metadata
base_model: BAAI/bge-large-en-v1.5
language:
- en
license: mit
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
- mteb
- openvino
- nncf
- 8-bit
model-index:
- name: bge-large-en-v1.5
results:
- task:
type: Classification
dataset:
name: MTEB AmazonCounterfactualClassification (en)
type: mteb/amazon_counterfactual
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
- type: accuracy
value: 75.8507462686567
- type: ap
value: 38.566457320228245
- type: f1
value: 69.69386648043475
- task:
type: Classification
dataset:
name: MTEB AmazonPolarityClassification
type: mteb/amazon_polarity
config: default
split: test
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
metrics:
- type: accuracy
value: 92.416675
- type: ap
value: 89.1928861155922
- type: f1
value: 92.39477019574215
- task:
type: Classification
dataset:
name: MTEB AmazonReviewsClassification (en)
type: mteb/amazon_reviews_multi
config: en
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy
value: 48.175999999999995
- type: f1
value: 47.80712792870253
- task:
type: Retrieval
dataset:
name: MTEB ArguAna
type: arguana
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 40.184999999999995
- type: map_at_10
value: 55.654
- type: map_at_100
value: 56.25
- type: map_at_1000
value: 56.255
- type: map_at_3
value: 51.742999999999995
- type: map_at_5
value: 54.129000000000005
- type: mrr_at_1
value: 40.967
- type: mrr_at_10
value: 55.96
- type: mrr_at_100
value: 56.54900000000001
- type: mrr_at_1000
value: 56.554
- type: mrr_at_3
value: 51.980000000000004
- type: mrr_at_5
value: 54.44
- type: ndcg_at_1
value: 40.184999999999995
- type: ndcg_at_10
value: 63.542
- type: ndcg_at_100
value: 65.96499999999999
- type: ndcg_at_1000
value: 66.08699999999999
- type: ndcg_at_3
value: 55.582
- type: ndcg_at_5
value: 59.855000000000004
- type: precision_at_1
value: 40.184999999999995
- type: precision_at_10
value: 8.841000000000001
- type: precision_at_100
value: 0.987
- type: precision_at_1000
value: 0.1
- type: precision_at_3
value: 22.238
- type: precision_at_5
value: 15.405
- type: recall_at_1
value: 40.184999999999995
- type: recall_at_10
value: 88.407
- type: recall_at_100
value: 98.72
- type: recall_at_1000
value: 99.644
- type: recall_at_3
value: 66.714
- type: recall_at_5
value: 77.027
- task:
type: Clustering
dataset:
name: MTEB ArxivClusteringP2P
type: mteb/arxiv-clustering-p2p
config: default
split: test
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
metrics:
- type: v_measure
value: 48.567077926750066
- task:
type: Clustering
dataset:
name: MTEB ArxivClusteringS2S
type: mteb/arxiv-clustering-s2s
config: default
split: test
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
metrics:
- type: v_measure
value: 43.19453389182364
- task:
type: Reranking
dataset:
name: MTEB AskUbuntuDupQuestions
type: mteb/askubuntudupquestions-reranking
config: default
split: test
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
metrics:
- type: map
value: 64.46555939623092
- type: mrr
value: 77.82361605768807
- task:
type: STS
dataset:
name: MTEB BIOSSES
type: mteb/biosses-sts
config: default
split: test
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
metrics:
- type: cos_sim_pearson
value: 84.9554128814735
- type: cos_sim_spearman
value: 84.65373612172036
- type: euclidean_pearson
value: 83.2905059954138
- type: euclidean_spearman
value: 84.52240782811128
- type: manhattan_pearson
value: 82.99533802997436
- type: manhattan_spearman
value: 84.20673798475734
- task:
type: Classification
dataset:
name: MTEB Banking77Classification
type: mteb/banking77
config: default
split: test
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
metrics:
- type: accuracy
value: 87.78896103896103
- type: f1
value: 87.77189310964883
- task:
type: Clustering
dataset:
name: MTEB BiorxivClusteringP2P
type: mteb/biorxiv-clustering-p2p
config: default
split: test
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
metrics:
- type: v_measure
value: 39.714538337650495
- task:
type: Clustering
dataset:
name: MTEB BiorxivClusteringS2S
type: mteb/biorxiv-clustering-s2s
config: default
split: test
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
metrics:
- type: v_measure
value: 36.90108349284447
- task:
type: Retrieval
dataset:
name: MTEB CQADupstackAndroidRetrieval
type: BeIR/cqadupstack
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 32.795
- type: map_at_10
value: 43.669000000000004
- type: map_at_100
value: 45.151
- type: map_at_1000
value: 45.278
- type: map_at_3
value: 40.006
- type: map_at_5
value: 42.059999999999995
- type: mrr_at_1
value: 39.771
- type: mrr_at_10
value: 49.826
- type: mrr_at_100
value: 50.504000000000005
- type: mrr_at_1000
value: 50.549
- type: mrr_at_3
value: 47.115
- type: mrr_at_5
value: 48.832
- type: ndcg_at_1
value: 39.771
- type: ndcg_at_10
value: 50.217999999999996
- type: ndcg_at_100
value: 55.454
- type: ndcg_at_1000
value: 57.37
- type: ndcg_at_3
value: 44.885000000000005
- type: ndcg_at_5
value: 47.419
- type: precision_at_1
value: 39.771
- type: precision_at_10
value: 9.642000000000001
- type: precision_at_100
value: 1.538
- type: precision_at_1000
value: 0.198
- type: precision_at_3
value: 21.268
- type: precision_at_5
value: 15.536
- type: recall_at_1
value: 32.795
- type: recall_at_10
value: 62.580999999999996
- type: recall_at_100
value: 84.438
- type: recall_at_1000
value: 96.492
- type: recall_at_3
value: 47.071000000000005
- type: recall_at_5
value: 54.079
- type: map_at_1
value: 32.671
- type: map_at_10
value: 43.334
- type: map_at_100
value: 44.566
- type: map_at_1000
value: 44.702999999999996
- type: map_at_3
value: 40.343
- type: map_at_5
value: 41.983
- type: mrr_at_1
value: 40.764
- type: mrr_at_10
value: 49.382
- type: mrr_at_100
value: 49.988
- type: mrr_at_1000
value: 50.03300000000001
- type: mrr_at_3
value: 47.293
- type: mrr_at_5
value: 48.51
- type: ndcg_at_1
value: 40.764
- type: ndcg_at_10
value: 49.039
- type: ndcg_at_100
value: 53.259
