
- type: v_measure_std
value: 1.3769867487457566
task:
type: Clustering
- dataset:
config: de
name: MTEB MintakaRetrieval (de)
revision: efa78cc2f74bbcd21eff2261f9e13aebe40b814e
split: test
type: jinaai/mintakaqa
metrics:
- type: main_score
value: 27.025
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task:
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name: MTEB MintakaRetrieval (fr)
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- type: nauc_map_at_5_max
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- type: nauc_map_at_5_std
value: 19.928449977400504
- type: nauc_mrr_at_1000_diff1
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- type: nauc_mrr_at_1000_max
value: 47.240929150603336
- type: nauc_mrr_at_1000_std
value: 20.559244258100275
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- type: nauc_mrr_at_100_max
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- type: nauc_mrr_at_100_std
value: 20.581498156895265
- type: nauc_mrr_at_10_diff1
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- type: nauc_mrr_at_10_max
value: 47.815880040221344
- type: nauc_mrr_at_10_std
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- type: nauc_mrr_at_1_max
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- type: nauc_mrr_at_1_std
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- type: nauc_mrr_at_20_diff1
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- type: nauc_mrr_at_20_max
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- type: nauc_mrr_at_5_std
value: 19.928449977400504
- type: nauc_ndcg_at_1000_diff1
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- type: nauc_ndcg_at_1000_max
value: 45.626323944336114
- type: nauc_ndcg_at_1000_std
value: 22.125600410796515
- type: nauc_ndcg_at_100_diff1
value: 12.302204843705244
- type: nauc_ndcg_at_100_max
value: 44.46856314559079
- type: nauc_ndcg_at_100_std
value: 23.084984546328677
- type: nauc_ndcg_at_10_diff1
value: 14.001226213368275
- type: nauc_ndcg_at_10_max
value: 47.37780636546918
- type: nauc_ndcg_at_10_std
value: 21.702709032840637
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value: 27.297525357600776
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value: 47.18835074959486
- type: nauc_ndcg_at_1_std
value: 18.304203168281834
- type: nauc_ndcg_at_20_diff1
value: 13.317759910171056
- type: nauc_ndcg_at_20_max
value: 46.25171251043813
- type: nauc_ndcg_at_20_std
value: 22.309331575402595
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value: 49.48635590260059
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value: 19.734570962933674
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- type: nauc_ndcg_at_5_std
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value: 38.9013414992826
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value: -5.290395978742176
- type: nauc_precision_at_100_max
value: 31.340480360546845
- type: nauc_precision_at_100_std
value: 33.6897935720505
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value: 5.965001997926562
- type: nauc_precision_at_10_max
value: 46.12515296162247
- type: nauc_precision_at_10_std
value: 25.409433135253558
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value: 3.4438127279827744
- type: nauc_precision_at_20_max
value: 42.36095587714494
- type: nauc_precision_at_20_std
value: 27.367900512797906
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value: 13.165017224718916
- type: nauc_precision_at_3_max
value: 50.58931825484506
- type: nauc_precision_at_3_std
value: 20.852009214609442
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value: 7.840087177549876
- type: nauc_precision_at_5_max
value: 46.99388755575109
- type: nauc_precision_at_5_std
value: 23.048702393099834
- type: nauc_recall_at_1000_diff1
value: -15.591898698252932
- type: nauc_recall_at_1000_max
value: 20.5459842853537
- type: nauc_recall_at_1000_std
value: 38.901341499282395
- type: nauc_recall_at_100_diff1
value: -5.290395978742165
- type: nauc_recall_at_100_max
value: 31.340480360546863
- type: nauc_recall_at_100_std
value: 33.68979357205046
- type: nauc_recall_at_10_diff1
value: 5.96500199792656
- type: nauc_recall_at_10_max
value: 46.1251529616225
- type: nauc_recall_at_10_std
value: 25.409433135253543
- type: nauc_recall_at_1_diff1
value: 27.297525357600776
- type: nauc_recall_at_1_max
value: 47.18835074959486
- type: nauc_recall_at_1_std
value: 18.304203168281834
- type: nauc_recall_at_20_diff1
value: 3.4438127279827833
- type: nauc_recall_at_20_max
value: 42.36095587714498
- type: nauc_recall_at_20_std
value: 27.36790051279787
- type: nauc_recall_at_3_diff1
value: 13.165017224718916
- type: nauc_recall_at_3_max
value: 50.589318254845054
- type: nauc_recall_at_3_std
value: 20.852009214609435
- type: nauc_recall_at_5_diff1
value: 7.840087177549891
- type: nauc_recall_at_5_max
value: 46.99388755575112
- type: nauc_recall_at_5_std
value: 23.048702393099845
- type: ndcg_at_1
value: 14.701
- type: ndcg_at_10
value: 26.909
- type: ndcg_at_100
value: 32.727000000000004
- type: ndcg_at_1000
value: 36.086
- type: ndcg_at_20
value: 29.236
- type: ndcg_at_3
value: 22.004
- type: ndcg_at_5
value: 24.615000000000002
- type: precision_at_1
value: 14.701
- type: precision_at_10
value: 4.062
- type: precision_at_100
value: 0.688
- type: precision_at_1000
value: 0.096
- type: precision_at_20
value: 2.488
- type: precision_at_3
value: 9.036
- type: precision_at_5
value: 6.699
- type: recall_at_1
value: 14.701
- type: recall_at_10
value: 40.622
- type: recall_at_100
value: 68.796
- type: recall_at_1000
value: 96.314
- type: recall_at_20
value: 49.754
- type: recall_at_3
value: 27.108999999999998
- type: recall_at_5
value: 33.497
task:
type: Retrieval
- dataset:
config: default
name: MTEB MultilingualSentiment (default)
revision: 46958b007a63fdbf239b7672c25d0bea67b5ea1a
split: test
type: C-MTEB/MultilingualSentiment-classification
metrics:
- type: accuracy
value: 73.20999999999998
- type: f1
value: 73.18755986777474
- type: f1_weighted
value: 73.18755986777475
- type: main_score
value: 73.20999999999998
task:
type: Classification
- dataset:
config: default
name: MTEB NFCorpus (default)
revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
split: test
type: mteb/nfcorpus
metrics:
- type: map_at_1
value: 4.822
- type: map_at_10
value: 13.144
- type: map_at_100
value: 17.254
- type: map_at_1000
value: 18.931
- type: map_at_20
value: 14.834
- type: map_at_3
value: 8.975
- type: map_at_5
value: 10.922
- type: mrr_at_1
value: 47.059
- type: mrr_at_10
value: 55.806999999999995
- type: mrr_at_100
value: 56.286
- type: mrr_at_1000
value: 56.327000000000005
- type: mrr_at_20
value: 56.00000000000001
- type: mrr_at_3
value: 54.17999999999999
- type: mrr_at_5
value: 55.155
- type: ndcg_at_1
value: 44.427
- type: ndcg_at_10
value: 36.623
- type: ndcg_at_100
value: 33.664
- type: ndcg_at_1000
value: 42.538
- type: ndcg_at_20
value: 34.066
- type: ndcg_at_3
value: 41.118
- type: ndcg_at_5
value: 39.455
- type: precision_at_1
value: 46.44
- type: precision_at_10
value: 28.607
- type: precision_at_100
value: 9.189
- type: precision_at_1000
value: 2.261
- type: precision_at_20
value: 21.238
- type: precision_at_3
value: 39.628
- type: precision_at_5
value: 35.604
- type: recall_at_1
value: 4.822
- type: recall_at_10
value: 17.488999999999997
- type: recall_at_100
value: 35.052
- type: recall_at_1000
value: 66.67999999999999
- type: recall_at_20
value: 21.343999999999998
- type: recall_at_3
value: 10.259
- type: recall_at_5
value: 13.406
- type: main_score
value: 36.623
task:
type: Retrieval
- dataset:
config: default
name: MTEB NQ (default)
revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
split: test
type: mteb/nq
metrics:
- type: map_at_1
value: 41.411
- type: map_at_10
value: 57.179
- type: map_at_100
value: 57.945
- type: map_at_1000
value: 57.967999999999996
- type: map_at_20
value: 57.687
- type: map_at_3
value: 53.46300000000001
- type: map_at_5
value: 55.696999999999996
- type: mrr_at_1
value: 46.233999999999995
- type: mrr_at_10
value: 59.831999999999994
- type: mrr_at_100
value: 60.33500000000001
- type: mrr_at_1000
value: 60.348
- type: mrr_at_20
value: 60.167
- type: mrr_at_3
value: 56.972
- type: mrr_at_5
value: 58.74
- type: ndcg_at_1
value: 46.205
- type: ndcg_at_10
value: 64.23100000000001
- type: ndcg_at_100
value: 67.242
- type: ndcg_at_1000
value: 67.72500000000001
- type: ndcg_at_20
value: 65.77300000000001
- type: ndcg_at_3
value: 57.516
- type: ndcg_at_5
value: 61.11600000000001
- type: precision_at_1
value: 46.205
- type: precision_at_10
value: 9.873
- type: precision_at_100
value: 1.158
- type: precision_at_1000
value: 0.12
- type: precision_at_20
value: 5.319
- type: precision_at_3
value: 25.424999999999997
- type: precision_at_5
value: 17.375
- type: recall_at_1
value: 41.411
- type: recall_at_10
value: 82.761
- type: recall_at_100
value: 95.52199999999999
- type: recall_at_1000
value: 99.02499999999999
- type: recall_at_20
value: 88.34
- type: recall_at_3
value: 65.73
- type: recall_at_5
value: 73.894
- type: main_score
value: 64.23100000000001
task:
type: Retrieval
- dataset:
config: default
name: MTEB Ocnli (default)
revision: 66e76a618a34d6d565d5538088562851e6daa7ec
split: validation
type: C-MTEB/OCNLI
metrics:
- type: cosine_accuracy
value: 62.3714131023281
- type: cosine_accuracy_threshold
value: 79.70921993255615
- type: cosine_ap
value: 66.41380155495659
- type: cosine_f1
value: 68.89547185780786
- type: cosine_f1_threshold
value: 72.91591167449951
- type: cosine_precision
value: 57.485875706214685
- type: cosine_recall
value: 85.95564941921859
- type: dot_accuracy
value: 60.47644829453167
- type: dot_accuracy_threshold
value: 36627.362060546875
- type: dot_ap
value: 63.696303449293204
- type: dot_f1
value: 68.3986041101202
- type: dot_f1_threshold
value: 30452.72216796875
- type: dot_precision
value: 54.04411764705882
- type: dot_recall
value: 93.13621964097149
- type: euclidean_accuracy
value: 63.02111532214402
- type: euclidean_accuracy_threshold
value: 1392.76762008667
- type: euclidean_ap
value: 66.65907089443218
- type: euclidean_f1
value: 69.05036524413688
- type: euclidean_f1_threshold
value: 1711.5310668945312
- type: euclidean_precision
value: 54.29262394195889
- type: euclidean_recall
value: 94.82576557550159
- type: main_score
value: 63.02111532214402
- type: manhattan_accuracy
value: 62.75040606388739
- type: manhattan_accuracy_threshold
value: 32475.347900390625
- type: manhattan_ap
value: 66.50943585125434
- type: manhattan_f1
value: 69.08382066276802
- type: manhattan_f1_threshold
value: 41238.470458984375
- type: manhattan_precision
value: 54.75896168108776
- type: manhattan_recall
value: 93.55860612460401
- type: max_accuracy
value: 63.02111532214402
- type: max_ap
value: 66.65907089443218
- type: max_f1
value: 69.08382066276802
- type: max_precision
value: 57.485875706214685
- type: max_recall
value: 94.82576557550159
- type: similarity_accuracy
value: 62.3714131023281
- type: similarity_accuracy_threshold
value: 79.70921993255615
- type: similarity_ap
value: 66.41380155495659
- type: similarity_f1
value: 68.89547185780786
- type: similarity_f1_threshold
value: 72.91591167449951
- type: similarity_precision
value: 57.485875706214685
- type: similarity_recall
value: 85.95564941921859
task:
type: PairClassification
- dataset:
config: default
name: MTEB OnlineShopping (default)
revision: e610f2ebd179a8fda30ae534c3878750a96db120
split: test
type: C-MTEB/OnlineShopping-classification
metrics:
- type: accuracy
value: 91.88000000000001
- type: ap
value: 89.52463684448476
- type: ap_weighted
value: 89.52463684448476
- type: f1
value: 91.86313022306673
- type: f1_weighted
value: 91.87806318146912
- type: main_score
value: 91.88000000000001
task:
type: Classification
- dataset:
config: en
name: MTEB OpusparcusPC (en)
revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
split: test.full
type: GEM/opusparcus
metrics:
- type: cosine_accuracy
value: 92.65578635014838
- type: cosine_accuracy_threshold
value: 74.02530312538147
- type: cosine_ap
value: 98.3834226153613
- type: cosine_f1
value: 94.92567913890312
- type: cosine_f1_threshold
value: 74.02530312538147
- type: cosine_precision
value: 95.562435500516
- type: cosine_recall
value: 94.29735234215886
- type: dot_accuracy
value: 91.54302670623146
- type: dot_accuracy_threshold
value: 34452.29187011719
- type: dot_ap
value: 98.1237257754439
- type: dot_f1
value: 94.22400803616273
- type: dot_f1_threshold
value: 33670.41931152344
- type: dot_precision
value: 92.9633300297324
- type: dot_recall
value: 95.5193482688391
- type: euclidean_accuracy
value: 92.28486646884274
- type: euclidean_accuracy_threshold
value: 1602.8022766113281
- type: euclidean_ap
value: 98.3099021504706
- type: euclidean_f1
value: 94.75277497477296
- type: euclidean_f1_threshold
value: 1604.7462463378906
- type: euclidean_precision
value: 93.89999999999999
- type: euclidean_recall
value: 95.62118126272912
- type: main_score
value: 98.3834226153613
- type: manhattan_accuracy
value: 92.2106824925816
- type: manhattan_accuracy_threshold
value: 38872.90954589844
- type: manhattan_ap
value: 98.28694101230218
- type: manhattan_f1
value: 94.67815509376584
- type: manhattan_f1_threshold
value: 38872.90954589844
- type: manhattan_precision
value: 94.24823410696267
- type: manhattan_recall
value: 95.11201629327903
- type: max_accuracy
value: 92.65578635014838
- type: max_ap
value: 98.3834226153613
- type: max_f1
value: 94.92567913890312
- type: max_precision
value: 95.562435500516
- type: max_recall
value: 95.62118126272912
- type: similarity_accuracy
value: 92.65578635014838
- type: similarity_accuracy_threshold
value: 74.02530312538147
- type: similarity_ap
value: 98.3834226153613
- type: similarity_f1
value: 94.92567913890312
- type: similarity_f1_threshold
value: 74.02530312538147
- type: similarity_precision
value: 95.562435500516
- type: similarity_recall
value: 94.29735234215886
task:
type: PairClassification
- dataset:
config: de
name: MTEB OpusparcusPC (de)
revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
split: test.full
type: GEM/opusparcus
metrics:
- type: cosine_accuracy
value: 87.72178850248403
- type: cosine_accuracy_threshold
value: 73.33863377571106
