metadata
tags:
- mteb
model-index:
- name: sf_model_e5
results:
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en)
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
- type: accuracy
value: 70.85074626865672
- type: ap
value: 33.779217850079206
- type: f1
value: 64.96977487239377
- task:
type: Classification
dataset:
type: mteb/amazon_polarity
name: MTEB AmazonPolarityClassification
config: default
split: test
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
metrics:
- type: accuracy
value: 91.80945
- type: ap
value: 88.22978189506895
- type: f1
value: 91.7858219911604
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (en)
config: en
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy
value: 48.94200000000001
- type: f1
value: 47.911934405973895
- task:
type: Retrieval
dataset:
type: arguana
name: MTEB ArguAna
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 39.616
- type: map_at_10
value: 55.938
- type: map_at_100
value: 56.552
- type: map_at_1000
value: 56.556
- type: map_at_3
value: 51.754
- type: map_at_5
value: 54.623999999999995
- type: mrr_at_1
value: 40.967
- type: mrr_at_10
value: 56.452999999999996
- type: mrr_at_100
value: 57.053
- type: mrr_at_1000
value: 57.057
- type: mrr_at_3
value: 52.312000000000005
- type: mrr_at_5
value: 55.1
- type: ndcg_at_1
value: 39.616
- type: ndcg_at_10
value: 64.067
- type: ndcg_at_100
value: 66.384
- type: ndcg_at_1000
value: 66.468
- type: ndcg_at_3
value: 55.74
- type: ndcg_at_5
value: 60.889
- type: precision_at_1
value: 39.616
- type: precision_at_10
value: 8.953999999999999
- type: precision_at_100
value: 0.9900000000000001
- type: precision_at_1000
value: 0.1
- type: precision_at_3
value: 22.428
- type: precision_at_5
value: 15.946
- type: recall_at_1
value: 39.616
- type: recall_at_10
value: 89.545
- type: recall_at_100
value: 99.004
- type: recall_at_1000
value: 99.644
- type: recall_at_3
value: 67.283
- type: recall_at_5
value: 79.73
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-p2p
name: MTEB ArxivClusteringP2P
config: default
split: test
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
metrics:
- type: v_measure
value: 48.72923923743124
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-s2s
name: MTEB ArxivClusteringS2S
config: default
split: test
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
metrics:
- type: v_measure
value: 42.87449955203238
- task:
type: Reranking
dataset:
type: mteb/askubuntudupquestions-reranking
name: MTEB AskUbuntuDupQuestions
config: default
split: test
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
metrics:
- type: map
value: 64.3214434754065
- type: mrr
value: 77.87879787187265
- task:
type: STS
dataset:
type: mteb/biosses-sts
name: MTEB BIOSSES
config: default
split: test
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
metrics:
- type: cos_sim_pearson
value: 88.82418607751953
- type: cos_sim_spearman
value: 86.74535004562274
- type: euclidean_pearson
value: 86.58792166831103
- type: euclidean_spearman
value: 86.74535004562274
- type: manhattan_pearson
value: 86.23957813056677
- type: manhattan_spearman
value: 86.41522204150452
- task:
type: Classification
dataset:
type: mteb/banking77
name: MTEB Banking77Classification
config: default
split: test
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
metrics:
- type: accuracy
value: 84.61363636363636
- type: f1
value: 83.98373241136187
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-p2p
name: MTEB BiorxivClusteringP2P
config: default
split: test
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
metrics:
- type: v_measure
value: 39.73148995791471
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-s2s
name: MTEB BiorxivClusteringS2S
config: default
split: test
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
metrics:
- type: v_measure
value: 37.23723038699733
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackAndroidRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 32.217
- type: map_at_10
value: 43.453
- type: map_at_100
value: 45.038
- type: map_at_1000
value: 45.162
- type: map_at_3
value: 39.589
- type: map_at_5
value: 41.697
- type: mrr_at_1
value: 39.628
- type: mrr_at_10
value: 49.698
- type: mrr_at_100
value: 50.44
- type: mrr_at_1000
value: 50.482000000000006
- type: mrr_at_3
value: 46.781
- type: mrr_at_5
value: 48.548
- type: ndcg_at_1
value: 39.628
- type: ndcg_at_10
value: 50.158
- type: ndcg_at_100
value: 55.687
- type: ndcg_at_1000
value: 57.499
- type: ndcg_at_3
value: 44.594
- type: ndcg_at_5
value: 47.198
- type: precision_at_1
value: 39.628
- type: precision_at_10
value: 9.828000000000001
- type: precision_at_100
value: 1.591
- type: precision_at_1000
value: 0.20600000000000002
- type: precision_at_3
value: 21.507
- type: precision_at_5
value: 15.765
- type: recall_at_1
value: 32.217
- type: recall_at_10
value: 62.717999999999996
- type: recall_at_100
value: 85.992
- type: recall_at_1000
value: 97.271
- type: recall_at_3
value: 46.694
- type: recall_at_5
value: 53.952
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackEnglishRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 30.862000000000002
- type: map_at_10
value: 41.287
- type: map_at_100
value: 42.526
- type: map_at_1000
value: 42.653999999999996
- type: map_at_3
value: 38.055
- type: map_at_5
value: 40.022000000000006
- type: mrr_at_1
value: 38.408
- type: mrr_at_10
value: 46.943
- type: mrr_at_100
value: 47.597
- type: mrr_at_1000
value: 47.64
- type: mrr_at_3
value: 44.607
- type: mrr_at_5
value: 46.079
- type: ndcg_at_1
value: 38.408
- type: ndcg_at_10
value: 46.936
- type: ndcg_at_100
value: 51.307
- type: ndcg_at_1000
value: 53.312000000000005
- type: ndcg_at_3
value: 42.579
- type: ndcg_at_5
value: 44.877
- type: precision_at_1
value: 38.408
- type: precision_at_10
value: 8.885
- type: precision_at_100
value: 1.4449999999999998
- type: precision_at_1000
value: 0.192
- type: precision_at_3
value: 20.616
- type: precision_at_5
value: 14.841
- type: recall_at_1
value: 30.862000000000002
- type: recall_at_10
value: 56.994
- type: recall_at_100
value: 75.347
- type: recall_at_1000
value: 87.911
- type: recall_at_3
value: 44.230000000000004
- type: recall_at_5
value: 50.625
