metadata
tags:
- mteb
model-index:
- name: xlm3b5_step3len260_b128g8_lr1e-5
results:
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en)
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
- type: accuracy
value: 69.01492537313432
- type: ap
value: 30.936372983952477
- type: f1
value: 62.58864357716914
- task:
type: Classification
dataset:
type: mteb/amazon_polarity
name: MTEB AmazonPolarityClassification
config: default
split: test
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
metrics:
- type: accuracy
value: 95.088975
- type: ap
value: 92.9329025853096
- type: f1
value: 95.0864056657106
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (en)
config: en
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy
value: 50.524
- type: f1
value: 49.93715365750685
- task:
type: Retrieval
dataset:
type: arguana
name: MTEB ArguAna
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 17.781
- type: map_at_10
value: 30.854
- type: map_at_100
value: 32.344
- type: map_at_1000
value: 32.364
- type: map_at_3
value: 25.711000000000002
- type: map_at_5
value: 28.254
- type: mrr_at_1
value: 18.563
- type: mrr_at_10
value: 31.137999999999998
- type: mrr_at_100
value: 32.621
- type: mrr_at_1000
value: 32.641
- type: mrr_at_3
value: 25.984
- type: mrr_at_5
value: 28.53
- type: ndcg_at_1
value: 17.781
- type: ndcg_at_10
value: 39.206
- type: ndcg_at_100
value: 45.751
- type: ndcg_at_1000
value: 46.225
- type: ndcg_at_3
value: 28.313
- type: ndcg_at_5
value: 32.919
- type: precision_at_1
value: 17.781
- type: precision_at_10
value: 6.65
- type: precision_at_100
value: 0.9560000000000001
- type: precision_at_1000
value: 0.099
- type: precision_at_3
value: 11.949
- type: precision_at_5
value: 9.417
- type: recall_at_1
value: 17.781
- type: recall_at_10
value: 66.501
- type: recall_at_100
value: 95.59
- type: recall_at_1000
value: 99.21799999999999
- type: recall_at_3
value: 35.846000000000004
- type: recall_at_5
value: 47.083999999999996
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-p2p
name: MTEB ArxivClusteringP2P
config: default
split: test
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
metrics:
- type: v_measure
value: 44.44154312957711
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-s2s
name: MTEB ArxivClusteringS2S
config: default
split: test
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
metrics:
- type: v_measure
value: 34.189712542346385
- task:
type: Reranking
dataset:
type: mteb/askubuntudupquestions-reranking
name: MTEB AskUbuntuDupQuestions
config: default
split: test
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
metrics:
- type: map
value: 62.72571219134687
- type: mrr
value: 76.3612979817966
- task:
type: STS
dataset:
type: mteb/biosses-sts
name: MTEB BIOSSES
config: default
split: test
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
metrics:
- type: cos_sim_pearson
value: 83.62762841254953
- type: cos_sim_spearman
value: 80.72111639383013
- type: euclidean_pearson
value: 82.63506732956259
- type: euclidean_spearman
value: 81.177753304636
- type: manhattan_pearson
value: 82.5891836637346
- type: manhattan_spearman
value: 81.06811225217339
- task:
type: Classification
dataset:
type: mteb/banking77
name: MTEB Banking77Classification
config: default
split: test
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
metrics:
- type: accuracy
value: 1.422077922077922
- type: f1
value: 0.06502366027548179
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-p2p
name: MTEB BiorxivClusteringP2P
config: default
split: test
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
metrics:
- type: v_measure
value: 37.82441952130262
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-s2s
name: MTEB BiorxivClusteringS2S
config: default
split: test
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
metrics:
- type: v_measure
value: 32.132057843418416
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackAndroidRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 34.23
- type: map_at_10
value: 46.763
- type: map_at_100
value: 48.454
- type: map_at_1000
value: 48.58
- type: map_at_3
value: 43.167
- type: map_at_5
value: 45.214
- type: mrr_at_1
value: 42.775
- type: mrr_at_10
value: 53.190000000000005
- type: mrr_at_100
value: 53.928
- type: mrr_at_1000
value: 53.964
- type: mrr_at_3
value: 51.168
- type: mrr_at_5
value: 52.434000000000005
- type: ndcg_at_1
value: 42.775
- type: ndcg_at_10
value: 53.376999999999995
- type: ndcg_at_100
value: 58.748
- type: ndcg_at_1000
value: 60.461
- type: ndcg_at_3
value: 48.929
- type: ndcg_at_5
value: 50.99399999999999
- type: precision_at_1
value: 42.775
- type: precision_at_10
value: 10.428999999999998
- type: precision_at_100
value: 1.678
- type: precision_at_1000
value: 0.215
- type: precision_at_3
value: 23.939
- type: precision_at_5
value: 17.082
- type: recall_at_1
value: 34.23
- type: recall_at_10
value: 64.96300000000001
- type: recall_at_100
value: 86.803
- type: recall_at_1000
value: 97.917
- type: recall_at_3
value: 51.815
- type: recall_at_5
value: 57.781000000000006
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackEnglishRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 28.935
- type: map_at_10
value: 39.574999999999996
- type: map_at_100
value: 40.891
- type: map_at_1000
value: 41.043
- type: map_at_3
value: 36.248999999999995
- type: map_at_5
value: 38.157999999999994
- type: mrr_at_1
value: 36.624
- type: mrr_at_10
value: 45.241
- type: mrr_at_100
value: 46.028000000000006
- type: mrr_at_1000
value: 46.082
- type: mrr_at_3
value: 42.93
- type: mrr_at_5
value: 44.417
- type: ndcg_at_1
value: 36.624
- type: ndcg_at_10
value: 45.423
- type: ndcg_at_100
value: 49.971
- type: ndcg_at_1000
value: 52.382
- type: ndcg_at_3
value: 41.019
- type: ndcg_at_5
value: 43.254
- type: precision_at_1
value: 36.624
- type: precision_at_10
value: 8.86
- type: precision_at_100
value: 1.458
- type: precision_at_1000
value: 0.198
- type: precision_at_3
value: 20.276
- type: precision_at_5