- type: cosine_ap
value: 96.98901408834976
- type: cosine_f1
value: 91.89944134078212
- type: cosine_f1_threshold
value: 71.45810127258301
- type: cosine_precision
value: 89.64577656675749
- type: cosine_recall
value: 94.26934097421203
- type: dot_accuracy
value: 86.30234208658624
- type: dot_accuracy_threshold
value: 32027.130126953125
- type: dot_ap
value: 96.12260574893256
- type: dot_f1
value: 91.31602506714414
- type: dot_f1_threshold
value: 30804.376220703125
- type: dot_precision
value: 85.93091828138164
- type: dot_recall
value: 97.42120343839542
- type: euclidean_accuracy
value: 87.9347054648687
- type: euclidean_accuracy_threshold
value: 1609.6670150756836
- type: euclidean_ap
value: 97.00238860358252
- type: euclidean_f1
value: 92.1089063221043
- type: euclidean_f1_threshold
value: 1641.8487548828125
- type: euclidean_precision
value: 89.10714285714286
- type: euclidean_recall
value: 95.31996179560649
- type: main_score
value: 97.00238860358252
- type: manhattan_accuracy
value: 87.72178850248403
- type: manhattan_accuracy_threshold
value: 40137.060546875
- type: manhattan_ap
value: 96.98653728159941
- type: manhattan_f1
value: 92.03865623561896
- type: manhattan_f1_threshold
value: 40137.060546875
- type: manhattan_precision
value: 88.80994671403198
- type: manhattan_recall
value: 95.51098376313276
- type: max_accuracy
value: 87.9347054648687
- type: max_ap
value: 97.00238860358252
- type: max_f1
value: 92.1089063221043
- type: max_precision
value: 89.64577656675749
- type: max_recall
value: 97.42120343839542
- type: similarity_accuracy
value: 87.72178850248403
- type: similarity_accuracy_threshold
value: 73.33863377571106
- type: similarity_ap
value: 96.98901408834976
- type: similarity_f1
value: 91.89944134078212
- type: similarity_f1_threshold
value: 71.45810127258301
- type: similarity_precision
value: 89.64577656675749
- type: similarity_recall
value: 94.26934097421203
task:
type: PairClassification
- dataset:
config: fr
name: MTEB OpusparcusPC (fr)
revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
split: test.full
type: GEM/opusparcus
metrics:
- type: cosine_accuracy
value: 80.92643051771117
- type: cosine_accuracy_threshold
value: 76.68856382369995
- type: cosine_ap
value: 93.74622381534307
- type: cosine_f1
value: 87.12328767123287
- type: cosine_f1_threshold
value: 71.64022922515869
- type: cosine_precision
value: 80.64243448858834
- type: cosine_recall
value: 94.73684210526315
- type: dot_accuracy
value: 80.858310626703
- type: dot_accuracy_threshold
value: 34028.3935546875
- type: dot_ap
value: 91.18448457633308
- type: dot_f1
value: 86.82606657290202
- type: dot_f1_threshold
value: 34028.3935546875
- type: dot_precision
value: 82.2380106571936
- type: dot_recall
value: 91.9563058589871
- type: euclidean_accuracy
value: 80.858310626703
- type: euclidean_accuracy_threshold
value: 1595.7651138305664
- type: euclidean_ap
value: 93.8182717829648
- type: euclidean_f1
value: 87.04044117647058
- type: euclidean_f1_threshold
value: 1609.2475891113281
- type: euclidean_precision
value: 81.00940975192472
- type: euclidean_recall
value: 94.04170804369414
- type: main_score
value: 93.8182717829648
- type: manhattan_accuracy
value: 80.99455040871935
- type: manhattan_accuracy_threshold
value: 38092.132568359375
- type: manhattan_ap
value: 93.77563401151711
- type: manhattan_f1
value: 86.91983122362869
- type: manhattan_f1_threshold
value: 38092.132568359375
- type: manhattan_precision
value: 82.32682060390763
- type: manhattan_recall
value: 92.05561072492551
- type: max_accuracy
value: 80.99455040871935
- type: max_ap
value: 93.8182717829648
- type: max_f1
value: 87.12328767123287
- type: max_precision
value: 82.32682060390763
- type: max_recall
value: 94.73684210526315
- type: similarity_accuracy
value: 80.92643051771117
- type: similarity_accuracy_threshold
value: 76.68856382369995
- type: similarity_ap
value: 93.74622381534307
- type: similarity_f1
value: 87.12328767123287
- type: similarity_f1_threshold
value: 71.64022922515869
- type: similarity_precision
value: 80.64243448858834
- type: similarity_recall
value: 94.73684210526315
task:
type: PairClassification
- dataset:
config: ru
name: MTEB OpusparcusPC (ru)
revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
split: test.full
type: GEM/opusparcus
metrics:
- type: cosine_accuracy
value: 76.83823529411765
- type: cosine_accuracy_threshold
value: 72.70769476890564
- type: cosine_ap
value: 89.56692049908222
- type: cosine_f1
value: 83.99832003359934
- type: cosine_f1_threshold
value: 70.9052324295044
- type: cosine_precision
value: 76.16146230007617
- type: cosine_recall
value: 93.63295880149812
- type: dot_accuracy
value: 76.28676470588235
- type: dot_accuracy_threshold
value: 33740.68908691406
- type: dot_ap
value: 87.77185177141567
- type: dot_f1
value: 83.62251375370292
- type: dot_f1_threshold
value: 32726.611328125
- type: dot_precision
value: 76.29343629343629
- type: dot_recall
value: 92.50936329588015
- type: euclidean_accuracy
value: 77.32843137254902
- type: euclidean_accuracy_threshold
value: 1566.510009765625
- type: euclidean_ap
value: 89.60605626791111
- type: euclidean_f1
value: 84.06546080964686
- type: euclidean_f1_threshold
value: 1576.4202117919922
- type: euclidean_precision
value: 77.83094098883574
- type: euclidean_recall
value: 91.38576779026218
- type: main_score
value: 89.60605626791111
- type: manhattan_accuracy
value: 76.89950980392157
- type: manhattan_accuracy_threshold
value: 38202.215576171875
- type: manhattan_ap
value: 89.55766894104868
- type: manhattan_f1
value: 83.80462724935732
- type: manhattan_f1_threshold
value: 38934.375
- type: manhattan_precision
value: 77.25118483412322
- type: manhattan_recall
value: 91.57303370786516
- type: max_accuracy
value: 77.32843137254902
- type: max_ap
value: 89.60605626791111
- type: max_f1
value: 84.06546080964686
- type: max_precision
value: 77.83094098883574
- type: max_recall
value: 93.63295880149812
- type: similarity_accuracy
value: 76.83823529411765
- type: similarity_accuracy_threshold
value: 72.70769476890564
- type: similarity_ap
value: 89.56692049908222
- type: similarity_f1
value: 83.99832003359934
- type: similarity_f1_threshold
value: 70.9052324295044
- type: similarity_precision
value: 76.16146230007617
- type: similarity_recall
value: 93.63295880149812
task:
type: PairClassification
- dataset:
config: default
name: MTEB PAC (default)
revision: fc69d1c153a8ccdcf1eef52f4e2a27f88782f543
split: test
type: laugustyniak/abusive-clauses-pl
metrics:
- type: accuracy
value: 68.39559803069794
- type: ap
value: 77.68074206719457
- type: ap_weighted
value: 77.68074206719457
- type: f1
value: 66.23485605467732
- type: f1_weighted
value: 69.03201442129347
- type: main_score
value: 68.39559803069794
task:
type: Classification
- dataset:
config: default
name: MTEB PAWSX (default)
revision: 9c6a90e430ac22b5779fb019a23e820b11a8b5e1
split: test
type: C-MTEB/PAWSX
metrics:
- type: cosine_pearson
value: 13.161523266433587
- type: cosine_spearman
value: 15.557333873773386
- type: euclidean_pearson
value: 17.147508431907525
- type: euclidean_spearman
value: 15.664112857732146
- type: main_score
value: 15.557333873773386
- type: manhattan_pearson
value: 17.130875906264386
- type: manhattan_spearman
value: 15.624397342229637
- type: pearson
value: 13.161523266433587
- type: spearman
value: 15.557333873773386
task:
type: STS
- dataset:
config: default
name: MTEB PSC (default)
revision: d05a294af9e1d3ff2bfb6b714e08a24a6cabc669
split: test
type: PL-MTEB/psc-pairclassification
metrics:
- type: cosine_accuracy
value: 97.86641929499072
- type: cosine_accuracy_threshold
value: 79.0391206741333
- type: cosine_ap
value: 99.19403807771533
- type: cosine_f1
value: 96.45608628659475
- type: cosine_f1_threshold
value: 79.0391206741333
- type: cosine_precision
value: 97.50778816199377
- type: cosine_recall
value: 95.42682926829268
- type: dot_accuracy
value: 98.14471243042672
- type: dot_accuracy_threshold
value: 29808.1787109375
- type: dot_ap
value: 99.331999859971
- type: dot_f1
value: 97.01492537313433
- type: dot_f1_threshold
value: 29808.1787109375
- type: dot_precision
value: 95.02923976608187
- type: dot_recall
value: 99.08536585365853
- type: euclidean_accuracy
value: 97.49536178107606
- type: euclidean_accuracy_threshold
value: 1276.227855682373
- type: euclidean_ap
value: 98.91056467717377
- type: euclidean_f1
value: 95.83975346687212
- type: euclidean_f1_threshold
value: 1276.227855682373
- type: euclidean_precision
value: 96.88473520249221
- type: euclidean_recall
value: 94.8170731707317
- type: main_score
value: 99.331999859971
- type: manhattan_accuracy
value: 97.49536178107606
- type: manhattan_accuracy_threshold
value: 31097.674560546875
- type: manhattan_ap
value: 98.95694691792707
- type: manhattan_f1
value: 95.83975346687212
- type: manhattan_f1_threshold
value: 31097.674560546875
- type: manhattan_precision
value: 96.88473520249221
- type: manhattan_recall
value: 94.8170731707317
- type: max_accuracy
value: 98.14471243042672
- type: max_ap
value: 99.331999859971
- type: max_f1
value: 97.01492537313433
- type: max_precision
value: 97.50778816199377
- type: max_recall
value: 99.08536585365853
- type: similarity_accuracy
value: 97.86641929499072
- type: similarity_accuracy_threshold
value: 79.0391206741333
- type: similarity_ap
value: 99.19403807771533
- type: similarity_f1
value: 96.45608628659475
- type: similarity_f1_threshold
value: 79.0391206741333
- type: similarity_precision
value: 97.50778816199377
- type: similarity_recall
value: 95.42682926829268
task:
type: PairClassification
- dataset:
config: en
name: MTEB PawsXPairClassification (en)
revision: 8a04d940a42cd40658986fdd8e3da561533a3646
split: test
type: google-research-datasets/paws-x
metrics:
- type: cosine_accuracy
value: 61.8
- type: cosine_accuracy_threshold
value: 99.5664119720459
- type: cosine_ap
value: 60.679317786040585
- type: cosine_f1
value: 63.17354143441101
- type: cosine_f1_threshold
value: 97.22164869308472
- type: cosine_precision
value: 47.6457399103139
- type: cosine_recall
value: 93.71554575523705
- type: dot_accuracy
value: 55.7
- type: dot_accuracy_threshold
value: 48353.62548828125
- type: dot_ap
value: 48.53805970536875
- type: dot_f1
value: 62.42214532871972
- type: dot_f1_threshold
value: 38215.53955078125
- type: dot_precision
value: 45.48663640948058
- type: dot_recall
value: 99.44873208379272
- type: euclidean_accuracy
value: 61.75000000000001
- type: euclidean_accuracy_threshold
value: 189.0761137008667
- type: euclidean_ap
value: 60.55517418691518
- type: euclidean_f1
value: 63.07977736549165
- type: euclidean_f1_threshold
value: 504.3168067932129
- type: euclidean_precision
value: 47.53914988814318
- type: euclidean_recall
value: 93.71554575523705
- type: main_score
value: 60.679317786040585
- type: manhattan_accuracy
value: 61.9
- type: manhattan_accuracy_threshold
value: 4695.778274536133
- type: manhattan_ap
value: 60.48686620413608
- type: manhattan_f1
value: 62.92880855772778
- type: manhattan_f1_threshold
value: 12542.36831665039
- type: manhattan_precision
value: 47.28381374722838
- type: manhattan_recall
value: 94.04630650496141
- type: max_accuracy
value: 61.9
- type: max_ap
value: 60.679317786040585
- type: max_f1
value: 63.17354143441101
- type: max_precision
value: 47.6457399103139
- type: max_recall
value: 99.44873208379272
- type: similarity_accuracy
value: 61.8
- type: similarity_accuracy_threshold
value: 99.5664119720459
- type: similarity_ap
value: 60.679317786040585
- type: similarity_f1
value: 63.17354143441101
- type: similarity_f1_threshold
value: 97.22164869308472
- type: similarity_precision
value: 47.6457399103139
- type: similarity_recall
value: 93.71554575523705
task:
type: PairClassification
- dataset:
config: de
name: MTEB PawsXPairClassification (de)
revision: 8a04d940a42cd40658986fdd8e3da561533a3646
split: test
type: google-research-datasets/paws-x
metrics:
- type: cosine_accuracy
value: 60.25
- type: cosine_accuracy_threshold
value: 99.54338073730469
- type: cosine_ap
value: 56.7863613689054
- type: cosine_f1
value: 62.23499820337766
- type: cosine_f1_threshold
value: 89.95014429092407
- type: cosine_precision
value: 45.86864406779661
- type: cosine_recall
value: 96.75977653631284
- type: dot_accuracy
value: 56.8
- type: dot_accuracy_threshold
value: 47349.78332519531
- type: dot_ap
value: 49.7857806061729
- type: dot_f1
value: 62.31225986727209
- type: dot_f1_threshold
value: 30143.206787109375
- type: dot_precision
value: 45.32520325203252
- type: dot_recall
value: 99.66480446927373
- type: euclidean_accuracy
value: 60.3
- type: euclidean_accuracy_threshold
value: 219.78106498718262
- type: euclidean_ap
value: 56.731544327179606
- type: euclidean_f1
value: 62.19895287958115
- type: euclidean_f1_threshold
value: 1792.1623229980469
- type: euclidean_precision
value: 45.22842639593909
- type: euclidean_recall
value: 99.55307262569832
- type: main_score
value: 56.7863613689054
- type: manhattan_accuracy
value: 60.150000000000006
- type: manhattan_accuracy_threshold
value: 5104.503631591797
- type: manhattan_ap
value: 56.70304479768734
- type: manhattan_f1
value: 62.22067039106145
- type: manhattan_f1_threshold
value: 42839.471435546875
- type: manhattan_precision
value: 45.2513966480447
- type: manhattan_recall
value: 99.55307262569832
- type: max_accuracy
value: 60.3
- type: max_ap
value: 56.7863613689054
- type: max_f1
value: 62.31225986727209
- type: max_precision
value: 45.86864406779661
- type: max_recall
value: 99.66480446927373
- type: similarity_accuracy
value: 60.25
- type: similarity_accuracy_threshold
value: 99.54338073730469
- type: similarity_ap
value: 56.7863613689054
- type: similarity_f1
value: 62.23499820337766
- type: similarity_f1_threshold
value: 89.95014429092407
- type: similarity_precision
value: 45.86864406779661
- type: similarity_recall
value: 96.75977653631284
task:
type: PairClassification
- dataset:
config: es
name: MTEB PawsXPairClassification (es)
revision: 8a04d940a42cd40658986fdd8e3da561533a3646
split: test
type: google-research-datasets/paws-x
metrics:
- type: cosine_accuracy
value: 59.699999999999996
- type: cosine_accuracy_threshold
value: 99.55930709838867
- type: cosine_ap