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackGamingRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 39.076
- type: map_at_10
value: 52.535
- type: map_at_100
value: 53.537
- type: map_at_1000
value: 53.591
- type: map_at_3
value: 48.961
- type: map_at_5
value: 50.96000000000001
- type: mrr_at_1
value: 44.765
- type: mrr_at_10
value: 55.615
- type: mrr_at_100
value: 56.24
- type: mrr_at_1000
value: 56.264
- type: mrr_at_3
value: 52.925999999999995
- type: mrr_at_5
value: 54.493
- type: ndcg_at_1
value: 44.765
- type: ndcg_at_10
value: 58.777
- type: ndcg_at_100
value: 62.574
- type: ndcg_at_1000
value: 63.624
- type: ndcg_at_3
value: 52.81
- type: ndcg_at_5
value: 55.657999999999994
- type: precision_at_1
value: 44.765
- type: precision_at_10
value: 9.693
- type: precision_at_100
value: 1.248
- type: precision_at_1000
value: 0.13799999999999998
- type: precision_at_3
value: 23.866
- type: precision_at_5
value: 16.489
- type: recall_at_1
value: 39.076
- type: recall_at_10
value: 74.01299999999999
- type: recall_at_100
value: 90.363
- type: recall_at_1000
value: 97.782
- type: recall_at_3
value: 58.056
- type: recall_at_5
value: 65.029
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackGisRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 26.357000000000003
- type: map_at_10
value: 35.492000000000004
- type: map_at_100
value: 36.504999999999995
- type: map_at_1000
value: 36.578
- type: map_at_3
value: 32.696999999999996
- type: map_at_5
value: 34.388999999999996
- type: mrr_at_1
value: 28.136
- type: mrr_at_10
value: 37.383
- type: mrr_at_100
value: 38.271
- type: mrr_at_1000
value: 38.324999999999996
- type: mrr_at_3
value: 34.782999999999994
- type: mrr_at_5
value: 36.416
- type: ndcg_at_1
value: 28.136
- type: ndcg_at_10
value: 40.741
- type: ndcg_at_100
value: 45.803
- type: ndcg_at_1000
value: 47.637
- type: ndcg_at_3
value: 35.412
- type: ndcg_at_5
value: 38.251000000000005
- type: precision_at_1
value: 28.136
- type: precision_at_10
value: 6.315999999999999
- type: precision_at_100
value: 0.931
- type: precision_at_1000
value: 0.11299999999999999
- type: precision_at_3
value: 15.254000000000001
- type: precision_at_5
value: 10.757
- type: recall_at_1
value: 26.357000000000003
- type: recall_at_10
value: 55.021
- type: recall_at_100
value: 78.501
- type: recall_at_1000
value: 92.133
- type: recall_at_3
value: 40.798
- type: recall_at_5
value: 47.591
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackMathematicaRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 17.302
- type: map_at_10
value: 26.365
- type: map_at_100
value: 27.581
- type: map_at_1000
value: 27.705999999999996
- type: map_at_3
value: 23.682
- type: map_at_5
value: 25.304
- type: mrr_at_1
value: 21.891
- type: mrr_at_10
value: 31.227
- type: mrr_at_100
value: 32.22
- type: mrr_at_1000
value: 32.282
- type: mrr_at_3
value: 28.711
- type: mrr_at_5
value: 30.314999999999998
- type: ndcg_at_1
value: 21.891
- type: ndcg_at_10
value: 31.965
- type: ndcg_at_100
value: 37.869
- type: ndcg_at_1000
value: 40.642
- type: ndcg_at_3
value: 27.184
- type: ndcg_at_5
value: 29.686
- type: precision_at_1
value: 21.891
- type: precision_at_10
value: 5.9830000000000005
- type: precision_at_100
value: 1.0250000000000001
- type: precision_at_1000
value: 0.14100000000000001
- type: precision_at_3
value: 13.391
- type: precision_at_5
value: 9.801
- type: recall_at_1
value: 17.302
- type: recall_at_10
value: 44.312000000000005
- type: recall_at_100
value: 70.274
- type: recall_at_1000
value: 89.709
- type: recall_at_3
value: 31.117
- type: recall_at_5
value: 37.511
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackPhysicsRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 29.404000000000003
- type: map_at_10
value: 40.571
- type: map_at_100
value: 42.049
- type: map_at_1000
value: 42.156
- type: map_at_3
value: 37.413000000000004
- type: map_at_5
value: 39.206
- type: mrr_at_1
value: 36.285000000000004
- type: mrr_at_10
value: 46.213
- type: mrr_at_100
value: 47.129
- type: mrr_at_1000
value: 47.168
- type: mrr_at_3
value: 43.84
- type: mrr_at_5
value: 45.226
- type: ndcg_at_1
value: 36.285000000000004
- type: ndcg_at_10
value: 46.809
- type: ndcg_at_100
value: 52.615
- type: ndcg_at_1000
value: 54.538
- type: ndcg_at_3
value: 41.91
- type: ndcg_at_5
value: 44.224999999999994
- type: precision_at_1
value: 36.285000000000004
- type: precision_at_10
value: 8.527
- type: precision_at_100
value: 1.3259999999999998
- type: precision_at_1000
value: 0.167
- type: precision_at_3
value: 20.083000000000002
- type: precision_at_5
value: 14.071
- type: recall_at_1
value: 29.404000000000003
- type: recall_at_10
value: 59.611999999999995
- type: recall_at_100
value: 83.383
- type: recall_at_1000
value: 95.703
- type: recall_at_3
value: 45.663
- type: recall_at_5
value: 51.971999999999994
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackProgrammersRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 25.317
- type: map_at_10
value: 35.217999999999996
- type: map_at_100
value: 36.665
- type: map_at_1000
value: 36.768
- type: map_at_3
value: 31.924000000000003
- type: map_at_5
value: 33.591
- type: mrr_at_1
value: 31.507
- type: mrr_at_10
value: 40.671
- type: mrr_at_100
value: 41.609
- type: mrr_at_1000
value: 41.657
- type: mrr_at_3
value: 38.261
- type: mrr_at_5
value: 39.431
- type: ndcg_at_1
value: 31.507
- type: ndcg_at_10
value: 41.375
- type: ndcg_at_100
value: 47.426
- type: ndcg_at_1000
value: 49.504
- type: ndcg_at_3
value: 35.989
- type: ndcg_at_5
value: 38.068000000000005
- type: precision_at_1
value: 31.507
- type: precision_at_10
value: 7.8420000000000005
- type: precision_at_100
value: 1.257
- type: precision_at_1000
value: 0.16199999999999998
- type: precision_at_3
value: 17.352
- type: precision_at_5
value: 12.328999999999999
- type: recall_at_1
value: 25.317
- type: recall_at_10
value: 54.254999999999995
- type: recall_at_100
value: 80.184
- type: recall_at_1000
value: 94.07
- type: recall_at_3
value: 39.117000000000004
- type: recall_at_5
value: 44.711
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 25.813000000000002
- type: map_at_10
value: 35.47183333333334
- type: map_at_100
value: 36.71775
- type: map_at_1000