value: 14.573
- type: recall_at_1
value: 28.935
- type: recall_at_10
value: 55.745999999999995
- type: recall_at_100
value: 74.977
- type: recall_at_1000
value: 90.505
- type: recall_at_3
value: 42.575
- type: recall_at_5
value: 48.902
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackGamingRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 38.828
- type: map_at_10
value: 50.888999999999996
- type: map_at_100
value: 52.001
- type: map_at_1000
value: 52.054
- type: map_at_3
value: 47.638999999999996
- type: map_at_5
value: 49.423
- type: mrr_at_1
value: 44.765
- type: mrr_at_10
value: 54.408
- type: mrr_at_100
value: 55.116
- type: mrr_at_1000
value: 55.144000000000005
- type: mrr_at_3
value: 52.038
- type: mrr_at_5
value: 53.323
- type: ndcg_at_1
value: 44.765
- type: ndcg_at_10
value: 56.724
- type: ndcg_at_100
value: 61.058
- type: ndcg_at_1000
value: 62.125
- type: ndcg_at_3
value: 51.324000000000005
- type: ndcg_at_5
value: 53.805
- type: precision_at_1
value: 44.765
- type: precision_at_10
value: 9.248000000000001
- type: precision_at_100
value: 1.234
- type: precision_at_1000
value: 0.136
- type: precision_at_3
value: 23.093
- type: precision_at_5
value: 15.799
- type: recall_at_1
value: 38.828
- type: recall_at_10
value: 70.493
- type: recall_at_100
value: 89.293
- type: recall_at_1000
value: 96.872
- type: recall_at_3
value: 55.74400000000001
- type: recall_at_5
value: 61.95
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackGisRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 22.085
- type: map_at_10
value: 30.070000000000004
- type: map_at_100
value: 31.206
- type: map_at_1000
value: 31.291999999999998
- type: map_at_3
value: 27.011000000000003
- type: map_at_5
value: 28.854999999999997
- type: mrr_at_1
value: 23.842
- type: mrr_at_10
value: 31.755
- type: mrr_at_100
value: 32.778
- type: mrr_at_1000
value: 32.845
- type: mrr_at_3
value: 28.851
- type: mrr_at_5
value: 30.574
- type: ndcg_at_1
value: 23.842
- type: ndcg_at_10
value: 35.052
- type: ndcg_at_100
value: 40.550999999999995
- type: ndcg_at_1000
value: 42.789
- type: ndcg_at_3
value: 29.096
- type: ndcg_at_5
value: 32.251000000000005
- type: precision_at_1
value: 23.842
- type: precision_at_10
value: 5.605
- type: precision_at_100
value: 0.877
- type: precision_at_1000
value: 0.11100000000000002
- type: precision_at_3
value: 12.316
- type: precision_at_5
value: 9.13
- type: recall_at_1
value: 22.085
- type: recall_at_10
value: 48.815999999999995
- type: recall_at_100
value: 74.039
- type: recall_at_1000
value: 90.872
- type: recall_at_3
value: 33.098
- type: recall_at_5
value: 40.647
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackMathematicaRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 14.088999999999999
- type: map_at_10
value: 21.526
- type: map_at_100
value: 22.832
- type: map_at_1000
value: 22.958000000000002
- type: map_at_3
value: 18.747
- type: map_at_5
value: 20.396
- type: mrr_at_1
value: 17.662
- type: mrr_at_10
value: 25.513
- type: mrr_at_100
value: 26.621
- type: mrr_at_1000
value: 26.698
- type: mrr_at_3
value: 22.658
- type: mrr_at_5
value: 24.449
- type: ndcg_at_1
value: 17.662
- type: ndcg_at_10
value: 26.506999999999998
- type: ndcg_at_100
value: 32.782
- type: ndcg_at_1000
value: 35.709999999999994
- type: ndcg_at_3
value: 21.279
- type: ndcg_at_5
value: 23.998
- type: precision_at_1
value: 17.662
- type: precision_at_10
value: 5.124
- type: precision_at_100
value: 0.951
- type: precision_at_1000
value: 0.133
- type: precision_at_3
value: 10.323
- type: precision_at_5
value: 8.158999999999999
- type: recall_at_1
value: 14.088999999999999
- type: recall_at_10
value: 37.874
- type: recall_at_100
value: 65.34100000000001
- type: recall_at_1000
value: 86.06099999999999
- type: recall_at_3
value: 23.738999999999997
- type: recall_at_5
value: 30.359
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackPhysicsRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 24.75
- type: map_at_10
value: 34.156
- type: map_at_100
value: 35.638999999999996
- type: map_at_1000
value: 35.754999999999995
- type: map_at_3
value: 31.047000000000004
- type: map_at_5
value: 32.823
- type: mrr_at_1
value: 30.991000000000003
- type: mrr_at_10
value: 39.509
- type: mrr_at_100
value: 40.582
- type: mrr_at_1000
value: 40.636
- type: mrr_at_3
value: 37.103
- type: mrr_at_5
value: 38.503
- type: ndcg_at_1
value: 30.991000000000003
- type: ndcg_at_10
value: 39.719
- type: ndcg_at_100
value: 45.984
- type: ndcg_at_1000
value: 48.293
- type: ndcg_at_3
value: 34.92
- type: ndcg_at_5
value: 37.253
- type: precision_at_1
value: 30.991000000000003
- type: precision_at_10
value: 7.3340000000000005
- type: precision_at_100
value: 1.225
- type: precision_at_1000
value: 0.16
- type: precision_at_3
value: 16.586000000000002
- type: precision_at_5
value: 12.127
- type: recall_at_1
value: 24.75
- type: recall_at_10
value: 51.113
- type: recall_at_100
value: 77.338
- type: recall_at_1000
value: 92.764
- type: recall_at_3
value: 37.338
- type: recall_at_5
value: 43.437
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackProgrammersRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 23.158
- type: map_at_10
value: 32.877
- type: map_at_100
value: 34.226
- type: map_at_1000
value: 34.35
- type: map_at_3
value: 29.43
- type: map_at_5
value: 31.319000000000003
- type: mrr_at_1
value: 29.224
- type: mrr_at_10
value: 38.080000000000005
- type: mrr_at_100
value: 39.04
- type: mrr_at_1000
value: 39.097
- type: mrr_at_3
value: 35.407
- type: mrr_at_5
value: 36.771
- type: ndcg_at_1
value: 29.224
- type: ndcg_at_10
value: 38.805
- type: ndcg_at_100
value: 44.746
- type: ndcg_at_1000
value: 47.038000000000004
- type: ndcg_at_3
value: 33.269
- type: ndcg_at_5
value: 35.611
- type: precision_at_1
value: 29.224
- type: precision_at_10
value: 7.454
- type: precision_at_100
value: 1.221
- type: precision_at_1000
value: 0.16199999999999998
- type: precision_at_3
value: 16.134
- type: precision_at_5