value: 57.31662248806265
- type: cosine_f1
value: 62.444061962134256
- type: cosine_f1_threshold
value: 74.75898265838623
- type: cosine_precision
value: 45.3953953953954
- type: cosine_recall
value: 100.0
- type: dot_accuracy
value: 55.900000000000006
- type: dot_accuracy_threshold
value: 47512.90283203125
- type: dot_ap
value: 49.39339147787568
- type: dot_f1
value: 62.487082328625554
- type: dot_f1_threshold
value: 34989.03503417969
- type: dot_precision
value: 45.44088176352705
- type: dot_recall
value: 100.0
- type: euclidean_accuracy
value: 59.599999999999994
- type: euclidean_accuracy_threshold
value: 200.82547664642334
- type: euclidean_ap
value: 57.19737488445163
- type: euclidean_f1
value: 62.444061962134256
- type: euclidean_f1_threshold
value: 1538.8837814331055
- type: euclidean_precision
value: 45.3953953953954
- type: euclidean_recall
value: 100.0
- type: main_score
value: 57.31662248806265
- type: manhattan_accuracy
value: 59.550000000000004
- type: manhattan_accuracy_threshold
value: 5016.501617431641
- type: manhattan_ap
value: 57.089959907945065
- type: manhattan_f1
value: 62.444061962134256
- type: manhattan_f1_threshold
value: 37523.53515625
- type: manhattan_precision
value: 45.3953953953954
- type: manhattan_recall
value: 100.0
- type: max_accuracy
value: 59.699999999999996
- type: max_ap
value: 57.31662248806265
- type: max_f1
value: 62.487082328625554
- type: max_precision
value: 45.44088176352705
- type: max_recall
value: 100.0
- type: similarity_accuracy
value: 59.699999999999996
- type: similarity_accuracy_threshold
value: 99.55930709838867
- type: similarity_ap
value: 57.31662248806265
- type: similarity_f1
value: 62.444061962134256
- type: similarity_f1_threshold
value: 74.75898265838623
- type: similarity_precision
value: 45.3953953953954
- type: similarity_recall
value: 100.0
task:
type: PairClassification
- dataset:
config: fr
name: MTEB PawsXPairClassification (fr)
revision: 8a04d940a42cd40658986fdd8e3da561533a3646
split: test
type: google-research-datasets/paws-x
metrics:
- type: cosine_accuracy
value: 61.150000000000006
- type: cosine_accuracy_threshold
value: 99.36153888702393
- type: cosine_ap
value: 59.43845317938599
- type: cosine_f1
value: 62.51298026998961
- type: cosine_f1_threshold
value: 76.77866220474243
- type: cosine_precision
value: 45.468277945619334
- type: cosine_recall
value: 100.0
- type: dot_accuracy
value: 55.75
- type: dot_accuracy_threshold
value: 48931.55212402344
- type: dot_ap
value: 50.15949290538757
- type: dot_f1
value: 62.53462603878117
- type: dot_f1_threshold
value: 34415.7958984375
- type: dot_precision
value: 45.4911838790932
- type: dot_recall
value: 100.0
- type: euclidean_accuracy
value: 61.050000000000004
- type: euclidean_accuracy_threshold
value: 240.8097267150879
- type: euclidean_ap
value: 59.367971294226216
- type: euclidean_f1
value: 62.51298026998961
- type: euclidean_f1_threshold
value: 1444.132423400879
- type: euclidean_precision
value: 45.468277945619334
- type: euclidean_recall
value: 100.0
- type: main_score
value: 59.43845317938599
- type: manhattan_accuracy
value: 60.95
- type: manhattan_accuracy_threshold
value: 5701.206207275391
- type: manhattan_ap
value: 59.30094096378774
- type: manhattan_f1
value: 62.53462603878117
- type: manhattan_f1_threshold
value: 33445.672607421875
- type: manhattan_precision
value: 45.4911838790932
- type: manhattan_recall
value: 100.0
- type: max_accuracy
value: 61.150000000000006
- type: max_ap
value: 59.43845317938599
- type: max_f1
value: 62.53462603878117
- type: max_precision
value: 45.4911838790932
- type: max_recall
value: 100.0
- type: similarity_accuracy
value: 61.150000000000006
- type: similarity_accuracy_threshold
value: 99.36153888702393
- type: similarity_ap
value: 59.43845317938599
- type: similarity_f1
value: 62.51298026998961
- type: similarity_f1_threshold
value: 76.77866220474243
- type: similarity_precision
value: 45.468277945619334
- type: similarity_recall
value: 100.0
task:
type: PairClassification
- dataset:
config: zh
name: MTEB PawsXPairClassification (zh)
revision: 8a04d940a42cd40658986fdd8e3da561533a3646
split: test
type: google-research-datasets/paws-x
metrics:
- type: cosine_accuracy
value: 58.85
- type: cosine_accuracy_threshold
value: 99.73838329315186
- type: cosine_ap
value: 54.66913160570546
- type: cosine_f1
value: 62.32136632973162
- type: cosine_f1_threshold
value: 76.4499306678772
- type: cosine_precision
value: 45.265822784810126
- type: cosine_recall
value: 100.0
- type: dot_accuracy
value: 56.25
- type: dot_accuracy_threshold
value: 47351.9287109375
- type: dot_ap
value: 48.5266232989438
- type: dot_f1
value: 62.277951933124356
- type: dot_f1_threshold
value: 31325.28076171875
- type: dot_precision
value: 45.220030349013655
- type: dot_recall
value: 100.0
- type: euclidean_accuracy
value: 58.9
- type: euclidean_accuracy_threshold
value: 144.24468278884888
- type: euclidean_ap
value: 54.66981490353506
- type: euclidean_f1
value: 62.32136632973162
- type: euclidean_f1_threshold
value: 1484.908676147461
- type: euclidean_precision
value: 45.265822784810126
- type: euclidean_recall
value: 100.0
- type: main_score
value: 54.66981490353506
- type: manhattan_accuracy
value: 58.9
- type: manhattan_accuracy_threshold
value: 3586.785125732422
- type: manhattan_ap
value: 54.668355260247736
- type: manhattan_f1
value: 62.32136632973162
- type: manhattan_f1_threshold
value: 36031.22863769531
- type: manhattan_precision
value: 45.265822784810126
- type: manhattan_recall
value: 100.0
- type: max_accuracy
value: 58.9
- type: max_ap
value: 54.66981490353506
- type: max_f1
value: 62.32136632973162
- type: max_precision
value: 45.265822784810126
- type: max_recall
value: 100.0
- type: similarity_accuracy
value: 58.85
- type: similarity_accuracy_threshold
value: 99.73838329315186
- type: similarity_ap
value: 54.66913160570546
- type: similarity_f1
value: 62.32136632973162
- type: similarity_f1_threshold
value: 76.4499306678772
- type: similarity_precision
value: 45.265822784810126
- type: similarity_recall
value: 100.0
task:
type: PairClassification
- dataset:
config: default
name: MTEB PolEmo2.0-IN (default)
revision: d90724373c70959f17d2331ad51fb60c71176b03
split: test
type: PL-MTEB/polemo2_in
metrics:
- type: accuracy
value: 83.75346260387812
- type: f1
value: 81.98304891214909
- type: f1_weighted
value: 84.29623200830078
- type: main_score
value: 83.75346260387812
task:
type: Classification
- dataset:
config: default
name: MTEB PolEmo2.0-OUT (default)
revision: 6a21ab8716e255ab1867265f8b396105e8aa63d4
split: test
type: PL-MTEB/polemo2_out
metrics:
- type: accuracy
value: 66.53846153846153
- type: f1
value: 52.71826064368638
- type: f1_weighted
value: 69.10010124630334
- type: main_score
value: 66.53846153846153
task:
type: Classification
- dataset:
config: default
name: MTEB PpcPC (default)
revision: 2c7d2df57801a591f6b1e3aaf042e7a04ec7d9f2
split: test
type: PL-MTEB/ppc-pairclassification
metrics:
- type: cosine_accuracy
value: 81.8
- type: cosine_accuracy_threshold
value: 90.47793745994568
- type: cosine_ap
value: 91.42490266080884
- type: cosine_f1
value: 85.4632587859425
- type: cosine_f1_threshold
value: 90.47793745994568
- type: cosine_precision
value: 82.56172839506173
- type: cosine_recall
value: 88.57615894039735
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value: 74.6
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value: 42102.23693847656
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value: 86.20060009096979
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value: 80.02842928216063
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value: 38970.16906738281
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value: 70.1120797011208
- type: dot_recall
value: 93.21192052980133
- type: euclidean_accuracy
value: 81.5
- type: euclidean_accuracy_threshold
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- type: euclidean_ap
value: 91.33143477982087
- type: euclidean_f1
value: 85.44600938967135
- type: euclidean_f1_threshold
value: 964.0384674072266
- type: euclidean_precision
value: 81.00890207715133
- type: euclidean_recall
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- type: main_score
value: 91.42490266080884
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value: 81.3
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value: 22100.830078125
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value: 85.38102643856921
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value: 24043.515014648438
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value: 80.49853372434018
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value: 90.89403973509934
- type: max_accuracy
value: 81.8
- type: max_ap
value: 91.42490266080884
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value: 85.4632587859425
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value: 82.56172839506173
- type: max_recall
value: 93.21192052980133
- type: similarity_accuracy
value: 81.8
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value: 90.47793745994568
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value: 91.42490266080884
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value: 85.4632587859425
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value: 90.47793745994568
- type: similarity_precision
value: 82.56172839506173
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value: 88.57615894039735
task:
type: PairClassification
- dataset:
config: default
name: MTEB QuoraRetrieval (default)
revision: e4e08e0b7dbe3c8700f0daef558ff32256715259
split: test
type: mteb/quora
metrics:
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value: 71.419
- type: map_at_10
value: 85.542
- type: map_at_100
value: 86.161
- type: map_at_1000
value: 86.175
- type: map_at_20
value: 85.949
- type: map_at_3
value: 82.623
- type: map_at_5
value: 84.5
- type: mrr_at_1
value: 82.27
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value: 88.21900000000001
- type: mrr_at_100
value: 88.313
- type: mrr_at_1000
value: 88.31400000000001
- type: mrr_at_20
value: 88.286
- type: mrr_at_3
value: 87.325
- type: mrr_at_5
value: 87.97500000000001
- type: ndcg_at_1
value: 82.3
- type: ndcg_at_10
value: 89.088
- type: ndcg_at_100
value: 90.217
- type: ndcg_at_1000
value: 90.29700000000001
- type: ndcg_at_20
value: 89.697
- type: ndcg_at_3
value: 86.435
- type: ndcg_at_5
value: 87.966
- type: precision_at_1
value: 82.3
- type: precision_at_10
value: 13.527000000000001
- type: precision_at_100
value: 1.537
- type: precision_at_1000
value: 0.157
- type: precision_at_20
value: 7.165000000000001
- type: precision_at_3
value: 37.92
- type: precision_at_5
value: 24.914
- type: recall_at_1
value: 71.419
- type: recall_at_10
value: 95.831
- type: recall_at_100
value: 99.64
- type: recall_at_1000
value: 99.988
- type: recall_at_20
value: 97.76599999999999
- type: recall_at_3
value: 88.081
- type: recall_at_5
value: 92.50500000000001
- type: main_score
value: 89.088
task:
type: Retrieval
- dataset:
config: default
name: MTEB RUParaPhraserSTS (default)
revision: 43265056790b8f7c59e0139acb4be0a8dad2c8f4
split: test
type: merionum/ru_paraphraser
metrics:
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value: 67.91177744712421
- type: cosine_spearman
value: 76.77113726753656
- type: euclidean_pearson
value: 73.81454206068638
- type: euclidean_spearman
value: 76.92529493599028
- type: main_score
value: 76.77113726753656
- type: manhattan_pearson
value: 73.81690454439168
- type: manhattan_spearman
value: 76.87333776705002
- type: pearson
value: 67.91177744712421
- type: spearman
value: 76.77113726753656
task:
type: STS
- dataset:
config: default
name: MTEB RedditClustering (default)
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
split: test
type: mteb/reddit-clustering
metrics:
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value: 55.39924225216962
- type: v_measure
value: 55.39924225216962
- type: v_measure_std
value: 4.723802279292467
task:
type: Clustering
- dataset:
config: default
name: MTEB RedditClusteringP2P (default)
revision: 385e3cb46b4cfa89021f56c4380204149d0efe33
split: test
type: mteb/reddit-clustering-p2p
metrics:
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value: 62.87465161304012
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value: 62.87465161304012
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value: 12.082670914488473
task:
type: Clustering
- dataset:
config: default
name: MTEB RiaNewsRetrieval (default)
revision: 82374b0bbacda6114f39ff9c5b925fa1512ca5d7
split: test
type: ai-forever/ria-news-retrieval
metrics:
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- type: map_at_1000
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task:
type: Retrieval
- dataset:
config: default
name: MTEB RuBQReranking (default)
revision: 2e96b8f098fa4b0950fc58eacadeb31c0d0c7fa2
split: test
type: ai-forever/rubq-reranking
metrics:
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value: 70.51408205663526
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value: 28.5206955462174
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value: 14.207162454694227
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value: 10.725721001555296
task:
type: Reranking
- dataset:
config: default
name: MTEB RuBQRetrieval (default)
revision: e19b6ffa60b3bc248e0b41f4cc37c26a55c2a67b
split: test
type: ai-forever/rubq-retrieval
metrics:
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value: 39.096348529742095
- type: nauc_ndcg_at_5_max
value: 34.075926475544165
- type: nauc_ndcg_at_5_std
value: -7.238045445366631
- type: nauc_precision_at_1000_diff1
value: -14.283799754212609
- type: nauc_precision_at_1000_max
value: 6.449741756717101
- type: nauc_precision_at_1000_std
value: 4.862828679759048
- type: nauc_precision_at_100_diff1
value: -13.23173132700258
- type: nauc_precision_at_100_max
value: 11.058898534529195
- type: nauc_precision_at_100_std
value: 7.343683941814956
- type: nauc_precision_at_10_diff1
value: -7.202951643546464
- type: nauc_precision_at_10_max
value: 17.499446869433278
- type: nauc_precision_at_10_std
value: 2.8367985220406307
- type: nauc_precision_at_1_diff1
value: 53.45970160222764
