metadata
language:
- en
license: apache-2.0
library_name: sentence-transformers
tags:
- mteb
- transformers.js
- transformers
- llama-cpp
- gguf-my-repo
pipeline_tag: feature-extraction
model-index:
- name: mxbai-angle-large-v1
results:
- task:
type: Classification
dataset:
name: MTEB AmazonCounterfactualClassification (en)
type: mteb/amazon_counterfactual
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
- type: accuracy
value: 75.044776119403
- type: ap
value: 37.7362433623053
- type: f1
value: 68.92736573359774
- task:
type: Classification
dataset:
name: MTEB AmazonPolarityClassification
type: mteb/amazon_polarity
config: default
split: test
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
metrics:
- type: accuracy
value: 93.84025000000001
- type: ap
value: 90.93190875404055
- type: f1
value: 93.8297833897293
- task:
type: Classification
dataset:
name: MTEB AmazonReviewsClassification (en)
type: mteb/amazon_reviews_multi
config: en
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy
value: 49.184
- type: f1
value: 48.74163227751588
- task:
type: Retrieval
dataset:
name: MTEB ArguAna
type: arguana
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 41.252
- type: map_at_10
value: 57.778
- type: map_at_100
value: 58.233000000000004
- type: map_at_1000
value: 58.23700000000001
- type: map_at_3
value: 53.449999999999996
- type: map_at_5
value: 56.376000000000005
- type: mrr_at_1
value: 41.679
- type: mrr_at_10
value: 57.92699999999999
- type: mrr_at_100
value: 58.389
- type: mrr_at_1000
value: 58.391999999999996
- type: mrr_at_3
value: 53.651
- type: mrr_at_5
value: 56.521
- type: ndcg_at_1
value: 41.252
- type: ndcg_at_10
value: 66.018
- type: ndcg_at_100
value: 67.774
- type: ndcg_at_1000
value: 67.84400000000001
- type: ndcg_at_3
value: 57.372
- type: ndcg_at_5
value: 62.646
- type: precision_at_1
value: 41.252
- type: precision_at_10
value: 9.189
- type: precision_at_100
value: 0.991
- type: precision_at_1000
value: 0.1
- type: precision_at_3
value: 22.902
- type: precision_at_5
value: 16.302
- type: recall_at_1
value: 41.252
- type: recall_at_10
value: 91.892
- type: recall_at_100
value: 99.14699999999999
- type: recall_at_1000
value: 99.644
- type: recall_at_3
value: 68.706
- type: recall_at_5
value: 81.50800000000001
- task:
type: Clustering
dataset:
name: MTEB ArxivClusteringP2P
type: mteb/arxiv-clustering-p2p
config: default
split: test
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
metrics:
- type: v_measure
value: 48.97294504317859
- task:
type: Clustering
dataset:
name: MTEB ArxivClusteringS2S
type: mteb/arxiv-clustering-s2s
config: default
split: test
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
metrics:
- type: v_measure
value: 42.98071077674629
- task:
type: Reranking
dataset:
name: MTEB AskUbuntuDupQuestions
type: mteb/askubuntudupquestions-reranking
config: default
split: test
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
metrics:
- type: map
value: 65.16477858490782
- type: mrr
value: 78.23583080508287
- task:
type: STS
dataset:
name: MTEB BIOSSES
type: mteb/biosses-sts
config: default
split: test
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
metrics:
- type: cos_sim_pearson
value: 89.6277629421789
- type: cos_sim_spearman
value: 88.4056288400568
- type: euclidean_pearson
value: 87.94871847578163
- type: euclidean_spearman
value: 88.4056288400568
- type: manhattan_pearson
value: 87.73271254229648
- type: manhattan_spearman
value: 87.91826833762677
- task:
type: Classification
dataset:
name: MTEB Banking77Classification
type: mteb/banking77
config: default
split: test
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
metrics:
- type: accuracy
value: 87.81818181818181
- type: f1
value: 87.79879337316918
- task:
type: Clustering
dataset:
name: MTEB BiorxivClusteringP2P
type: mteb/biorxiv-clustering-p2p
config: default
split: test
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
metrics:
- type: v_measure
value: 39.91773608582761
- task:
type: Clustering
dataset:
name: MTEB BiorxivClusteringS2S
type: mteb/biorxiv-clustering-s2s
config: default
split: test
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
metrics:
- type: v_measure
value: 36.73059477462478
- task:
type: Retrieval
dataset:
name: MTEB CQADupstackAndroidRetrieval
type: BeIR/cqadupstack
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 32.745999999999995
- type: map_at_10
value: 43.632
- type: map_at_100
value: 45.206
- type: map_at_1000
value: 45.341
- type: map_at_3
value: 39.956
- type: map_at_5
value: 42.031
- type: mrr_at_1
value: 39.485
- type: mrr_at_10
value: 49.537
- type: mrr_at_100
value: 50.249
- type: mrr_at_1000
value: 50.294000000000004
- type: mrr_at_3
value: 46.757
- type: mrr_at_5
value: 48.481
- type: ndcg_at_1
value: 39.485
- type: ndcg_at_10
value: 50.058
- type: ndcg_at_100
value: 55.586
- type: ndcg_at_1000
value: 57.511
- type: ndcg_at_3
value: 44.786
- type: ndcg_at_5
value: 47.339999999999996
- type: precision_at_1
value: 39.485
- type: precision_at_10
value: 9.557
- type: precision_at_100
value: 1.552
- type: precision_at_1000
value: 0.202
- type: precision_at_3
value: 21.412
- type: precision_at_5
value: 15.479000000000001
- type: recall_at_1
value: 32.745999999999995
- type: recall_at_10
value: 62.056
- type: recall_at_100
value: 85.088
- type: recall_at_1000
value: 96.952
- type: recall_at_3
value: 46.959
- type: recall_at_5
value: 54.06999999999999
- type: map_at_1
value: 31.898
- type: map_at_10
value: 42.142
- type: map_at_100
value: 43.349
- type: map_at_1000
value: 43.483
- type: map_at_3
value: 39.18
- type: map_at_5
value: 40.733000000000004
- type: mrr_at_1
value: 39.617999999999995
- type: mrr_at_10
value: 47.922
- type: mrr_at_100
value: 48.547000000000004
- type: mrr_at_1000
value: 48.597
- type: mrr_at_3
value: 45.86
- type: mrr_at_5
value: 46.949000000000005
- type: ndcg_at_1
value: 39.617999999999995
- type: ndcg_at_10
value: 47.739
- type: ndcg_at_100
value: 51.934999999999995
- type: ndcg_at_1000
value: 54.007000000000005
- type: ndcg_at_3
