Add benchmark to MTEB
#7
by
sam-gab
- opened
This looks really promising. It would be great to see how it compared to other models on MTEB leaderboard
Thanks for your interest in our work! The current MTEB focuses on single language retrieval (English/Chinese), while the goal of bge-m3 is versatility(Multi-Functionality, Multi-Linguality, and Multi-Granularity),
so we didn't report the performance of bge-m3 on it.
We are working on testing the performance of bge-m3 on more datasets, and will release these results as soon as possible.
Ran around 50% of MTEB, here are some scores for orientation.
tags:
- mteb
model-index:
- name: bge-m3
results:
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en)
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
- type: accuracy
value: 75.61194029850746
- type: ap
value: 39.4441857734361
- type: f1
value: 69.97034098944273
- task:
type: Classification
dataset:
type: mteb/amazon_polarity
name: MTEB AmazonPolarityClassification
config: default
split: test
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
metrics:
- type: accuracy
value: 91.005775
- type: ap
value: 87.2965129654928
- type: f1
value: 90.99368816155456
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (en)
config: en
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy
value: 46.976
- type: f1
value: 44.92055541556327
- task:
type: Retrieval
dataset:
type: arguana
name: MTEB ArguAna
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 28.733999999999998
- type: map_at_10
value: 45.134
- type: map_at_100
value: 46.04
- type: map_at_1000
value: 46.047
- type: map_at_3
value: 40.149
- type: map_at_5
value: 43.24
- type: mrr_at_1
value: 29.587000000000003
- type: mrr_at_10
value: 45.428000000000004
- type: mrr_at_100
value: 46.336
- type: mrr_at_1000
value: 46.343
- type: mrr_at_3
value: 40.505
- type: mrr_at_5
value: 43.531
- type: ndcg_at_1
value: 28.733999999999998
- type: ndcg_at_10
value: 53.994
- type: ndcg_at_100
value: 57.742000000000004
- type: ndcg_at_1000
value: 57.908
- type: ndcg_at_3
value: 43.901
- type: ndcg_at_5
value: 49.437999999999995
- type: precision_at_1
value: 28.733999999999998
- type: precision_at_10
value: 8.215
- type: precision_at_100
value: 0.9820000000000001
- type: precision_at_1000
value: 0.1
- type: precision_at_3
value: 18.255
- type: precision_at_5
value: 13.627
- type: recall_at_1
value: 28.733999999999998
- type: recall_at_10
value: 82.148
- type: recall_at_100
value: 98.222
- type: recall_at_1000
value: 99.502
- type: recall_at_3
value: 54.765
- type: recall_at_5
value: 68.137
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-p2p
name: MTEB ArxivClusteringP2P
config: default
split: test
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
metrics:
- type: v_measure
value: 39.418453651259746
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-s2s
name: MTEB ArxivClusteringS2S
config: default
split: test
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
metrics:
- type: v_measure
value: 27.769780397780057
- task:
type: Reranking
dataset:
type: mteb/askubuntudupquestions-reranking
name: MTEB AskUbuntuDupQuestions
config: default
split: test
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
metrics:
- type: map
value: 61.47747150445644
- type: mrr
value: 74.28241656773513
- task:
type: BitextMining
dataset:
type: mteb/bucc-bitext-mining
name: MTEB BUCC (de-en)
config: de-en
split: test
revision: d51519689f32196a32af33b075a01d0e7c51e252
metrics:
- type: accuracy
value: 99.53027139874739
- type: f1
value: 99.45720250521921
- type: precision
value: 99.42066805845512
- type: recall
value: 99.53027139874739
- task:
type: BitextMining
dataset:
type: mteb/bucc-bitext-mining
name: MTEB BUCC (fr-en)
config: fr-en
split: test
revision: d51519689f32196a32af33b075a01d0e7c51e252
metrics:
- type: accuracy
value: 98.72331058771738
- type: f1
value: 98.55088414410449
- type: precision
value: 98.46650524616628
- type: recall
value: 98.72331058771738
- task:
type: BitextMining
dataset:
type: mteb/bucc-bitext-mining
name: MTEB BUCC (ru-en)
config: ru-en