- type: nauc_precision_at_1_max
value: 33.14759013278075
- type: nauc_precision_at_1_std
value: -12.579833891774847
- type: nauc_precision_at_20_diff1
value: -9.477122699154124
- type: nauc_precision_at_20_max
value: 16.80556031564312
- type: nauc_precision_at_20_std
value: 6.420218284416923
- type: nauc_precision_at_3_diff1
value: 5.5276143574150245
- type: nauc_precision_at_3_max
value: 23.65952688481666
- type: nauc_precision_at_3_std
value: -1.8730348729295785
- type: nauc_precision_at_5_diff1
value: -2.4537029093721308
- type: nauc_precision_at_5_max
value: 21.41469327545133
- type: nauc_precision_at_5_std
value: 0.1543890645722277
- type: nauc_recall_at_1000_diff1
value: -1.7474947956413491
- type: nauc_recall_at_1000_max
value: 46.22670991970479
- type: nauc_recall_at_1000_std
value: 62.582840705588794
- type: nauc_recall_at_100_diff1
value: 16.116089801097345
- type: nauc_recall_at_100_max
value: 52.54794580975103
- type: nauc_recall_at_100_std
value: 33.720245696003246
- type: nauc_recall_at_10_diff1
value: 23.134924318655482
- type: nauc_recall_at_10_max
value: 38.73754275649077
- type: nauc_recall_at_10_std
value: 0.6137471711639239
- type: nauc_recall_at_1_diff1
value: 47.66181128677822
- type: nauc_recall_at_1_max
value: 21.75204233166764
- type: nauc_recall_at_1_std
value: -8.06951079061697
- type: nauc_recall_at_20_diff1
value: 24.130616271355017
- type: nauc_recall_at_20_max
value: 48.306178640146136
- type: nauc_recall_at_20_std
value: 9.290819557000022
- type: nauc_recall_at_3_diff1
value: 29.767415016250226
- type: nauc_recall_at_3_max
value: 28.54289782140701
- type: nauc_recall_at_3_std
value: -5.1395675072005576
- type: nauc_recall_at_5_diff1
value: 25.410613126870174
- type: nauc_recall_at_5_max
value: 33.24658754857624
- type: nauc_recall_at_5_std
value: -4.211226036746632
- type: ndcg_at_1
value: 62.175000000000004
- type: ndcg_at_10
value: 72.306
- type: ndcg_at_100
value: 75.074
- type: ndcg_at_1000
value: 75.581
- type: ndcg_at_20
value: 73.875
- type: ndcg_at_3
value: 65.641
- type: ndcg_at_5
value: 69.48299999999999
- type: precision_at_1
value: 62.175000000000004
- type: precision_at_10
value: 13.907
- type: precision_at_100
value: 1.591
- type: precision_at_1000
value: 0.166
- type: precision_at_20
value: 7.446999999999999
- type: precision_at_3
value: 35.619
- type: precision_at_5
value: 24.917
- type: recall_at_1
value: 44.187
- type: recall_at_10
value: 85.10600000000001
- type: recall_at_100
value: 95.488
- type: recall_at_1000
value: 98.831
- type: recall_at_20
value: 90.22200000000001
- type: recall_at_3
value: 68.789
- type: recall_at_5
value: 77.85499999999999
task:
type: Retrieval
- dataset:
config: default
name: MTEB RuReviewsClassification (default)
revision: f6d2c31f4dc6b88f468552750bfec05b4b41b05a
split: test
type: ai-forever/ru-reviews-classification
metrics:
- type: accuracy
value: 67.5830078125
- type: f1
value: 67.56931936632446
- type: f1_weighted
value: 67.57137733752779
- type: main_score
value: 67.5830078125
task:
type: Classification
- dataset:
config: default
name: MTEB RuSTSBenchmarkSTS (default)
revision: 7cf24f325c6da6195df55bef3d86b5e0616f3018
split: test
type: ai-forever/ru-stsbenchmark-sts
metrics:
- type: cosine_pearson
value: 85.90493484626788
- type: cosine_spearman
value: 86.21965691667411
- type: euclidean_pearson
value: 86.07499842984909
- type: euclidean_spearman
value: 86.55506818735688
- type: main_score
value: 86.21965691667411
- type: manhattan_pearson
value: 85.95976420231729
- type: manhattan_spearman
value: 86.48604243661234
- type: pearson
value: 85.90493484626788
- type: spearman
value: 86.21965691667411
task:
type: STS
- dataset:
config: default
name: MTEB RuSciBenchGRNTIClassification (default)
revision: 673a610d6d3dd91a547a0d57ae1b56f37ebbf6a1
split: test
type: ai-forever/ru-scibench-grnti-classification
metrics:
- type: accuracy
value: 59.1943359375
- type: f1
value: 58.894480861440414
- type: f1_weighted
value: 58.903615560240866
- type: main_score
value: 59.1943359375
task:
type: Classification
- dataset:
config: default
name: MTEB RuSciBenchGRNTIClusteringP2P (default)
revision: 673a610d6d3dd91a547a0d57ae1b56f37ebbf6a1
split: test
type: ai-forever/ru-scibench-grnti-classification
metrics:
- type: main_score
value: 57.99209448663228
- type: v_measure
value: 57.99209448663228
- type: v_measure_std
value: 1.0381163861993816
task:
type: Clustering
- dataset:
config: default
name: MTEB RuSciBenchOECDClassification (default)
revision: 26c88e99dcaba32bb45d0e1bfc21902337f6d471
split: test
type: ai-forever/ru-scibench-oecd-classification
metrics:
- type: accuracy
value: 45.556640625
- type: f1
value: 45.159163104085906
- type: f1_weighted
value: 45.16098316398626
- type: main_score
value: 45.556640625
task:
type: Classification
- dataset:
config: default
name: MTEB RuSciBenchOECDClusteringP2P (default)
revision: 26c88e99dcaba32bb45d0e1bfc21902337f6d471
split: test
type: ai-forever/ru-scibench-oecd-classification
metrics:
- type: main_score
value: 50.787548070488974
- type: v_measure
value: 50.787548070488974
- type: v_measure_std
value: 0.8569958168946827
task:
type: Clustering
- dataset:
config: default
name: MTEB SCIDOCS (default)
revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88
split: test
type: mteb/scidocs
metrics:
- type: map_at_1
value: 4.843
- type: map_at_10
value: 11.752
- type: map_at_100
value: 13.919
- type: map_at_1000
value: 14.198
- type: map_at_20
value: 12.898000000000001
- type: map_at_3
value: 8.603
- type: map_at_5
value: 10.069
- type: mrr_at_1
value: 23.799999999999997
- type: mrr_at_10
value: 34.449999999999996
- type: mrr_at_100
value: 35.64
- type: mrr_at_1000
value: 35.691
- type: mrr_at_20
value: 35.213
- type: mrr_at_3
value: 31.383
- type: mrr_at_5
value: 33.062999999999995
- type: ndcg_at_1
value: 23.799999999999997
- type: ndcg_at_10
value: 19.811
- type: ndcg_at_100
value: 28.108
- type: ndcg_at_1000
value: 33.1
- type: ndcg_at_20
value: 22.980999999999998
- type: ndcg_at_3
value: 19.153000000000002
- type: ndcg_at_5
value: 16.408
- type: precision_at_1
value: 23.799999999999997
- type: precision_at_10
value: 10.16
- type: precision_at_100
value: 2.1999999999999997
- type: precision_at_1000
value: 0.34099999999999997
- type: precision_at_20
value: 6.915
- type: precision_at_3
value: 17.8
- type: precision_at_5
value: 14.14
- type: recall_at_1
value: 4.843
- type: recall_at_10
value: 20.595
- type: recall_at_100
value: 44.66
- type: recall_at_1000
value: 69.152
- type: recall_at_20
value: 28.04
- type: recall_at_3
value: 10.833
- type: recall_at_5
value: 14.346999999999998
- type: main_score
value: 19.811
task:
type: Retrieval
- dataset:
config: default
name: MTEB SICK-E-PL (default)
revision: 71bba34b0ece6c56dfcf46d9758a27f7a90f17e9
split: test
type: PL-MTEB/sicke-pl-pairclassification
metrics:
- type: cosine_accuracy
value: 80.90093762739502
- type: cosine_accuracy_threshold
value: 94.40930485725403
- type: cosine_ap
value: 71.15400909912427
- type: cosine_f1
value: 66.8213457076566
- type: cosine_f1_threshold
value: 91.53673648834229
- type: cosine_precision
value: 62.4922504649721
- type: cosine_recall
value: 71.7948717948718
- type: dot_accuracy
value: 78.41418671015083
- type: dot_accuracy_threshold
value: 42924.45068359375
- type: dot_ap
value: 63.34003025365763
- type: dot_f1
value: 62.518258837277244
- type: dot_f1_threshold
value: 40900.738525390625
- type: dot_precision
value: 52.99653293709758
- type: dot_recall
value: 76.21082621082621
- type: euclidean_accuracy
value: 80.67672238075826
- type: euclidean_accuracy_threshold
value: 696.0524559020996
- type: euclidean_ap
value: 70.88762835990224
- type: euclidean_f1
value: 66.711051930759
- type: euclidean_f1_threshold
value: 878.5581588745117
- type: euclidean_precision
value: 62.625
- type: euclidean_recall
value: 71.36752136752136
- type: main_score
value: 71.15400909912427
- type: manhattan_accuracy
value: 80.65633917651854
- type: manhattan_accuracy_threshold
value: 17277.72674560547
- type: manhattan_ap
value: 70.67105336611716
- type: manhattan_f1
value: 66.51346027577151
- type: manhattan_f1_threshold
value: 21687.957763671875
- type: manhattan_precision
value: 61.69305724725944
- type: manhattan_recall
value: 72.15099715099716
- type: max_accuracy
value: 80.90093762739502
- type: max_ap
value: 71.15400909912427
- type: max_f1
value: 66.8213457076566
- type: max_precision
value: 62.625
- type: max_recall
value: 76.21082621082621
- type: similarity_accuracy
value: 80.90093762739502
- type: similarity_accuracy_threshold
value: 94.40930485725403
- type: similarity_ap
value: 71.15400909912427
- type: similarity_f1
value: 66.8213457076566
- type: similarity_f1_threshold
value: 91.53673648834229
- type: similarity_precision
value: 62.4922504649721
- type: similarity_recall
value: 71.7948717948718
task:
type: PairClassification
- dataset:
config: default
name: MTEB SICK-R (default)
revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
split: test
type: mteb/sickr-sts
metrics:
- type: cosine_pearson
value: 92.3339946866199
- type: cosine_spearman
value: 89.61697355115497
- type: euclidean_pearson
value: 90.3264916449669
- type: euclidean_spearman
value: 89.36270451308866
- type: main_score
value: 89.61697355115497
- type: manhattan_pearson
value: 90.18909339052534
- type: manhattan_spearman
value: 89.28337093097377
- type: pearson
value: 92.3339946866199
- type: spearman
value: 89.61697355115497
task:
type: STS
- dataset:
config: default
name: MTEB SICK-R-PL (default)
revision: fd5c2441b7eeff8676768036142af4cfa42c1339
split: test
type: PL-MTEB/sickr-pl-sts
metrics:
- type: cosine_pearson
value: 85.27883048457821
- type: cosine_spearman
value: 80.53204892678619
- type: euclidean_pearson
value: 82.78520705216168
- type: euclidean_spearman
value: 80.27848359873212
- type: main_score
value: 80.53204892678619
- type: manhattan_pearson
value: 82.63270640583454
- type: manhattan_spearman
value: 80.21507977473146
- type: pearson
value: 85.27883048457821
- type: spearman
value: 80.53204892678619
task:
type: STS
- dataset:
config: default
name: MTEB SICKFr (default)
revision: e077ab4cf4774a1e36d86d593b150422fafd8e8a
split: test
type: Lajavaness/SICK-fr
metrics:
- type: cosine_pearson
value: 88.77029361817212
- type: cosine_spearman
value: 83.9453600346894
- type: euclidean_pearson
value: 85.85331086208573
- type: euclidean_spearman
value: 83.70852031985308
- type: main_score
value: 83.9453600346894
- type: manhattan_pearson
value: 85.66222265885914
- type: manhattan_spearman
value: 83.60833111525962
- type: pearson
value: 88.77029361817212
- type: spearman
value: 83.9453600346894
task:
type: STS
- dataset:
config: default
name: MTEB STS12 (default)
revision: a0d554a64d88156834ff5ae9920b964011b16384
split: test
type: mteb/sts12-sts
metrics:
- type: cosine_pearson
value: 88.76435859522375
- type: cosine_spearman
value: 82.43768167804375
- type: euclidean_pearson
value: 87.43566183874832
- type: euclidean_spearman
value: 82.82166873757507
- type: main_score
value: 82.43768167804375
- type: manhattan_pearson
value: 87.39450871380951
- type: manhattan_spearman
value: 82.89253043430163
- type: pearson
value: 88.76435859522375
- type: spearman
value: 82.43768167804375
task:
type: STS
- dataset:
config: default
name: MTEB STS13 (default)
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
split: test
type: mteb/sts13-sts
metrics:
- type: cosine_pearson
value: 88.86627241652141
- type: cosine_spearman
value: 89.49011599120688
- type: euclidean_pearson
value: 89.3314120073772
- type: euclidean_spearman
value: 89.8226502776963
- type: main_score
value: 89.49011599120688
- type: manhattan_pearson
value: 89.2252179076963
- type: manhattan_spearman
value: 89.74573844021225
- type: pearson
value: 88.86627241652141
- type: spearman
value: 89.49011599120688
task:
type: STS
- dataset:
config: default
name: MTEB STS14 (default)
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
split: test
type: mteb/sts14-sts
metrics:
- type: cosine_pearson
value: 87.22891405215968
- type: cosine_spearman
value: 84.9467188157614
- type: euclidean_pearson
value: 87.20330004726237
- type: euclidean_spearman
value: 85.34806059461808
- type: main_score
value: 84.9467188157614
- type: manhattan_pearson
value: 87.15224666107623
- type: manhattan_spearman
value: 85.34596898699708
- type: pearson
value: 87.22891405215968
- type: spearman
value: 84.9467188157614
task:
type: STS
- dataset:
config: default
name: MTEB STS15 (default)
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
split: test
type: mteb/sts15-sts
metrics:
- type: cosine_pearson
value: 88.14066430111033
- type: cosine_spearman
value: 89.31337445552545
- type: euclidean_pearson
value: 89.08039335366983
- type: euclidean_spearman
value: 89.6658762856415
- type: main_score
value: 89.31337445552545
- type: manhattan_pearson
value: 89.08057438154486
- type: manhattan_spearman
value: 89.68673984203022
- type: pearson
value: 88.14066430111033
- type: spearman
value: 89.31337445552545
task:
type: STS
- dataset:
config: default
name: MTEB STS16 (default)
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
split: test
type: mteb/sts16-sts
metrics:
- type: cosine_pearson
value: 85.14908856657084
- type: cosine_spearman
value: 86.84648320786727
- type: euclidean_pearson
value: 86.11454713131947
- type: euclidean_spearman
value: 86.77738862047961
- type: main_score
value: 86.84648320786727
- type: manhattan_pearson
value: 86.07804821916372
- type: manhattan_spearman
value: 86.78676064310474
- type: pearson
value: 85.14908856657084
- type: spearman
value: 86.84648320786727
task:
type: STS
- dataset:
config: en-en
name: MTEB STS17 (en-en)
revision: faeb762787bd10488a50c8b5be4a3b82e411949c
split: test
type: mteb/sts17-crosslingual-sts
metrics:
- type: cosine_pearson
value: 89.61633502468356
- type: cosine_spearman
value: 89.99772663224805
- type: euclidean_pearson
value: 90.14056501501044
- type: euclidean_spearman
value: 90.04496896837503
- type: main_score
value: 89.99772663224805
- type: manhattan_pearson
value: 90.08964860311801
- type: manhattan_spearman
value: 90.00091712362196
- type: pearson
value: 89.61633502468356
- type: spearman
value: 89.99772663224805
task:
type: STS