- type: ndcg_at_1000
value: 55.253
- type: ndcg_at_3
value: 45.091
- type: ndcg_at_5
value: 46.839999999999996
- type: precision_at_1
value: 40.764
- type: precision_at_10
value: 9.191
- type: precision_at_100
value: 1.476
- type: precision_at_1000
value: 0.19499999999999998
- type: precision_at_3
value: 21.72
- type: precision_at_5
value: 15.299
- type: recall_at_1
value: 32.671
- type: recall_at_10
value: 58.816
- type: recall_at_100
value: 76.654
- type: recall_at_1000
value: 89.05999999999999
- type: recall_at_3
value: 46.743
- type: recall_at_5
value: 51.783
- type: map_at_1
value: 40.328
- type: map_at_10
value: 53.32599999999999
- type: map_at_100
value: 54.37499999999999
- type: map_at_1000
value: 54.429
- type: map_at_3
value: 49.902
- type: map_at_5
value: 52.002
- type: mrr_at_1
value: 46.332
- type: mrr_at_10
value: 56.858
- type: mrr_at_100
value: 57.522
- type: mrr_at_1000
value: 57.54899999999999
- type: mrr_at_3
value: 54.472
- type: mrr_at_5
value: 55.996
- type: ndcg_at_1
value: 46.332
- type: ndcg_at_10
value: 59.313
- type: ndcg_at_100
value: 63.266999999999996
- type: ndcg_at_1000
value: 64.36
- type: ndcg_at_3
value: 53.815000000000005
- type: ndcg_at_5
value: 56.814
- type: precision_at_1
value: 46.332
- type: precision_at_10
value: 9.53
- type: precision_at_100
value: 1.238
- type: precision_at_1000
value: 0.13699999999999998
- type: precision_at_3
value: 24.054000000000002
- type: precision_at_5
value: 16.589000000000002
- type: recall_at_1
value: 40.328
- type: recall_at_10
value: 73.421
- type: recall_at_100
value: 90.059
- type: recall_at_1000
value: 97.81
- type: recall_at_3
value: 59.009
- type: recall_at_5
value: 66.352
- type: map_at_1
value: 27.424
- type: map_at_10
value: 36.332
- type: map_at_100
value: 37.347
- type: map_at_1000
value: 37.422
- type: map_at_3
value: 33.743
- type: map_at_5
value: 35.176
- type: mrr_at_1
value: 29.153000000000002
- type: mrr_at_10
value: 38.233
- type: mrr_at_100
value: 39.109
- type: mrr_at_1000
value: 39.164
- type: mrr_at_3
value: 35.876000000000005
- type: mrr_at_5
value: 37.169000000000004
- type: ndcg_at_1
value: 29.153000000000002
- type: ndcg_at_10
value: 41.439
- type: ndcg_at_100
value: 46.42
- type: ndcg_at_1000
value: 48.242000000000004
- type: ndcg_at_3
value: 36.362
- type: ndcg_at_5
value: 38.743
- type: precision_at_1
value: 29.153000000000002
- type: precision_at_10
value: 6.315999999999999
- type: precision_at_100
value: 0.927
- type: precision_at_1000
value: 0.11199999999999999
- type: precision_at_3
value: 15.443000000000001
- type: precision_at_5
value: 10.644
- type: recall_at_1
value: 27.424
- type: recall_at_10
value: 55.364000000000004
- type: recall_at_100
value: 78.211
- type: recall_at_1000
value: 91.74600000000001
- type: recall_at_3
value: 41.379
- type: recall_at_5
value: 47.14
- type: map_at_1
value: 19.601
- type: map_at_10
value: 27.826
- type: map_at_100
value: 29.017
- type: map_at_1000
value: 29.137
- type: map_at_3
value: 25.125999999999998
- type: map_at_5
value: 26.765
- type: mrr_at_1
value: 24.005000000000003
- type: mrr_at_10
value: 32.716
- type: mrr_at_100
value: 33.631
- type: mrr_at_1000
value: 33.694
- type: mrr_at_3
value: 29.934
- type: mrr_at_5
value: 31.630999999999997
- type: ndcg_at_1
value: 24.005000000000003
- type: ndcg_at_10
value: 33.158
- type: ndcg_at_100
value: 38.739000000000004
- type: ndcg_at_1000
value: 41.495
- type: ndcg_at_3
value: 28.185
- type: ndcg_at_5
value: 30.796
- type: precision_at_1
value: 24.005000000000003
- type: precision_at_10
value: 5.908
- type: precision_at_100
value: 1.005
- type: precision_at_1000
value: 0.13899999999999998
- type: precision_at_3
value: 13.391
- type: precision_at_5
value: 9.876
- type: recall_at_1
value: 19.601
- type: recall_at_10
value: 44.746
- type: recall_at_100
value: 68.82300000000001
- type: recall_at_1000
value: 88.215
- type: recall_at_3
value: 31.239
- type: recall_at_5
value: 37.695
- type: map_at_1
value: 30.130000000000003
- type: map_at_10
value: 40.96
- type: map_at_100
value: 42.282
- type: map_at_1000
value: 42.392
- type: map_at_3
value: 37.889
- type: map_at_5
value: 39.661
- type: mrr_at_1
value: 36.958999999999996
- type: mrr_at_10
value: 46.835
- type: mrr_at_100
value: 47.644
- type: mrr_at_1000
value: 47.688
- type: mrr_at_3
value: 44.562000000000005
- type: mrr_at_5
value: 45.938
- type: ndcg_at_1
value: 36.958999999999996
- type: ndcg_at_10
value: 47.06
- type: ndcg_at_100
value: 52.345
- type: ndcg_at_1000
value: 54.35
- type: ndcg_at_3
value: 42.301
- type: ndcg_at_5
value: 44.635999999999996
- type: precision_at_1
value: 36.958999999999996
- type: precision_at_10
value: 8.479000000000001
- type: precision_at_100
value: 1.284
- type: precision_at_1000
value: 0.163
- type: precision_at_3
value: 20.244
- type: precision_at_5
value: 14.224999999999998
- type: recall_at_1
value: 30.130000000000003
- type: recall_at_10
value: 59.27
- type: recall_at_100
value: 81.195
- type: recall_at_1000
value: 94.21199999999999
- type: recall_at_3
value: 45.885
- type: recall_at_5
value: 52.016
- type: map_at_1
value: 26.169999999999998
- type: map_at_10
value: 36.451
- type: map_at_100
value: 37.791000000000004
- type: map_at_1000
value: 37.897
- type: map_at_3
value: 33.109
- type: map_at_5
value: 34.937000000000005
- type: mrr_at_1
value: 32.877
- type: mrr_at_10
value: 42.368
- type: mrr_at_100
value: 43.201
- type: mrr_at_1000
value: 43.259
- type: mrr_at_3
value: 39.763999999999996
- type: mrr_at_5
value: 41.260000000000005
- type: ndcg_at_1
value: 32.877
- type: ndcg_at_10
value: 42.659000000000006
- type: ndcg_at_100
value: 48.161
- type: ndcg_at_1000
value: 50.345
- type: ndcg_at_3
value: 37.302
- type: ndcg_at_5
value: 39.722
- type: precision_at_1
value: 32.877
- type: precision_at_10
value: 7.9
- type: precision_at_100
value: 1.236
- type: precision_at_1000
value: 0.158
- type: precision_at_3
value: 17.846
- type: precision_at_5
value: 12.9
- type: recall_at_1