value: 36.833000000000006
- type: map_at_3
value: 32.449916666666674
- type: map_at_5
value: 34.1235
- type: mrr_at_1
value: 30.766750000000005
- type: mrr_at_10
value: 39.77508333333334
- type: mrr_at_100
value: 40.64233333333333
- type: mrr_at_1000
value: 40.69658333333333
- type: mrr_at_3
value: 37.27349999999999
- type: mrr_at_5
value: 38.723416666666665
- type: ndcg_at_1
value: 30.766750000000005
- type: ndcg_at_10
value: 41.141416666666665
- type: ndcg_at_100
value: 46.42016666666666
- type: ndcg_at_1000
value: 48.61916666666667
- type: ndcg_at_3
value: 36.06883333333333
- type: ndcg_at_5
value: 38.43966666666666
- type: precision_at_1
value: 30.766750000000005
- type: precision_at_10
value: 7.340000000000001
- type: precision_at_100
value: 1.1796666666666666
- type: precision_at_1000
value: 0.15625
- type: precision_at_3
value: 16.763833333333334
- type: precision_at_5
value: 11.972166666666666
- type: recall_at_1
value: 25.813000000000002
- type: recall_at_10
value: 53.62741666666667
- type: recall_at_100
value: 76.70125000000002
- type: recall_at_1000
value: 91.85566666666666
- type: recall_at_3
value: 39.55075
- type: recall_at_5
value: 45.645250000000004
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackStatsRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 23.249
- type: map_at_10
value: 31.095
- type: map_at_100
value: 32.056000000000004
- type: map_at_1000
value: 32.163000000000004
- type: map_at_3
value: 29.275000000000002
- type: map_at_5
value: 30.333
- type: mrr_at_1
value: 26.687
- type: mrr_at_10
value: 34.122
- type: mrr_at_100
value: 34.958
- type: mrr_at_1000
value: 35.039
- type: mrr_at_3
value: 32.541
- type: mrr_at_5
value: 33.43
- type: ndcg_at_1
value: 26.687
- type: ndcg_at_10
value: 35.248000000000005
- type: ndcg_at_100
value: 39.933
- type: ndcg_at_1000
value: 42.616
- type: ndcg_at_3
value: 31.980999999999998
- type: ndcg_at_5
value: 33.583
- type: precision_at_1
value: 26.687
- type: precision_at_10
value: 5.445
- type: precision_at_100
value: 0.848
- type: precision_at_1000
value: 0.11499999999999999
- type: precision_at_3
value: 13.957
- type: precision_at_5
value: 9.479
- type: recall_at_1
value: 23.249
- type: recall_at_10
value: 45.005
- type: recall_at_100
value: 66.175
- type: recall_at_1000
value: 86.116
- type: recall_at_3
value: 36.03
- type: recall_at_5
value: 40.037
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackTexRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 17.592
- type: map_at_10
value: 25.003999999999998
- type: map_at_100
value: 26.208
- type: map_at_1000
value: 26.333000000000002
- type: map_at_3
value: 22.479
- type: map_at_5
value: 23.712
- type: mrr_at_1
value: 21.37
- type: mrr_at_10
value: 28.951999999999998
- type: mrr_at_100
value: 29.915999999999997
- type: mrr_at_1000
value: 29.99
- type: mrr_at_3
value: 26.503
- type: mrr_at_5
value: 27.728
- type: ndcg_at_1
value: 21.37
- type: ndcg_at_10
value: 29.944
- type: ndcg_at_100
value: 35.632000000000005
- type: ndcg_at_1000
value: 38.393
- type: ndcg_at_3
value: 25.263999999999996
- type: ndcg_at_5
value: 27.115000000000002
- type: precision_at_1
value: 21.37
- type: precision_at_10
value: 5.568
- type: precision_at_100
value: 0.992
- type: precision_at_1000
value: 0.13999999999999999
- type: precision_at_3
value: 11.895
- type: precision_at_5
value: 8.61
- type: recall_at_1
value: 17.592
- type: recall_at_10
value: 40.976
- type: recall_at_100
value: 66.487
- type: recall_at_1000
value: 85.954
- type: recall_at_3
value: 27.797
- type: recall_at_5
value: 32.553
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackUnixRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 25.173000000000002
- type: map_at_10
value: 34.611999999999995
- type: map_at_100
value: 35.735
- type: map_at_1000
value: 35.842
- type: map_at_3
value: 31.345
- type: map_at_5
value: 33.123000000000005
- type: mrr_at_1
value: 29.570999999999998
- type: mrr_at_10
value: 38.775999999999996
- type: mrr_at_100
value: 39.621
- type: mrr_at_1000
value: 39.684000000000005
- type: mrr_at_3
value: 35.992000000000004
- type: mrr_at_5
value: 37.586999999999996
- type: ndcg_at_1
value: 29.570999999999998
- type: ndcg_at_10
value: 40.388000000000005
- type: ndcg_at_100
value: 45.59
- type: ndcg_at_1000
value: 47.948
- type: ndcg_at_3
value: 34.497
- type: ndcg_at_5
value: 37.201
- type: precision_at_1
value: 29.570999999999998
- type: precision_at_10
value: 6.931
- type: precision_at_100
value: 1.082
- type: precision_at_1000
value: 0.13999999999999999
- type: precision_at_3
value: 15.609
- type: precision_at_5
value: 11.286999999999999
- type: recall_at_1
value: 25.173000000000002
- type: recall_at_10
value: 53.949000000000005
- type: recall_at_100
value: 76.536
- type: recall_at_1000
value: 92.979
- type: recall_at_3
value: 37.987
- type: recall_at_5
value: 44.689
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackWebmastersRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 24.224
- type: map_at_10
value: 32.903
- type: map_at_100
value: 34.65
- type: map_at_1000
value: 34.873
- type: map_at_3
value: 29.673
- type: map_at_5
value: 31.361
- type: mrr_at_1
value: 30.435000000000002
- type: mrr_at_10
value: 38.677
- type: mrr_at_100
value: 39.805
- type: mrr_at_1000
value: 39.851
- type: mrr_at_3
value: 35.935
- type: mrr_at_5
value: 37.566
- type: ndcg_at_1
value: 30.435000000000002
- type: ndcg_at_10
value: 39.012
- type: ndcg_at_100
value: 45.553
- type: ndcg_at_1000
value: 47.919
- type: ndcg_at_3
value: 33.809
- type: ndcg_at_5
value: 36.120999999999995
- type: precision_at_1
value: 30.435000000000002
- type: precision_at_10
value: 7.628
- type: precision_at_100
value: 1.5810000000000002
- type: precision_at_1000
value: 0.243
- type: precision_at_3
value: 15.744
- type: precision_at_5
value: 11.66
- type: recall_at_1
value: 24.224
- type: recall_at_10
value: 50.009
- type: recall_at_100
value: 78.839
- type: recall_at_1000
value: 93.71300000000001
- type: recall_at_3
value: 35.512
- type: recall_at_5
value: 41.541
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackWordpressRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 18.983
- type: map_at_10
value: 27.127000000000002
- type: map_at_100