value: 43.748
- type: ndcg_at_5
value: 45.345
- type: precision_at_1
value: 39.617999999999995
- type: precision_at_10
value: 8.962
- type: precision_at_100
value: 1.436
- type: precision_at_1000
value: 0.192
- type: precision_at_3
value: 21.083
- type: precision_at_5
value: 14.752
- type: recall_at_1
value: 31.898
- type: recall_at_10
value: 57.587999999999994
- type: recall_at_100
value: 75.323
- type: recall_at_1000
value: 88.304
- type: recall_at_3
value: 45.275
- type: recall_at_5
value: 49.99
- type: map_at_1
value: 40.458
- type: map_at_10
value: 52.942
- type: map_at_100
value: 53.974
- type: map_at_1000
value: 54.031
- type: map_at_3
value: 49.559999999999995
- type: map_at_5
value: 51.408
- type: mrr_at_1
value: 46.27
- type: mrr_at_10
value: 56.31699999999999
- type: mrr_at_100
value: 56.95099999999999
- type: mrr_at_1000
value: 56.98
- type: mrr_at_3
value: 53.835
- type: mrr_at_5
value: 55.252
- type: ndcg_at_1
value: 46.27
- type: ndcg_at_10
value: 58.964000000000006
- type: ndcg_at_100
value: 62.875
- type: ndcg_at_1000
value: 63.969
- type: ndcg_at_3
value: 53.297000000000004
- type: ndcg_at_5
value: 55.938
- type: precision_at_1
value: 46.27
- type: precision_at_10
value: 9.549000000000001
- type: precision_at_100
value: 1.2409999999999999
- type: precision_at_1000
value: 0.13799999999999998
- type: precision_at_3
value: 23.762
- type: precision_at_5
value: 16.262999999999998
- type: recall_at_1
value: 40.458
- type: recall_at_10
value: 73.446
- type: recall_at_100
value: 90.12400000000001
- type: recall_at_1000
value: 97.795
- type: recall_at_3
value: 58.123000000000005
- type: recall_at_5
value: 64.68
- type: map_at_1
value: 27.443
- type: map_at_10
value: 36.081
- type: map_at_100
value: 37.163000000000004
- type: map_at_1000
value: 37.232
- type: map_at_3
value: 33.308
- type: map_at_5
value: 34.724
- type: mrr_at_1
value: 29.492
- type: mrr_at_10
value: 38.138
- type: mrr_at_100
value: 39.065
- type: mrr_at_1000
value: 39.119
- type: mrr_at_3
value: 35.593
- type: mrr_at_5
value: 36.785000000000004
- type: ndcg_at_1
value: 29.492
- type: ndcg_at_10
value: 41.134
- type: ndcg_at_100
value: 46.300999999999995
- type: ndcg_at_1000
value: 48.106
- type: ndcg_at_3
value: 35.77
- type: ndcg_at_5
value: 38.032
- type: precision_at_1
value: 29.492
- type: precision_at_10
value: 6.249
- type: precision_at_100
value: 0.9299999999999999
- type: precision_at_1000
value: 0.11199999999999999
- type: precision_at_3
value: 15.065999999999999
- type: precision_at_5
value: 10.373000000000001
- type: recall_at_1
value: 27.443
- type: recall_at_10
value: 54.80199999999999
- type: recall_at_100
value: 78.21900000000001
- type: recall_at_1000
value: 91.751
- type: recall_at_3
value: 40.211000000000006
- type: recall_at_5
value: 45.599000000000004
- type: map_at_1
value: 18.731
- type: map_at_10
value: 26.717999999999996
- type: map_at_100
value: 27.897
- type: map_at_1000
value: 28.029
- type: map_at_3
value: 23.91
- type: map_at_5
value: 25.455
- type: mrr_at_1
value: 23.134
- type: mrr_at_10
value: 31.769
- type: mrr_at_100
value: 32.634
- type: mrr_at_1000
value: 32.707
- type: mrr_at_3
value: 28.938999999999997
- type: mrr_at_5
value: 30.531000000000002
- type: ndcg_at_1
value: 23.134
- type: ndcg_at_10
value: 32.249
- type: ndcg_at_100
value: 37.678
- type: ndcg_at_1000
value: 40.589999999999996
- type: ndcg_at_3
value: 26.985999999999997
- type: ndcg_at_5
value: 29.457
- type: precision_at_1
value: 23.134
- type: precision_at_10
value: 5.8709999999999996
- type: precision_at_100
value: 0.988
- type: precision_at_1000
value: 0.13799999999999998
- type: precision_at_3
value: 12.852
- type: precision_at_5
value: 9.428
- type: recall_at_1
value: 18.731
- type: recall_at_10
value: 44.419
- type: recall_at_100
value: 67.851
- type: recall_at_1000
value: 88.103
- type: recall_at_3
value: 29.919
- type: recall_at_5
value: 36.230000000000004
- type: map_at_1
value: 30.324
- type: map_at_10
value: 41.265
- type: map_at_100
value: 42.559000000000005
- type: map_at_1000
value: 42.669000000000004
- type: map_at_3
value: 38.138
- type: map_at_5
value: 39.881
- type: mrr_at_1
value: 36.67
- type: mrr_at_10
value: 46.774
- type: mrr_at_100
value: 47.554
- type: mrr_at_1000
value: 47.593
- type: mrr_at_3
value: 44.338
- type: mrr_at_5
value: 45.723
- type: ndcg_at_1
value: 36.67
- type: ndcg_at_10
value: 47.367
- type: ndcg_at_100
value: 52.623
- type: ndcg_at_1000
value: 54.59
- type: ndcg_at_3
value: 42.323
- type: ndcg_at_5
value: 44.727
- type: precision_at_1
value: 36.67
- type: precision_at_10
value: 8.518
- type: precision_at_100
value: 1.2890000000000001
- type: precision_at_1000
value: 0.163
- type: precision_at_3
value: 19.955000000000002
- type: precision_at_5
value: 14.11
- type: recall_at_1
value: 30.324
- type: recall_at_10
value: 59.845000000000006
- type: recall_at_100
value: 81.77499999999999
- type: recall_at_1000
value: 94.463
- type: recall_at_3
value: 46.019
- type: recall_at_5
value: 52.163000000000004
- type: map_at_1
value: 24.229
- type: map_at_10
value: 35.004000000000005
- type: map_at_100
value: 36.409000000000006
- type: map_at_1000
value: 36.521
- type: map_at_3
value: 31.793
- type: map_at_5
value: 33.432
- type: mrr_at_1
value: 30.365
- type: mrr_at_10
value: 40.502
- type: mrr_at_100
value: 41.372
- type: mrr_at_1000
value: 41.435
- type: mrr_at_3
value: 37.804
- type: mrr_at_5
value: 39.226
- type: ndcg_at_1
value: 30.365
- type: ndcg_at_10
value: 41.305
- type: ndcg_at_100
value: 47.028999999999996
- type: ndcg_at_1000
value: 49.375
- type: ndcg_at_3
value: 35.85
- type: ndcg_at_5
value: 38.12
- type: precision_at_1
value: 30.365
- type: precision_at_10
value: 7.808
- type: precision_at_100
value: 1.228
- type: precision_at_1000
value: 0.161
- type: precision_at_3
value: 17.352
- type: precision_at_5
value: 12.42
- type: recall_at_1
value: 24.229
- type: recall_at_10
value: 54.673
- type: recall_at_100
value: 78.766
- type: recall_at_1000
value: 94.625
- type: recall_at_3
value: 39.602