- dataset:
config: es-en
name: MTEB STS17 (es-en)
revision: faeb762787bd10488a50c8b5be4a3b82e411949c
split: test
type: mteb/sts17-crosslingual-sts
metrics:
- type: cosine_pearson
value: 86.44548026840202
- type: cosine_spearman
value: 87.26263108768539
- type: euclidean_pearson
value: 86.42844593583838
- type: euclidean_spearman
value: 86.89388428664364
- type: main_score
value: 87.26263108768539
- type: manhattan_pearson
value: 86.47186940800881
- type: manhattan_spearman
value: 87.02163091089946
- type: pearson
value: 86.44548026840202
- type: spearman
value: 87.26263108768539
task:
type: STS
- dataset:
config: en-de
name: MTEB STS17 (en-de)
revision: faeb762787bd10488a50c8b5be4a3b82e411949c
split: test
type: mteb/sts17-crosslingual-sts
metrics:
- type: cosine_pearson
value: 87.89345132532758
- type: cosine_spearman
value: 87.96246221327699
- type: euclidean_pearson
value: 88.49013032701419
- type: euclidean_spearman
value: 87.81981265317344
- type: main_score
value: 87.96246221327699
- type: manhattan_pearson
value: 88.31360914178538
- type: manhattan_spearman
value: 87.62734530005075
- type: pearson
value: 87.89345132532758
- type: spearman
value: 87.96246221327699
task:
type: STS
- dataset:
config: es-es
name: MTEB STS17 (es-es)
revision: faeb762787bd10488a50c8b5be4a3b82e411949c
split: test
type: mteb/sts17-crosslingual-sts
metrics:
- type: cosine_pearson
value: 88.4084678497171
- type: cosine_spearman
value: 88.77640638748285
- type: euclidean_pearson
value: 89.60124312475843
- type: euclidean_spearman
value: 88.4321442688528
- type: main_score
value: 88.77640638748285
- type: manhattan_pearson
value: 89.62375118021299
- type: manhattan_spearman
value: 88.46998118661577
- type: pearson
value: 88.4084678497171
- type: spearman
value: 88.77640638748285
task:
type: STS
- dataset:
config: fr-en
name: MTEB STS17 (fr-en)
revision: faeb762787bd10488a50c8b5be4a3b82e411949c
split: test
type: mteb/sts17-crosslingual-sts
metrics:
- type: cosine_pearson
value: 87.30688801326498
- type: cosine_spearman
value: 87.55684697258378
- type: euclidean_pearson
value: 87.89672951056794
- type: euclidean_spearman
value: 87.28050429201674
- type: main_score
value: 87.55684697258378
- type: manhattan_pearson
value: 87.74292745320572
- type: manhattan_spearman
value: 87.16383993876582
- type: pearson
value: 87.30688801326498
- type: spearman
value: 87.55684697258378
task:
type: STS
- dataset:
config: zh-en
name: MTEB STS22 (zh-en)
revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
split: test
type: mteb/sts22-crosslingual-sts
metrics:
- type: cosine_pearson
value: 73.46180375170147
- type: cosine_spearman
value: 73.39559590127081
- type: euclidean_pearson
value: 73.72613901293681
- type: euclidean_spearman
value: 71.85465165176795
- type: main_score
value: 73.39559590127081
- type: manhattan_pearson
value: 73.07859140869076
- type: manhattan_spearman
value: 71.22047343718893
- type: pearson
value: 73.46180375170147
- type: spearman
value: 73.39559590127081
task:
type: STS
- dataset:
config: zh
name: MTEB STS22 (zh)
revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
split: test
type: mteb/sts22-crosslingual-sts
metrics:
- type: cosine_pearson
value: 62.47531620842637
- type: cosine_spearman
value: 66.22504667157702
- type: euclidean_pearson
value: 66.76201254783692
- type: euclidean_spearman
value: 66.86115760269463
- type: main_score
value: 66.22504667157702
- type: manhattan_pearson
value: 66.73847836793489
- type: manhattan_spearman
value: 66.7677116377695
- type: pearson
value: 62.47531620842637
- type: spearman
value: 66.22504667157702
task:
type: STS
- dataset:
config: es
name: MTEB STS22 (es)
revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
split: test
type: mteb/sts22-crosslingual-sts
metrics:
- type: cosine_pearson
value: 69.89707002436481
- type: cosine_spearman
value: 72.2054865735116
- type: euclidean_pearson
value: 71.81856615570756
- type: euclidean_spearman
value: 72.72593304629407
- type: main_score
value: 72.2054865735116
- type: manhattan_pearson
value: 72.00362684700072
- type: manhattan_spearman
value: 72.62783534769964
- type: pearson
value: 69.89707002436481
- type: spearman
value: 72.2054865735116
task:
type: STS
- dataset:
config: fr
name: MTEB STS22 (fr)
revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
split: test
type: mteb/sts22-crosslingual-sts
metrics:
- type: cosine_pearson
value: 81.59623734395916
- type: cosine_spearman
value: 83.28946105111358
- type: euclidean_pearson
value: 79.377330171466
- type: euclidean_spearman
value: 81.81029781662205
- type: main_score
value: 83.28946105111358
- type: manhattan_pearson
value: 78.96970881689698
- type: manhattan_spearman
value: 81.91773236079703
- type: pearson
value: 81.59623734395916
- type: spearman
value: 83.28946105111358
task:
type: STS
- dataset:
config: de-fr
name: MTEB STS22 (de-fr)
revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
split: test
type: mteb/sts22-crosslingual-sts
metrics:
- type: cosine_pearson
value: 55.03825643126142
- type: cosine_spearman
value: 58.25792501780429
- type: euclidean_pearson
value: 50.38007603973409
- type: euclidean_spearman
value: 59.39961789383097
- type: main_score
value: 58.25792501780429
- type: manhattan_pearson
value: 50.518568927999155
- type: manhattan_spearman
value: 59.84185466003894
- type: pearson
value: 55.03825643126142
- type: spearman
value: 58.25792501780429
task:
type: STS
- dataset:
config: pl-en
name: MTEB STS22 (pl-en)
revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
split: test
type: mteb/sts22-crosslingual-sts
metrics:
- type: cosine_pearson
value: 77.77233721490776
- type: cosine_spearman
value: 76.17596588017625
- type: euclidean_pearson
value: 74.47600468156611
- type: euclidean_spearman
value: 72.61278728057012
- type: main_score
value: 76.17596588017625
- type: manhattan_pearson
value: 74.48118910099699
- type: manhattan_spearman
value: 73.33167419101696
- type: pearson
value: 77.77233721490776
- type: spearman
value: 76.17596588017625
task:
type: STS
- dataset:
config: pl
name: MTEB STS22 (pl)
revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
split: test
type: mteb/sts22-crosslingual-sts
metrics:
- type: cosine_pearson
value: 42.87453608131507
- type: cosine_spearman
value: 45.137849894401185
- type: euclidean_pearson
value: 31.66964197694796
- type: euclidean_spearman
value: 44.1014900837869
- type: main_score
value: 45.137849894401185
- type: manhattan_pearson
value: 31.007199259384745
- type: manhattan_spearman
value: 43.48181523288926
- type: pearson
value: 42.87453608131507
- type: spearman
value: 45.137849894401185
task:
type: STS
- dataset:
config: en
name: MTEB STS22 (en)
revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
split: test
type: mteb/sts22-crosslingual-sts
metrics:
- type: cosine_pearson
value: 66.87400150638176
- type: cosine_spearman
value: 67.27861354834066
- type: euclidean_pearson
value: 66.81789582140216
- type: euclidean_spearman
value: 66.44220479858708
- type: main_score
value: 67.27861354834066
- type: manhattan_pearson
value: 66.92509859033235
- type: manhattan_spearman
value: 66.46841124185076
- type: pearson
value: 66.87400150638176
- type: spearman
value: 67.27861354834066
task:
type: STS
- dataset:
config: ru
name: MTEB STS22 (ru)
revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
split: test
type: mteb/sts22-crosslingual-sts
metrics:
- type: cosine_pearson
value: 61.819804551576084
- type: cosine_spearman
value: 65.0864146772135
- type: euclidean_pearson
value: 62.518151090361876
- type: euclidean_spearman
value: 65.13608138548017
- type: main_score
value: 65.0864146772135
- type: manhattan_pearson
value: 62.51413246915267
- type: manhattan_spearman
value: 65.19077543064323
- type: pearson
value: 61.819804551576084
- type: spearman
value: 65.0864146772135
task:
type: STS
- dataset:
config: de
name: MTEB STS22 (de)
revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
split: test
type: mteb/sts22-crosslingual-sts
metrics:
- type: cosine_pearson
value: 54.85728696035389
- type: cosine_spearman
value: 61.60906359227576
- type: euclidean_pearson
value: 52.57582587901851
- type: euclidean_spearman
value: 61.41823097598308
- type: main_score
value: 61.60906359227576
- type: manhattan_pearson
value: 52.500978361080506
- type: manhattan_spearman
value: 61.30365596659758
- type: pearson
value: 54.85728696035389
- type: spearman
value: 61.60906359227576
task:
type: STS
- dataset:
config: fr-pl
name: MTEB STS22 (fr-pl)
revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
split: test
type: mteb/sts22-crosslingual-sts
metrics:
- type: cosine_pearson
value: 67.68016005631422
- type: cosine_spearman
value: 84.51542547285167
- type: euclidean_pearson
value: 66.19871164667245
- type: euclidean_spearman
value: 73.24670207647144
- type: main_score
value: 84.51542547285167
- type: manhattan_pearson
value: 67.0443525268974
- type: manhattan_spearman
value: 73.24670207647144
- type: pearson
value: 67.68016005631422
- type: spearman
value: 84.51542547285167
task:
type: STS
- dataset:
config: de-pl
name: MTEB STS22 (de-pl)
revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
split: test
type: mteb/sts22-crosslingual-sts
metrics:
- type: cosine_pearson
value: 47.49467414030747
- type: cosine_spearman
value: 56.81512095681289
- type: euclidean_pearson
value: 48.42860221765214
- type: euclidean_spearman
value: 58.63197306329092
- type: main_score
value: 56.81512095681289
- type: manhattan_pearson
value: 48.39594959260441
- type: manhattan_spearman
value: 58.63197306329092
- type: pearson
value: 47.49467414030747
- type: spearman
value: 56.81512095681289
task:
type: STS
- dataset:
config: es-en
name: MTEB STS22 (es-en)
revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
split: test
type: mteb/sts22-crosslingual-sts
metrics:
- type: cosine_pearson
value: 76.8364678896155
- type: cosine_spearman
value: 78.45516413087114
- type: euclidean_pearson
value: 78.62779318576634
- type: euclidean_spearman
value: 78.88760695649488
- type: main_score
value: 78.45516413087114
- type: manhattan_pearson
value: 78.62131335760031
- type: manhattan_spearman
value: 78.81861844200388
- type: pearson
value: 76.8364678896155
- type: spearman
value: 78.45516413087114
task:
type: STS
- dataset:
config: de-en
name: MTEB STS22 (de-en)
revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
split: test
type: mteb/sts22-crosslingual-sts
metrics:
- type: cosine_pearson
value: 65.16640313911604
- type: cosine_spearman
value: 60.887608967403914
- type: euclidean_pearson
value: 67.49902244990913
- type: euclidean_spearman
value: 59.2458787136538
- type: main_score
value: 60.887608967403914
- type: manhattan_pearson
value: 67.34313506388378
- type: manhattan_spearman
value: 59.05283429200166
- type: pearson
value: 65.16640313911604
- type: spearman
value: 60.887608967403914
task:
type: STS
- dataset:
config: default
name: MTEB STSB (default)
revision: 0cde68302b3541bb8b3c340dc0644b0b745b3dc0
split: test
type: C-MTEB/STSB
metrics:
- type: cosine_pearson
value: 81.5092853013241
- type: cosine_spearman
value: 83.54005474244292
- type: euclidean_pearson
value: 83.7246578378554
- type: euclidean_spearman
value: 84.46767551087716
- type: main_score
value: 83.54005474244292
- type: manhattan_pearson
value: 83.65922665594636
- type: manhattan_spearman
value: 84.42431449101848
- type: pearson
value: 81.5092853013241
- type: spearman
value: 83.54005474244292
task:
type: STS
- dataset:
config: default
name: MTEB STSBenchmark (default)
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
split: test
type: mteb/stsbenchmark-sts
metrics:
- type: cosine_pearson
value: 87.70246866744966
- type: cosine_spearman
value: 89.44070045346106
- type: euclidean_pearson
value: 89.56956519641007
- type: euclidean_spearman
value: 89.95830112784283
- type: main_score
value: 89.44070045346106
- type: manhattan_pearson
value: 89.48264471425145
- type: manhattan_spearman
value: 89.87900732483114
- type: pearson
value: 87.70246866744966
- type: spearman
value: 89.44070045346106
task:
type: STS
- dataset:
config: de
name: MTEB STSBenchmarkMultilingualSTS (de)
revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
split: test
type: mteb/stsb_multi_mt
metrics:
- type: cosine_pearson
value: 86.83701990805217
- type: cosine_spearman
value: 87.80280785492258
- type: euclidean_pearson
value: 87.77325330043514
- type: euclidean_spearman
value: 88.3564607283144
- type: main_score
value: 87.80280785492258
- type: manhattan_pearson
value: 87.6745449945946
- type: manhattan_spearman
value: 88.30660465978795
- type: pearson
value: 86.83701990805217
- type: spearman
value: 87.80280785492258
task:
type: STS
- dataset:
config: zh
name: MTEB STSBenchmarkMultilingualSTS (zh)
revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
split: test
type: mteb/stsb_multi_mt
metrics:
- type: cosine_pearson
value: 84.27751020600267
- type: cosine_spearman
value: 85.63500407412486
- type: euclidean_pearson
value: 85.21829891649696
- type: euclidean_spearman
value: 85.9384575715382
- type: main_score
value: 85.63500407412486
- type: manhattan_pearson
value: 85.10797194089801
- type: manhattan_spearman
value: 85.8770162042784
- type: pearson
value: 84.27751020600267
- type: spearman
value: 85.63500407412486
task:
type: STS
- dataset:
config: fr
name: MTEB STSBenchmarkMultilingualSTS (fr)
revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
split: test
type: mteb/stsb_multi_mt
metrics:
- type: cosine_pearson
value: 86.56833656723254
- type: cosine_spearman
value: 87.4393978501382
- type: euclidean_pearson
value: 87.45171512751267
- type: euclidean_spearman
value: 88.13106516566947
- type: main_score
value: 87.4393978501382
- type: manhattan_pearson
value: 87.33010961793333
- type: manhattan_spearman
value: 88.06707425102182
- type: pearson
value: 86.56833656723254
- type: spearman
value: 87.4393978501382
task:
type: STS
- dataset:
config: pl
name: MTEB STSBenchmarkMultilingualSTS (pl)
revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
split: test
type: mteb/stsb_multi_mt
metrics:
- type: cosine_pearson
value: 85.45065540325523
- type: cosine_spearman
value: 85.47881076789359
- type: euclidean_pearson
value: 85.1999493863155
- type: euclidean_spearman