value: 11.895
- type: recall_at_1
value: 23.158
- type: recall_at_10
value: 51.487
- type: recall_at_100
value: 77.464
- type: recall_at_1000
value: 92.525
- type: recall_at_3
value: 35.478
- type: recall_at_5
value: 41.722
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 24.456916666666668
- type: map_at_10
value: 33.5495
- type: map_at_100
value: 34.86808333333333
- type: map_at_1000
value: 34.98908333333333
- type: map_at_3
value: 30.59158333333334
- type: map_at_5
value: 32.24916666666667
- type: mrr_at_1
value: 29.387250000000005
- type: mrr_at_10
value: 37.73958333333333
- type: mrr_at_100
value: 38.6595
- type: mrr_at_1000
value: 38.718250000000005
- type: mrr_at_3
value: 35.31658333333333
- type: mrr_at_5
value: 36.69441666666667
- type: ndcg_at_1
value: 29.387250000000005
- type: ndcg_at_10
value: 38.910333333333334
- type: ndcg_at_100
value: 44.40241666666666
- type: ndcg_at_1000
value: 46.72008333333334
- type: ndcg_at_3
value: 34.045583333333326
- type: ndcg_at_5
value: 36.33725
- type: precision_at_1
value: 29.387250000000005
- type: precision_at_10
value: 7.034666666666668
- type: precision_at_100
value: 1.1698333333333333
- type: precision_at_1000
value: 0.15599999999999997
- type: precision_at_3
value: 15.866416666666666
- type: precision_at_5
value: 11.456333333333331
- type: recall_at_1
value: 24.456916666666668
- type: recall_at_10
value: 50.47758333333333
- type: recall_at_100
value: 74.52275
- type: recall_at_1000
value: 90.7105
- type: recall_at_3
value: 36.86275
- type: recall_at_5
value: 42.76533333333333
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackStatsRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 19.356
- type: map_at_10
value: 25.378
- type: map_at_100
value: 26.349
- type: map_at_1000
value: 26.451
- type: map_at_3
value: 23.403
- type: map_at_5
value: 24.614
- type: mrr_at_1
value: 22.086
- type: mrr_at_10
value: 28.072000000000003
- type: mrr_at_100
value: 28.887
- type: mrr_at_1000
value: 28.965999999999998
- type: mrr_at_3
value: 26.074
- type: mrr_at_5
value: 27.293
- type: ndcg_at_1
value: 22.086
- type: ndcg_at_10
value: 29.107
- type: ndcg_at_100
value: 34
- type: ndcg_at_1000
value: 36.793
- type: ndcg_at_3
value: 25.407999999999998
- type: ndcg_at_5
value: 27.375
- type: precision_at_1
value: 22.086
- type: precision_at_10
value: 4.678
- type: precision_at_100
value: 0.7779999999999999
- type: precision_at_1000
value: 0.11
- type: precision_at_3
value: 10.992
- type: precision_at_5
value: 7.853000000000001
- type: recall_at_1
value: 19.356
- type: recall_at_10
value: 37.913999999999994
- type: recall_at_100
value: 60.507999999999996
- type: recall_at_1000
value: 81.459
- type: recall_at_3
value: 27.874
- type: recall_at_5
value: 32.688
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackTexRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 16.008
- type: map_at_10
value: 22.431
- type: map_at_100
value: 23.61
- type: map_at_1000
value: 23.743
- type: map_at_3
value: 20.358
- type: map_at_5
value: 21.371000000000002
- type: mrr_at_1
value: 19.752
- type: mrr_at_10
value: 26.333000000000002
- type: mrr_at_100
value: 27.297
- type: mrr_at_1000
value: 27.378000000000004
- type: mrr_at_3
value: 24.358
- type: mrr_at_5
value: 25.354
- type: ndcg_at_1
value: 19.752
- type: ndcg_at_10
value: 26.712000000000003
- type: ndcg_at_100
value: 32.294
- type: ndcg_at_1000
value: 35.410000000000004
- type: ndcg_at_3
value: 22.974
- type: ndcg_at_5
value: 24.412
- type: precision_at_1
value: 19.752
- type: precision_at_10
value: 4.986
- type: precision_at_100
value: 0.924
- type: precision_at_1000
value: 0.13699999999999998
- type: precision_at_3
value: 10.966
- type: precision_at_5
value: 7.832
- type: recall_at_1
value: 16.008
- type: recall_at_10
value: 35.716
- type: recall_at_100
value: 60.76200000000001
- type: recall_at_1000
value: 83.204
- type: recall_at_3
value: 25.092
- type: recall_at_5
value: 28.858
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackUnixRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 24.743000000000002
- type: map_at_10
value: 34.492
- type: map_at_100
value: 35.716
- type: map_at_1000
value: 35.815999999999995
- type: map_at_3
value: 31.201
- type: map_at_5
value: 32.926
- type: mrr_at_1
value: 29.384
- type: mrr_at_10
value: 38.333
- type: mrr_at_100
value: 39.278
- type: mrr_at_1000
value: 39.330999999999996
- type: mrr_at_3
value: 35.65
- type: mrr_at_5
value: 36.947
- type: ndcg_at_1
value: 29.384
- type: ndcg_at_10
value: 40.195
- type: ndcg_at_100
value: 45.686
- type: ndcg_at_1000
value: 47.906
- type: ndcg_at_3
value: 34.477000000000004
- type: ndcg_at_5
value: 36.89
- type: precision_at_1
value: 29.384
- type: precision_at_10
value: 7.164
- type: precision_at_100
value: 1.111
- type: precision_at_1000
value: 0.13999999999999999
- type: precision_at_3
value: 15.983
- type: precision_at_5
value: 11.418000000000001
- type: recall_at_1
value: 24.743000000000002
- type: recall_at_10
value: 53.602000000000004
- type: recall_at_100
value: 77.266
- type: recall_at_1000
value: 92.857
- type: recall_at_3
value: 37.921
- type: recall_at_5
value: 44.124
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackWebmastersRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 26.531
- type: map_at_10
value: 35.933
- type: map_at_100
value: 37.913000000000004
- type: map_at_1000
value: 38.146
- type: map_at_3
value: 32.713
- type: map_at_5
value: 34.339999999999996
- type: mrr_at_1
value: 32.806000000000004
- type: mrr_at_10
value: 41.728
- type: mrr_at_100
value: 42.731
- type: mrr_at_1000
value: 42.777
- type: mrr_at_3
value: 39.065
- type: mrr_at_5
value: 40.467999999999996
- type: ndcg_at_1
value: 32.806000000000004
- type: ndcg_at_10
value: 42.254999999999995
- type: ndcg_at_100
value: 48.687999999999995
- type: ndcg_at_1000
value: 50.784
- type: ndcg_at_3
value: 37.330999999999996
- type: ndcg_at_5
value: 39.305
- type: precision_at_1
value: 32.806000000000004