- type: recall_at_5
value: 45.558
- type: map_at_1
value: 26.695
- type: map_at_10
value: 36.0895
- type: map_at_100
value: 37.309416666666664
- type: map_at_1000
value: 37.42558333333334
- type: map_at_3
value: 33.19616666666666
- type: map_at_5
value: 34.78641666666667
- type: mrr_at_1
value: 31.486083333333337
- type: mrr_at_10
value: 40.34774999999999
- type: mrr_at_100
value: 41.17533333333333
- type: mrr_at_1000
value: 41.231583333333326
- type: mrr_at_3
value: 37.90075
- type: mrr_at_5
value: 39.266999999999996
- type: ndcg_at_1
value: 31.486083333333337
- type: ndcg_at_10
value: 41.60433333333334
- type: ndcg_at_100
value: 46.74525
- type: ndcg_at_1000
value: 48.96166666666667
- type: ndcg_at_3
value: 36.68825
- type: ndcg_at_5
value: 38.966499999999996
- type: precision_at_1
value: 31.486083333333337
- type: precision_at_10
value: 7.29675
- type: precision_at_100
value: 1.1621666666666666
- type: precision_at_1000
value: 0.1545
- type: precision_at_3
value: 16.8815
- type: precision_at_5
value: 11.974583333333333
- type: recall_at_1
value: 26.695
- type: recall_at_10
value: 53.651916666666665
- type: recall_at_100
value: 76.12083333333332
- type: recall_at_1000
value: 91.31191666666668
- type: recall_at_3
value: 40.03575
- type: recall_at_5
value: 45.876666666666665
- type: map_at_1
value: 25.668000000000003
- type: map_at_10
value: 32.486
- type: map_at_100
value: 33.371
- type: map_at_1000
value: 33.458
- type: map_at_3
value: 30.261
- type: map_at_5
value: 31.418000000000003
- type: mrr_at_1
value: 28.988000000000003
- type: mrr_at_10
value: 35.414
- type: mrr_at_100
value: 36.149
- type: mrr_at_1000
value: 36.215
- type: mrr_at_3
value: 33.333
- type: mrr_at_5
value: 34.43
- type: ndcg_at_1
value: 28.988000000000003
- type: ndcg_at_10
value: 36.732
- type: ndcg_at_100
value: 41.331
- type: ndcg_at_1000
value: 43.575
- type: ndcg_at_3
value: 32.413
- type: ndcg_at_5
value: 34.316
- type: precision_at_1
value: 28.988000000000003
- type: precision_at_10
value: 5.7059999999999995
- type: precision_at_100
value: 0.882
- type: precision_at_1000
value: 0.11299999999999999
- type: precision_at_3
value: 13.65
- type: precision_at_5
value: 9.417
- type: recall_at_1
value: 25.668000000000003
- type: recall_at_10
value: 47.147
- type: recall_at_100
value: 68.504
- type: recall_at_1000
value: 85.272
- type: recall_at_3
value: 35.19
- type: recall_at_5
value: 39.925
- type: map_at_1
value: 17.256
- type: map_at_10
value: 24.58
- type: map_at_100
value: 25.773000000000003
- type: map_at_1000
value: 25.899
- type: map_at_3
value: 22.236
- type: map_at_5
value: 23.507
- type: mrr_at_1
value: 20.957
- type: mrr_at_10
value: 28.416000000000004
- type: mrr_at_100
value: 29.447000000000003
- type: mrr_at_1000
value: 29.524
- type: mrr_at_3
value: 26.245
- type: mrr_at_5
value: 27.451999999999998
- type: ndcg_at_1
value: 20.957
- type: ndcg_at_10
value: 29.285
- type: ndcg_at_100
value: 35.003
- type: ndcg_at_1000
value: 37.881
- type: ndcg_at_3
value: 25.063000000000002
- type: ndcg_at_5
value: 26.983
- type: precision_at_1
value: 20.957
- type: precision_at_10
value: 5.344
- type: precision_at_100
value: 0.958
- type: precision_at_1000
value: 0.13799999999999998
- type: precision_at_3
value: 11.918
- type: precision_at_5
value: 8.596
- type: recall_at_1
value: 17.256
- type: recall_at_10
value: 39.644
- type: recall_at_100
value: 65.279
- type: recall_at_1000
value: 85.693
- type: recall_at_3
value: 27.825
- type: recall_at_5
value: 32.792
- type: map_at_1
value: 26.700000000000003
- type: map_at_10
value: 36.205999999999996
- type: map_at_100
value: 37.316
- type: map_at_1000
value: 37.425000000000004
- type: map_at_3
value: 33.166000000000004
- type: map_at_5
value: 35.032999999999994
- type: mrr_at_1
value: 31.436999999999998
- type: mrr_at_10
value: 40.61
- type: mrr_at_100
value: 41.415
- type: mrr_at_1000
value: 41.48
- type: mrr_at_3
value: 37.966
- type: mrr_at_5
value: 39.599000000000004
- type: ndcg_at_1
value: 31.436999999999998
- type: ndcg_at_10
value: 41.771
- type: ndcg_at_100
value: 46.784
- type: ndcg_at_1000
value: 49.183
- type: ndcg_at_3
value: 36.437000000000005
- type: ndcg_at_5
value: 39.291
- type: precision_at_1
value: 31.436999999999998
- type: precision_at_10
value: 6.987
- type: precision_at_100
value: 1.072
- type: precision_at_1000
value: 0.13899999999999998
- type: precision_at_3
value: 16.448999999999998
- type: precision_at_5
value: 11.866
- type: recall_at_1
value: 26.700000000000003
- type: recall_at_10
value: 54.301
- type: recall_at_100
value: 75.871
- type: recall_at_1000
value: 92.529
- type: recall_at_3
value: 40.201
- type: recall_at_5
value: 47.208
- type: map_at_1
value: 24.296
- type: map_at_10
value: 33.116
- type: map_at_100
value: 34.81
- type: map_at_1000
value: 35.032000000000004
- type: map_at_3
value: 30.105999999999998
- type: map_at_5
value: 31.839000000000002
- type: mrr_at_1
value: 29.051
- type: mrr_at_10
value: 37.803
- type: mrr_at_100
value: 38.856
- type: mrr_at_1000
value: 38.903999999999996
- type: mrr_at_3
value: 35.211
- type: mrr_at_5
value: 36.545
- type: ndcg_at_1
value: 29.051
- type: ndcg_at_10
value: 39.007
- type: ndcg_at_100
value: 45.321
- type: ndcg_at_1000
value: 47.665
- type: ndcg_at_3
value: 34.1
- type: ndcg_at_5
value: 36.437000000000005
- type: precision_at_1
value: 29.051
- type: precision_at_10
value: 7.668
- type: precision_at_100
value: 1.542
- type: precision_at_1000
value: 0.24
- type: precision_at_3
value: 16.14
- type: precision_at_5
value: 11.897
- type: recall_at_1
value: 24.296
- type: recall_at_10
value: 49.85
- type: recall_at_100
value: 78.457
- type: recall_at_1000
value: 92.618
- type: recall_at_3
value: 36.138999999999996
- type: recall_at_5
value: 42.223
- type: map_at_1
value: 20.591
- type: map_at_10
value: 28.902
- type: map_at_100
value: 29.886000000000003
- type: map_at_1000
value: 29.987000000000002
- type: map_at_3
value: 26.740000000000002
- type: map_at_5
value: 27.976
- type: mrr_at_1
value: 22.366
- type: mrr_at_10
value: 30.971