value: 26.169999999999998
- type: recall_at_10
value: 55.35
- type: recall_at_100
value: 78.755
- type: recall_at_1000
value: 93.518
- type: recall_at_3
value: 40.176
- type: recall_at_5
value: 46.589000000000006
- type: map_at_1
value: 27.15516666666667
- type: map_at_10
value: 36.65741666666667
- type: map_at_100
value: 37.84991666666666
- type: map_at_1000
value: 37.96316666666667
- type: map_at_3
value: 33.74974999999999
- type: map_at_5
value: 35.3765
- type: mrr_at_1
value: 32.08233333333334
- type: mrr_at_10
value: 41.033833333333334
- type: mrr_at_100
value: 41.84524999999999
- type: mrr_at_1000
value: 41.89983333333333
- type: mrr_at_3
value: 38.62008333333333
- type: mrr_at_5
value: 40.03441666666666
- type: ndcg_at_1
value: 32.08233333333334
- type: ndcg_at_10
value: 42.229
- type: ndcg_at_100
value: 47.26716666666667
- type: ndcg_at_1000
value: 49.43466666666667
- type: ndcg_at_3
value: 37.36408333333333
- type: ndcg_at_5
value: 39.6715
- type: precision_at_1
value: 32.08233333333334
- type: precision_at_10
value: 7.382583333333334
- type: precision_at_100
value: 1.16625
- type: precision_at_1000
value: 0.15408333333333332
- type: precision_at_3
value: 17.218
- type: precision_at_5
value: 12.21875
- type: recall_at_1
value: 27.15516666666667
- type: recall_at_10
value: 54.36683333333333
- type: recall_at_100
value: 76.37183333333333
- type: recall_at_1000
value: 91.26183333333333
- type: recall_at_3
value: 40.769916666666674
- type: recall_at_5
value: 46.702333333333335
- type: map_at_1
value: 25.749
- type: map_at_10
value: 33.001999999999995
- type: map_at_100
value: 33.891
- type: map_at_1000
value: 33.993
- type: map_at_3
value: 30.703999999999997
- type: map_at_5
value: 31.959
- type: mrr_at_1
value: 28.834
- type: mrr_at_10
value: 35.955
- type: mrr_at_100
value: 36.709
- type: mrr_at_1000
value: 36.779
- type: mrr_at_3
value: 33.947
- type: mrr_at_5
value: 35.089
- type: ndcg_at_1
value: 28.834
- type: ndcg_at_10
value: 37.329
- type: ndcg_at_100
value: 41.79
- type: ndcg_at_1000
value: 44.169000000000004
- type: ndcg_at_3
value: 33.184999999999995
- type: ndcg_at_5
value: 35.107
- type: precision_at_1
value: 28.834
- type: precision_at_10
value: 5.7669999999999995
- type: precision_at_100
value: 0.876
- type: precision_at_1000
value: 0.11399999999999999
- type: precision_at_3
value: 14.213000000000001
- type: precision_at_5
value: 9.754999999999999
- type: recall_at_1
value: 25.749
- type: recall_at_10
value: 47.791
- type: recall_at_100
value: 68.255
- type: recall_at_1000
value: 85.749
- type: recall_at_3
value: 36.199
- type: recall_at_5
value: 41.071999999999996
- type: map_at_1
value: 17.777
- type: map_at_10
value: 25.201
- type: map_at_100
value: 26.423999999999996
- type: map_at_1000
value: 26.544
- type: map_at_3
value: 22.869
- type: map_at_5
value: 24.023
- type: mrr_at_1
value: 21.473
- type: mrr_at_10
value: 29.12
- type: mrr_at_100
value: 30.144
- type: mrr_at_1000
value: 30.215999999999998
- type: mrr_at_3
value: 26.933
- type: mrr_at_5
value: 28.051
- type: ndcg_at_1
value: 21.473
- type: ndcg_at_10
value: 30.003
- type: ndcg_at_100
value: 35.766
- type: ndcg_at_1000
value: 38.501000000000005
- type: ndcg_at_3
value: 25.773000000000003
- type: ndcg_at_5
value: 27.462999999999997
- type: precision_at_1
value: 21.473
- type: precision_at_10
value: 5.482
- type: precision_at_100
value: 0.975
- type: precision_at_1000
value: 0.13799999999999998
- type: precision_at_3
value: 12.205
- type: precision_at_5
value: 8.692
- type: recall_at_1
value: 17.777
- type: recall_at_10
value: 40.582
- type: recall_at_100
value: 66.305
- type: recall_at_1000
value: 85.636
- type: recall_at_3
value: 28.687
- type: recall_at_5
value: 33.089
- type: map_at_1
value: 26.677
- type: map_at_10
value: 36.309000000000005
- type: map_at_100
value: 37.403999999999996
- type: map_at_1000
value: 37.496
- type: map_at_3
value: 33.382
- type: map_at_5
value: 34.98
- type: mrr_at_1
value: 31.343
- type: mrr_at_10
value: 40.549
- type: mrr_at_100
value: 41.342
- type: mrr_at_1000
value: 41.397
- type: mrr_at_3
value: 38.029
- type: mrr_at_5
value: 39.451
- type: ndcg_at_1
value: 31.343
- type: ndcg_at_10
value: 42.1
- type: ndcg_at_100
value: 47.089999999999996
- type: ndcg_at_1000
value: 49.222
- type: ndcg_at_3
value: 36.836999999999996
- type: ndcg_at_5
value: 39.21
- type: precision_at_1
value: 31.343
- type: precision_at_10
value: 7.164
- type: precision_at_100
value: 1.0959999999999999
- type: precision_at_1000
value: 0.13899999999999998
- type: precision_at_3
value: 16.915
- type: precision_at_5
value: 11.940000000000001
- type: recall_at_1
value: 26.677
- type: recall_at_10
value: 55.54599999999999
- type: recall_at_100
value: 77.094
- type: recall_at_1000
value: 92.01
- type: recall_at_3
value: 41.191
- type: recall_at_5
value: 47.006
- type: map_at_1
value: 24.501
- type: map_at_10
value: 33.102
- type: map_at_100
value: 34.676
- type: map_at_1000
value: 34.888000000000005
- type: map_at_3
value: 29.944
- type: map_at_5
value: 31.613999999999997
- type: mrr_at_1
value: 29.447000000000003
- type: mrr_at_10
value: 37.996
- type: mrr_at_100
value: 38.946
- type: mrr_at_1000
value: 38.995000000000005
- type: mrr_at_3
value: 35.079
- type: mrr_at_5
value: 36.69
- type: ndcg_at_1
value: 29.447000000000003
- type: ndcg_at_10
value: 39.232
- type: ndcg_at_100
value: 45.247
- type: ndcg_at_1000
value: 47.613
- type: ndcg_at_3
value: 33.922999999999995
- type: ndcg_at_5
value: 36.284
- type: precision_at_1
value: 29.447000000000003
- type: precision_at_10
value: 7.648000000000001
- type: precision_at_100
value: 1.516
- type: precision_at_1000
value: 0.23900000000000002
- type: precision_at_3
value: 16.008
- type: precision_at_5
value: 11.779
- type: recall_at_1
value: 24.501
- type: recall_at_10
value: 51.18899999999999
- type: recall_at_100
value: 78.437
- type: recall_at_1000
value: 92.842
- type: recall_at_3
value: 35.808
- type: recall_at_5
value: 42.197