- type: precision_at_10
value: 8.34
- type: precision_at_100
value: 1.7209999999999999
- type: precision_at_1000
value: 0.252
- type: precision_at_3
value: 17.589
- type: precision_at_5
value: 12.845999999999998
- type: recall_at_1
value: 26.531
- type: recall_at_10
value: 53.266000000000005
- type: recall_at_100
value: 81.49499999999999
- type: recall_at_1000
value: 94.506
- type: recall_at_3
value: 38.848
- type: recall_at_5
value: 44.263000000000005
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackWordpressRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 20.77
- type: map_at_10
value: 28.504
- type: map_at_100
value: 29.580000000000002
- type: map_at_1000
value: 29.681
- type: map_at_3
value: 26.134
- type: map_at_5
value: 27.551
- type: mrr_at_1
value: 22.736
- type: mrr_at_10
value: 30.713
- type: mrr_at_100
value: 31.628
- type: mrr_at_1000
value: 31.701
- type: mrr_at_3
value: 28.497
- type: mrr_at_5
value: 29.799999999999997
- type: ndcg_at_1
value: 22.736
- type: ndcg_at_10
value: 33.048
- type: ndcg_at_100
value: 38.321
- type: ndcg_at_1000
value: 40.949999999999996
- type: ndcg_at_3
value: 28.521
- type: ndcg_at_5
value: 30.898999999999997
- type: precision_at_1
value: 22.736
- type: precision_at_10
value: 5.194
- type: precision_at_100
value: 0.86
- type: precision_at_1000
value: 0.11800000000000001
- type: precision_at_3
value: 12.2
- type: precision_at_5
value: 8.762
- type: recall_at_1
value: 20.77
- type: recall_at_10
value: 44.741
- type: recall_at_100
value: 68.987
- type: recall_at_1000
value: 88.984
- type: recall_at_3
value: 32.830999999999996
- type: recall_at_5
value: 38.452999999999996
- task:
type: Retrieval
dataset:
type: climate-fever
name: MTEB ClimateFEVER
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 9.646
- type: map_at_10
value: 17.432
- type: map_at_100
value: 19.347
- type: map_at_1000
value: 19.555
- type: map_at_3
value: 14.355
- type: map_at_5
value: 15.83
- type: mrr_at_1
value: 21.433
- type: mrr_at_10
value: 32.583
- type: mrr_at_100
value: 33.708
- type: mrr_at_1000
value: 33.751999999999995
- type: mrr_at_3
value: 28.979
- type: mrr_at_5
value: 30.979
- type: ndcg_at_1
value: 21.433
- type: ndcg_at_10
value: 25.025
- type: ndcg_at_100
value: 32.818999999999996
- type: ndcg_at_1000
value: 36.549
- type: ndcg_at_3
value: 19.689
- type: ndcg_at_5
value: 21.462
- type: precision_at_1
value: 21.433
- type: precision_at_10
value: 8.085
- type: precision_at_100
value: 1.6340000000000001
- type: precision_at_1000
value: 0.233
- type: precision_at_3
value: 14.832
- type: precision_at_5
value: 11.530999999999999
- type: recall_at_1
value: 9.646
- type: recall_at_10
value: 31.442999999999998
- type: recall_at_100
value: 58.48
- type: recall_at_1000
value: 79.253
- type: recall_at_3
value: 18.545
- type: recall_at_5
value: 23.362
- task:
type: Retrieval
dataset:
type: dbpedia-entity
name: MTEB DBPedia
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 8.48
- type: map_at_10
value: 18.127
- type: map_at_100
value: 25.563999999999997
- type: map_at_1000
value: 27.386
- type: map_at_3
value: 13.189
- type: map_at_5
value: 15.417
- type: mrr_at_1
value: 63.74999999999999
- type: mrr_at_10
value: 71.34899999999999
- type: mrr_at_100
value: 71.842
- type: mrr_at_1000
value: 71.851
- type: mrr_at_3
value: 69.167
- type: mrr_at_5
value: 70.479
- type: ndcg_at_1
value: 51.87500000000001
- type: ndcg_at_10
value: 38.792
- type: ndcg_at_100
value: 43.889
- type: ndcg_at_1000
value: 51.561
- type: ndcg_at_3
value: 42.686
- type: ndcg_at_5
value: 40.722
- type: precision_at_1
value: 63.74999999999999
- type: precision_at_10
value: 30.375000000000004
- type: precision_at_100
value: 10.103
- type: precision_at_1000
value: 2.257
- type: precision_at_3
value: 45.167
- type: precision_at_5
value: 38.95
- type: recall_at_1
value: 8.48
- type: recall_at_10
value: 23.008
- type: recall_at_100
value: 48.875
- type: recall_at_1000
value: 73.402
- type: recall_at_3
value: 14.377
- type: recall_at_5
value: 17.819
- task:
type: Classification
dataset:
type: mteb/emotion
name: MTEB EmotionClassification
config: default
split: test
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
metrics:
- type: accuracy
value: 47.605
- type: f1
value: 42.345081371303316
- task:
type: Retrieval
dataset:
type: fever
name: MTEB FEVER
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 62.247
- type: map_at_10
value: 72.782
- type: map_at_100
value: 73.095
- type: map_at_1000
value: 73.112
- type: map_at_3
value: 70.928
- type: map_at_5
value: 72.173
- type: mrr_at_1
value: 67.372
- type: mrr_at_10
value: 77.538
- type: mrr_at_100
value: 77.741
- type: mrr_at_1000
value: 77.74600000000001
- type: mrr_at_3
value: 75.938
- type: mrr_at_5
value: 77.054
- type: ndcg_at_1
value: 67.372
- type: ndcg_at_10
value: 78.001
- type: ndcg_at_100
value: 79.295
- type: ndcg_at_1000
value: 79.648
- type: ndcg_at_3
value: 74.71
- type: ndcg_at_5
value: 76.712
- type: precision_at_1
value: 67.372
- type: precision_at_10
value: 9.844999999999999
- type: precision_at_100
value: 1.065
- type: precision_at_1000
value: 0.11100000000000002
- type: precision_at_3
value: 29.308
- type: precision_at_5
value: 18.731
- type: recall_at_1
value: 62.247
- type: recall_at_10
value: 89.453
- type: recall_at_100
value: 94.998
- type: recall_at_1000
value: 97.385
- type: recall_at_3
value: 80.563
- type: recall_at_5
value: 85.58099999999999
- task:
type: Retrieval
dataset:
type: fiqa
name: MTEB FiQA2018
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 22.587
- type: map_at_10
value: 37.316
- type: map_at_100
value: 39.542
- type: map_at_1000
value: 39.701
- type: map_at_3
value: 32.332
- type: map_at_5
value: 35.172
- type: mrr_at_1
value: 42.437999999999995
- type: mrr_at_10
value: 51.98500000000001
- type: mrr_at_100
value: 52.910999999999994
- type: mrr_at_1000
value: 52.944
- type: mrr_at_3
value: 49.691
- type: mrr_at_5
value: 51.15
- type: ndcg_at_1
value: 42.437999999999995
- type: ndcg_at_10