- type: mrr_at_100
value: 31.865
- type: mrr_at_1000
value: 31.930999999999997
- type: mrr_at_3
value: 28.927999999999997
- type: mrr_at_5
value: 30.231
- type: ndcg_at_1
value: 22.366
- type: ndcg_at_10
value: 33.641
- type: ndcg_at_100
value: 38.477
- type: ndcg_at_1000
value: 41.088
- type: ndcg_at_3
value: 29.486
- type: ndcg_at_5
value: 31.612000000000002
- type: precision_at_1
value: 22.366
- type: precision_at_10
value: 5.3420000000000005
- type: precision_at_100
value: 0.828
- type: precision_at_1000
value: 0.11800000000000001
- type: precision_at_3
value: 12.939
- type: precision_at_5
value: 9.094
- type: recall_at_1
value: 20.591
- type: recall_at_10
value: 46.052
- type: recall_at_100
value: 68.193
- type: recall_at_1000
value: 87.638
- type: recall_at_3
value: 34.966
- type: recall_at_5
value: 40.082
- task:
type: Retrieval
dataset:
name: MTEB ClimateFEVER
type: climate-fever
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 15.091
- type: map_at_10
value: 26.38
- type: map_at_100
value: 28.421999999999997
- type: map_at_1000
value: 28.621999999999996
- type: map_at_3
value: 21.597
- type: map_at_5
value: 24.12
- type: mrr_at_1
value: 34.266999999999996
- type: mrr_at_10
value: 46.864
- type: mrr_at_100
value: 47.617
- type: mrr_at_1000
value: 47.644
- type: mrr_at_3
value: 43.312
- type: mrr_at_5
value: 45.501000000000005
- type: ndcg_at_1
value: 34.266999999999996
- type: ndcg_at_10
value: 36.095
- type: ndcg_at_100
value: 43.447
- type: ndcg_at_1000
value: 46.661
- type: ndcg_at_3
value: 29.337999999999997
- type: ndcg_at_5
value: 31.824
- type: precision_at_1
value: 34.266999999999996
- type: precision_at_10
value: 11.472
- type: precision_at_100
value: 1.944
- type: precision_at_1000
value: 0.255
- type: precision_at_3
value: 21.933
- type: precision_at_5
value: 17.224999999999998
- type: recall_at_1
value: 15.091
- type: recall_at_10
value: 43.022
- type: recall_at_100
value: 68.075
- type: recall_at_1000
value: 85.76
- type: recall_at_3
value: 26.564
- type: recall_at_5
value: 33.594
- task:
type: Retrieval
dataset:
name: MTEB DBPedia
type: dbpedia-entity
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 9.252
- type: map_at_10
value: 20.923
- type: map_at_100
value: 30.741000000000003
- type: map_at_1000
value: 32.542
- type: map_at_3
value: 14.442
- type: map_at_5
value: 17.399
- type: mrr_at_1
value: 70.25
- type: mrr_at_10
value: 78.17
- type: mrr_at_100
value: 78.444
- type: mrr_at_1000
value: 78.45100000000001
- type: mrr_at_3
value: 76.958
- type: mrr_at_5
value: 77.571
- type: ndcg_at_1
value: 58.375
- type: ndcg_at_10
value: 44.509
- type: ndcg_at_100
value: 49.897999999999996
- type: ndcg_at_1000
value: 57.269999999999996
- type: ndcg_at_3
value: 48.64
- type: ndcg_at_5
value: 46.697
- type: precision_at_1
value: 70.25
- type: precision_at_10
value: 36.05
- type: precision_at_100
value: 11.848
- type: precision_at_1000
value: 2.213
- type: precision_at_3
value: 52.917
- type: precision_at_5
value: 45.7
- type: recall_at_1
value: 9.252
- type: recall_at_10
value: 27.006999999999998
- type: recall_at_100
value: 57.008
- type: recall_at_1000
value: 80.697
- type: recall_at_3
value: 15.798000000000002
- type: recall_at_5
value: 20.4
- task:
type: Classification
dataset:
name: MTEB EmotionClassification
type: mteb/emotion
config: default
split: test
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
metrics:
- type: accuracy
value: 50.88
- type: f1
value: 45.545495028653384
- task:
type: Retrieval
dataset:
name: MTEB FEVER
type: fever
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 75.424
- type: map_at_10
value: 83.435
- type: map_at_100
value: 83.66900000000001
- type: map_at_1000
value: 83.685
- type: map_at_3
value: 82.39800000000001
- type: map_at_5
value: 83.07
- type: mrr_at_1
value: 81.113
- type: mrr_at_10
value: 87.77199999999999
- type: mrr_at_100
value: 87.862
- type: mrr_at_1000
value: 87.86500000000001
- type: mrr_at_3
value: 87.17099999999999
- type: mrr_at_5
value: 87.616
- type: ndcg_at_1
value: 81.113
- type: ndcg_at_10
value: 86.909
- type: ndcg_at_100
value: 87.746
- type: ndcg_at_1000
value: 88.017
- type: ndcg_at_3
value: 85.368
- type: ndcg_at_5
value: 86.28099999999999
- type: precision_at_1
value: 81.113
- type: precision_at_10
value: 10.363
- type: precision_at_100
value: 1.102
- type: precision_at_1000
value: 0.11399999999999999
- type: precision_at_3
value: 32.507999999999996
- type: precision_at_5
value: 20.138
- type: recall_at_1
value: 75.424
- type: recall_at_10
value: 93.258
- type: recall_at_100
value: 96.545
- type: recall_at_1000
value: 98.284
- type: recall_at_3
value: 89.083
- type: recall_at_5
value: 91.445
- task:
type: Retrieval
dataset:
name: MTEB FiQA2018
type: fiqa
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 22.532
- type: map_at_10
value: 37.141999999999996
- type: map_at_100
value: 39.162
- type: map_at_1000
value: 39.322
- type: map_at_3
value: 32.885
- type: map_at_5
value: 35.093999999999994
- type: mrr_at_1
value: 44.29
- type: mrr_at_10
value: 53.516
- type: mrr_at_100
value: 54.24
- type: mrr_at_1000
value: 54.273
- type: mrr_at_3
value: 51.286
- type: mrr_at_5
value: 52.413
- type: ndcg_at_1
value: 44.29
- type: ndcg_at_10
value: 45.268
- type: ndcg_at_100
value: 52.125
- type: ndcg_at_1000
value: 54.778000000000006
- type: ndcg_at_3
value: 41.829
- type: ndcg_at_5
value: 42.525
- type: precision_at_1
value: 44.29
- type: precision_at_10
value: 12.5
- type: precision_at_100
value: 1.9720000000000002
- type: precision_at_1000
value: 0.245
- type: precision_at_3
value: 28.035
- type: precision_at_5
value: 20.093
- type: recall_at_1
value: 22.532
- type: recall_at_10
value: 52.419000000000004
- type: recall_at_100
value: 77.43299999999999
- type: recall_at_1000
value: 93.379
- type: recall_at_3
value: 38.629000000000005
- type: recall_at_5
value: 43.858000000000004
- task:
type: Retrieval
dataset:
name: MTEB HotpotQA
type: hotpotqa
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 39.359
- type: map_at_10
value: 63.966