- type: map_at_1
value: 22.039
- type: map_at_10
value: 30.377
- type: map_at_100
value: 31.275
- type: map_at_1000
value: 31.379
- type: map_at_3
value: 27.98
- type: map_at_5
value: 29.358
- type: mrr_at_1
value: 24.03
- type: mrr_at_10
value: 32.568000000000005
- type: mrr_at_100
value: 33.403
- type: mrr_at_1000
value: 33.475
- type: mrr_at_3
value: 30.436999999999998
- type: mrr_at_5
value: 31.796000000000003
- type: ndcg_at_1
value: 24.03
- type: ndcg_at_10
value: 35.198
- type: ndcg_at_100
value: 39.668
- type: ndcg_at_1000
value: 42.296
- type: ndcg_at_3
value: 30.709999999999997
- type: ndcg_at_5
value: 33.024
- type: precision_at_1
value: 24.03
- type: precision_at_10
value: 5.564
- type: precision_at_100
value: 0.828
- type: precision_at_1000
value: 0.117
- type: precision_at_3
value: 13.309000000000001
- type: precision_at_5
value: 9.39
- type: recall_at_1
value: 22.039
- type: recall_at_10
value: 47.746
- type: recall_at_100
value: 68.23599999999999
- type: recall_at_1000
value: 87.852
- type: recall_at_3
value: 35.852000000000004
- type: recall_at_5
value: 41.410000000000004
- task:
type: Retrieval
dataset:
name: MTEB ClimateFEVER
type: climate-fever
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 15.692999999999998
- type: map_at_10
value: 26.903
- type: map_at_100
value: 28.987000000000002
- type: map_at_1000
value: 29.176999999999996
- type: map_at_3
value: 22.137
- type: map_at_5
value: 24.758
- type: mrr_at_1
value: 35.57
- type: mrr_at_10
value: 47.821999999999996
- type: mrr_at_100
value: 48.608000000000004
- type: mrr_at_1000
value: 48.638999999999996
- type: mrr_at_3
value: 44.452000000000005
- type: mrr_at_5
value: 46.546
- type: ndcg_at_1
value: 35.57
- type: ndcg_at_10
value: 36.567
- type: ndcg_at_100
value: 44.085
- type: ndcg_at_1000
value: 47.24
- type: ndcg_at_3
value: 29.964000000000002
- type: ndcg_at_5
value: 32.511
- type: precision_at_1
value: 35.57
- type: precision_at_10
value: 11.485
- type: precision_at_100
value: 1.9619999999999997
- type: precision_at_1000
value: 0.256
- type: precision_at_3
value: 22.237000000000002
- type: precision_at_5
value: 17.471999999999998
- type: recall_at_1
value: 15.692999999999998
- type: recall_at_10
value: 43.056
- type: recall_at_100
value: 68.628
- type: recall_at_1000
value: 86.075
- type: recall_at_3
value: 26.918999999999997
- type: recall_at_5
value: 34.14
- task:
type: Retrieval
dataset:
name: MTEB DBPedia
type: dbpedia-entity
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 9.53
- type: map_at_10
value: 20.951
- type: map_at_100
value: 30.136000000000003
- type: map_at_1000
value: 31.801000000000002
- type: map_at_3
value: 15.021
- type: map_at_5
value: 17.471999999999998
- type: mrr_at_1
value: 71
- type: mrr_at_10
value: 79.176
- type: mrr_at_100
value: 79.418
- type: mrr_at_1000
value: 79.426
- type: mrr_at_3
value: 78.125
- type: mrr_at_5
value: 78.61200000000001
- type: ndcg_at_1
value: 58.5
- type: ndcg_at_10
value: 44.106
- type: ndcg_at_100
value: 49.268
- type: ndcg_at_1000
value: 56.711999999999996
- type: ndcg_at_3
value: 48.934
- type: ndcg_at_5
value: 45.826
- type: precision_at_1
value: 71
- type: precision_at_10
value: 35
- type: precision_at_100
value: 11.360000000000001
- type: precision_at_1000
value: 2.046
- type: precision_at_3
value: 52.833
- type: precision_at_5
value: 44.15
- type: recall_at_1
value: 9.53
- type: recall_at_10
value: 26.811
- type: recall_at_100
value: 55.916999999999994
- type: recall_at_1000
value: 79.973
- type: recall_at_3
value: 16.413
- type: recall_at_5
value: 19.980999999999998
- task:
type: Classification
dataset:
name: MTEB EmotionClassification
type: mteb/emotion
config: default
split: test
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
metrics:
- type: accuracy
value: 51.519999999999996
- type: f1
value: 46.36601294761231
- task:
type: Retrieval
dataset:
name: MTEB FEVER
type: fever
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 74.413
- type: map_at_10
value: 83.414
- type: map_at_100
value: 83.621
- type: map_at_1000
value: 83.635
- type: map_at_3
value: 82.337
- type: map_at_5
value: 83.039
- type: mrr_at_1
value: 80.19800000000001
- type: mrr_at_10
value: 87.715
- type: mrr_at_100
value: 87.778
- type: mrr_at_1000
value: 87.779
- type: mrr_at_3
value: 87.106
- type: mrr_at_5
value: 87.555
- type: ndcg_at_1
value: 80.19800000000001
- type: ndcg_at_10
value: 87.182
- type: ndcg_at_100
value: 87.90299999999999
- type: ndcg_at_1000
value: 88.143
- type: ndcg_at_3
value: 85.60600000000001
- type: ndcg_at_5
value: 86.541
- type: precision_at_1
value: 80.19800000000001
- type: precision_at_10
value: 10.531
- type: precision_at_100
value: 1.113
- type: precision_at_1000
value: 0.11499999999999999
- type: precision_at_3
value: 32.933
- type: precision_at_5
value: 20.429
- type: recall_at_1
value: 74.413
- type: recall_at_10
value: 94.363
- type: recall_at_100
value: 97.165
- type: recall_at_1000
value: 98.668
- type: recall_at_3
value: 90.108
- type: recall_at_5
value: 92.52
- task:
type: Retrieval
dataset:
name: MTEB FiQA2018
type: fiqa
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 22.701
- type: map_at_10
value: 37.122
- type: map_at_100
value: 39.178000000000004
- type: map_at_1000
value: 39.326
- type: map_at_3
value: 32.971000000000004
- type: map_at_5
value: 35.332
- type: mrr_at_1
value: 44.753
- type: mrr_at_10
value: 53.452
- type: mrr_at_100
value: 54.198
- type: mrr_at_1000
value: 54.225
- type: mrr_at_3
value: 50.952
- type: mrr_at_5
value: 52.464
- type: ndcg_at_1
value: 44.753
- type: ndcg_at_10
value: 45.021
- type: ndcg_at_100
value: 52.028
- type: ndcg_at_1000
value: 54.596000000000004
- type: ndcg_at_3
value: 41.622
- type: ndcg_at_5
value: 42.736000000000004
- type: precision_at_1
value: 44.753
- type: precision_at_10
value: 12.284
- type: precision_at_100
value: 1.955
- type: precision_at_1000
value: 0.243
- type: precision_at_3
value: 27.828999999999997
- type: precision_at_5