value: 28.063
- type: map_at_1000
value: 28.17
- type: map_at_3
value: 24.306
- type: map_at_5
value: 25.784000000000002
- type: mrr_at_1
value: 20.518
- type: mrr_at_10
value: 29.024
- type: mrr_at_100
value: 29.902
- type: mrr_at_1000
value: 29.976999999999997
- type: mrr_at_3
value: 26.401999999999997
- type: mrr_at_5
value: 27.862
- type: ndcg_at_1
value: 20.518
- type: ndcg_at_10
value: 32.344
- type: ndcg_at_100
value: 37.053000000000004
- type: ndcg_at_1000
value: 39.798
- type: ndcg_at_3
value: 26.796999999999997
- type: ndcg_at_5
value: 29.293000000000003
- type: precision_at_1
value: 20.518
- type: precision_at_10
value: 5.434
- type: precision_at_100
value: 0.83
- type: precision_at_1000
value: 0.11800000000000001
- type: precision_at_3
value: 11.892
- type: precision_at_5
value: 8.577
- type: recall_at_1
value: 18.983
- type: recall_at_10
value: 46.665
- type: recall_at_100
value: 68.33399999999999
- type: recall_at_1000
value: 88.927
- type: recall_at_3
value: 31.608000000000004
- type: recall_at_5
value: 37.532
- task:
type: Retrieval
dataset:
type: climate-fever
name: MTEB ClimateFEVER
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 11.200000000000001
- type: map_at_10
value: 20.241999999999997
- type: map_at_100
value: 22.357
- type: map_at_1000
value: 22.556
- type: map_at_3
value: 16.564999999999998
- type: map_at_5
value: 18.443
- type: mrr_at_1
value: 25.277
- type: mrr_at_10
value: 37.582
- type: mrr_at_100
value: 38.525999999999996
- type: mrr_at_1000
value: 38.564
- type: mrr_at_3
value: 33.898
- type: mrr_at_5
value: 36.191
- type: ndcg_at_1
value: 25.277
- type: ndcg_at_10
value: 28.74
- type: ndcg_at_100
value: 36.665
- type: ndcg_at_1000
value: 40.08
- type: ndcg_at_3
value: 22.888
- type: ndcg_at_5
value: 25.081999999999997
- type: precision_at_1
value: 25.277
- type: precision_at_10
value: 9.251
- type: precision_at_100
value: 1.773
- type: precision_at_1000
value: 0.241
- type: precision_at_3
value: 17.329
- type: precision_at_5
value: 13.746
- type: recall_at_1
value: 11.200000000000001
- type: recall_at_10
value: 35.419
- type: recall_at_100
value: 62.41
- type: recall_at_1000
value: 81.467
- type: recall_at_3
value: 21.275
- type: recall_at_5
value: 27.201999999999998
- task:
type: Retrieval
dataset:
type: dbpedia-entity
name: MTEB DBPedia
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 9.396
- type: map_at_10
value: 20.735
- type: map_at_100
value: 30.098000000000003
- type: map_at_1000
value: 31.866
- type: map_at_3
value: 14.71
- type: map_at_5
value: 17.259
- type: mrr_at_1
value: 70.25
- type: mrr_at_10
value: 77.09700000000001
- type: mrr_at_100
value: 77.398
- type: mrr_at_1000
value: 77.40899999999999
- type: mrr_at_3
value: 75.542
- type: mrr_at_5
value: 76.354
- type: ndcg_at_1
value: 57.75
- type: ndcg_at_10
value: 42.509
- type: ndcg_at_100
value: 48.94
- type: ndcg_at_1000
value: 56.501000000000005
- type: ndcg_at_3
value: 46.827000000000005
- type: ndcg_at_5
value: 44.033
- type: precision_at_1
value: 70.25
- type: precision_at_10
value: 33.85
- type: precision_at_100
value: 11.373
- type: precision_at_1000
value: 2.136
- type: precision_at_3
value: 50.917
- type: precision_at_5
value: 42.8
- type: recall_at_1
value: 9.396
- type: recall_at_10
value: 26.472
- type: recall_at_100
value: 57.30800000000001
- type: recall_at_1000
value: 80.983
- type: recall_at_3
value: 15.859000000000002
- type: recall_at_5
value: 19.758
- task:
type: Classification
dataset:
type: mteb/emotion
name: MTEB EmotionClassification
config: default
split: test
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
metrics:
- type: accuracy
value: 54.900000000000006
- type: f1
value: 48.14707395235448
- task:
type: Retrieval
dataset:
type: fever
name: MTEB FEVER
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 66.369
- type: map_at_10
value: 76.708
- type: map_at_100
value: 76.981
- type: map_at_1000
value: 76.995
- type: map_at_3
value: 75.114
- type: map_at_5
value: 76.116
- type: mrr_at_1
value: 71.557
- type: mrr_at_10
value: 80.95
- type: mrr_at_100
value: 81.075
- type: mrr_at_1000
value: 81.07900000000001
- type: mrr_at_3
value: 79.728
- type: mrr_at_5
value: 80.522
- type: ndcg_at_1
value: 71.557
- type: ndcg_at_10
value: 81.381
- type: ndcg_at_100
value: 82.421
- type: ndcg_at_1000
value: 82.709
- type: ndcg_at_3
value: 78.671
- type: ndcg_at_5
value: 80.17
- type: precision_at_1
value: 71.557
- type: precision_at_10
value: 10.159
- type: precision_at_100
value: 1.089
- type: precision_at_1000
value: 0.11299999999999999
- type: precision_at_3
value: 30.668
- type: precision_at_5
value: 19.337
- type: recall_at_1
value: 66.369
- type: recall_at_10
value: 91.482
- type: recall_at_100
value: 95.848
- type: recall_at_1000
value: 97.749
- type: recall_at_3
value: 84.185
- type: recall_at_5
value: 87.908
- task:
type: Retrieval
dataset:
type: fiqa
name: MTEB FiQA2018
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 20.902
- type: map_at_10
value: 34.554
- type: map_at_100
value: 36.632
- type: map_at_1000
value: 36.811
- type: map_at_3
value: 30.264000000000003
- type: map_at_5
value: 32.714999999999996
- type: mrr_at_1
value: 42.13
- type: mrr_at_10
value: 51.224000000000004
- type: mrr_at_100
value: 52.044999999999995
- type: mrr_at_1000
value: 52.075
- type: mrr_at_3
value: 48.842999999999996
- type: mrr_at_5
value: 50.108
- type: ndcg_at_1
value: 42.13
- type: ndcg_at_10
value: 42.643
- type: ndcg_at_100
value: 49.806
- type: ndcg_at_1000
value: 52.583
- type: ndcg_at_3
value: 38.927
- type: ndcg_at_5
value: 40.071
- type: precision_at_1
value: 42.13
- type: precision_at_10
value: 11.928999999999998
- type: precision_at_100
value: 1.931
- type: precision_at_1000
value: 0.243
- type: precision_at_3
value: 26.337
- type: precision_at_5
value: 19.29
- type: recall_at_1
value: 20.902
- type: recall_at_10
value: 49.527
- type: recall_at_100
value: 75.754
- type: recall_at_1000
value: 92.171
- type: recall_at_3
value: 35.024
- type: recall_at_5
value: 41.207
- task:
type: Retrieval
dataset:
type: hotpotqa
name: MTEB HotpotQA
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 39.831
- type: map_at_10
value: 63.958999999999996
- type: map_at_100
value: 64.869