value: 45.016
- type: ndcg_at_100
value: 52.541000000000004
- type: ndcg_at_1000
value: 54.99699999999999
- type: ndcg_at_3
value: 41.175
- type: ndcg_at_5
value: 42.647
- type: precision_at_1
value: 42.437999999999995
- type: precision_at_10
value: 12.855
- type: precision_at_100
value: 2.049
- type: precision_at_1000
value: 0.247
- type: precision_at_3
value: 27.675
- type: precision_at_5
value: 20.617
- type: recall_at_1
value: 22.587
- type: recall_at_10
value: 51.547
- type: recall_at_100
value: 78.88
- type: recall_at_1000
value: 93.741
- type: recall_at_3
value: 37.256
- type: recall_at_5
value: 44.295
- task:
type: Retrieval
dataset:
type: hotpotqa
name: MTEB HotpotQA
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 32.451
- type: map_at_10
value: 48.082
- type: map_at_100
value: 49.08
- type: map_at_1000
value: 49.163000000000004
- type: map_at_3
value: 44.766
- type: map_at_5
value: 46.722
- type: mrr_at_1
value: 64.902
- type: mrr_at_10
value: 72.195
- type: mrr_at_100
value: 72.572
- type: mrr_at_1000
value: 72.589
- type: mrr_at_3
value: 70.774
- type: mrr_at_5
value: 71.611
- type: ndcg_at_1
value: 64.902
- type: ndcg_at_10
value: 57.14399999999999
- type: ndcg_at_100
value: 60.916000000000004
- type: ndcg_at_1000
value: 62.649
- type: ndcg_at_3
value: 52.09
- type: ndcg_at_5
value: 54.70399999999999
- type: precision_at_1
value: 64.902
- type: precision_at_10
value: 12.136
- type: precision_at_100
value: 1.51
- type: precision_at_1000
value: 0.174
- type: precision_at_3
value: 32.933
- type: precision_at_5
value: 21.823
- type: recall_at_1
value: 32.451
- type: recall_at_10
value: 60.682
- type: recall_at_100
value: 75.523
- type: recall_at_1000
value: 87.063
- type: recall_at_3
value: 49.399
- type: recall_at_5
value: 54.55799999999999
- task:
type: Classification
dataset:
type: mteb/imdb
name: MTEB ImdbClassification
config: default
split: test
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
metrics:
- type: accuracy
value: 89.48759999999997
- type: ap
value: 85.15533983465178
- type: f1
value: 89.46732838870311
- task:
type: Retrieval
dataset:
type: msmarco
name: MTEB MSMARCO
config: default
split: dev
revision: None
metrics:
- type: map_at_1
value: 17.942
- type: map_at_10
value: 29.755
- type: map_at_100
value: 31.008000000000003
- type: map_at_1000
value: 31.067
- type: map_at_3
value: 25.959
- type: map_at_5
value: 28.044999999999998
- type: mrr_at_1
value: 18.467
- type: mrr_at_10
value: 30.253000000000004
- type: mrr_at_100
value: 31.461
- type: mrr_at_1000
value: 31.513
- type: mrr_at_3
value: 26.528000000000002
- type: mrr_at_5
value: 28.588
- type: ndcg_at_1
value: 18.467
- type: ndcg_at_10
value: 36.510999999999996
- type: ndcg_at_100
value: 42.748999999999995
- type: ndcg_at_1000
value: 44.188
- type: ndcg_at_3
value: 28.752
- type: ndcg_at_5
value: 32.462
- type: precision_at_1
value: 18.467
- type: precision_at_10
value: 6.006
- type: precision_at_100
value: 0.9169999999999999
- type: precision_at_1000
value: 0.104
- type: precision_at_3
value: 12.55
- type: precision_at_5
value: 9.395000000000001
- type: recall_at_1
value: 17.942
- type: recall_at_10
value: 57.440000000000005
- type: recall_at_100
value: 86.66199999999999
- type: recall_at_1000
value: 97.613
- type: recall_at_3
value: 36.271
- type: recall_at_5
value: 45.167
- task:
type: Classification
dataset:
type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (en)
config: en
split: test
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
metrics:
- type: accuracy
value: 36.3657090743274
- type: f1
value: 27.22838800222161
- task:
type: Classification
dataset:
type: mteb/mtop_intent
name: MTEB MTOPIntentClassification (en)
config: en
split: test
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
metrics:
- type: accuracy
value: 1.0168718650250799
- type: f1
value: 0.0674636098084213
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (en)
config: en
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 1.8829858776059176
- type: f1
value: 0.08021151737444676
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (en)
config: en
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 8.681909885675857
- type: f1
value: 2.752826896423761
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-p2p
name: MTEB MedrxivClusteringP2P
config: default
split: test
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
metrics:
- type: v_measure
value: 33.88016176143737
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-s2s
name: MTEB MedrxivClusteringS2S
config: default
split: test
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
metrics:
- type: v_measure
value: 32.07643038274053
- task:
type: Reranking
dataset:
type: mteb/mind_small
name: MTEB MindSmallReranking
config: default
split: test
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
metrics:
- type: map
value: 30.81344342001539
- type: mrr
value: 31.82078962760685
- task:
type: Retrieval
dataset:
type: nfcorpus
name: MTEB NFCorpus
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 4.617
- type: map_at_10
value: 11.501
- type: map_at_100
value: 14.729999999999999
- type: map_at_1000
value: 16.209
- type: map_at_3
value: 8.275
- type: map_at_5
value: 9.853000000000002
- type: mrr_at_1
value: 41.486000000000004
- type: mrr_at_10
value: 51.471999999999994
- type: mrr_at_100
value: 52.020999999999994
- type: mrr_at_1000
value: 52.066
- type: mrr_at_3
value: 49.484
- type: mrr_at_5
value: 50.660000000000004
- type: ndcg_at_1
value: 38.854
- type: ndcg_at_10
value: 31.567
- type: ndcg_at_100
value: 29.842999999999996
- type: ndcg_at_1000
value: 38.995000000000005
- type: ndcg_at_3
value: 36.785000000000004
- type: ndcg_at_5
value: 34.955000000000005
- type: precision_at_1
value: 40.867
- type: precision_at_10
value: 23.591
- type: precision_at_100
value: 7.771
- type: precision_at_1000
value: 2.11
- type: precision_at_3
value: 35.397
- type: precision_at_5
value: 30.959999999999997
- type: recall_at_1
value: 4.617