value: 20.061999999999998
- type: recall_at_1
value: 22.701
- type: recall_at_10
value: 51.432
- type: recall_at_100
value: 77.009
- type: recall_at_1000
value: 92.511
- type: recall_at_3
value: 37.919000000000004
- type: recall_at_5
value: 44.131
- task:
type: Retrieval
dataset:
name: MTEB HotpotQA
type: hotpotqa
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 40.189
- type: map_at_10
value: 66.24600000000001
- type: map_at_100
value: 67.098
- type: map_at_1000
value: 67.149
- type: map_at_3
value: 62.684
- type: map_at_5
value: 64.974
- type: mrr_at_1
value: 80.378
- type: mrr_at_10
value: 86.127
- type: mrr_at_100
value: 86.29299999999999
- type: mrr_at_1000
value: 86.297
- type: mrr_at_3
value: 85.31400000000001
- type: mrr_at_5
value: 85.858
- type: ndcg_at_1
value: 80.378
- type: ndcg_at_10
value: 74.101
- type: ndcg_at_100
value: 76.993
- type: ndcg_at_1000
value: 77.948
- type: ndcg_at_3
value: 69.232
- type: ndcg_at_5
value: 72.04599999999999
- type: precision_at_1
value: 80.378
- type: precision_at_10
value: 15.595999999999998
- type: precision_at_100
value: 1.7840000000000003
- type: precision_at_1000
value: 0.191
- type: precision_at_3
value: 44.884
- type: precision_at_5
value: 29.145
- type: recall_at_1
value: 40.189
- type: recall_at_10
value: 77.981
- type: recall_at_100
value: 89.21
- type: recall_at_1000
value: 95.48299999999999
- type: recall_at_3
value: 67.326
- type: recall_at_5
value: 72.863
- task:
type: Classification
dataset:
name: MTEB ImdbClassification
type: mteb/imdb
config: default
split: test
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
metrics:
- type: accuracy
value: 92.84599999999999
- type: ap
value: 89.4710787567357
- type: f1
value: 92.83752676932258
- task:
type: Retrieval
dataset:
name: MTEB MSMARCO
type: msmarco
config: default
split: dev
revision: None
metrics:
- type: map_at_1
value: 23.132
- type: map_at_10
value: 35.543
- type: map_at_100
value: 36.702
- type: map_at_1000
value: 36.748999999999995
- type: map_at_3
value: 31.737
- type: map_at_5
value: 33.927
- type: mrr_at_1
value: 23.782
- type: mrr_at_10
value: 36.204
- type: mrr_at_100
value: 37.29
- type: mrr_at_1000
value: 37.330999999999996
- type: mrr_at_3
value: 32.458999999999996
- type: mrr_at_5
value: 34.631
- type: ndcg_at_1
value: 23.782
- type: ndcg_at_10
value: 42.492999999999995
- type: ndcg_at_100
value: 47.985
- type: ndcg_at_1000
value: 49.141
- type: ndcg_at_3
value: 34.748000000000005
- type: ndcg_at_5
value: 38.651
- type: precision_at_1
value: 23.782
- type: precision_at_10
value: 6.665
- type: precision_at_100
value: 0.941
- type: precision_at_1000
value: 0.104
- type: precision_at_3
value: 14.776
- type: precision_at_5
value: 10.84
- type: recall_at_1
value: 23.132
- type: recall_at_10
value: 63.794
- type: recall_at_100
value: 89.027
- type: recall_at_1000
value: 97.807
- type: recall_at_3
value: 42.765
- type: recall_at_5
value: 52.11
- task:
type: Classification
dataset:
name: MTEB MTOPDomainClassification (en)
type: mteb/mtop_domain
config: en
split: test
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
metrics:
- type: accuracy
value: 94.59188326493388
- type: f1
value: 94.3842594786827
- task:
type: Classification
dataset:
name: MTEB MTOPIntentClassification (en)
type: mteb/mtop_intent
config: en
split: test
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
metrics:
- type: accuracy
value: 79.49384404924761
- type: f1
value: 59.7580539534629
- task:
type: Classification
dataset:
name: MTEB MassiveIntentClassification (en)
type: mteb/amazon_massive_intent
config: en
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 77.56220578345663
- type: f1
value: 75.27228165561478
- task:
type: Classification
dataset:
name: MTEB MassiveScenarioClassification (en)
type: mteb/amazon_massive_scenario
config: en
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 80.53463349024884
- type: f1
value: 80.4893958236536
- task:
type: Clustering
dataset:
name: MTEB MedrxivClusteringP2P
type: mteb/medrxiv-clustering-p2p
config: default
split: test
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
metrics:
- type: v_measure
value: 32.56100273484962
- task:
type: Clustering
dataset:
name: MTEB MedrxivClusteringS2S
type: mteb/medrxiv-clustering-s2s
config: default
split: test
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
metrics:
- type: v_measure
value: 31.470380028839607
- task:
type: Reranking
dataset:
name: MTEB MindSmallReranking
type: mteb/mind_small
config: default
split: test
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
metrics:
- type: map
value: 32.06102792457849
- type: mrr
value: 33.30709199672238
- task:
type: Retrieval
dataset:
name: MTEB NFCorpus
type: nfcorpus
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 6.776999999999999
- type: map_at_10
value: 14.924000000000001
- type: map_at_100
value: 18.955
- type: map_at_1000
value: 20.538999999999998
- type: map_at_3
value: 10.982
- type: map_at_5
value: 12.679000000000002
- type: mrr_at_1
value: 47.988
- type: mrr_at_10
value: 57.232000000000006
- type: mrr_at_100
value: 57.818999999999996
- type: mrr_at_1000
value: 57.847
- type: mrr_at_3
value: 54.901999999999994
- type: mrr_at_5
value: 56.481
- type: ndcg_at_1
value: 46.594
- type: ndcg_at_10
value: 38.129000000000005
- type: ndcg_at_100
value: 35.54
- type: ndcg_at_1000
value: 44.172
- type: ndcg_at_3
value: 43.025999999999996
- type: ndcg_at_5
value: 41.052
- type: precision_at_1
value: 47.988
- type: precision_at_10
value: 28.111000000000004
- type: precision_at_100
value: 8.929
- type: precision_at_1000
value: 2.185
- type: precision_at_3
value: 40.144000000000005
- type: precision_at_5
value: 35.232
- type: recall_at_1
value: 6.776999999999999
- type: recall_at_10
value: 19.289
- type: recall_at_100
value: 36.359
- type: recall_at_1000
value: 67.54
- type: recall_at_3
value: 11.869
- type: recall_at_5
value: 14.999
- task:
type: Retrieval
dataset:
name: MTEB NQ
type: nq