- type: map_at_100
value: 64.87
- type: map_at_1000
value: 64.92599999999999
- type: map_at_3
value: 60.409
- type: map_at_5
value: 62.627
- type: mrr_at_1
value: 78.717
- type: mrr_at_10
value: 84.468
- type: mrr_at_100
value: 84.655
- type: mrr_at_1000
value: 84.661
- type: mrr_at_3
value: 83.554
- type: mrr_at_5
value: 84.133
- type: ndcg_at_1
value: 78.717
- type: ndcg_at_10
value: 72.03399999999999
- type: ndcg_at_100
value: 75.158
- type: ndcg_at_1000
value: 76.197
- type: ndcg_at_3
value: 67.049
- type: ndcg_at_5
value: 69.808
- type: precision_at_1
value: 78.717
- type: precision_at_10
value: 15.201
- type: precision_at_100
value: 1.764
- type: precision_at_1000
value: 0.19
- type: precision_at_3
value: 43.313
- type: precision_at_5
value: 28.165000000000003
- type: recall_at_1
value: 39.359
- type: recall_at_10
value: 76.003
- type: recall_at_100
value: 88.197
- type: recall_at_1000
value: 95.003
- type: recall_at_3
value: 64.97
- type: recall_at_5
value: 70.41199999999999
- task:
type: Classification
dataset:
name: MTEB ImdbClassification
type: mteb/imdb
config: default
split: test
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
metrics:
- type: accuracy
value: 92.83200000000001
- type: ap
value: 89.33560571859861
- type: f1
value: 92.82322915005167
- task:
type: Retrieval
dataset:
name: MTEB MSMARCO
type: msmarco
config: default
split: dev
revision: None
metrics:
- type: map_at_1
value: 21.983
- type: map_at_10
value: 34.259
- type: map_at_100
value: 35.432
- type: map_at_1000
value: 35.482
- type: map_at_3
value: 30.275999999999996
- type: map_at_5
value: 32.566
- type: mrr_at_1
value: 22.579
- type: mrr_at_10
value: 34.882999999999996
- type: mrr_at_100
value: 35.984
- type: mrr_at_1000
value: 36.028
- type: mrr_at_3
value: 30.964999999999996
- type: mrr_at_5
value: 33.245000000000005
- type: ndcg_at_1
value: 22.564
- type: ndcg_at_10
value: 41.258
- type: ndcg_at_100
value: 46.824
- type: ndcg_at_1000
value: 48.037
- type: ndcg_at_3
value: 33.17
- type: ndcg_at_5
value: 37.263000000000005
- type: precision_at_1
value: 22.564
- type: precision_at_10
value: 6.572
- type: precision_at_100
value: 0.935
- type: precision_at_1000
value: 0.104
- type: precision_at_3
value: 14.130999999999998
- type: precision_at_5
value: 10.544
- type: recall_at_1
value: 21.983
- type: recall_at_10
value: 62.775000000000006
- type: recall_at_100
value: 88.389
- type: recall_at_1000
value: 97.603
- type: recall_at_3
value: 40.878
- type: recall_at_5
value: 50.690000000000005
- task:
type: Classification
dataset:
name: MTEB MTOPDomainClassification (en)
type: mteb/mtop_domain
config: en
split: test
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
metrics:
- type: accuracy
value: 93.95120839033288
- type: f1
value: 93.73824125055208
- task:
type: Classification
dataset:
name: MTEB MTOPIntentClassification (en)
type: mteb/mtop_intent
config: en
split: test
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
metrics:
- type: accuracy
value: 76.78978568171455
- type: f1
value: 57.50180552858304
- task:
type: Classification
dataset:
name: MTEB MassiveIntentClassification (en)
type: mteb/amazon_massive_intent
config: en
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 76.24411566913248
- type: f1
value: 74.37851403532832
- task:
type: Classification
dataset:
name: MTEB MassiveScenarioClassification (en)
type: mteb/amazon_massive_scenario
config: en
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 79.94620040349699
- type: f1
value: 80.21293397970435
- task:
type: Clustering
dataset:
name: MTEB MedrxivClusteringP2P
type: mteb/medrxiv-clustering-p2p
config: default
split: test
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
metrics:
- type: v_measure
value: 33.44403096245675
- task:
type: Clustering
dataset:
name: MTEB MedrxivClusteringS2S
type: mteb/medrxiv-clustering-s2s
config: default
split: test
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
metrics:
- type: v_measure
value: 31.659594631336812
- task:
type: Reranking
dataset:
name: MTEB MindSmallReranking
type: mteb/mind_small
config: default
split: test
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
metrics:
- type: map
value: 32.53833075108798
- type: mrr
value: 33.78840823218308
- task:
type: Retrieval
dataset:
name: MTEB NFCorpus
type: nfcorpus
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 7.185999999999999
- type: map_at_10
value: 15.193999999999999
- type: map_at_100
value: 19.538
- type: map_at_1000
value: 21.178
- type: map_at_3
value: 11.208
- type: map_at_5
value: 12.745999999999999
- type: mrr_at_1
value: 48.916
- type: mrr_at_10
value: 58.141
- type: mrr_at_100
value: 58.656
- type: mrr_at_1000
value: 58.684999999999995
- type: mrr_at_3
value: 55.521
- type: mrr_at_5
value: 57.239
- type: ndcg_at_1
value: 47.059
- type: ndcg_at_10
value: 38.644
- type: ndcg_at_100
value: 36.272999999999996
- type: ndcg_at_1000
value: 44.996
- type: ndcg_at_3
value: 43.293
- type: ndcg_at_5
value: 40.819
- type: precision_at_1
value: 48.916
- type: precision_at_10
value: 28.607
- type: precision_at_100
value: 9.195
- type: precision_at_1000
value: 2.225
- type: precision_at_3
value: 40.454
- type: precision_at_5
value: 34.985
- type: recall_at_1
value: 7.185999999999999
- type: recall_at_10
value: 19.654
- type: recall_at_100
value: 37.224000000000004
- type: recall_at_1000
value: 68.663
- type: recall_at_3
value: 12.158
- type: recall_at_5
value: 14.674999999999999
- task:
type: Retrieval
dataset:
name: MTEB NQ
type: nq
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 31.552000000000003
- type: map_at_10
value: 47.75
- type: map_at_100
value: 48.728
- type: map_at_1000
value: 48.754
- type: map_at_3
value: 43.156
- type: map_at_5
value: 45.883
- type: mrr_at_1
value: 35.66
- type: mrr_at_10
value: 50.269
- type: mrr_at_100
value: 50.974
- type: mrr_at_1000
value: 50.991
- type: mrr_at_3
value: 46.519
- type: mrr_at_5
value: 48.764
- type: ndcg_at_1
value: 35.632000000000005
- type: ndcg_at_10
value: 55.786
- type: ndcg_at_100