- type: map_at_1000
value: 64.924
- type: map_at_3
value: 60.25
- type: map_at_5
value: 62.572
- type: mrr_at_1
value: 79.662
- type: mrr_at_10
value: 85.57900000000001
- type: mrr_at_100
value: 85.744
- type: mrr_at_1000
value: 85.748
- type: mrr_at_3
value: 84.718
- type: mrr_at_5
value: 85.312
- type: ndcg_at_1
value: 79.662
- type: ndcg_at_10
value: 72.366
- type: ndcg_at_100
value: 75.42999999999999
- type: ndcg_at_1000
value: 76.469
- type: ndcg_at_3
value: 67.258
- type: ndcg_at_5
value: 70.14099999999999
- type: precision_at_1
value: 79.662
- type: precision_at_10
value: 15.254999999999999
- type: precision_at_100
value: 1.763
- type: precision_at_1000
value: 0.19
- type: precision_at_3
value: 43.358000000000004
- type: precision_at_5
value: 28.288999999999998
- type: recall_at_1
value: 39.831
- type: recall_at_10
value: 76.273
- type: recall_at_100
value: 88.163
- type: recall_at_1000
value: 95.017
- type: recall_at_3
value: 65.037
- type: recall_at_5
value: 70.722
- task:
type: Classification
dataset:
type: mteb/imdb
name: MTEB ImdbClassification
config: default
split: test
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
metrics:
- type: accuracy
value: 93.13879999999999
- type: ap
value: 89.94638859649079
- type: f1
value: 93.13371537570421
- task:
type: Retrieval
dataset:
type: msmarco
name: MTEB MSMARCO
config: default
split: dev
revision: None
metrics:
- type: map_at_1
value: 21.482
- type: map_at_10
value: 33.635999999999996
- type: map_at_100
value: 34.792
- type: map_at_1000
value: 34.839999999999996
- type: map_at_3
value: 29.553
- type: map_at_5
value: 31.892
- type: mrr_at_1
value: 22.076999999999998
- type: mrr_at_10
value: 34.247
- type: mrr_at_100
value: 35.337
- type: mrr_at_1000
value: 35.38
- type: mrr_at_3
value: 30.208000000000002
- type: mrr_at_5
value: 32.554
- type: ndcg_at_1
value: 22.092
- type: ndcg_at_10
value: 40.657
- type: ndcg_at_100
value: 46.251999999999995
- type: ndcg_at_1000
value: 47.466
- type: ndcg_at_3
value: 32.353
- type: ndcg_at_5
value: 36.532
- type: precision_at_1
value: 22.092
- type: precision_at_10
value: 6.5040000000000004
- type: precision_at_100
value: 0.9329999999999999
- type: precision_at_1000
value: 0.104
- type: precision_at_3
value: 13.719999999999999
- type: precision_at_5
value: 10.344000000000001
- type: recall_at_1
value: 21.482
- type: recall_at_10
value: 62.316
- type: recall_at_100
value: 88.283
- type: recall_at_1000
value: 97.554
- type: recall_at_3
value: 39.822
- type: recall_at_5
value: 49.805
- task:
type: Classification
dataset:
type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (en)
config: en
split: test
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
metrics:
- type: accuracy
value: 93.63657090743274
- type: f1
value: 93.49355466580484
- task:
type: Classification
dataset:
type: mteb/mtop_intent
name: MTEB MTOPIntentClassification (en)
config: en
split: test
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
metrics:
- type: accuracy
value: 66.01459188326493
- type: f1
value: 48.48386472180784
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (en)
config: en
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 73.49024882313383
- type: f1
value: 71.8750196914349
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (en)
config: en
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 77.38063214525891
- type: f1
value: 76.87364042122763
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-p2p
name: MTEB MedrxivClusteringP2P
config: default
split: test
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
metrics:
- type: v_measure
value: 34.30572302322684
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-s2s
name: MTEB MedrxivClusteringS2S
config: default
split: test
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
metrics:
- type: v_measure
value: 32.18418556367587
- task:
type: Reranking
dataset:
type: mteb/mind_small
name: MTEB MindSmallReranking
config: default
split: test
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
metrics:
- type: map
value: 32.268707296386154
- type: mrr
value: 33.481925531215055
- task:
type: Retrieval
dataset:
type: nfcorpus
name: MTEB NFCorpus
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 6.586
- type: map_at_10
value: 14.954999999999998
- type: map_at_100
value: 19.03
- type: map_at_1000
value: 20.653
- type: map_at_3
value: 10.859
- type: map_at_5
value: 12.577
- type: mrr_at_1
value: 47.988
- type: mrr_at_10
value: 57.57
- type: mrr_at_100
value: 58.050000000000004
- type: mrr_at_1000
value: 58.083
- type: mrr_at_3
value: 55.212
- type: mrr_at_5
value: 56.713
- type: ndcg_at_1
value: 45.975
- type: ndcg_at_10
value: 38.432
- type: ndcg_at_100
value: 35.287
- type: ndcg_at_1000
value: 44.35
- type: ndcg_at_3
value: 43.077
- type: ndcg_at_5
value: 40.952
- type: precision_at_1
value: 47.368
- type: precision_at_10
value: 28.483000000000004
- type: precision_at_100
value: 8.882
- type: precision_at_1000
value: 2.217
- type: precision_at_3
value: 40.144000000000005
- type: precision_at_5
value: 35.17
- type: recall_at_1
value: 6.586
- type: recall_at_10
value: 19.688
- type: recall_at_100
value: 35.426
- type: recall_at_1000
value: 68.09100000000001
- type: recall_at_3
value: 12.234
- type: recall_at_5
value: 14.937000000000001
- task:
type: Retrieval
dataset:
type: nq
name: MTEB NQ
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 27.322000000000003
- type: map_at_10
value: 43.224000000000004
- type: map_at_100
value: 44.275999999999996
- type: map_at_1000
value: 44.308
- type: map_at_3
value: 38.239000000000004
- type: map_at_5
value: 41.244
- type: mrr_at_1
value: 31.025000000000002
- type: mrr_at_10
value: 45.635
- type: mrr_at_100
value: 46.425
- type: mrr_at_1000
value: 46.445
- type: mrr_at_3
value: 41.42
- type: mrr_at_5
value: 44.038
- type: ndcg_at_1
value: 30.997000000000003
- type: ndcg_at_10
value: 51.55499999999999
- type: ndcg_at_100
value: 55.964999999999996
- type: ndcg_at_1000
value: 56.657000000000004
- type: ndcg_at_3
value: 42.185
- type: ndcg_at_5
value: 47.229
- type: precision_at_1
value: 30.997000000000003
- type: precision_at_10
value: 8.885
- type: precision_at_100
value: 1.1360000000000001
- type: precision_at_1000