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 31.108000000000004
- type: map_at_10
value: 47.126000000000005
- type: map_at_100
value: 48.171
- type: map_at_1000
value: 48.199
- type: map_at_3
value: 42.734
- type: map_at_5
value: 45.362
- type: mrr_at_1
value: 34.936
- type: mrr_at_10
value: 49.571
- type: mrr_at_100
value: 50.345
- type: mrr_at_1000
value: 50.363
- type: mrr_at_3
value: 45.959
- type: mrr_at_5
value: 48.165
- type: ndcg_at_1
value: 34.936
- type: ndcg_at_10
value: 55.028999999999996
- type: ndcg_at_100
value: 59.244
- type: ndcg_at_1000
value: 59.861
- type: ndcg_at_3
value: 46.872
- type: ndcg_at_5
value: 51.217999999999996
- type: precision_at_1
value: 34.936
- type: precision_at_10
value: 9.099
- type: precision_at_100
value: 1.145
- type: precision_at_1000
value: 0.12
- type: precision_at_3
value: 21.456
- type: precision_at_5
value: 15.411
- type: recall_at_1
value: 31.108000000000004
- type: recall_at_10
value: 76.53999999999999
- type: recall_at_100
value: 94.39
- type: recall_at_1000
value: 98.947
- type: recall_at_3
value: 55.572
- type: recall_at_5
value: 65.525
- task:
type: Retrieval
dataset:
name: MTEB QuoraRetrieval
type: quora
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 71.56400000000001
- type: map_at_10
value: 85.482
- type: map_at_100
value: 86.114
- type: map_at_1000
value: 86.13
- type: map_at_3
value: 82.607
- type: map_at_5
value: 84.405
- type: mrr_at_1
value: 82.42
- type: mrr_at_10
value: 88.304
- type: mrr_at_100
value: 88.399
- type: mrr_at_1000
value: 88.399
- type: mrr_at_3
value: 87.37
- type: mrr_at_5
value: 88.024
- type: ndcg_at_1
value: 82.45
- type: ndcg_at_10
value: 89.06500000000001
- type: ndcg_at_100
value: 90.232
- type: ndcg_at_1000
value: 90.305
- type: ndcg_at_3
value: 86.375
- type: ndcg_at_5
value: 87.85300000000001
- type: precision_at_1
value: 82.45
- type: precision_at_10
value: 13.486999999999998
- type: precision_at_100
value: 1.534
- type: precision_at_1000
value: 0.157
- type: precision_at_3
value: 37.813
- type: precision_at_5
value: 24.773999999999997
- type: recall_at_1
value: 71.56400000000001
- type: recall_at_10
value: 95.812
- type: recall_at_100
value: 99.7
- type: recall_at_1000
value: 99.979
- type: recall_at_3
value: 87.966
- type: recall_at_5
value: 92.268
- task:
type: Clustering
dataset:
name: MTEB RedditClustering
type: mteb/reddit-clustering
config: default
split: test
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
metrics:
- type: v_measure
value: 57.241876648614145
- task:
type: Clustering
dataset:
name: MTEB RedditClusteringP2P
type: mteb/reddit-clustering-p2p
config: default
split: test
revision: 282350215ef01743dc01b456c7f5241fa8937f16
metrics:
- type: v_measure
value: 64.66212576446223
- task:
type: Retrieval
dataset:
name: MTEB SCIDOCS
type: scidocs
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 5.308
- type: map_at_10
value: 13.803
- type: map_at_100
value: 16.176
- type: map_at_1000
value: 16.561
- type: map_at_3
value: 9.761000000000001
- type: map_at_5
value: 11.802
- type: mrr_at_1
value: 26.200000000000003
- type: mrr_at_10
value: 37.621
- type: mrr_at_100
value: 38.767
- type: mrr_at_1000
value: 38.815
- type: mrr_at_3
value: 34.117
- type: mrr_at_5
value: 36.107
- type: ndcg_at_1
value: 26.200000000000003
- type: ndcg_at_10
value: 22.64
- type: ndcg_at_100
value: 31.567
- type: ndcg_at_1000
value: 37.623
- type: ndcg_at_3
value: 21.435000000000002
- type: ndcg_at_5
value: 18.87
- type: precision_at_1
value: 26.200000000000003
- type: precision_at_10
value: 11.74
- type: precision_at_100
value: 2.465
- type: precision_at_1000
value: 0.391
- type: precision_at_3
value: 20.033
- type: precision_at_5
value: 16.64
- type: recall_at_1
value: 5.308
- type: recall_at_10
value: 23.794999999999998
- type: recall_at_100
value: 50.015
- type: recall_at_1000
value: 79.283
- type: recall_at_3
value: 12.178
- type: recall_at_5
value: 16.882
- task:
type: STS
dataset:
name: MTEB SICK-R
type: mteb/sickr-sts
config: default
split: test
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
metrics:
- type: cos_sim_pearson
value: 84.93231134675553
- type: cos_sim_spearman
value: 81.68319292603205
- type: euclidean_pearson
value: 81.8396814380367
- type: euclidean_spearman
value: 81.24641903349945
- type: manhattan_pearson
value: 81.84698799204274
- type: manhattan_spearman
value: 81.24269997904105
- task:
type: STS
dataset:
name: MTEB STS12
type: mteb/sts12-sts
config: default
split: test
revision: a0d554a64d88156834ff5ae9920b964011b16384
metrics:
- type: cos_sim_pearson
value: 86.73241671587446
- type: cos_sim_spearman
value: 79.05091082971826
- type: euclidean_pearson
value: 83.91146869578044
- type: euclidean_spearman
value: 79.87978465370936
- type: manhattan_pearson
value: 83.90888338917678
- type: manhattan_spearman
value: 79.87482848584241
- task:
type: STS
dataset:
name: MTEB STS13
type: mteb/sts13-sts
config: default
split: test
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
metrics:
- type: cos_sim_pearson
value: 85.14970731146177
- type: cos_sim_spearman
value: 86.37363490084627
- type: euclidean_pearson
value: 83.02154218530433
- type: euclidean_spearman
value: 83.80258761957367
- type: manhattan_pearson
value: 83.01664495119347
- type: manhattan_spearman
value: 83.77567458007952
- task:
type: STS
dataset:
name: MTEB STS14
type: mteb/sts14-sts
config: default
split: test
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
metrics:
- type: cos_sim_pearson
value: 83.40474139886784
- type: cos_sim_spearman
value: 82.77768789165984
- type: euclidean_pearson
value: 80.7065877443695
- type: euclidean_spearman
value: 81.375940662505
- type: manhattan_pearson
value: 80.6507552270278
- type: manhattan_spearman
value: 81.32782179098741
- task:
type: STS
dataset:
name: MTEB STS15
type: mteb/sts15-sts
config: default
split: test
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
metrics:
- type: cos_sim_pearson
value: 87.08585968722274