value: 85.7874947669187
- type: main_score
value: 85.47881076789359
- type: manhattan_pearson
value: 85.06075305990376
- type: manhattan_spearman
value: 85.71563015639558
- type: pearson
value: 85.45065540325523
- type: spearman
value: 85.47881076789359
task:
type: STS
- dataset:
config: es
name: MTEB STSBenchmarkMultilingualSTS (es)
revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
split: test
type: mteb/stsb_multi_mt
metrics:
- type: cosine_pearson
value: 87.11952824079832
- type: cosine_spearman
value: 87.9643473573153
- type: euclidean_pearson
value: 88.11750364639971
- type: euclidean_spearman
value: 88.63695109016498
- type: main_score
value: 87.9643473573153
- type: manhattan_pearson
value: 88.00294453126699
- type: manhattan_spearman
value: 88.53750241758391
- type: pearson
value: 87.11952824079832
- type: spearman
value: 87.9643473573153
task:
type: STS
- dataset:
config: ru
name: MTEB STSBenchmarkMultilingualSTS (ru)
revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
split: test
type: mteb/stsb_multi_mt
metrics:
- type: cosine_pearson
value: 85.99804354414991
- type: cosine_spearman
value: 86.30252111551002
- type: euclidean_pearson
value: 86.1880652037762
- type: euclidean_spearman
value: 86.69556223944502
- type: main_score
value: 86.30252111551002
- type: manhattan_pearson
value: 86.0736400320898
- type: manhattan_spearman
value: 86.61747927593393
- type: pearson
value: 85.99804354414991
- type: spearman
value: 86.30252111551002
task:
type: STS
- dataset:
config: en
name: MTEB STSBenchmarkMultilingualSTS (en)
revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
split: test
type: mteb/stsb_multi_mt
metrics:
- type: cosine_pearson
value: 87.70246861738103
- type: cosine_spearman
value: 89.44070045346106
- type: euclidean_pearson
value: 89.56956518833663
- type: euclidean_spearman
value: 89.95830112784283
- type: main_score
value: 89.44070045346106
- type: manhattan_pearson
value: 89.48264470792915
- type: manhattan_spearman
value: 89.87900732483114
- type: pearson
value: 87.70246861738103
- type: spearman
value: 89.44070045346106
task:
type: STS
- dataset:
config: default
name: MTEB SciDocsRR (default)
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
split: test
type: mteb/scidocs-reranking
metrics:
- type: map
value: 84.88064122814694
- type: mrr
value: 95.84832651009123
- type: main_score
value: 84.88064122814694
task:
type: Reranking
- dataset:
config: default
name: MTEB SciFact (default)
revision: 0228b52cf27578f30900b9e5271d331663a030d7
split: test
type: mteb/scifact
metrics:
- type: map_at_1
value: 57.289
- type: map_at_10
value: 67.88499999999999
- type: map_at_100
value: 68.477
- type: map_at_1000
value: 68.50500000000001
- type: map_at_20
value: 68.33500000000001
- type: map_at_3
value: 65.08
- type: map_at_5
value: 67.001
- type: mrr_at_1
value: 59.667
- type: mrr_at_10
value: 68.626
- type: mrr_at_100
value: 69.082
- type: mrr_at_1000
value: 69.108
- type: mrr_at_20
value: 68.958
- type: mrr_at_3
value: 66.667
- type: mrr_at_5
value: 67.983
- type: ndcg_at_1
value: 59.667
- type: ndcg_at_10
value: 72.309
- type: ndcg_at_100
value: 74.58399999999999
- type: ndcg_at_1000
value: 75.25500000000001
- type: ndcg_at_20
value: 73.656
- type: ndcg_at_3
value: 67.791
- type: ndcg_at_5
value: 70.45
- type: precision_at_1
value: 59.667
- type: precision_at_10
value: 9.567
- type: precision_at_100
value: 1.073
- type: precision_at_1000
value: 0.11299999999999999
- type: precision_at_20
value: 5.083
- type: precision_at_3
value: 26.333000000000002
- type: precision_at_5
value: 17.666999999999998
- type: recall_at_1
value: 57.289
- type: recall_at_10
value: 84.756
- type: recall_at_100
value: 94.5
- type: recall_at_1000
value: 99.667
- type: recall_at_20
value: 89.7
- type: recall_at_3
value: 73.22800000000001
- type: recall_at_5
value: 79.444
- type: main_score
value: 72.309
task:
type: Retrieval
- dataset:
config: default
name: MTEB SpanishNewsClusteringP2P (default)
revision: bf8ca8ddc5b7da4f7004720ddf99bbe0483480e6
split: test
type: jinaai/spanish_news_clustering
metrics:
- type: main_score
value: 45.04477709795154
- type: v_measure
value: 45.04477709795154
- type: v_measure_std
value: 0.0
task:
type: Clustering
- dataset:
config: default
name: MTEB SpanishPassageRetrievalS2S (default)
revision: 9cddf2ce5209ade52c2115ccfa00eb22c6d3a837
split: test
type: jinaai/spanish_passage_retrieval
metrics:
- type: main_score
value: 69.83
- type: map_at_1
value: 15.736
- type: map_at_10
value: 52.027
- type: map_at_100
value: 65.08800000000001
- type: map_at_1000
value: 65.08800000000001
- type: map_at_20
value: 60.79900000000001
- type: map_at_3
value: 32.869
- type: map_at_5
value: 41.436
- type: mrr_at_1
value: 75.44910179640718
- type: mrr_at_10
value: 84.43446440452426
- type: mrr_at_100
value: 84.48052612723271
- type: mrr_at_1000
value: 84.48052612723271
- type: mrr_at_20
value: 84.48052612723271
- type: mrr_at_3
value: 83.13373253493013
- type: mrr_at_5
value: 84.3013972055888
- type: nauc_map_at_1000_diff1
value: 50.611540149694356
- type: nauc_map_at_1000_max
value: 2.1102430434260238
- type: nauc_map_at_1000_std
value: -18.88993521335793
- type: nauc_map_at_100_diff1
value: 50.611540149694356
- type: nauc_map_at_100_max
value: 2.1102430434260238
- type: nauc_map_at_100_std
value: -18.88993521335793
- type: nauc_map_at_10_diff1
value: 59.13518981755268
- type: nauc_map_at_10_max
value: -9.810386627392807
- type: nauc_map_at_10_std
value: -38.31810152345078
- type: nauc_map_at_1_diff1
value: 74.96782567287174
- type: nauc_map_at_1_max
value: -29.648279252607875
- type: nauc_map_at_1_std
value: -54.017459339141595
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name: MTEB SprintDuplicateQuestions (default)
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
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type: mteb/sprintduplicatequestions-pairclassification
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task:
type: PairClassification
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config: default
name: MTEB StackExchangeClustering (default)
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
split: test
type: mteb/stackexchange-clustering
metrics:
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task:
type: Clustering
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config: default
name: MTEB StackExchangeClusteringP2P (default)
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
split: test
type: mteb/stackexchange-clustering-p2p
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task:
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config: default
name: MTEB StackOverflowDupQuestions (default)
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
split: test
type: mteb/stackoverflowdupquestions-reranking
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task:
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name: MTEB SummEval (default)
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
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type: mteb/summeval
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task:
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revision: b385812de6a9577b6f4d0f88c6a6e35395a94054
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task:
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revision: b205c5084a0934ce8af14338bf03feb19499c84d
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type: lyon-nlp/mteb-fr-reranking-syntec-s2p
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revision: 19661ccdca4dfc2d15122d776b61685f48c68ca9
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- type: nauc_recall_at_3_std
value: 7.649686453053851
- type: nauc_recall_at_5_diff1
value: 43.5224089635856
- type: nauc_recall_at_5_max
value: 16.92343604108335
- type: nauc_recall_at_5_std
value: -10.854341736694499
- type: ndcg_at_1
value: 68.0
- type: ndcg_at_10
value: 83.851
- type: ndcg_at_100
value: 84.36099999999999
- type: ndcg_at_1000
value: 84.36099999999999
- type: ndcg_at_20
value: 84.36099999999999
- type: ndcg_at_3
value: 80.333
- type: ndcg_at_5
value: 83.21600000000001
- type: precision_at_1
value: 68.0
- type: precision_at_10
value: 9.8
- type: precision_at_100
value: 1.0
- type: precision_at_1000
value: 0.1
- type: precision_at_20
value: 5.0
- type: precision_at_3
value: 29.666999999999998
- type: precision_at_5
value: 19.2
- type: recall_at_1
value: 68.0
- type: recall_at_10
value: 98.0
- type: recall_at_100
value: 100.0
- type: recall_at_1000
value: 100.0
- type: recall_at_20
value: 100.0
- type: recall_at_3
value: 89.0
- type: recall_at_5
value: 96.0
task:
type: Retrieval
- dataset:
config: default
name: MTEB T2Reranking (default)
revision: 76631901a18387f85eaa53e5450019b87ad58ef9
split: dev
type: C-MTEB/T2Reranking
metrics:
- type: map
value: 65.3088203970324
- type: mrr
value: 74.79505862376546
- type: main_score
value: 65.3088203970324
task:
type: Reranking
- dataset:
config: default
name: MTEB T2Retrieval (default)
revision: 8731a845f1bf500a4f111cf1070785c793d10e64
split: dev
type: C-MTEB/T2Retrieval
metrics:
- type: main_score
value: 83.163
- type: map_at_1
value: 26.875
- type: map_at_10
value: 75.454
- type: map_at_100
value: 79.036
- type: map_at_1000
value: 79.111
- type: map_at_20
value: 78.145
- type: map_at_3
value: 53.181
- type: map_at_5
value: 65.362
- type: mrr_at_1
value: 88.90057864281957
- type: mrr_at_10
value: 91.53186397301344
- type: mrr_at_100
value: 91.62809075510003
- type: mrr_at_1000
value: 91.63198173030787
- type: mrr_at_20
value: 91.59414668799909
- type: mrr_at_3
value: 91.0792565316499
- type: mrr_at_5
value: 91.35718043135199
- type: nauc_map_at_1000_diff1
value: 12.364843957982409
- type: nauc_map_at_1000_max
value: 52.07043464458799
- type: nauc_map_at_1000_std
value: 16.040095055100494
- type: nauc_map_at_100_diff1
value: 12.370621073823022
- type: nauc_map_at_100_max
value: 51.960738727635636
- type: nauc_map_at_100_std
value: 15.935832440430747
- type: nauc_map_at_10_diff1
value: 16.852819486606585
- type: nauc_map_at_10_max
value: 40.11184760756059
- type: nauc_map_at_10_std
value: 0.9306648364102376
- type: nauc_map_at_1_diff1
value: 52.87356542654683
- type: nauc_map_at_1_max
value: -22.210039746171255
- type: nauc_map_at_1_std
value: -38.11345358035342
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value: 13.045089059562837
- type: nauc_map_at_20_max
value: 49.591383082160036
- type: nauc_map_at_20_std
value: 12.54330050352008
- type: nauc_map_at_3_diff1
value: 38.08172234377615
- type: nauc_map_at_3_max
value: -6.868621684867697
- type: nauc_map_at_3_std
value: -35.4712388845996
- type: nauc_map_at_5_diff1
value: 29.665551705577474
- type: nauc_map_at_5_max
value: 10.958628576519045
- type: nauc_map_at_5_std
value: -25.113120842097057
- type: nauc_mrr_at_1000_diff1
value: 47.39372999496945
- type: nauc_mrr_at_1000_max
value: 83.11274997493808
- type: nauc_mrr_at_1000_std
value: 39.74195374546631
- type: nauc_mrr_at_100_diff1
value: 47.396678946057676
- type: nauc_mrr_at_100_max
value: 83.1192584274415
- type: nauc_mrr_at_100_std
value: 39.75840860374685
- type: nauc_mrr_at_10_diff1
value: 47.35365644138715
- type: nauc_mrr_at_10_max
value: 83.189165639531
- type: nauc_mrr_at_10_std
value: 39.83653157887758
- type: nauc_mrr_at_1_diff1
value: 47.98740362820094
- type: nauc_mrr_at_1_max
value: 80.32340034580369
- type: nauc_mrr_at_1_std
value: 34.57857131423388
- type: nauc_mrr_at_20_diff1
value: 47.399132055537194
- type: nauc_mrr_at_20_max
value: 83.16329919869686
- type: nauc_mrr_at_20_std
value: 39.84204692042734
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value: 47.09295580511751
- type: nauc_mrr_at_3_max
value: 82.95831045602642
- type: nauc_mrr_at_3_std
value: 38.98036804692351
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value: 47.20100268549764
- type: nauc_mrr_at_5_max
value: 83.16652480381642
- type: nauc_mrr_at_5_std
value: 39.55690491560902
- type: nauc_ndcg_at_1000_diff1
value: 17.201962509184547
- type: nauc_ndcg_at_1000_max
value: 63.75820559259539
- type: nauc_ndcg_at_1000_std
value: 29.28676096486067
- type: nauc_ndcg_at_100_diff1
value: 16.76847216096811
- type: nauc_ndcg_at_100_max
value: 62.646517934470744
- type: nauc_ndcg_at_100_std
value: 28.7441617667637
- type: nauc_ndcg_at_10_diff1
value: 16.559511980751886
- type: nauc_ndcg_at_10_max
value: 54.35027464277944
- type: nauc_ndcg_at_10_std
value: 16.98089333577716
- type: nauc_ndcg_at_1_diff1
value: 47.98740362820094
- type: nauc_ndcg_at_1_max
value: 80.32340034580369
- type: nauc_ndcg_at_1_std
value: 34.57857131423388
- type: nauc_ndcg_at_20_diff1
value: 16.721525245428243
- type: nauc_ndcg_at_20_max
value: 57.683661870555724
- type: nauc_ndcg_at_20_std
value: 21.736044200026853
- type: nauc_ndcg_at_3_diff1
value: 12.488009696556192
- type: nauc_ndcg_at_3_max
value: 69.2365575305502
- type: nauc_ndcg_at_3_std
value: 30.622418945055323
- type: nauc_ndcg_at_5_diff1
value: 12.364114556230609
- type: nauc_ndcg_at_5_max
value: 62.33360746285387
- type: nauc_ndcg_at_5_std
value: 24.898000803570227
- type: nauc_precision_at_1000_diff1
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- type: nauc_precision_at_1000_max
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- type: nauc_precision_at_1000_std
value: 62.43036496029399
- type: nauc_precision_at_100_diff1
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- type: nauc_precision_at_100_max
value: 50.87010333741109
- type: nauc_precision_at_100_std
value: 63.418221030407175
- type: nauc_precision_at_10_diff1
value: -34.84255710936113
- type: nauc_precision_at_10_max
value: 56.588401051428825
- type: nauc_precision_at_10_std
value: 57.4763370653757
- type: nauc_precision_at_1_diff1
value: 47.98740362820094
- type: nauc_precision_at_1_max
value: 80.32340034580369
- type: nauc_precision_at_1_std
value: 34.57857131423388
- type: nauc_precision_at_20_diff1
value: -35.165762365233505
- type: nauc_precision_at_20_max
value: 54.148762449660424
- type: nauc_precision_at_20_std
value: 61.569719669368716
- type: nauc_precision_at_3_diff1
value: -28.63023175340299
- type: nauc_precision_at_3_max
value: 68.69825987618499
- type: nauc_precision_at_3_std
value: 48.15479495755423