- type: recall_at_10
value: 15.609
- type: recall_at_100
value: 31.313999999999997
- type: recall_at_1000
value: 63.085
- type: recall_at_3
value: 9.746
- type: recall_at_5
value: 12.295
- task:
type: Retrieval
dataset:
type: nq
name: MTEB NQ
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 28.797
- type: map_at_10
value: 44.822
- type: map_at_100
value: 45.891999999999996
- type: map_at_1000
value: 45.919
- type: map_at_3
value: 40.237
- type: map_at_5
value: 42.913000000000004
- type: mrr_at_1
value: 32.561
- type: mrr_at_10
value: 46.982
- type: mrr_at_100
value: 47.827
- type: mrr_at_1000
value: 47.843999999999994
- type: mrr_at_3
value: 43.26
- type: mrr_at_5
value: 45.527
- type: ndcg_at_1
value: 32.532
- type: ndcg_at_10
value: 52.832
- type: ndcg_at_100
value: 57.343999999999994
- type: ndcg_at_1000
value: 57.93899999999999
- type: ndcg_at_3
value: 44.246
- type: ndcg_at_5
value: 48.698
- type: precision_at_1
value: 32.532
- type: precision_at_10
value: 9.003
- type: precision_at_100
value: 1.1480000000000001
- type: precision_at_1000
value: 0.12
- type: precision_at_3
value: 20.605999999999998
- type: precision_at_5
value: 14.954
- type: recall_at_1
value: 28.797
- type: recall_at_10
value: 75.065
- type: recall_at_100
value: 94.6
- type: recall_at_1000
value: 98.967
- type: recall_at_3
value: 52.742
- type: recall_at_5
value: 63.012
- task:
type: Retrieval
dataset:
type: quora
name: MTEB QuoraRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 69.84700000000001
- type: map_at_10
value: 83.91499999999999
- type: map_at_100
value: 84.568
- type: map_at_1000
value: 84.584
- type: map_at_3
value: 80.87299999999999
- type: map_at_5
value: 82.76299999999999
- type: mrr_at_1
value: 80.4
- type: mrr_at_10
value: 86.843
- type: mrr_at_100
value: 86.956
- type: mrr_at_1000
value: 86.957
- type: mrr_at_3
value: 85.843
- type: mrr_at_5
value: 86.521
- type: ndcg_at_1
value: 80.4
- type: ndcg_at_10
value: 87.787
- type: ndcg_at_100
value: 89.039
- type: ndcg_at_1000
value: 89.137
- type: ndcg_at_3
value: 84.76700000000001
- type: ndcg_at_5
value: 86.413
- type: precision_at_1
value: 80.4
- type: precision_at_10
value: 13.391
- type: precision_at_100
value: 1.533
- type: precision_at_1000
value: 0.157
- type: precision_at_3
value: 37.123
- type: precision_at_5
value: 24.462
- type: recall_at_1
value: 69.84700000000001
- type: recall_at_10
value: 95.296
- type: recall_at_100
value: 99.543
- type: recall_at_1000
value: 99.98700000000001
- type: recall_at_3
value: 86.75
- type: recall_at_5
value: 91.33099999999999
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering
name: MTEB RedditClustering
config: default
split: test
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
metrics:
- type: v_measure
value: 54.24501738730203
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering-p2p
name: MTEB RedditClusteringP2P
config: default
split: test
revision: 282350215ef01743dc01b456c7f5241fa8937f16
metrics:
- type: v_measure
value: 61.28243705082983
- task:
type: Retrieval
dataset:
type: scidocs
name: MTEB SCIDOCS
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 3.473
- type: map_at_10
value: 8.944
- type: map_at_100
value: 11.21
- type: map_at_1000
value: 11.601
- type: map_at_3
value: 6.167
- type: map_at_5
value: 7.438000000000001
- type: mrr_at_1
value: 17.1
- type: mrr_at_10
value: 26.487
- type: mrr_at_100
value: 27.888
- type: mrr_at_1000
value: 27.961000000000002
- type: mrr_at_3
value: 23.25
- type: mrr_at_5
value: 24.91
- type: ndcg_at_1
value: 17.1
- type: ndcg_at_10
value: 15.615000000000002
- type: ndcg_at_100
value: 24.667
- type: ndcg_at_1000
value: 31.467
- type: ndcg_at_3
value: 14.035
- type: ndcg_at_5
value: 12.443
- type: precision_at_1
value: 17.1
- type: precision_at_10
value: 8.4
- type: precision_at_100
value: 2.149
- type: precision_at_1000
value: 0.378
- type: precision_at_3
value: 13.200000000000001
- type: precision_at_5
value: 11.06
- type: recall_at_1
value: 3.473
- type: recall_at_10
value: 17.087
- type: recall_at_100
value: 43.641999999999996
- type: recall_at_1000
value: 76.7
- type: recall_at_3
value: 8.037999999999998
- type: recall_at_5
value: 11.232000000000001
- task:
type: STS
dataset:
type: mteb/sickr-sts
name: MTEB SICK-R
config: default
split: test
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
metrics:
- type: cos_sim_pearson
value: 86.07032781899852
- type: cos_sim_spearman
value: 81.86668245459153
- type: euclidean_pearson
value: 83.75572948495356
- type: euclidean_spearman
value: 81.88575221829207
- type: manhattan_pearson
value: 83.73171218997966
- type: manhattan_spearman
value: 81.85928771458329
- task:
type: STS
dataset:
type: mteb/sts12-sts
name: MTEB STS12
config: default
split: test
revision: a0d554a64d88156834ff5ae9920b964011b16384
metrics:
- type: cos_sim_pearson
value: 80.29008828604368
- type: cos_sim_spearman
value: 70.7510437896188
- type: euclidean_pearson
value: 76.65867322096001
- type: euclidean_spearman
value: 70.53984435296805
- type: manhattan_pearson
value: 76.6398826461678
- type: manhattan_spearman
value: 70.55153706770477
- task:
type: STS
dataset:
type: mteb/sts13-sts
name: MTEB STS13
config: default
split: test
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
metrics:
- type: cos_sim_pearson
value: 83.55610063096913
- type: cos_sim_spearman
value: 84.36676850545378
- type: euclidean_pearson
value: 82.81438612985889
- type: euclidean_spearman
value: 84.182693686057
- type: manhattan_pearson
value: 82.8355239074719
- type: manhattan_spearman
value: 84.19280249146543
- task:
type: STS
dataset:
type: mteb/sts14-sts
name: MTEB STS14
config: default
split: test
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
metrics:
- type: cos_sim_pearson
value: 78.94275022740113
- type: cos_sim_spearman
value: 74.50851813226338
- type: euclidean_pearson
value: 77.30867917552419
- type: euclidean_spearman
value: 74.55661368823343
- type: manhattan_pearson
value: 77.31883134876524