split: test
revision: d51519689f32196a32af33b075a01d0e7c51e252
metrics:
- type: accuracy
value: 97.90093522687911
- type: f1
value: 97.64923219027827
- type: precision
value: 97.52338067197783
- type: recall
value: 97.90093522687911
- task:
type: BitextMining
dataset:
type: mteb/bucc-bitext-mining
name: MTEB BUCC (zh-en)
config: zh-en
split: test
revision: d51519689f32196a32af33b075a01d0e7c51e252
metrics:
- type: accuracy
value: 99.0521327014218
- type: f1
value: 98.99947340705634
- type: precision
value: 98.97314375987362
- type: recall
value: 99.0521327014218
- task:
type: Classification
dataset:
type: mteb/banking77
name: MTEB Banking77Classification
config: default
split: test
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
metrics:
- type: accuracy
value: 81.93181818181819
- type: f1
value: 81.0852312152688
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-p2p
name: MTEB BiorxivClusteringP2P
config: default
split: test
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
metrics:
- type: v_measure
value: 32.856148672160444
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-s2s
name: MTEB BiorxivClusteringS2S
config: default
split: test
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
metrics:
- type: v_measure
value: 25.729734227390967
- task:
type: BitextMining
dataset:
type: strombergnlp/bornholmsk_parallel
name: MTEB BornholmBitextMining
config: default
split: test
revision: 3bc5cfb4ec514264fe2db5615fac9016f7251552
metrics:
- type: accuracy
value: 52.6
- type: f1
value: 44.05714285714286
- type: precision
value: 40.93380952380952
- type: recall
value: 52.6
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackAndroidRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 31.1
- type: map_at_10
value: 42.028
- type: map_at_100
value: 43.57
- type: map_at_1000
value: 43.683
- type: map_at_3
value: 38.479
- type: map_at_5
value: 40.502
- type: mrr_at_1
value: 38.054
- type: mrr_at_10
value: 48.073
- type: mrr_at_100
value: 48.824
- type: mrr_at_1000
value: 48.856
- type: mrr_at_3
value: 45.231
- type: mrr_at_5
value: 46.941
- type: ndcg_at_1
value: 37.911
- type: ndcg_at_10
value: 48.406
- type: ndcg_at_100
value: 54.057
- type: ndcg_at_1000
value: 55.81700000000001
- type: ndcg_at_3
value: 42.988
- type: ndcg_at_5
value: 45.686
- type: precision_at_1
value: 37.911
- type: precision_at_10
value: 9.285
- type: precision_at_100
value: 1.498
- type: precision_at_1000
value: 0.196
- type: precision_at_3
value: 20.41
- type: precision_at_5
value: 14.907
- type: recall_at_1
value: 31.1
- type: recall_at_10
value: 60.50299999999999
- type: recall_at_100
value: 84.313
- type: recall_at_1000
value: 95.44500000000001
- type: recall_at_3
value: 45.550000000000004
- type: recall_at_5
value: 52.735
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackEnglishRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 28.720000000000002
- type: map_at_10
value: 38.87
- type: map_at_100
value: 40.141
- type: map_at_1000
value: 40.27
- type: map_at_3
value: 36.064
- type: map_at_5
value: 37.659
- type: mrr_at_1
value: 35.86
- type: mrr_at_10
value: 44.458
- type: mrr_at_100
value: 45.221000000000004
- type: mrr_at_1000
value: 45.266
- type: mrr_at_3
value: 42.335
- type: mrr_at_5
value: 43.59
- type: ndcg_at_1
value: 35.86
- type: ndcg_at_10
value: 44.397
- type: ndcg_at_100
value: 48.924
- type: ndcg_at_1000
value: 50.949
- type: ndcg_at_3
value: 40.382
- type: ndcg_at_5
value: 42.308
- type: precision_at_1
value: 35.86
- type: precision_at_10
value: 8.369
- type: precision_at_100
value: 1.369
- type: precision_at_1000
value: 0.181
- type: precision_at_3
value: 19.448
- type: precision_at_5
value: 13.783000000000001
- type: recall_at_1
value: 28.720000000000002
- type: recall_at_10
value: 54.057
- type: recall_at_100
value: 73.015
- type: recall_at_1000
value: 85.90100000000001
- type: recall_at_3
value: 42.561
- type: recall_at_5
value: 47.827999999999996
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackGamingRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 37.798