- type: nauc_precision_at_5_diff1
value: -34.13811355456687
- type: nauc_precision_at_5_max
value: 62.369363941490604
- type: nauc_precision_at_5_std
value: 52.282904411187914
- type: nauc_recall_at_1000_diff1
value: 8.686444579162663
- type: nauc_recall_at_1000_max
value: 59.58864478011338
- type: nauc_recall_at_1000_std
value: 56.692774954297455
- type: nauc_recall_at_100_diff1
value: 8.820596225758342
- type: nauc_recall_at_100_max
value: 53.15048885657892
- type: nauc_recall_at_100_std
value: 39.78931159236714
- type: nauc_recall_at_10_diff1
value: 16.022301106315027
- type: nauc_recall_at_10_max
value: 29.83242342459543
- type: nauc_recall_at_10_std
value: -4.805965555875844
- type: nauc_recall_at_1_diff1
value: 52.87356542654683
- type: nauc_recall_at_1_max
value: -22.210039746171255
- type: nauc_recall_at_1_std
value: -38.11345358035342
- type: nauc_recall_at_20_diff1
value: 10.35772828627265
- type: nauc_recall_at_20_max
value: 43.06420839754062
- type: nauc_recall_at_20_std
value: 15.040522218235692
- type: nauc_recall_at_3_diff1
value: 36.23953684770224
- type: nauc_recall_at_3_max
value: -11.709269151700374
- type: nauc_recall_at_3_std
value: -38.13943178150384
- type: nauc_recall_at_5_diff1
value: 28.644872415763384
- type: nauc_recall_at_5_max
value: 2.062151266111129
- type: nauc_recall_at_5_std
value: -30.81114034774277
- type: ndcg_at_1
value: 88.901
- type: ndcg_at_10
value: 83.163
- type: ndcg_at_100
value: 86.854
- type: ndcg_at_1000
value: 87.602
- type: ndcg_at_20
value: 84.908
- type: ndcg_at_3
value: 84.848
- type: ndcg_at_5
value: 83.372
- type: precision_at_1
value: 88.901
- type: precision_at_10
value: 41.343
- type: precision_at_100
value: 4.957000000000001
- type: precision_at_1000
value: 0.513
- type: precision_at_20
value: 22.955000000000002
- type: precision_at_3
value: 74.29599999999999
- type: precision_at_5
value: 62.251999999999995
- type: recall_at_1
value: 26.875
- type: recall_at_10
value: 81.902
- type: recall_at_100
value: 93.988
- type: recall_at_1000
value: 97.801
- type: recall_at_20
value: 87.809
- type: recall_at_3
value: 54.869
- type: recall_at_5
value: 68.728
task:
type: Retrieval
- dataset:
config: default
name: MTEB TERRa (default)
revision: 7b58f24536063837d644aab9a023c62199b2a612
split: dev
type: ai-forever/terra-pairclassification
metrics:
- type: cosine_accuracy
value: 60.586319218241044
- type: cosine_accuracy_threshold
value: 82.49806761741638
- type: cosine_ap
value: 58.73198048427448
- type: cosine_f1
value: 67.37967914438502
- type: cosine_f1_threshold
value: 77.46461033821106
- type: cosine_precision
value: 57.01357466063348
- type: cosine_recall
value: 82.35294117647058
- type: dot_accuracy
value: 60.26058631921825
- type: dot_accuracy_threshold
value: 35627.020263671875
- type: dot_ap
value: 57.418783612898224
- type: dot_f1
value: 66.51982378854623
- type: dot_f1_threshold
value: 27620.843505859375
- type: dot_precision
value: 50.16611295681063
- type: dot_recall
value: 98.69281045751634
- type: euclidean_accuracy
value: 60.26058631921825
- type: euclidean_accuracy_threshold
value: 1255.4466247558594
- type: euclidean_ap
value: 58.748656145387955
- type: euclidean_f1
value: 66.99029126213591
- type: euclidean_f1_threshold
value: 1565.1330947875977
- type: euclidean_precision
value: 53.28185328185329
- type: euclidean_recall
value: 90.19607843137256
- type: main_score
value: 58.8479126365766
- type: manhattan_accuracy
value: 59.934853420195445
- type: manhattan_accuracy_threshold
value: 29897.271728515625
- type: manhattan_ap
value: 58.8479126365766
- type: manhattan_f1
value: 66.81318681318683
- type: manhattan_f1_threshold
value: 46291.802978515625
- type: manhattan_precision
value: 50.331125827814574
- type: manhattan_recall
value: 99.34640522875817
- type: max_accuracy
value: 60.586319218241044
- type: max_ap
value: 58.8479126365766
- type: max_f1
value: 67.37967914438502
- type: max_precision
value: 57.01357466063348
- type: max_recall
value: 99.34640522875817
- type: similarity_accuracy
value: 60.586319218241044
- type: similarity_accuracy_threshold
value: 82.49806761741638
- type: similarity_ap
value: 58.73198048427448
- type: similarity_f1
value: 67.37967914438502
- type: similarity_f1_threshold
value: 77.46461033821106
- type: similarity_precision
value: 57.01357466063348
- type: similarity_recall
value: 82.35294117647058
task:
type: PairClassification
- dataset:
config: default
name: MTEB TNews (default)
revision: 317f262bf1e6126357bbe89e875451e4b0938fe4
split: validation
type: C-MTEB/TNews-classification
metrics:
- type: accuracy
value: 45.967999999999996
- type: f1
value: 44.699306100915706
- type: f1_weighted
value: 46.03730319014832
- type: main_score
value: 45.967999999999996
task:
type: Classification
- dataset:
config: default
name: MTEB TRECCOVID (default)
revision: bb9466bac8153a0349341eb1b22e06409e78ef4e
split: test
type: mteb/trec-covid
metrics:
- type: map_at_1
value: 0.251
- type: map_at_10
value: 1.9480000000000002
- type: map_at_100
value: 11.082
- type: map_at_1000
value: 26.700000000000003
- type: map_at_20
value: 3.3529999999999998
- type: map_at_3
value: 0.679
- type: map_at_5
value: 1.079
- type: mrr_at_1
value: 94.0
- type: mrr_at_10
value: 95.786
- type: mrr_at_100
value: 95.786
- type: mrr_at_1000
value: 95.786
- type: mrr_at_20
value: 95.786
- type: mrr_at_3
value: 95.0
- type: mrr_at_5
value: 95.5
- type: ndcg_at_1
value: 91.0
- type: ndcg_at_10
value: 77.71900000000001
- type: ndcg_at_100
value: 57.726
- type: ndcg_at_1000
value: 52.737
- type: ndcg_at_20
value: 72.54
- type: ndcg_at_3
value: 83.397
- type: ndcg_at_5
value: 80.806
- type: precision_at_1
value: 94.0
- type: precision_at_10
value: 81.0
- type: precision_at_100
value: 59.199999999999996
- type: precision_at_1000
value: 23.244
- type: precision_at_20
value: 75.2
- type: precision_at_3
value: 88.0
- type: precision_at_5
value: 84.8
- type: recall_at_1
value: 0.251
- type: recall_at_10
value: 2.1229999999999998
- type: recall_at_100
value: 14.496999999999998
- type: recall_at_1000
value: 50.09
- type: recall_at_20
value: 3.8309999999999995
- type: recall_at_3
value: 0.696
- type: recall_at_5
value: 1.1400000000000001
- type: main_score
value: 77.71900000000001
task:
type: Retrieval
- dataset:
config: default
name: MTEB TenKGnadClusteringP2P (default)
revision: 5c59e41555244b7e45c9a6be2d720ab4bafae558
split: test
type: slvnwhrl/tenkgnad-clustering-p2p
metrics:
- type: main_score
value: 43.763609722295215
- type: v_measure
value: 43.763609722295215
- type: v_measure_std
value: 2.8751199473862457
task:
type: Clustering
- dataset:
config: default
name: MTEB TenKGnadClusteringS2S (default)
revision: 6cddbe003f12b9b140aec477b583ac4191f01786
split: test
type: slvnwhrl/tenkgnad-clustering-s2s
metrics:
- type: main_score
value: 39.762424448504355
- type: v_measure
value: 39.762424448504355
- type: v_measure_std
value: 3.30146124979502
task:
type: Clustering
- dataset:
config: default
name: MTEB ThuNewsClusteringP2P (default)
revision: 5798586b105c0434e4f0fe5e767abe619442cf93
split: test
type: C-MTEB/ThuNewsClusteringP2P
metrics:
- type: main_score
value: 63.133819258289456
- type: v_measure
value: 63.133819258289456
- type: v_measure_std
value: 1.8854253356479695
task:
type: Clustering
- dataset:
config: default
name: MTEB ThuNewsClusteringS2S (default)
revision: 8a8b2caeda43f39e13c4bc5bea0f8a667896e10d
split: test
type: C-MTEB/ThuNewsClusteringS2S
metrics:
- type: main_score
value: 58.98195851785808
- type: v_measure
value: 58.98195851785808
- type: v_measure_std
value: 1.6237600076393737
task:
type: Clustering
- dataset:
config: default
name: MTEB Touche2020 (default)
revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
split: test
type: mteb/touche2020
metrics:
- type: map_at_1
value: 3.3550000000000004
- type: map_at_10
value: 10.08
- type: map_at_100
value: 16.136
- type: map_at_1000
value: 17.605
- type: map_at_20
value: 12.561
- type: map_at_3
value: 5.641
- type: map_at_5
value: 7.3260000000000005
- type: mrr_at_1
value: 46.939
- type: mrr_at_10
value: 58.152
- type: mrr_at_100
value: 58.594
- type: mrr_at_1000
value: 58.601000000000006
- type: mrr_at_20
value: 58.279
- type: mrr_at_3
value: 55.102
- type: mrr_at_5
value: 56.531
- type: ndcg_at_1
value: 44.897999999999996
- type: ndcg_at_10
value: 26.298
- type: ndcg_at_100
value: 37.596000000000004
- type: ndcg_at_1000
value: 49.424
- type: ndcg_at_20
value: 27.066000000000003
- type: ndcg_at_3
value: 31.528
- type: ndcg_at_5
value: 28.219
- type: precision_at_1
value: 46.939
- type: precision_at_10
value: 22.245
- type: precision_at_100
value: 7.531000000000001
- type: precision_at_1000
value: 1.5350000000000001
- type: precision_at_20
value: 17.041
- type: precision_at_3
value: 30.612000000000002
- type: precision_at_5
value: 26.122
- type: recall_at_1
value: 3.3550000000000004
- type: recall_at_10
value: 16.41
- type: recall_at_100
value: 47.272
- type: recall_at_1000
value: 83.584
- type: recall_at_20
value: 24.091
- type: recall_at_3
value: 6.8180000000000005
- type: recall_at_5
value: 9.677
- type: main_score
value: 26.298
task:
type: Retrieval
- dataset:
config: default
name: MTEB ToxicConversationsClassification (default)
revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
split: test
type: mteb/toxic_conversations_50k
metrics:
- type: accuracy
value: 91.2890625
- type: ap
value: 33.95547153875715
- type: ap_weighted
value: 33.95547153875715
- type: f1
value: 75.10768597556462
- type: f1_weighted
value: 92.00161208992606
- type: main_score
value: 91.2890625
task:
type: Classification
- dataset:
config: default
name: MTEB TweetSentimentExtractionClassification (default)
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
split: test
type: mteb/tweet_sentiment_extraction
metrics:
- type: accuracy
value: 71.3978494623656
- type: f1
value: 71.7194818511814
- type: f1_weighted
value: 71.13860187349744
- type: main_score
value: 71.3978494623656
task:
type: Classification
- dataset:
config: default
name: MTEB TwentyNewsgroupsClustering (default)
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
split: test
type: mteb/twentynewsgroups-clustering
metrics:
- type: main_score
value: 52.4921688720602
- type: v_measure
value: 52.4921688720602
- type: v_measure_std
value: 0.992768152658908
task:
type: Clustering
- dataset:
config: default
name: MTEB TwitterSemEval2015 (default)
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
split: test
type: mteb/twittersemeval2015-pairclassification
metrics:
- type: cosine_accuracy
value: 85.11652858079513
- type: cosine_accuracy_threshold
value: 87.90839910507202
- type: cosine_ap
value: 70.90459908851724
- type: cosine_f1
value: 65.66581227877457
- type: cosine_f1_threshold
value: 85.13308763504028
- type: cosine_precision
value: 61.094708153531684
- type: cosine_recall
value: 70.97625329815304
- type: dot_accuracy
value: 83.41181379269239
- type: dot_accuracy_threshold
value: 43110.113525390625
- type: dot_ap
value: 65.64869491143095
- type: dot_f1
value: 62.05308447460914
- type: dot_f1_threshold
value: 41412.542724609375
- type: dot_precision
value: 57.38623626989464
- type: dot_recall
value: 67.54617414248021
- type: euclidean_accuracy
value: 85.15229182809799
- type: euclidean_accuracy_threshold
value: 1043.08500289917
- type: euclidean_ap
value: 70.71204383269375
- type: euclidean_f1
value: 65.20304568527919
- type: euclidean_f1_threshold
value: 1179.2595863342285
- type: euclidean_precision
value: 62.81173594132029
- type: euclidean_recall
value: 67.78364116094987
- type: main_score
value: 70.90459908851724
- type: manhattan_accuracy
value: 85.1820945341837
- type: manhattan_accuracy_threshold
value: 26115.0390625
- type: manhattan_ap
value: 70.66113937117431
- type: manhattan_f1
value: 65.33383628819313
- type: manhattan_f1_threshold
value: 29105.181884765625
- type: manhattan_precision
value: 62.40691808791736
- type: manhattan_recall
value: 68.54881266490766
- type: max_accuracy
value: 85.1820945341837
- type: max_ap
value: 70.90459908851724
- type: max_f1
value: 65.66581227877457
- type: max_precision
value: 62.81173594132029
- type: max_recall
value: 70.97625329815304
- type: similarity_accuracy
value: 85.11652858079513
- type: similarity_accuracy_threshold
value: 87.90839910507202
- type: similarity_ap
value: 70.90459908851724
- type: similarity_f1
value: 65.66581227877457
- type: similarity_f1_threshold
value: 85.13308763504028
- type: similarity_precision
value: 61.094708153531684
- type: similarity_recall
value: 70.97625329815304
task:
type: PairClassification
- dataset:
config: default
name: MTEB TwitterURLCorpus (default)
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
split: test
type: mteb/twitterurlcorpus-pairclassification
metrics:
- type: cosine_accuracy
value: 88.10299996119068
- type: cosine_accuracy_threshold
value: 84.34982895851135
- type: cosine_ap
value: 84.13755787769226
- type: cosine_f1
value: 76.0967548076923
- type: cosine_f1_threshold
value: 82.8936219215393
- type: cosine_precision
value: 74.28864769727193
- type: cosine_recall
value: 77.99507237449954
- type: dot_accuracy
value: 86.64182869561843
- type: dot_accuracy_threshold
value: 38794.677734375
- type: dot_ap
value: 80.20301567411457
- type: dot_f1
value: 73.50650291634967
- type: dot_f1_threshold
value: 37447.23205566406
- type: dot_precision
value: 69.41498460485802
- type: dot_recall
value: 78.11056359716662
- type: euclidean_accuracy
value: 87.9361198432103
- type: euclidean_accuracy_threshold
value: 1184.421157836914
- type: euclidean_ap
value: 83.79582690117218
- type: euclidean_f1
value: 75.81431709042175
- type: euclidean_f1_threshold
value: 1258.2727432250977
- type: euclidean_precision
value: 73.39099099099099
- type: euclidean_recall
value: 78.40314136125654
- type: main_score
value: 84.13755787769226
- type: manhattan_accuracy
value: 87.96134590755618
- type: manhattan_accuracy_threshold
value: 29077.291870117188
- type: manhattan_ap
value: 83.79487172269923
- type: manhattan_f1
value: 75.82421603424935
- type: manhattan_f1_threshold
value: 31224.124145507812
- type: manhattan_precision
value: 72.24740255212329
- type: manhattan_recall
value: 79.77363720357253
- type: max_accuracy