value: 0.12
- type: precision_at_3
value: 19.457
- type: precision_at_5
value: 14.554
- type: recall_at_1
value: 27.322000000000003
- type: recall_at_10
value: 74.59400000000001
- type: recall_at_100
value: 93.699
- type: recall_at_1000
value: 98.76599999999999
- type: recall_at_3
value: 50.43
- type: recall_at_5
value: 62.073
- task:
type: Retrieval
dataset:
type: quora
name: MTEB QuoraRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 71.109
- type: map_at_10
value: 85.137
- type: map_at_100
value: 85.759
- type: map_at_1000
value: 85.774
- type: map_at_3
value: 82.25200000000001
- type: map_at_5
value: 84.031
- type: mrr_at_1
value: 82.01
- type: mrr_at_10
value: 87.97
- type: mrr_at_100
value: 88.076
- type: mrr_at_1000
value: 88.076
- type: mrr_at_3
value: 87.06
- type: mrr_at_5
value: 87.694
- type: ndcg_at_1
value: 81.99
- type: ndcg_at_10
value: 88.738
- type: ndcg_at_100
value: 89.928
- type: ndcg_at_1000
value: 90.01400000000001
- type: ndcg_at_3
value: 86.042
- type: ndcg_at_5
value: 87.505
- type: precision_at_1
value: 81.99
- type: precision_at_10
value: 13.468
- type: precision_at_100
value: 1.534
- type: precision_at_1000
value: 0.157
- type: precision_at_3
value: 37.702999999999996
- type: precision_at_5
value: 24.706
- type: recall_at_1
value: 71.109
- type: recall_at_10
value: 95.58
- type: recall_at_100
value: 99.62299999999999
- type: recall_at_1000
value: 99.98899999999999
- type: recall_at_3
value: 87.69
- type: recall_at_5
value: 91.982
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering
name: MTEB RedditClustering
config: default
split: test
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
metrics:
- type: v_measure
value: 59.43361510023748
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering-p2p
name: MTEB RedditClusteringP2P
config: default
split: test
revision: 282350215ef01743dc01b456c7f5241fa8937f16
metrics:
- type: v_measure
value: 64.53582642500159
- task:
type: Retrieval
dataset:
type: scidocs
name: MTEB SCIDOCS
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 4.2299999999999995
- type: map_at_10
value: 11.802
- type: map_at_100
value: 14.454
- type: map_at_1000
value: 14.865
- type: map_at_3
value: 7.911
- type: map_at_5
value: 9.912
- type: mrr_at_1
value: 21
- type: mrr_at_10
value: 32.722
- type: mrr_at_100
value: 33.989000000000004
- type: mrr_at_1000
value: 34.026
- type: mrr_at_3
value: 28.65
- type: mrr_at_5
value: 31.075000000000003
- type: ndcg_at_1
value: 21
- type: ndcg_at_10
value: 20.161
- type: ndcg_at_100
value: 30.122
- type: ndcg_at_1000
value: 36.399
- type: ndcg_at_3
value: 17.881
- type: ndcg_at_5
value: 16.439999999999998
- type: precision_at_1
value: 21
- type: precision_at_10
value: 10.94
- type: precision_at_100
value: 2.5340000000000003
- type: precision_at_1000
value: 0.402
- type: precision_at_3
value: 17.067
- type: precision_at_5
value: 15.120000000000001
- type: recall_at_1
value: 4.2299999999999995
- type: recall_at_10
value: 22.163
- type: recall_at_100
value: 51.42
- type: recall_at_1000
value: 81.652
- type: recall_at_3
value: 10.353
- type: recall_at_5
value: 15.323
- task:
type: STS
dataset:
type: mteb/sickr-sts
name: MTEB SICK-R
config: default
split: test
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
metrics:
- type: cos_sim_pearson
value: 86.44056731476951
- type: cos_sim_spearman
value: 82.32974396072802
- type: euclidean_pearson
value: 83.63616080755894
- type: euclidean_spearman
value: 82.32974071069209
- type: manhattan_pearson
value: 83.64149958303744
- type: manhattan_spearman
value: 82.32161014878858
- task:
type: STS
dataset:
type: mteb/sts12-sts
name: MTEB STS12
config: default
split: test
revision: a0d554a64d88156834ff5ae9920b964011b16384
metrics:
- type: cos_sim_pearson
value: 85.65083720426293
- type: cos_sim_spearman
value: 77.60786500521749
- type: euclidean_pearson
value: 81.8149634918642
- type: euclidean_spearman
value: 77.60637450428892
- type: manhattan_pearson
value: 81.83507575657566
- type: manhattan_spearman
value: 77.613220311151
- task:
type: STS
dataset:
type: mteb/sts13-sts
name: MTEB STS13
config: default
split: test
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
metrics:
- type: cos_sim_pearson
value: 87.35683624595698
- type: cos_sim_spearman
value: 87.94550696434106
- type: euclidean_pearson
value: 87.50272679030367
- type: euclidean_spearman
value: 87.94550696434106
- type: manhattan_pearson
value: 87.4759786099497
- type: manhattan_spearman
value: 87.90226811166427
- task:
type: STS
dataset:
type: mteb/sts14-sts
name: MTEB STS14
config: default
split: test
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
metrics:
- type: cos_sim_pearson
value: 86.27438743391316
- type: cos_sim_spearman
value: 83.85378984594779
- type: euclidean_pearson
value: 85.25840635223642
- type: euclidean_spearman
value: 83.85378983163673
- type: manhattan_pearson
value: 85.24936075631025
- type: manhattan_spearman
value: 83.85052479958138
- task:
type: STS
dataset:
type: mteb/sts15-sts
name: MTEB STS15
config: default
split: test
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
metrics:
- type: cos_sim_pearson
value: 87.4783814521557
- type: cos_sim_spearman
value: 88.473284566453
- type: euclidean_pearson
value: 87.94757741870404
- type: euclidean_spearman
value: 88.47327698999878
- type: manhattan_pearson
value: 87.93617414057984
- type: manhattan_spearman
value: 88.45889274229359
- task:
type: STS
dataset:
type: mteb/sts16-sts
name: MTEB STS16
config: default
split: test
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
metrics:
- type: cos_sim_pearson
value: 84.68359147631057
- type: cos_sim_spearman
value: 86.46426572535646
- type: euclidean_pearson
value: 85.98303971468599
- type: euclidean_spearman
value: 86.46426572535646
- type: manhattan_pearson
value: 85.95109710640726
- type: manhattan_spearman
value: 86.43282632541583
- task:
type: STS
dataset:
type: mteb/sts17-crosslingual-sts
name: MTEB STS17 (en-en)
config: en-en
split: test
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
metrics:
- type: cos_sim_pearson
value: 88.88758959688604
- type: cos_sim_spearman
value: 88.70384784133324
- type: euclidean_pearson
value: 89.27293800474978
- type: euclidean_spearman