- type: map_at_10
value: 49.559999999999995
- type: map_at_100
value: 50.586
- type: map_at_1000
value: 50.64300000000001
- type: map_at_3
value: 46.686
- type: map_at_5
value: 48.292
- type: mrr_at_1
value: 42.884
- type: mrr_at_10
value: 52.864999999999995
- type: mrr_at_100
value: 53.549
- type: mrr_at_1000
value: 53.583000000000006
- type: mrr_at_3
value: 50.658
- type: mrr_at_5
value: 51.834
- type: ndcg_at_1
value: 42.884
- type: ndcg_at_10
value: 55.147
- type: ndcg_at_100
value: 59.205
- type: ndcg_at_1000
value: 60.431999999999995
- type: ndcg_at_3
value: 50.268
- type: ndcg_at_5
value: 52.595000000000006
- type: precision_at_1
value: 42.884
- type: precision_at_10
value: 8.802999999999999
- type: precision_at_100
value: 1.1769999999999998
- type: precision_at_1000
value: 0.133
- type: precision_at_3
value: 22.299
- type: precision_at_5
value: 15.160000000000002
- type: recall_at_1
value: 37.798
- type: recall_at_10
value: 68.28
- type: recall_at_100
value: 85.697
- type: recall_at_1000
value: 94.447
- type: recall_at_3
value: 55.184999999999995
- type: recall_at_5
value: 60.940000000000005
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackGisRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 24.935
- type: map_at_10
value: 32.757999999999996
- type: map_at_100
value: 33.633
- type: map_at_1000
value: 33.716
- type: map_at_3
value: 30.168
- type: map_at_5
value: 31.513999999999996
- type: mrr_at_1
value: 27.119
- type: mrr_at_10
value: 34.885
- type: mrr_at_100
value: 35.674
- type: mrr_at_1000
value: 35.739
- type: mrr_at_3
value: 32.505
- type: mrr_at_5
value: 33.714
- type: ndcg_at_1
value: 27.006000000000004
- type: ndcg_at_10
value: 37.56
- type: ndcg_at_100
value: 42.025
- type: ndcg_at_1000
value: 44.297
- type: ndcg_at_3
value: 32.408
- type: ndcg_at_5
value: 34.64
- type: precision_at_1
value: 27.006000000000004
- type: precision_at_10
value: 5.774
- type: precision_at_100
value: 0.844
- type: precision_at_1000
value: 0.108
- type: precision_at_3
value: 13.635
- type: precision_at_5
value: 9.424000000000001
- type: recall_at_1
value: 24.935
- type: recall_at_10
value: 50.608
- type: recall_at_100
value: 71.344
- type: recall_at_1000
value: 88.67699999999999
- type: recall_at_3
value: 36.368
- type: recall_at_5
value: 41.81
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackMathematicaRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 15.723
- type: map_at_10
value: 22.159000000000002
- type: map_at_100
value: 23.399
- type: map_at_1000
value: 23.513
- type: map_at_3
value: 19.792
- type: map_at_5
value: 21.102999999999998
- type: mrr_at_1
value: 19.527
- type: mrr_at_10
value: 26.346999999999998
- type: mrr_at_100
value: 27.48
- type: mrr_at_1000
value: 27.544999999999998
- type: mrr_at_3
value: 23.983999999999998
- type: mrr_at_5
value: 25.178
- type: ndcg_at_1
value: 19.403000000000002
- type: ndcg_at_10
value: 26.789
- type: ndcg_at_100
value: 32.791
- type: ndcg_at_1000
value: 35.58
- type: ndcg_at_3
value: 22.235
- type: ndcg_at_5
value: 24.27
- type: precision_at_1
value: 19.403000000000002
- type: precision_at_10
value: 4.913
- type: precision_at_100
value: 0.903
- type: precision_at_1000
value: 0.128
- type: precision_at_3
value: 10.488999999999999
- type: precision_at_5
value: 7.710999999999999
- type: recall_at_1
value: 15.723
- type: recall_at_10
value: 37.143
- type: recall_at_100
value: 63.402
- type: recall_at_1000
value: 83.291
- type: recall_at_3
value: 24.446
- type: recall_at_5
value: 29.544999999999998
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackPhysicsRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 26.606
- type: map_at_10
value: 36.495
- type: map_at_100
value: 37.759
- type: map_at_1000
value: 37.877
- type: map_at_3
value: 33.542
- type: map_at_5
value: 35.256
- type: mrr_at_1
value: 32.435
- type: mrr_at_10
value: 42.126999999999995
- type: mrr_at_100
value: 42.96
- type: mrr_at_1000
value: 43.006
- type: mrr_at_3
value: 39.75
- type: mrr_at_5
value: 41.169
- type: ndcg_at_1
value: 32.531
- type: ndcg_at_10