- type: cos_sim_spearman
value: 88.03110031451399
- type: euclidean_pearson
value: 85.74012019602384
- type: euclidean_spearman
value: 86.13592849438209
- type: manhattan_pearson
value: 85.74404842369206
- type: manhattan_spearman
value: 86.14492318960154
- task:
type: STS
dataset:
name: MTEB STS16
type: mteb/sts16-sts
config: default
split: test
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
metrics:
- type: cos_sim_pearson
value: 84.95069052788875
- type: cos_sim_spearman
value: 86.4867991595147
- type: euclidean_pearson
value: 84.31013325754635
- type: euclidean_spearman
value: 85.01529258006482
- type: manhattan_pearson
value: 84.26995570085374
- type: manhattan_spearman
value: 84.96982104986162
- 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: 87.54617647971897
- type: cos_sim_spearman
value: 87.49834181751034
- type: euclidean_pearson
value: 86.01015322577122
- type: euclidean_spearman
value: 84.63362652063199
- type: manhattan_pearson
value: 86.13807574475706
- type: manhattan_spearman
value: 84.7772370721132
- 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: 67.20047755786615
- type: cos_sim_spearman
value: 67.05324077987636
- type: euclidean_pearson
value: 66.91930642976601
- type: euclidean_spearman
value: 65.21491856099105
- type: manhattan_pearson
value: 66.78756851976624
- type: manhattan_spearman
value: 65.12356257740728
- task:
type: STS
dataset:
name: MTEB STSBenchmark
type: mteb/stsbenchmark-sts
config: default
split: test
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
metrics:
- type: cos_sim_pearson
value: 86.19852871539686
- type: cos_sim_spearman
value: 87.5161895296395
- type: euclidean_pearson
value: 84.59848645207485
- type: euclidean_spearman
value: 85.26427328757919
- type: manhattan_pearson
value: 84.59747366996524
- type: manhattan_spearman
value: 85.24045855146915
- task:
type: Reranking
dataset:
name: MTEB SciDocsRR
type: mteb/scidocs-reranking
config: default
split: test
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
metrics:
- type: map
value: 87.63320317811032
- type: mrr
value: 96.26242947321379
- task:
type: Retrieval
dataset:
name: MTEB SciFact
type: scifact
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 60.928000000000004
- type: map_at_10
value: 70.112
- type: map_at_100
value: 70.59299999999999
- type: map_at_1000
value: 70.623
- type: map_at_3
value: 66.846
- type: map_at_5
value: 68.447
- type: mrr_at_1
value: 64
- type: mrr_at_10
value: 71.212
- type: mrr_at_100
value: 71.616
- type: mrr_at_1000
value: 71.64500000000001
- type: mrr_at_3
value: 68.77799999999999
- type: mrr_at_5
value: 70.094
- type: ndcg_at_1
value: 64
- type: ndcg_at_10
value: 74.607
- type: ndcg_at_100
value: 76.416
- type: ndcg_at_1000
value: 77.102
- type: ndcg_at_3
value: 69.126
- type: ndcg_at_5
value: 71.41300000000001
- type: precision_at_1
value: 64
- type: precision_at_10
value: 9.933
- type: precision_at_100
value: 1.077
- type: precision_at_1000
value: 0.11299999999999999
- type: precision_at_3
value: 26.556
- type: precision_at_5
value: 17.467
- type: recall_at_1
value: 60.928000000000004
- type: recall_at_10
value: 87.322
- type: recall_at_100
value: 94.833
- type: recall_at_1000
value: 100
- type: recall_at_3
value: 72.628
- type: recall_at_5
value: 78.428
- task:
type: PairClassification
dataset:
name: MTEB SprintDuplicateQuestions
type: mteb/sprintduplicatequestions-pairclassification
config: default
split: test
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
metrics:
- type: cos_sim_accuracy
value: 99.86237623762376
- type: cos_sim_ap
value: 96.72586477206649
- type: cos_sim_f1
value: 93.01858362631845
- type: cos_sim_precision
value: 93.4409687184662
- type: cos_sim_recall
value: 92.60000000000001
- type: dot_accuracy
value: 99.78019801980199
- type: dot_ap
value: 93.72748205246228
- type: dot_f1
value: 89.04109589041096
- type: dot_precision
value: 87.16475095785441
- type: dot_recall
value: 91
- type: euclidean_accuracy
value: 99.85445544554456
- type: euclidean_ap
value: 96.6661459876145
- type: euclidean_f1
value: 92.58337481333997
- type: euclidean_precision
value: 92.17046580773042
- type: euclidean_recall
value: 93
- type: manhattan_accuracy
value: 99.85445544554456
- type: manhattan_ap
value: 96.6883549244056
- type: manhattan_f1
value: 92.57598405580468
- type: manhattan_precision
value: 92.25422045680239
- type: manhattan_recall
value: 92.9
- type: max_accuracy
value: 99.86237623762376
- type: max_ap
value: 96.72586477206649
- type: max_f1
value: 93.01858362631845
- task:
type: Clustering
dataset:
name: MTEB StackExchangeClustering
type: mteb/stackexchange-clustering
config: default
split: test
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
metrics:
- type: v_measure
value: 66.39930057069995
- task:
type: Clustering
dataset:
name: MTEB StackExchangeClusteringP2P
type: mteb/stackexchange-clustering-p2p
config: default
split: test
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
metrics:
- type: v_measure
value: 34.96398659903402
- task:
type: Reranking
dataset:
name: MTEB StackOverflowDupQuestions
type: mteb/stackoverflowdupquestions-reranking
config: default
split: test
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
metrics:
- type: map
value: 55.946944700355395
- type: mrr
value: 56.97151398438164
- task:
type: Summarization
dataset:
name: MTEB SummEval
type: mteb/summeval
config: default
split: test
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
metrics:
- type: cos_sim_pearson
value: 31.541657650692905
- type: cos_sim_spearman
value: 31.605804192286303
- type: dot_pearson
value: 28.26905996736398
- type: dot_spearman
value: 27.864801765851187
- task:
type: Retrieval
dataset:
name: MTEB TRECCOVID
type: trec-covid
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 0.22599999999999998
- type: map_at_10
value: 1.8870000000000002
- type: map_at_100
value: 9.78
- type: map_at_1000
value: 22.514
- type: map_at_3
value: 0.6669999999999999
- type: map_at_5