value: 88.70384784133324
- type: manhattan_pearson
value: 89.41494348093664
- type: manhattan_spearman
value: 88.8330050824941
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (en)
config: en
split: test
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
metrics:
- type: cos_sim_pearson
value: 67.66759812551814
- type: cos_sim_spearman
value: 68.02368115471576
- type: euclidean_pearson
value: 69.52859542757353
- type: euclidean_spearman
value: 68.02368115471576
- type: manhattan_pearson
value: 69.50332399468952
- type: manhattan_spearman
value: 67.91228681203849
- task:
type: STS
dataset:
type: mteb/stsbenchmark-sts
name: MTEB STSBenchmark
config: default
split: test
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
metrics:
- type: cos_sim_pearson
value: 87.75891320010409
- type: cos_sim_spearman
value: 88.33063922402347
- type: euclidean_pearson
value: 88.02964654543274
- type: euclidean_spearman
value: 88.33063922402347
- type: manhattan_pearson
value: 88.03029440701458
- type: manhattan_spearman
value: 88.3158691488696
- task:
type: Reranking
dataset:
type: mteb/scidocs-reranking
name: MTEB SciDocsRR
config: default
split: test
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
metrics:
- type: map
value: 87.46897310470844
- type: mrr
value: 96.29042072669523
- task:
type: Retrieval
dataset:
type: scifact
name: MTEB SciFact
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 62.261
- type: map_at_10
value: 71.023
- type: map_at_100
value: 71.5
- type: map_at_1000
value: 71.518
- type: map_at_3
value: 67.857
- type: map_at_5
value: 69.44500000000001
- type: mrr_at_1
value: 65
- type: mrr_at_10
value: 72.11
- type: mrr_at_100
value: 72.479
- type: mrr_at_1000
value: 72.49600000000001
- type: mrr_at_3
value: 69.722
- type: mrr_at_5
value: 71.02199999999999
- type: ndcg_at_1
value: 65
- type: ndcg_at_10
value: 75.40599999999999
- type: ndcg_at_100
value: 77.41
- type: ndcg_at_1000
value: 77.83200000000001
- type: ndcg_at_3
value: 69.95599999999999
- type: ndcg_at_5
value: 72.296
- type: precision_at_1
value: 65
- type: precision_at_10
value: 9.966999999999999
- type: precision_at_100
value: 1.097
- type: precision_at_1000
value: 0.11299999999999999
- type: precision_at_3
value: 26.667
- type: precision_at_5
value: 17.666999999999998
- type: recall_at_1
value: 62.261
- type: recall_at_10
value: 87.822
- type: recall_at_100
value: 96.833
- type: recall_at_1000
value: 100
- type: recall_at_3
value: 73.06099999999999
- type: recall_at_5
value: 78.88300000000001
- task:
type: PairClassification
dataset:
type: mteb/sprintduplicatequestions-pairclassification
name: MTEB SprintDuplicateQuestions
config: default
split: test
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
metrics:
- type: cos_sim_accuracy
value: 99.86138613861387
- type: cos_sim_ap
value: 96.7851799601876
- type: cos_sim_f1
value: 92.94354838709677
- type: cos_sim_precision
value: 93.69918699186992
- type: cos_sim_recall
value: 92.2
- type: dot_accuracy
value: 99.86138613861387
- type: dot_ap
value: 96.78517996018759
- type: dot_f1
value: 92.94354838709677
- type: dot_precision
value: 93.69918699186992
- type: dot_recall
value: 92.2
- type: euclidean_accuracy
value: 99.86138613861387
- type: euclidean_ap
value: 96.78517996018759
- type: euclidean_f1
value: 92.94354838709677
- type: euclidean_precision
value: 93.69918699186992
- type: euclidean_recall
value: 92.2
- type: manhattan_accuracy
value: 99.86336633663366
- type: manhattan_ap
value: 96.79790073128503
- type: manhattan_f1
value: 93.0930930930931
- type: manhattan_precision
value: 93.18637274549098
- type: manhattan_recall
value: 93
- type: max_accuracy
value: 99.86336633663366
- type: max_ap
value: 96.79790073128503
- type: max_f1
value: 93.0930930930931
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering
name: MTEB StackExchangeClustering
config: default
split: test
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
metrics:
- type: v_measure
value: 65.07696952556874
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering-p2p
name: MTEB StackExchangeClusteringP2P
config: default
split: test
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
metrics:
- type: v_measure
value: 35.51701116515262
- task:
type: Reranking
dataset:
type: mteb/stackoverflowdupquestions-reranking
name: MTEB StackOverflowDupQuestions
config: default
split: test
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
metrics:
- type: map
value: 55.40099299306496
- type: mrr
value: 56.411316420507596
- task:
type: Summarization
dataset:
type: mteb/summeval
name: MTEB SummEval
config: default
split: test
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
metrics:
- type: cos_sim_pearson
value: 30.940008734510055
- type: cos_sim_spearman
value: 31.606997026865212
- type: dot_pearson
value: 30.940010256206353
- type: dot_spearman
value: 31.62194110302714
- task:
type: Retrieval
dataset:
type: trec-covid
name: MTEB TRECCOVID
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 0.197
- type: map_at_10
value: 1.6549999999999998
- type: map_at_100
value: 8.939
- type: map_at_1000
value: 22.402
- type: map_at_3
value: 0.587
- type: map_at_5
value: 0.931
- type: mrr_at_1
value: 74
- type: mrr_at_10
value: 84.667
- type: mrr_at_100
value: 84.667
- type: mrr_at_1000
value: 84.667
- type: mrr_at_3
value: 83.667
- type: mrr_at_5
value: 84.667
- type: ndcg_at_1
value: 69
- type: ndcg_at_10
value: 66.574
- type: ndcg_at_100
value: 51.074
- type: ndcg_at_1000
value: 47.263
- type: ndcg_at_3
value: 71.95
- type: ndcg_at_5
value: 70.52000000000001
- type: precision_at_1
value: 74
- type: precision_at_10
value: 70.39999999999999
- type: precision_at_100
value: 52.580000000000005
- type: precision_at_1000
value: 20.93
- type: precision_at_3
value: 76.667
- type: precision_at_5
value: 75.6
- type: recall_at_1
value: 0.197
- type: recall_at_10
value: 1.92
- type: recall_at_100
value: 12.655
- type: recall_at_1000
value: 44.522
- type: recall_at_3
value: 0.639
- type: recall_at_5
value: 1.03
- task:
type: Retrieval
dataset:
type: webis-touche2020
name: MTEB Touche2020
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 1.735
- type: map_at_10
value: 9.064
- type: map_at_100
value: 15.021999999999998