value: 42.382
- type: ndcg_at_100
value: 47.721000000000004
- type: ndcg_at_1000
value: 49.888
- type: ndcg_at_3
value: 37.687
- type: ndcg_at_5
value: 39.987
- type: precision_at_1
value: 32.531
- type: precision_at_10
value: 7.7
- type: precision_at_100
value: 1.209
- type: precision_at_1000
value: 0.159
- type: precision_at_3
value: 18.062
- type: precision_at_5
value: 12.723999999999998
- type: recall_at_1
value: 26.606
- type: recall_at_10
value: 54.277
- type: recall_at_100
value: 76.91
- type: recall_at_1000
value: 90.979
- type: recall_at_3
value: 40.692
- type: recall_at_5
value: 46.949999999999996
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackProgrammersRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 25.306
- type: map_at_10
value: 34.676
- type: map_at_100
value: 35.939
- type: map_at_1000
value: 36.044
- type: map_at_3
value: 31.418000000000003
- type: map_at_5
value: 33.323
- type: mrr_at_1
value: 31.507
- type: mrr_at_10
value: 39.893
- type: mrr_at_100
value: 40.808
- type: mrr_at_1000
value: 40.859
- type: mrr_at_3
value: 37.080999999999996
- type: mrr_at_5
value: 38.708
- type: ndcg_at_1
value: 31.392999999999997
- type: ndcg_at_10
value: 40.357
- type: ndcg_at_100
value: 45.878
- type: ndcg_at_1000
value: 48.101
- type: ndcg_at_3
value: 34.914
- type: ndcg_at_5
value: 37.476
- type: precision_at_1
value: 31.392999999999997
- type: precision_at_10
value: 7.352
- type: precision_at_100
value: 1.1769999999999998
- type: precision_at_1000
value: 0.153
- type: precision_at_3
value: 16.476
- type: precision_at_5
value: 11.918
- type: recall_at_1
value: 25.306
- type: recall_at_10
value: 52.528
- type: recall_at_100
value: 76.069
- type: recall_at_1000
value: 91.106
- type: recall_at_3
value: 37.275000000000006
- type: recall_at_5
value: 44.080999999999996
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackStatsRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 23.159
- type: map_at_10
value: 29.647000000000002
- type: map_at_100
value: 30.441000000000003
- type: map_at_1000
value: 30.531999999999996
- type: map_at_3
value: 27.076
- type: map_at_5
value: 28.792
- type: mrr_at_1
value: 25.613000000000003
- type: mrr_at_10
value: 32.123000000000005
- type: mrr_at_100
value: 32.814
- type: mrr_at_1000
value: 32.883
- type: mrr_at_3
value: 29.755
- type: mrr_at_5
value: 31.296000000000003
- type: ndcg_at_1
value: 25.613000000000003
- type: ndcg_at_10
value: 33.707
- type: ndcg_at_100
value: 37.62
- type: ndcg_at_1000
value: 40.042
- type: ndcg_at_3
value: 29.086000000000002
- type: ndcg_at_5
value: 31.823
- type: precision_at_1
value: 25.613000000000003
- type: precision_at_10
value: 5.2909999999999995
- type: precision_at_100
value: 0.7849999999999999
- type: precision_at_1000
value: 0.107
- type: precision_at_3
value: 12.27
- type: precision_at_5
value: 9.11
- type: recall_at_1
value: 23.159
- type: recall_at_10
value: 43.795
- type: recall_at_100
value: 61.436
- type: recall_at_1000
value: 79.511
- type: recall_at_3
value: 31.394
- type: recall_at_5
value: 38.002
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackTexRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 17.523
- type: map_at_10
value: 24.34
- type: map_at_100
value: 25.318
- type: map_at_1000
value: 25.432
- type: map_at_3
value: 22.31
- type: map_at_5
value: 23.406
- type: mrr_at_1
value: 21.163
- type: mrr_at_10
value: 27.907
- type: mrr_at_100
value: 28.816000000000003
- type: mrr_at_1000
value: 28.89
- type: mrr_at_3
value: 26.015
- type: mrr_at_5
value: 27.046
- type: ndcg_at_1
value: 21.129
- type: ndcg_at_10
value: 28.542
- type: ndcg_at_100
value: 33.465
- type: ndcg_at_1000
value: 36.339
- type: ndcg_at_3
value: 24.905
- type: ndcg_at_5
value: 26.489
- type: precision_at_1
value: 21.129
- type: precision_at_10
value: 5.045
- type: precision_at_100
value: 0.8699999999999999
- type: precision_at_1000
value: 0.129
- type: precision_at_3
value: 11.643
- type: precision_at_5
value: 8.245
- type: recall_at_1
value: 17.523
- type: recall_at_10
value: 37.682
- type: recall_at_100