value: 59.748999999999995
- type: ndcg_at_1000
value: 60.339
- type: ndcg_at_3
value: 47.292
- type: ndcg_at_5
value: 51.766999999999996
- type: precision_at_1
value: 35.632000000000005
- type: precision_at_10
value: 9.267
- type: precision_at_100
value: 1.149
- type: precision_at_1000
value: 0.12
- type: precision_at_3
value: 21.601
- type: precision_at_5
value: 15.539
- type: recall_at_1
value: 31.552000000000003
- type: recall_at_10
value: 77.62400000000001
- type: recall_at_100
value: 94.527
- type: recall_at_1000
value: 98.919
- type: recall_at_3
value: 55.898
- type: recall_at_5
value: 66.121
- task:
type: Retrieval
dataset:
name: MTEB QuoraRetrieval
type: quora
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 71.414
- type: map_at_10
value: 85.37400000000001
- type: map_at_100
value: 86.01100000000001
- type: map_at_1000
value: 86.027
- type: map_at_3
value: 82.562
- type: map_at_5
value: 84.284
- type: mrr_at_1
value: 82.24000000000001
- type: mrr_at_10
value: 88.225
- type: mrr_at_100
value: 88.324
- type: mrr_at_1000
value: 88.325
- type: mrr_at_3
value: 87.348
- type: mrr_at_5
value: 87.938
- type: ndcg_at_1
value: 82.24000000000001
- type: ndcg_at_10
value: 88.97699999999999
- type: ndcg_at_100
value: 90.16
- type: ndcg_at_1000
value: 90.236
- type: ndcg_at_3
value: 86.371
- type: ndcg_at_5
value: 87.746
- type: precision_at_1
value: 82.24000000000001
- type: precision_at_10
value: 13.481000000000002
- type: precision_at_100
value: 1.534
- type: precision_at_1000
value: 0.157
- type: precision_at_3
value: 37.86
- type: precision_at_5
value: 24.738
- type: recall_at_1
value: 71.414
- type: recall_at_10
value: 95.735
- type: recall_at_100
value: 99.696
- type: recall_at_1000
value: 99.979
- type: recall_at_3
value: 88.105
- type: recall_at_5
value: 92.17999999999999
- task:
type: Clustering
dataset:
name: MTEB RedditClustering
type: mteb/reddit-clustering
config: default
split: test
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
metrics:
- type: v_measure
value: 60.22146692057259
- task:
type: Clustering
dataset:
name: MTEB RedditClusteringP2P
type: mteb/reddit-clustering-p2p
config: default
split: test
revision: 282350215ef01743dc01b456c7f5241fa8937f16
metrics:
- type: v_measure
value: 65.29273320614578
- task:
type: Retrieval
dataset:
name: MTEB SCIDOCS
type: scidocs
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 5.023
- type: map_at_10
value: 14.161000000000001
- type: map_at_100
value: 16.68
- type: map_at_1000
value: 17.072000000000003
- type: map_at_3
value: 9.763
- type: map_at_5
value: 11.977
- type: mrr_at_1
value: 24.8
- type: mrr_at_10
value: 37.602999999999994
- type: mrr_at_100
value: 38.618
- type: mrr_at_1000
value: 38.659
- type: mrr_at_3
value: 34.117
- type: mrr_at_5
value: 36.082
- type: ndcg_at_1
value: 24.8
- type: ndcg_at_10
value: 23.316
- type: ndcg_at_100
value: 32.613
- type: ndcg_at_1000
value: 38.609
- type: ndcg_at_3
value: 21.697
- type: ndcg_at_5
value: 19.241
- type: precision_at_1
value: 24.8
- type: precision_at_10
value: 12.36
- type: precision_at_100
value: 2.593
- type: precision_at_1000
value: 0.402
- type: precision_at_3
value: 20.767
- type: precision_at_5
value: 17.34
- type: recall_at_1
value: 5.023
- type: recall_at_10
value: 25.069999999999997
- type: recall_at_100
value: 52.563
- type: recall_at_1000
value: 81.525
- type: recall_at_3
value: 12.613
- type: recall_at_5
value: 17.583
- task:
type: STS
dataset:
name: MTEB SICK-R
type: mteb/sickr-sts
config: default
split: test
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
metrics:
- type: cos_sim_pearson
value: 87.71506247604255
- type: cos_sim_spearman
value: 82.91813463738802
- type: euclidean_pearson
value: 85.5154616194479
- type: euclidean_spearman
value: 82.91815254466314
- type: manhattan_pearson
value: 85.5280917850374
- type: manhattan_spearman
value: 82.92276537286398
- task:
type: STS
dataset:
name: MTEB STS12
type: mteb/sts12-sts
config: default
split: test
revision: a0d554a64d88156834ff5ae9920b964011b16384
metrics:
- type: cos_sim_pearson
value: 87.43772054228462
- type: cos_sim_spearman
value: 78.75750601716682
- type: euclidean_pearson
value: 85.76074482955764
- type: euclidean_spearman
value: 78.75651057223058
- type: manhattan_pearson
value: 85.73390291701668
- type: manhattan_spearman
value: 78.72699385957797
- task:
type: STS
dataset:
name: MTEB STS13
type: mteb/sts13-sts
config: default
split: test
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
metrics:
- type: cos_sim_pearson
value: 89.58144067172472
- type: cos_sim_spearman
value: 90.3524512966946
- type: euclidean_pearson
value: 89.71365391594237
- type: euclidean_spearman
value: 90.35239632843408
- type: manhattan_pearson
value: 89.66905421746478
- type: manhattan_spearman
value: 90.31508211683513
- task:
type: STS
dataset:
name: MTEB STS14
type: mteb/sts14-sts
config: default
split: test
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
metrics:
- type: cos_sim_pearson
value: 87.77692637102102
- type: cos_sim_spearman
value: 85.45710562643485
- type: euclidean_pearson
value: 87.42456979928723
- type: euclidean_spearman
value: 85.45709386240908
- type: manhattan_pearson
value: 87.40754529526272
- type: manhattan_spearman
value: 85.44834854173303
- task:
type: STS
dataset:
name: MTEB STS15
type: mteb/sts15-sts
config: default
split: test
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
metrics:
- type: cos_sim_pearson
value: 88.28491331695997
- type: cos_sim_spearman
value: 89.62037029566964
- type: euclidean_pearson
value: 89.02479391362826
- type: euclidean_spearman
value: 89.62036733618466
- type: manhattan_pearson
value: 89.00394756040342
- type: manhattan_spearman
value: 89.60867744215236
- task:
type: STS
dataset:
name: MTEB STS16
type: mteb/sts16-sts
config: default
split: test
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
metrics:
- type: cos_sim_pearson
value: 85.08911381280191
- type: cos_sim_spearman
value: 86.5791780765767
- type: euclidean_pearson
value: 86.16063473577861