value: 1.077
- type: mrr_at_1
value: 82
- type: mrr_at_10
value: 89.86699999999999
- type: mrr_at_100
value: 89.86699999999999
- type: mrr_at_1000
value: 89.86699999999999
- type: mrr_at_3
value: 89.667
- type: mrr_at_5
value: 89.667
- type: ndcg_at_1
value: 79
- type: ndcg_at_10
value: 74.818
- type: ndcg_at_100
value: 53.715999999999994
- type: ndcg_at_1000
value: 47.082
- type: ndcg_at_3
value: 82.134
- type: ndcg_at_5
value: 79.81899999999999
- type: precision_at_1
value: 82
- type: precision_at_10
value: 78
- type: precision_at_100
value: 54.48
- type: precision_at_1000
value: 20.518
- type: precision_at_3
value: 87.333
- type: precision_at_5
value: 85.2
- type: recall_at_1
value: 0.22599999999999998
- type: recall_at_10
value: 2.072
- type: recall_at_100
value: 13.013
- type: recall_at_1000
value: 43.462
- type: recall_at_3
value: 0.695
- type: recall_at_5
value: 1.139
- task:
type: Retrieval
dataset:
name: MTEB Touche2020
type: webis-touche2020
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 2.328
- type: map_at_10
value: 9.795
- type: map_at_100
value: 15.801000000000002
- type: map_at_1000
value: 17.23
- type: map_at_3
value: 4.734
- type: map_at_5
value: 6.644
- type: mrr_at_1
value: 30.612000000000002
- type: mrr_at_10
value: 46.902
- type: mrr_at_100
value: 47.495
- type: mrr_at_1000
value: 47.495
- type: mrr_at_3
value: 41.156
- type: mrr_at_5
value: 44.218
- type: ndcg_at_1
value: 28.571
- type: ndcg_at_10
value: 24.806
- type: ndcg_at_100
value: 36.419000000000004
- type: ndcg_at_1000
value: 47.272999999999996
- type: ndcg_at_3
value: 25.666
- type: ndcg_at_5
value: 25.448999999999998
- type: precision_at_1
value: 30.612000000000002
- type: precision_at_10
value: 23.061
- type: precision_at_100
value: 7.714
- type: precision_at_1000
value: 1.484
- type: precision_at_3
value: 26.531
- type: precision_at_5
value: 26.122
- type: recall_at_1
value: 2.328
- type: recall_at_10
value: 16.524
- type: recall_at_100
value: 47.179
- type: recall_at_1000
value: 81.22200000000001
- type: recall_at_3
value: 5.745
- type: recall_at_5
value: 9.339
- task:
type: Classification
dataset:
name: MTEB ToxicConversationsClassification
type: mteb/toxic_conversations_50k
config: default
split: test
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
metrics:
- type: accuracy
value: 70.9142
- type: ap
value: 14.335574772555415
- type: f1
value: 54.62839595194111
- task:
type: Classification
dataset:
name: MTEB TweetSentimentExtractionClassification
type: mteb/tweet_sentiment_extraction
config: default
split: test
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
metrics:
- type: accuracy
value: 59.94340690435768
- type: f1
value: 60.286487936731916
- task:
type: Clustering
dataset:
name: MTEB TwentyNewsgroupsClustering
type: mteb/twentynewsgroups-clustering
config: default
split: test
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
metrics:
- type: v_measure
value: 51.26597708987974
- task:
type: PairClassification
dataset:
name: MTEB TwitterSemEval2015
type: mteb/twittersemeval2015-pairclassification
config: default
split: test
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
metrics:
- type: cos_sim_accuracy
value: 87.48882398521786
- type: cos_sim_ap
value: 79.04326607602204
- type: cos_sim_f1
value: 71.64566826860633
- type: cos_sim_precision
value: 70.55512918905092
- type: cos_sim_recall
value: 72.77044854881267
- type: dot_accuracy
value: 84.19264469213805
- type: dot_ap
value: 67.96360043562528
- type: dot_f1
value: 64.06418393006827
- type: dot_precision
value: 58.64941898706424
- type: dot_recall
value: 70.58047493403694
- type: euclidean_accuracy
value: 87.45902127913214
- type: euclidean_ap
value: 78.9742237648272
- type: euclidean_f1
value: 71.5553235908142
- type: euclidean_precision
value: 70.77955601445535
- type: euclidean_recall
value: 72.34828496042216
- type: manhattan_accuracy
value: 87.41729749061214
- type: manhattan_ap
value: 78.90073137580596
- type: manhattan_f1
value: 71.3942611553533
- type: manhattan_precision
value: 68.52705653967483
- type: manhattan_recall
value: 74.51187335092348
- type: max_accuracy
value: 87.48882398521786
- type: max_ap
value: 79.04326607602204
- type: max_f1
value: 71.64566826860633
- task:
type: PairClassification
dataset:
name: MTEB TwitterURLCorpus
type: mteb/twitterurlcorpus-pairclassification
config: default
split: test
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
metrics:
- type: cos_sim_accuracy
value: 88.68125897465751
- type: cos_sim_ap
value: 85.6003454431979
- type: cos_sim_f1
value: 77.6957163958641
- type: cos_sim_precision
value: 73.0110366307807
- type: cos_sim_recall
value: 83.02279026793964
- type: dot_accuracy
value: 87.7672992587418
- type: dot_ap
value: 82.4971301112899
- type: dot_f1
value: 75.90528233151184
- type: dot_precision
value: 72.0370626469368
- type: dot_recall
value: 80.21250384970742
- type: euclidean_accuracy
value: 88.4503434625684
- type: euclidean_ap
value: 84.91949884748384
- type: euclidean_f1
value: 76.92365018444684
- type: euclidean_precision
value: 74.53245721712759
- type: euclidean_recall
value: 79.47336002463813
- type: manhattan_accuracy
value: 88.47556952691427
- type: manhattan_ap
value: 84.8963689101517
- type: manhattan_f1
value: 76.85901249256395
- type: manhattan_precision
value: 74.31693989071039
- type: manhattan_recall
value: 79.58115183246073
- type: max_accuracy
value: 88.68125897465751
- type: max_ap
value: 85.6003454431979
- type: max_f1
value: 77.6957163958641
This model is a quantized version of BAAI/bge-large-en-v1.5 and is converted to the OpenVINO format. This model was obtained via the nncf-quantization space with optimum-intel.
First make sure you have optimum-intel installed:
pip install optimum[openvino]
To load your model you can do as follows:
from optimum.intel import OVModelForFeatureExtraction
model_id = "nskeatts/bge-large-en-v1.5-openvino-8bit"
model = OVModelForFeatureExtraction.from_pretrained(model_id)