- type: manhattan_spearman
value: 74.58999819014154
- task:
type: STS
dataset:
type: mteb/sts15-sts
name: MTEB STS15
config: default
split: test
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
metrics:
- type: cos_sim_pearson
value: 85.62907185533146
- type: cos_sim_spearman
value: 86.40667080261993
- type: euclidean_pearson
value: 85.15184748925726
- type: euclidean_spearman
value: 86.33853519247509
- type: manhattan_pearson
value: 85.21542426870172
- type: manhattan_spearman
value: 86.4076178438401
- task:
type: STS
dataset:
type: mteb/sts16-sts
name: MTEB STS16
config: default
split: test
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
metrics:
- type: cos_sim_pearson
value: 83.42449758804275
- type: cos_sim_spearman
value: 84.7411616479609
- type: euclidean_pearson
value: 83.56616729612806
- type: euclidean_spearman
value: 84.44493050289694
- type: manhattan_pearson
value: 83.50906591764574
- type: manhattan_spearman
value: 84.39704993090794
- task:
type: STS
dataset:
type: mteb/sts17-crosslingual-sts
name: MTEB STS17 (en-en)
config: en-en
split: test
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
metrics:
- type: cos_sim_pearson
value: 88.84843806728331
- type: cos_sim_spearman
value: 89.03139214250334
- type: euclidean_pearson
value: 89.63615835813032
- type: euclidean_spearman
value: 89.33022202130817
- type: manhattan_pearson
value: 89.67071925715891
- type: manhattan_spearman
value: 89.29339683171531
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (en)
config: en
split: test
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
metrics:
- type: cos_sim_pearson
value: 65.65559857216783
- type: cos_sim_spearman
value: 65.86805861979079
- type: euclidean_pearson
value: 66.69697475461513
- type: euclidean_spearman
value: 66.07735691378713
- type: manhattan_pearson
value: 66.63427637906918
- type: manhattan_spearman
value: 65.95720565040364
- task:
type: STS
dataset:
type: mteb/stsbenchmark-sts
name: MTEB STSBenchmark
config: default
split: test
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
metrics:
- type: cos_sim_pearson
value: 86.06435608928308
- type: cos_sim_spearman
value: 86.46139340079428
- type: euclidean_pearson
value: 86.4874804471064
- type: euclidean_spearman
value: 86.19390771731406
- type: manhattan_pearson
value: 86.51184704840284
- type: manhattan_spearman
value: 86.19094101171963
- task:
type: Reranking
dataset:
type: mteb/scidocs-reranking
name: MTEB SciDocsRR
config: default
split: test
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
metrics:
- type: map
value: 85.10723925640346
- type: mrr
value: 95.62579305226365
- task:
type: Retrieval
dataset:
type: scifact
name: MTEB SciFact
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 56.233
- type: map_at_10
value: 64.94
- type: map_at_100
value: 65.508
- type: map_at_1000
value: 65.537
- type: map_at_3
value: 62.121
- type: map_at_5
value: 63.92400000000001
- type: mrr_at_1
value: 58.667
- type: mrr_at_10
value: 66.352
- type: mrr_at_100
value: 66.751
- type: mrr_at_1000
value: 66.777
- type: mrr_at_3
value: 64.22200000000001
- type: mrr_at_5
value: 65.656
- type: ndcg_at_1
value: 58.667
- type: ndcg_at_10
value: 69.318
- type: ndcg_at_100
value: 71.822
- type: ndcg_at_1000
value: 72.578
- type: ndcg_at_3
value: 64.532
- type: ndcg_at_5
value: 67.292
- type: precision_at_1
value: 58.667
- type: precision_at_10
value: 9.133
- type: precision_at_100
value: 1.05
- type: precision_at_1000
value: 0.11199999999999999
- type: precision_at_3
value: 24.889
- type: precision_at_5
value: 16.733
- type: recall_at_1
value: 56.233
- type: recall_at_10
value: 81.206
- type: recall_at_100
value: 92.80000000000001
- type: recall_at_1000
value: 98.667
- type: recall_at_3
value: 68.672
- type: recall_at_5
value: 75.378
- task:
type: PairClassification
dataset:
type: mteb/sprintduplicatequestions-pairclassification
name: MTEB SprintDuplicateQuestions
config: default
split: test
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
metrics:
- type: cos_sim_accuracy
value: 99.56336633663366
- type: cos_sim_ap
value: 86.13024319858586
- type: cos_sim_f1
value: 76.80157946692991
- type: cos_sim_precision
value: 75.82846003898635
- type: cos_sim_recall
value: 77.8
- type: dot_accuracy
value: 99.56336633663366
- type: dot_ap
value: 86.13028343072267
- type: dot_f1
value: 76.80157946692991
- type: dot_precision
value: 75.82846003898635
- type: dot_recall
value: 77.8
- type: euclidean_accuracy
value: 99.56336633663366
- type: euclidean_ap
value: 86.13029040641543
- type: euclidean_f1
value: 76.80157946692991
- type: euclidean_precision
value: 75.82846003898635
- type: euclidean_recall
value: 77.8
- type: manhattan_accuracy
value: 99.56534653465347
- type: manhattan_ap
value: 86.24817068330776
- type: manhattan_f1
value: 77.13580246913581
- type: manhattan_precision
value: 76.19512195121952
- type: manhattan_recall
value: 78.10000000000001
- type: max_accuracy
value: 99.56534653465347
- type: max_ap
value: 86.24817068330776
- type: max_f1
value: 77.13580246913581
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering
name: MTEB StackExchangeClustering
config: default
split: test
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
metrics:
- type: v_measure
value: 64.69564559409538
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering-p2p
name: MTEB StackExchangeClusteringP2P
config: default
split: test
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
metrics:
- type: v_measure
value: 34.23127531581388
- task:
type: Reranking
dataset:
type: mteb/stackoverflowdupquestions-reranking
name: MTEB StackOverflowDupQuestions
config: default
split: test
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
metrics:
- type: map
value: 49.845357053686975
- type: mrr
value: 50.59803656311009
- task:
type: Summarization
dataset:
type: mteb/summeval
name: MTEB SummEval
config: default
split: test
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
metrics:
- type: cos_sim_pearson