- type: euclidean_spearman
value: 86.57917745378766
- type: manhattan_pearson
value: 86.13677924604175
- type: manhattan_spearman
value: 86.56115615768685
- task:
type: STS
dataset:
name: MTEB STS17 (en-en)
type: mteb/sts17-crosslingual-sts
config: en-en
split: test
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
metrics:
- type: cos_sim_pearson
value: 89.58029496205235
- type: cos_sim_spearman
value: 89.49551253826998
- type: euclidean_pearson
value: 90.13714840963748
- type: euclidean_spearman
value: 89.49551253826998
- type: manhattan_pearson
value: 90.13039633601363
- type: manhattan_spearman
value: 89.4513453745516
- task:
type: STS
dataset:
name: MTEB STS22 (en)
type: mteb/sts22-crosslingual-sts
config: en
split: test
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
metrics:
- type: cos_sim_pearson
value: 69.01546399666435
- type: cos_sim_spearman
value: 69.33824484595624
- type: euclidean_pearson
value: 70.76511642998874
- type: euclidean_spearman
value: 69.33824484595624
- type: manhattan_pearson
value: 70.84320785047453
- type: manhattan_spearman
value: 69.54233632223537
- task:
type: STS
dataset:
name: MTEB STSBenchmark
type: mteb/stsbenchmark-sts
config: default
split: test
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
metrics:
- type: cos_sim_pearson
value: 87.26389196390119
- type: cos_sim_spearman
value: 89.09721478341385
- type: euclidean_pearson
value: 88.97208685922517
- type: euclidean_spearman
value: 89.09720927308881
- type: manhattan_pearson
value: 88.97513670502573
- type: manhattan_spearman
value: 89.07647853984004
- task:
type: Reranking
dataset:
name: MTEB SciDocsRR
type: mteb/scidocs-reranking
config: default
split: test
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
metrics:
- type: map
value: 87.53075025771936
- type: mrr
value: 96.24327651288436
- task:
type: Retrieval
dataset:
name: MTEB SciFact
type: scifact
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 60.428000000000004
- type: map_at_10
value: 70.088
- type: map_at_100
value: 70.589
- type: map_at_1000
value: 70.614
- type: map_at_3
value: 67.191
- type: map_at_5
value: 68.515
- type: mrr_at_1
value: 63.333
- type: mrr_at_10
value: 71.13000000000001
- type: mrr_at_100
value: 71.545
- type: mrr_at_1000
value: 71.569
- type: mrr_at_3
value: 68.944
- type: mrr_at_5
value: 70.078
- type: ndcg_at_1
value: 63.333
- type: ndcg_at_10
value: 74.72800000000001
- type: ndcg_at_100
value: 76.64999999999999
- type: ndcg_at_1000
value: 77.176
- type: ndcg_at_3
value: 69.659
- type: ndcg_at_5
value: 71.626
- type: precision_at_1
value: 63.333
- type: precision_at_10
value: 10
- type: precision_at_100
value: 1.09
- type: precision_at_1000
value: 0.11299999999999999
- type: precision_at_3
value: 27.111
- type: precision_at_5
value: 17.666999999999998
- type: recall_at_1
value: 60.428000000000004
- type: recall_at_10
value: 87.98899999999999
- type: recall_at_100
value: 96.167
- type: recall_at_1000
value: 100
- type: recall_at_3
value: 74.006
- type: recall_at_5
value: 79.05
- task:
type: PairClassification
dataset:
name: MTEB SprintDuplicateQuestions
type: mteb/sprintduplicatequestions-pairclassification
config: default
split: test
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
metrics:
- type: cos_sim_accuracy
value: 99.87326732673267
- type: cos_sim_ap
value: 96.81770773701805
- type: cos_sim_f1
value: 93.6318407960199
- type: cos_sim_precision
value: 93.16831683168317
- type: cos_sim_recall
value: 94.1
- type: dot_accuracy
value: 99.87326732673267
- type: dot_ap
value: 96.8174218946665
- type: dot_f1
value: 93.6318407960199
- type: dot_precision
value: 93.16831683168317
- type: dot_recall
value: 94.1
- type: euclidean_accuracy
value: 99.87326732673267
- type: euclidean_ap
value: 96.81770773701807
- type: euclidean_f1
value: 93.6318407960199
- type: euclidean_precision
value: 93.16831683168317
- type: euclidean_recall
value: 94.1
- type: manhattan_accuracy
value: 99.87227722772278
- type: manhattan_ap
value: 96.83164126821747
- type: manhattan_f1
value: 93.54677338669335
- type: manhattan_precision
value: 93.5935935935936
- type: manhattan_recall
value: 93.5
- type: max_accuracy
value: 99.87326732673267
- type: max_ap
value: 96.83164126821747
- type: max_f1
value: 93.6318407960199
- task:
type: Clustering
dataset:
name: MTEB StackExchangeClustering
type: mteb/stackexchange-clustering
config: default
split: test
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
metrics:
- type: v_measure
value: 65.6212042420246
- task:
type: Clustering
dataset:
name: MTEB StackExchangeClusteringP2P
type: mteb/stackexchange-clustering-p2p
config: default
split: test
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
metrics:
- type: v_measure
value: 35.779230635982564
- task:
type: Reranking
dataset:
name: MTEB StackOverflowDupQuestions
type: mteb/stackoverflowdupquestions-reranking
config: default
split: test
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
metrics:
- type: map
value: 55.217701909036286
- type: mrr
value: 56.17658995416349
- task:
type: Summarization
dataset:
name: MTEB SummEval
type: mteb/summeval
config: default
split: test
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
metrics:
- type: cos_sim_pearson
value: 30.954206018888453
- type: cos_sim_spearman
value: 32.71062599450096
- type: dot_pearson
value: 30.95420929056943
- type: dot_spearman
value: 32.71062599450096
- task:
type: Retrieval
dataset:
name: MTEB TRECCOVID
type: trec-covid
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 0.22699999999999998
- type: map_at_10
value: 1.924
- type: map_at_100
value: 10.525
- type: map_at_1000
value: 24.973
- type: map_at_3
value: 0.638
- type: map_at_5
value: 1.0659999999999998
- type: mrr_at_1
value: 84
- type: mrr_at_10
value: 91.067
- type: mrr_at_100
value: 91.067
- type: mrr_at_1000
value: 91.067
- type: mrr_at_3
value: 90.667
- type: mrr_at_5
value: 91.067
- type: ndcg_at_1
value: 81
- type: ndcg_at_10
value: 75.566
- type: ndcg_at_100
value: 56.387
- type: ndcg_at_1000
value: 49.834
- type: ndcg_at_3