value: 88.10299996119068
- type: max_ap
value: 84.13755787769226
- type: max_f1
value: 76.0967548076923
- type: max_precision
value: 74.28864769727193
- type: max_recall
value: 79.77363720357253
- type: similarity_accuracy
value: 88.10299996119068
- type: similarity_accuracy_threshold
value: 84.34982895851135
- type: similarity_ap
value: 84.13755787769226
- type: similarity_f1
value: 76.0967548076923
- type: similarity_f1_threshold
value: 82.8936219215393
- type: similarity_precision
value: 74.28864769727193
- type: similarity_recall
value: 77.99507237449954
task:
type: PairClassification
- dataset:
config: default
name: MTEB VideoRetrieval (default)
revision: 58c2597a5943a2ba48f4668c3b90d796283c5639
split: dev
type: C-MTEB/VideoRetrieval
metrics:
- type: main_score
value: 70.433
- type: map_at_1
value: 55.7
- type: map_at_10
value: 66.013
- type: map_at_100
value: 66.534
- type: map_at_1000
value: 66.547
- type: map_at_20
value: 66.334
- type: map_at_3
value: 64.2
- type: map_at_5
value: 65.445
- type: mrr_at_1
value: 55.7
- type: mrr_at_10
value: 66.01329365079364
- type: mrr_at_100
value: 66.53350061744233
- type: mrr_at_1000
value: 66.54744831962995
- type: mrr_at_20
value: 66.3335147364675
- type: mrr_at_3
value: 64.2
- type: mrr_at_5
value: 65.44500000000002
- type: nauc_map_at_1000_diff1
value: 76.26428836976245
- type: nauc_map_at_1000_max
value: 35.41847367373575
- type: nauc_map_at_1000_std
value: -33.04639860831992
- type: nauc_map_at_100_diff1
value: 76.25793229023193
- type: nauc_map_at_100_max
value: 35.43663260110076
- type: nauc_map_at_100_std
value: -33.04238139882945
- type: nauc_map_at_10_diff1
value: 76.2108281297711
- type: nauc_map_at_10_max
value: 35.59442419423183
- type: nauc_map_at_10_std
value: -33.32346518997277
- type: nauc_map_at_1_diff1
value: 79.17728405262736
- type: nauc_map_at_1_max
value: 31.880738163589527
- type: nauc_map_at_1_std
value: -30.891888718004584
- type: nauc_map_at_20_diff1
value: 76.2181333410193
- type: nauc_map_at_20_max
value: 35.43448818430876
- type: nauc_map_at_20_std
value: -33.35682442863193
- type: nauc_map_at_3_diff1
value: 76.10046541433466
- type: nauc_map_at_3_max
value: 34.6831278555291
- type: nauc_map_at_3_std
value: -34.030826044831116
- type: nauc_map_at_5_diff1
value: 75.96513023582064
- type: nauc_map_at_5_max
value: 34.66920832438069
- type: nauc_map_at_5_std
value: -33.79799777830796
- type: nauc_mrr_at_1000_diff1
value: 76.26428836976245
- type: nauc_mrr_at_1000_max
value: 35.41847367373575
- type: nauc_mrr_at_1000_std
value: -33.04639860831992
- type: nauc_mrr_at_100_diff1
value: 76.25793229023193
- type: nauc_mrr_at_100_max
value: 35.43663260110076
- type: nauc_mrr_at_100_std
value: -33.04238139882945
- type: nauc_mrr_at_10_diff1
value: 76.2108281297711
- type: nauc_mrr_at_10_max
value: 35.59442419423183
- type: nauc_mrr_at_10_std
value: -33.32346518997277
- type: nauc_mrr_at_1_diff1
value: 79.17728405262736
- type: nauc_mrr_at_1_max
value: 31.880738163589527
- type: nauc_mrr_at_1_std
value: -30.891888718004584
- type: nauc_mrr_at_20_diff1
value: 76.2181333410193
- type: nauc_mrr_at_20_max
value: 35.43448818430876
- type: nauc_mrr_at_20_std
value: -33.35682442863193
- type: nauc_mrr_at_3_diff1
value: 76.10046541433466
- type: nauc_mrr_at_3_max
value: 34.6831278555291
- type: nauc_mrr_at_3_std
value: -34.030826044831116
- type: nauc_mrr_at_5_diff1
value: 75.96513023582064
- type: nauc_mrr_at_5_max
value: 34.66920832438069
- type: nauc_mrr_at_5_std
value: -33.79799777830796
- type: nauc_ndcg_at_1000_diff1
value: 75.68118206798317
- type: nauc_ndcg_at_1000_max
value: 37.12252980787349
- type: nauc_ndcg_at_1000_std
value: -31.457578337430505
- type: nauc_ndcg_at_100_diff1
value: 75.46730761564156
- type: nauc_ndcg_at_100_max
value: 37.549890025544265
- type: nauc_ndcg_at_100_std
value: -31.35066985945112
- type: nauc_ndcg_at_10_diff1
value: 75.09890404887037
- type: nauc_ndcg_at_10_max
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- type: nauc_ndcg_at_10_std
value: -33.67408368593356
- type: nauc_ndcg_at_1_diff1
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- type: nauc_ndcg_at_1_max
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- type: nauc_ndcg_at_1_std
value: -30.891888718004584
- type: nauc_ndcg_at_20_diff1
value: 75.12977548171354
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- type: nauc_ndcg_at_20_std
value: -33.771344674947485
- type: nauc_ndcg_at_3_diff1
value: 74.94037476984154
- type: nauc_ndcg_at_3_max
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- type: nauc_ndcg_at_3_std
value: -35.256991346321854
- type: nauc_ndcg_at_5_diff1
value: 74.54265907753783
- type: nauc_ndcg_at_5_max
value: 35.57662819978585
- type: nauc_ndcg_at_5_std
value: -34.879794448418465
- type: nauc_precision_at_1000_diff1
value: 74.52277207179142
- type: nauc_precision_at_1000_max
value: 94.25510945118707
- type: nauc_precision_at_1000_std
value: 91.6874157070222
- type: nauc_precision_at_100_diff1
value: 65.98346655735419
- type: nauc_precision_at_100_max
value: 78.81168727653687
- type: nauc_precision_at_100_std
value: 27.241465691967708
- type: nauc_precision_at_10_diff1
value: 69.55050319096688
- type: nauc_precision_at_10_max
value: 51.827749140893374
- type: nauc_precision_at_10_std
value: -34.60818605792837
- type: nauc_precision_at_1_diff1
value: 79.17728405262736
- type: nauc_precision_at_1_max
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- type: nauc_precision_at_1_std
value: -30.891888718004584
- type: nauc_precision_at_20_diff1
value: 68.08078305042736
- type: nauc_precision_at_20_max
value: 52.83318878288501
- type: nauc_precision_at_20_std
value: -35.46070292817927
- type: nauc_precision_at_3_diff1
value: 70.76249609881901
- type: nauc_precision_at_3_max
value: 38.86561868624655
- type: nauc_precision_at_3_std
value: -39.68917853446992
- type: nauc_precision_at_5_diff1
value: 68.39110629013278
- type: nauc_precision_at_5_max
value: 39.28677163904683
- type: nauc_precision_at_5_std
value: -39.39101423819562
- type: nauc_recall_at_1000_diff1
value: 74.52277207179175
- type: nauc_recall_at_1000_max
value: 94.25510945118776
- type: nauc_recall_at_1000_std
value: 91.68741570702382
- type: nauc_recall_at_100_diff1
value: 65.9834665573548
- type: nauc_recall_at_100_max
value: 78.81168727653679
- type: nauc_recall_at_100_std
value: 27.241465691967598
- type: nauc_recall_at_10_diff1
value: 69.55050319096708
- type: nauc_recall_at_10_max
value: 51.82774914089347
- type: nauc_recall_at_10_std
value: -34.6081860579283
- type: nauc_recall_at_1_diff1
value: 79.17728405262736
- type: nauc_recall_at_1_max
value: 31.880738163589527
- type: nauc_recall_at_1_std
value: -30.891888718004584
- type: nauc_recall_at_20_diff1
value: 68.08078305042746
- type: nauc_recall_at_20_max
value: 52.833188782885244
- type: nauc_recall_at_20_std
value: -35.46070292817895
- type: nauc_recall_at_3_diff1
value: 70.76249609881896
- type: nauc_recall_at_3_max
value: 38.865618686246464
- type: nauc_recall_at_3_std
value: -39.68917853446999
- type: nauc_recall_at_5_diff1
value: 68.39110629013274
- type: nauc_recall_at_5_max
value: 39.28677163904688
- type: nauc_recall_at_5_std
value: -39.39101423819562
- type: ndcg_at_1
value: 55.7
- type: ndcg_at_10
value: 70.433
- type: ndcg_at_100
value: 72.975
- type: ndcg_at_1000
value: 73.283
- type: ndcg_at_20
value: 71.58
- type: ndcg_at_3
value: 66.83099999999999
- type: ndcg_at_5
value: 69.085
- type: precision_at_1
value: 55.7
- type: precision_at_10
value: 8.4
- type: precision_at_100
value: 0.959
- type: precision_at_1000
value: 0.098
- type: precision_at_20
value: 4.425
- type: precision_at_3
value: 24.8
- type: precision_at_5
value: 15.98
- type: recall_at_1
value: 55.7
- type: recall_at_10
value: 84.0
- type: recall_at_100
value: 95.89999999999999
- type: recall_at_1000
value: 98.2
- type: recall_at_20
value: 88.5
- type: recall_at_3
value: 74.4
- type: recall_at_5
value: 79.9
task:
type: Retrieval
- dataset:
config: default
name: MTEB Waimai (default)
revision: 339287def212450dcaa9df8c22bf93e9980c7023
split: test
type: C-MTEB/waimai-classification
metrics:
- type: accuracy
value: 86.58999999999999
- type: ap
value: 70.02619249927523
- type: ap_weighted
value: 70.02619249927523
- type: f1
value: 84.97572770889423
- type: f1_weighted
value: 86.6865713531272
- type: main_score
value: 86.58999999999999
task:
type: Classification
- dataset:
config: en
name: MTEB XMarket (en)
revision: dfe57acff5b62c23732a7b7d3e3fb84ff501708b
split: test
type: jinaai/xmarket_ml
metrics:
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value: 34.772999999999996
- type: map_at_1
value: 7.2620000000000005
- type: map_at_10
value: 17.98
- type: map_at_100
value: 24.828
- type: map_at_1000
value: 26.633000000000003
- type: map_at_20
value: 20.699
- type: map_at_3
value: 12.383
- type: map_at_5
value: 14.871
- type: mrr_at_1
value: 34.718100890207715
- type: mrr_at_10
value: 43.9336827525092
- type: mrr_at_100
value: 44.66474011066837
- type: mrr_at_1000
value: 44.7075592197356
- type: mrr_at_20
value: 44.35984436569346
- type: mrr_at_3
value: 41.73901893981052
- type: mrr_at_5
value: 43.025973550207134
- type: nauc_map_at_1000_diff1
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value: 24.87925799401773
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value: -12.478790028708453
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revision: c99d599f0a6ab9b85b065da6f9d94f9cf731679f
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task:
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revision: c99d599f0a6ab9b85b065da6f9d94f9cf731679f
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- type: recall_at_10
value: 86.275
- type: recall_at_100
value: 98.017
- type: recall_at_1000
value: 99.8
- type: recall_at_20
value: 90.935
- type: recall_at_3
value: 70.167
- type: recall_at_5
value: 78.2
task:
type: Retrieval
---
The embedding model trained by Jina AI.
jina-embeddings-v3: Multilingual Embeddings With Task LoRA
## Quick Start
The easiest way to start using `jina-embeddings-v3` is with the [Jina Embedding API](https://jina.ai/embeddings/).
## Intended Usage & Model Info
`jina-embeddings-v3` is a **multilingual multi-task text embedding model** designed for a variety of NLP applications.
Based on the [Jina-XLM-RoBERTa architecture](https://huggingface.co/jinaai/xlm-roberta-flash-implementation),
this model supports Rotary Position Embeddings to handle long input sequences up to **8192 tokens**.
Additionally, it features 5 LoRA adapters to generate task-specific embeddings efficiently.
### Key Features:
- **Extended Sequence Length:** Supports up to 8192 tokens with RoPE.
- **Task-Specific Embedding:** Customize embeddings through the `task` argument with the following options:
- `retrieval.query`: Used for query embeddings in asymmetric retrieval tasks
- `retrieval.passage`: Used for passage embeddings in asymmetric retrieval tasks
- `separation`: Used for embeddings in clustering and re-ranking applications
- `classification`: Used for embeddings in classification tasks
- `text-matching`: Used for embeddings in tasks that quantify similarity between two texts, such as STS or symmetric retrieval tasks
- **Matryoshka Embeddings**: Supports flexible embedding sizes (`32, 64, 128, 256, 512, 768, 1024`), allowing for truncating embeddings to fit your application.
### Supported Languages:
While the foundation model supports 100 languages, we've focused our tuning efforts on the following 30 languages:
**Arabic, Bengali, Chinese, Danish, Dutch, English, Finnish, French, Georgian, German, Greek,
Hindi, Indonesian, Italian, Japanese, Korean, Latvian, Norwegian, Polish, Portuguese, Romanian,
Russian, Slovak, Spanish, Swedish, Thai, Turkish, Ukrainian, Urdu,** and **Vietnamese.**
## Usage
**Apply mean pooling when integrating the model.
**
### Why Use Mean Pooling?
Mean pooling takes all token embeddings from the model's output and averages them at the sentence or paragraph level.
This approach has been shown to produce high-quality sentence embeddings.
We provide an `encode` function that handles this for you automatically.
However, if you're working with the model directly, outside of the `encode` function,
you'll need to apply mean pooling manually. Here's how you can do it:
```python
import torch
import torch.nn.functional as F
from transformers import AutoTokenizer, AutoModel
def mean_pooling(model_output, attention_mask):
token_embeddings = model_output[0]
input_mask_expanded = (
attention_mask.unsqueeze(-1).expand(token_embeddings.size()).float()
)
return torch.sum(token_embeddings * input_mask_expanded, 1) / torch.clamp(
input_mask_expanded.sum(1), min=1e-9
)
sentences = ["How is the weather today?", "What is the current weather like today?"]
tokenizer = AutoTokenizer.from_pretrained("jinaai/jina-embeddings-v3")
model = AutoModel.from_pretrained("jinaai/jina-embeddings-v3", trust_remote_code=True)
encoded_input = tokenizer(sentences, padding=True, truncation=True, return_tensors="pt")
task = 'retrieval.query'
task_id = model._adaptation_map[task]
adapter_mask = torch.full((len(sentences),), task_id, dtype=torch.int32)
with torch.no_grad():
model_output = model(**encoded_input, adapter_mask=adapter_mask)
embeddings = mean_pooling(model_output, encoded_input["attention_mask"])
embeddings = F.normalize(embeddings, p=2, dim=1)
```
ONNX Inference.
**
You can use ONNX for efficient inference with `jina-embeddings-v3`:
```python
import onnxruntime
import numpy as np
from transformers import AutoTokenizer, PretrainedConfig
# Load tokenizer and model config
tokenizer = AutoTokenizer.from_pretrained('jinaai/jina-embeddings-v3')
config = PretrainedConfig.from_pretrained('jinaai/jina-embeddings-v3')
# Tokenize input
input_text = tokenizer('sample text', return_tensors='np')
# ONNX session
model_path = 'jina-embeddings-v3/onnx/model.onnx'
session = onnxruntime.InferenceSession(model_path)
# Prepare inputs for ONNX model
task_type = 'text-matching'
task_id = np.array(config.lora_adaptations.index(task_type), dtype=np.int64)
inputs = {
'input_ids': input_text['input_ids'],
'attention_mask': input_text['attention_mask'],
'task_id': task_id
}
# Run model
outputs = session.run(None, inputs)
```