- type: map_at_1000
value: 16.596
- type: map_at_3
value: 4.188
- type: map_at_5
value: 6.194999999999999
- type: mrr_at_1
value: 26.531
- type: mrr_at_10
value: 44.413000000000004
- type: mrr_at_100
value: 45.433
- type: mrr_at_1000
value: 45.452999999999996
- type: mrr_at_3
value: 41.497
- type: mrr_at_5
value: 42.925000000000004
- type: ndcg_at_1
value: 22.448999999999998
- type: ndcg_at_10
value: 22.597
- type: ndcg_at_100
value: 34.893
- type: ndcg_at_1000
value: 46.763
- type: ndcg_at_3
value: 24.366
- type: ndcg_at_5
value: 23.959
- type: precision_at_1
value: 26.531
- type: precision_at_10
value: 21.02
- type: precision_at_100
value: 7.51
- type: precision_at_1000
value: 1.541
- type: precision_at_3
value: 27.211000000000002
- type: precision_at_5
value: 25.306
- type: recall_at_1
value: 1.735
- type: recall_at_10
value: 15.870999999999999
- type: recall_at_100
value: 47.385
- type: recall_at_1000
value: 83.55
- type: recall_at_3
value: 5.813
- type: recall_at_5
value: 9.707
- task:
type: Classification
dataset:
type: mteb/toxic_conversations_50k
name: MTEB ToxicConversationsClassification
config: default
split: test
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
metrics:
- type: accuracy
value: 71.19
- type: ap
value: 15.106812062408629
- type: f1
value: 55.254852511954255
- task:
type: Classification
dataset:
type: mteb/tweet_sentiment_extraction
name: MTEB TweetSentimentExtractionClassification
config: default
split: test
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
metrics:
- type: accuracy
value: 61.553480475382
- type: f1
value: 61.697424438626435
- task:
type: Clustering
dataset:
type: mteb/twentynewsgroups-clustering
name: MTEB TwentyNewsgroupsClustering
config: default
split: test
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
metrics:
- type: v_measure
value: 53.12092298453447
- task:
type: PairClassification
dataset:
type: mteb/twittersemeval2015-pairclassification
name: MTEB TwitterSemEval2015
config: default
split: test
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
metrics:
- type: cos_sim_accuracy
value: 87.35173153722357
- type: cos_sim_ap
value: 78.22985044080261
- type: cos_sim_f1
value: 71.23356926188069
- type: cos_sim_precision
value: 68.36487142163999
- type: cos_sim_recall
value: 74.35356200527704
- type: dot_accuracy
value: 87.35173153722357
- type: dot_ap
value: 78.22985958574529
- type: dot_f1
value: 71.23356926188069
- type: dot_precision
value: 68.36487142163999
- type: dot_recall
value: 74.35356200527704
- type: euclidean_accuracy
value: 87.35173153722357
- type: euclidean_ap
value: 78.22985909816191
- type: euclidean_f1
value: 71.23356926188069
- type: euclidean_precision
value: 68.36487142163999
- type: euclidean_recall
value: 74.35356200527704
- type: manhattan_accuracy
value: 87.36365261965786
- type: manhattan_ap
value: 78.18108280854142
- type: manhattan_f1
value: 71.19958634953466
- type: manhattan_precision
value: 69.79219462747086
- type: manhattan_recall
value: 72.66490765171504
- type: max_accuracy
value: 87.36365261965786
- type: max_ap
value: 78.22985958574529
- type: max_f1
value: 71.23356926188069
- task:
type: PairClassification
dataset:
type: mteb/twitterurlcorpus-pairclassification
name: MTEB TwitterURLCorpus
config: default
split: test
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
metrics:
- type: cos_sim_accuracy
value: 88.71424690495596
- type: cos_sim_ap
value: 85.53000600450122
- type: cos_sim_f1
value: 77.95508274231679
- type: cos_sim_precision
value: 74.92189718829879
- type: cos_sim_recall
value: 81.24422543886665
- type: dot_accuracy
value: 88.71424690495596
- type: dot_ap
value: 85.53000387261983
- type: dot_f1
value: 77.95508274231679
- type: dot_precision
value: 74.92189718829879
- type: dot_recall
value: 81.24422543886665
- type: euclidean_accuracy
value: 88.71424690495596
- type: euclidean_ap
value: 85.53000527321076
- type: euclidean_f1
value: 77.95508274231679
- type: euclidean_precision
value: 74.92189718829879
- type: euclidean_recall
value: 81.24422543886665
- type: manhattan_accuracy
value: 88.7297706368611
- type: manhattan_ap
value: 85.49670114967172
- type: manhattan_f1
value: 77.91265729089562
- type: manhattan_precision
value: 75.01425313568986
- type: manhattan_recall
value: 81.04404065291038
- type: max_accuracy
value: 88.7297706368611
- type: max_ap
value: 85.53000600450122
- type: max_f1
value: 77.95508274231679
{MODEL_NAME}
This is a sentence-transformers model: It maps sentences & paragraphs to a 1024 dimensional dense vector space and can be used for tasks like clustering or semantic search.
Usage (Sentence-Transformers)
Using this model becomes easy when you have sentence-transformers installed:
pip install -U sentence-transformers
Then you can use the model like this:
from sentence_transformers import SentenceTransformer
sentences = ["This is an example sentence", "Each sentence is converted"]
model = SentenceTransformer('{MODEL_NAME}')
embeddings = model.encode(sentences)
print(embeddings)
Evaluation Results
For an automated evaluation of this model, see the Sentence Embeddings Benchmark: https://seb.sbert.net
Training
The model was trained with the parameters:
DataLoader:
torch.utils.data.dataloader.DataLoader of length 1196 with parameters:
{'batch_size': 10, 'sampler': 'torch.utils.data.sampler.SequentialSampler', 'batch_sampler': 'torch.utils.data.sampler.BatchSampler'}
Loss:
sentence_transformers.losses.MultipleNegativesRankingLoss.MultipleNegativesRankingLoss with parameters:
{'scale': 20.0, 'similarity_fct': 'cos_sim'}
Parameters of the fit()-Method:
{
"epochs": 5,
"evaluation_steps": 50,
"evaluator": "sentence_transformers.evaluation.InformationRetrievalEvaluator.InformationRetrievalEvaluator",
"max_grad_norm": 1,
"optimizer_class": "<class 'torch.optim.adamw.AdamW'>",
"optimizer_params": {
"lr": 2e-05
},
"scheduler": "WarmupLinear",
"steps_per_epoch": null,
"warmup_steps": 598,
"weight_decay": 0.01
}
Full Model Architecture
SentenceTransformer(
(0): Transformer({'max_seq_length': 512, 'do_lower_case': True}) with Transformer model: BertModel
(1): Pooling({'word_embedding_dimension': 1024, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False})
(2): Normalize()
)