value: 80.899
- type: ndcg_at_5
value: 80.75099999999999
- type: precision_at_1
value: 84
- type: precision_at_10
value: 79
- type: precision_at_100
value: 57.56
- type: precision_at_1000
value: 21.8
- type: precision_at_3
value: 84.667
- type: precision_at_5
value: 85.2
- type: recall_at_1
value: 0.22699999999999998
- type: recall_at_10
value: 2.136
- type: recall_at_100
value: 13.861
- type: recall_at_1000
value: 46.299
- type: recall_at_3
value: 0.6649999999999999
- type: recall_at_5
value: 1.145
- task:
type: Retrieval
dataset:
name: MTEB Touche2020
type: webis-touche2020
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 2.752
- type: map_at_10
value: 9.951
- type: map_at_100
value: 16.794999999999998
- type: map_at_1000
value: 18.251
- type: map_at_3
value: 5.288
- type: map_at_5
value: 6.954000000000001
- type: mrr_at_1
value: 38.775999999999996
- type: mrr_at_10
value: 50.458000000000006
- type: mrr_at_100
value: 51.324999999999996
- type: mrr_at_1000
value: 51.339999999999996
- type: mrr_at_3
value: 46.939
- type: mrr_at_5
value: 47.857
- type: ndcg_at_1
value: 36.735
- type: ndcg_at_10
value: 25.198999999999998
- type: ndcg_at_100
value: 37.938
- type: ndcg_at_1000
value: 49.145
- type: ndcg_at_3
value: 29.348000000000003
- type: ndcg_at_5
value: 25.804
- type: precision_at_1
value: 38.775999999999996
- type: precision_at_10
value: 22.041
- type: precision_at_100
value: 7.939
- type: precision_at_1000
value: 1.555
- type: precision_at_3
value: 29.932
- type: precision_at_5
value: 24.490000000000002
- type: recall_at_1
value: 2.752
- type: recall_at_10
value: 16.197
- type: recall_at_100
value: 49.166
- type: recall_at_1000
value: 84.18900000000001
- type: recall_at_3
value: 6.438000000000001
- type: recall_at_5
value: 9.093
- task:
type: Classification
dataset:
name: MTEB ToxicConversationsClassification
type: mteb/toxic_conversations_50k
config: default
split: test
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
metrics:
- type: accuracy
value: 71.47980000000001
- type: ap
value: 14.605194452178754
- type: f1
value: 55.07362924988948
- task:
type: Classification
dataset:
name: MTEB TweetSentimentExtractionClassification
type: mteb/tweet_sentiment_extraction
config: default
split: test
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
metrics:
- type: accuracy
value: 59.708545557441994
- type: f1
value: 60.04751270975683
- task:
type: Clustering
dataset:
name: MTEB TwentyNewsgroupsClustering
type: mteb/twentynewsgroups-clustering
config: default
split: test
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
metrics:
- type: v_measure
value: 53.21105960597211
- task:
type: PairClassification
dataset:
name: MTEB TwitterSemEval2015
type: mteb/twittersemeval2015-pairclassification
config: default
split: test
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
metrics:
- type: cos_sim_accuracy
value: 87.58419264469214
- type: cos_sim_ap
value: 78.55300004517404
- type: cos_sim_f1
value: 71.49673530889001
- type: cos_sim_precision
value: 68.20795400095831
- type: cos_sim_recall
value: 75.11873350923483
- type: dot_accuracy
value: 87.58419264469214
- type: dot_ap
value: 78.55297659559511
- type: dot_f1
value: 71.49673530889001
- type: dot_precision
value: 68.20795400095831
- type: dot_recall
value: 75.11873350923483
- type: euclidean_accuracy
value: 87.58419264469214
- type: euclidean_ap
value: 78.55300477331477
- type: euclidean_f1
value: 71.49673530889001
- type: euclidean_precision
value: 68.20795400095831
- type: euclidean_recall
value: 75.11873350923483
- type: manhattan_accuracy
value: 87.5663110210407
- type: manhattan_ap
value: 78.49982050876562
- type: manhattan_f1
value: 71.35488740722104
- type: manhattan_precision
value: 68.18946862226497
- type: manhattan_recall
value: 74.82849604221636
- type: max_accuracy
value: 87.58419264469214
- type: max_ap
value: 78.55300477331477
- type: max_f1
value: 71.49673530889001
- task:
type: PairClassification
dataset:
name: MTEB TwitterURLCorpus
type: mteb/twitterurlcorpus-pairclassification
config: default
split: test
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
metrics:
- type: cos_sim_accuracy
value: 89.09069740365584
- type: cos_sim_ap
value: 86.22749303724757
- type: cos_sim_f1
value: 78.36863452005407
- type: cos_sim_precision
value: 76.49560117302053
- type: cos_sim_recall
value: 80.33569448721897
- type: dot_accuracy
value: 89.09069740365584
- type: dot_ap
value: 86.22750233655673
- type: dot_f1
value: 78.36863452005407
- type: dot_precision
value: 76.49560117302053
- type: dot_recall
value: 80.33569448721897
- type: euclidean_accuracy
value: 89.09069740365584
- type: euclidean_ap
value: 86.22749355597347
- type: euclidean_f1
value: 78.36863452005407
- type: euclidean_precision
value: 76.49560117302053
- type: euclidean_recall
value: 80.33569448721897
- type: manhattan_accuracy
value: 89.08293553770326
- type: manhattan_ap
value: 86.21913616084771
- type: manhattan_f1
value: 78.3907031479847
- type: manhattan_precision
value: 75.0352013517319
- type: manhattan_recall
value: 82.06036341238065
- type: max_accuracy
value: 89.09069740365584
- type: max_ap
value: 86.22750233655673
- type: max_f1
value: 78.3907031479847
nadeem1362/mxbai-embed-large-v1-Q4_K_M-GGUF
This model was converted to GGUF format from mixedbread-ai/mxbai-embed-large-v1 using llama.cpp via the ggml.ai's GGUF-my-repo space.
Refer to the original model card for more details on the model.
Use with llama.cpp
Install llama.cpp through brew.
brew install ggerganov/ggerganov/llama.cpp
Invoke the llama.cpp server or the CLI.
CLI:
llama-cli --hf-repo nadeem1362/mxbai-embed-large-v1-Q4_K_M-GGUF --model mxbai-embed-large-v1.Q4_K_M.gguf -p "The meaning to life and the universe is"
Server:
llama-server --hf-repo nadeem1362/mxbai-embed-large-v1-Q4_K_M-GGUF --model mxbai-embed-large-v1.Q4_K_M.gguf -c 2048
Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.
git clone https://github.com/ggerganov/llama.cpp && cd llama.cpp && make && ./main -m mxbai-embed-large-v1.Q4_K_M.gguf -n 128