value: 29.02241691876377
- type: cos_sim_spearman
value: 29.017719340560923
- type: dot_pearson
value: 29.59373129445045
- type: dot_spearman
value: 29.616196388331968
- task:
type: Retrieval
dataset:
type: trec-covid
name: MTEB TRECCOVID
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 0.157
- type: map_at_10
value: 0.9440000000000001
- type: map_at_100
value: 4.61
- type: map_at_1000
value: 11.488
- type: map_at_3
value: 0.396
- type: map_at_5
value: 0.569
- type: mrr_at_1
value: 57.99999999999999
- type: mrr_at_10
value: 71.672
- type: mrr_at_100
value: 71.707
- type: mrr_at_1000
value: 71.707
- type: mrr_at_3
value: 68.333
- type: mrr_at_5
value: 70.533
- type: ndcg_at_1
value: 54
- type: ndcg_at_10
value: 45.216
- type: ndcg_at_100
value: 32.623999999999995
- type: ndcg_at_1000
value: 33.006
- type: ndcg_at_3
value: 51.76500000000001
- type: ndcg_at_5
value: 47.888999999999996
- type: precision_at_1
value: 57.99999999999999
- type: precision_at_10
value: 48
- type: precision_at_100
value: 32.74
- type: precision_at_1000
value: 14.588000000000001
- type: precision_at_3
value: 55.333
- type: precision_at_5
value: 51.2
- type: recall_at_1
value: 0.157
- type: recall_at_10
value: 1.212
- type: recall_at_100
value: 7.868
- type: recall_at_1000
value: 31.583
- type: recall_at_3
value: 0.443
- type: recall_at_5
value: 0.6779999999999999
- task:
type: Retrieval
dataset:
type: webis-touche2020
name: MTEB Touche2020
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 1.545
- type: map_at_10
value: 4.6690000000000005
- type: map_at_100
value: 8.982
- type: map_at_1000
value: 10.453999999999999
- type: map_at_3
value: 2.35
- type: map_at_5
value: 3.168
- type: mrr_at_1
value: 18.367
- type: mrr_at_10
value: 28.599999999999998
- type: mrr_at_100
value: 30.287
- type: mrr_at_1000
value: 30.339
- type: mrr_at_3
value: 24.490000000000002
- type: mrr_at_5
value: 27.040999999999997
- type: ndcg_at_1
value: 17.347
- type: ndcg_at_10
value: 13.868
- type: ndcg_at_100
value: 25.499
- type: ndcg_at_1000
value: 37.922
- type: ndcg_at_3
value: 13.746
- type: ndcg_at_5
value: 13.141
- type: precision_at_1
value: 18.367
- type: precision_at_10
value: 12.653
- type: precision_at_100
value: 5.776
- type: precision_at_1000
value: 1.3860000000000001
- type: precision_at_3
value: 13.605
- type: precision_at_5
value: 13.061
- type: recall_at_1
value: 1.545
- type: recall_at_10
value: 9.305
- type: recall_at_100
value: 38.084
- type: recall_at_1000
value: 75.897
- type: recall_at_3
value: 2.903
- type: recall_at_5
value: 4.8919999999999995
- task:
type: Classification
dataset:
type: mteb/toxic_conversations_50k
name: MTEB ToxicConversationsClassification
config: default
split: test
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
metrics:
- type: accuracy
value: 71.23839999999998
- type: ap
value: 14.810293385203243
- type: f1
value: 55.08401453918053
- task:
type: Classification
dataset:
type: mteb/tweet_sentiment_extraction
name: MTEB TweetSentimentExtractionClassification
config: default
split: test
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
metrics:
- type: accuracy
value: 58.21448783248444
- type: f1
value: 58.57246320620639
- task:
type: Clustering
dataset:
type: mteb/twentynewsgroups-clustering
name: MTEB TwentyNewsgroupsClustering
config: default
split: test
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
metrics:
- type: v_measure
value: 49.314744135178934
- task:
type: PairClassification
dataset:
type: mteb/twittersemeval2015-pairclassification
name: MTEB TwitterSemEval2015
config: default
split: test
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
metrics:
- type: cos_sim_accuracy
value: 84.13899982118377
- type: cos_sim_ap
value: 68.03329474978145
- type: cos_sim_f1
value: 63.31192005710206
- type: cos_sim_precision
value: 57.6473136915078
- type: cos_sim_recall
value: 70.21108179419525
- type: dot_accuracy
value: 84.13899982118377
- type: dot_ap
value: 68.03324775052695
- type: dot_f1
value: 63.31192005710206
- type: dot_precision
value: 57.6473136915078
- type: dot_recall
value: 70.21108179419525
- type: euclidean_accuracy
value: 84.13899982118377
- type: euclidean_ap
value: 68.03331114508686
- type: euclidean_f1
value: 63.31192005710206
- type: euclidean_precision
value: 57.6473136915078
- type: euclidean_recall
value: 70.21108179419525
- type: manhattan_accuracy
value: 84.12111819753234
- type: manhattan_ap
value: 67.97378509663328
- type: manhattan_f1
value: 63.38468945594607
- type: manhattan_precision
value: 58.2779991146525
- type: manhattan_recall
value: 69.47229551451187
- type: max_accuracy
value: 84.13899982118377
- type: max_ap
value: 68.03331114508686
- type: max_f1
value: 63.38468945594607
- task:
type: PairClassification
dataset:
type: mteb/twitterurlcorpus-pairclassification
name: MTEB TwitterURLCorpus
config: default
split: test
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
metrics:
- type: cos_sim_accuracy
value: 87.68774013272791
- type: cos_sim_ap
value: 83.51733662214374
- type: cos_sim_f1
value: 75.82190771045259
- type: cos_sim_precision
value: 72.72341628959276
- type: cos_sim_recall
value: 79.19618109023713
- type: dot_accuracy
value: 87.68774013272791
- type: dot_ap
value: 83.5173527754126
- type: dot_f1
value: 75.82190771045259
- type: dot_precision
value: 72.72341628959276
- type: dot_recall
value: 79.19618109023713
- type: euclidean_accuracy
value: 87.68774013272791
- type: euclidean_ap
value: 83.51734651146224
- type: euclidean_f1
value: 75.82190771045259
- type: euclidean_precision
value: 72.72341628959276
- type: euclidean_recall
value: 79.19618109023713
- type: manhattan_accuracy
value: 87.67221640082276
- type: manhattan_ap
value: 83.51179463759505
- type: manhattan_f1
value: 75.76243980738361
- type: manhattan_precision
value: 71.99112590127565
- type: manhattan_recall
value: 79.95072374499537
- type: max_accuracy
value: 87.68774013272791
- type: max_ap
value: 83.5173527754126
- type: max_f1
value: 75.82190771045259