value: 60.111000000000004
- type: recall_at_1000
value: 80.766
- type: recall_at_3
value: 27.412
- type: recall_at_5
value: 31.518
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackUnixRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 26.284000000000002
- type: map_at_10
value: 34.435
- type: map_at_100
value: 35.545
- type: map_at_1000
value: 35.644
- type: map_at_3
value: 32.036
- type: map_at_5
value: 33.335
- type: mrr_at_1
value: 30.784
- type: mrr_at_10
value: 38.261
- type: mrr_at_100
value: 39.153
- type: mrr_at_1000
value: 39.208999999999996
- type: mrr_at_3
value: 36.022999999999996
- type: mrr_at_5
value: 37.282
- type: ndcg_at_1
value: 30.784
- type: ndcg_at_10
value: 39.091
- type: ndcg_at_100
value: 44.391999999999996
- type: ndcg_at_1000
value: 46.681
- type: ndcg_at_3
value: 34.778
- type: ndcg_at_5
value: 36.664
- type: precision_at_1
value: 30.784
- type: precision_at_10
value: 6.446000000000001
- type: precision_at_100
value: 1.014
- type: precision_at_1000
value: 0.132
- type: precision_at_3
value: 15.672
- type: precision_at_5
value: 10.84
- type: recall_at_1
value: 26.284000000000002
- type: recall_at_10
value: 49.467
- type: recall_at_100
value: 73.039
- type: recall_at_1000
value: 89.037
- type: recall_at_3
value: 37.519999999999996
- type: recall_at_5
value: 42.435
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackWebmastersRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 25.263999999999996
- type: map_at_10
value: 34.665
- type: map_at_100
value: 36.137
- type: map_at_1000
value: 36.354
- type: map_at_3
value: 32.137
- type: map_at_5
value: 33.371
- type: mrr_at_1
value: 31.225
- type: mrr_at_10
value: 39.948
- type: mrr_at_100
value: 40.794999999999995
- type: mrr_at_1000
value: 40.858
- type: mrr_at_3
value: 37.879000000000005
- type: mrr_at_5
value: 39.035
- type: ndcg_at_1
value: 30.830000000000002
- type: ndcg_at_10
value: 40.516000000000005
- type: ndcg_at_100
value: 45.7
- type: ndcg_at_1000
value: 48.446
- type: ndcg_at_3
value: 36.603
- type: ndcg_at_5
value: 38.098
- type: precision_at_1
value: 30.830000000000002
- type: precision_at_10
value: 7.767
- type: precision_at_100
value: 1.48
- type: precision_at_1000
value: 0.23800000000000002
- type: precision_at_3
value: 17.391000000000002
- type: precision_at_5
value: 12.292
- type: recall_at_1
value: 25.263999999999996
- type: recall_at_10
value: 51.034
- type: recall_at_100
value: 74.493
- type: recall_at_1000
value: 92.15100000000001
- type: recall_at_3
value: 39.519999999999996
- type: recall_at_5
value: 43.74
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackWordpressRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 20.4
- type: map_at_10
value: 27.72
- type: map_at_100
value: 28.57
- type: map_at_1000
value: 28.682999999999996
- type: map_at_3
value: 25.365
- type: map_at_5
value: 26.773000000000003
- type: mrr_at_1
value: 22.551
- type: mrr_at_10
value: 29.829
- type: mrr_at_100
value: 30.604
- type: mrr_at_1000
value: 30.691000000000003
- type: mrr_at_3
value: 27.695999999999998
- type: mrr_at_5
value: 28.962
- type: ndcg_at_1
value: 22.551
- type: ndcg_at_10
value: 32.096999999999994
- type: ndcg_at_100
value: 36.518
- type: ndcg_at_1000
value: 39.487
- type: ndcg_at_3
value: 27.655
- type: ndcg_at_5
value: 29.975
- type: precision_at_1
value: 22.551
- type: precision_at_10
value: 5.083
- type: precision_at_100
value: 0.787
- type: precision_at_1000
value: 0.117
- type: precision_at_3
value: 11.83
- type: precision_at_5
value: 8.577
- type: recall_at_1
value: 20.4
- type: recall_at_10
value: 43.444
- type: recall_at_100
value: 64.19500000000001
- type: recall_at_1000
value: 86.586
- type: recall_at_3
value: 31.75
- type: recall_at_5
value: 37.214999999999996
- task:
type: Retrieval
dataset:
type: dbpedia-entity
name: MTEB DBPedia
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 8.709
- type: map_at_10
value: 18.137
- type: map_at_100
value: 25.337
- type: map_at_1000
value: 26.929
- type: map_at_3
value: 13.164000000000001
- type: map_at_5
value: 15.332
- type: mrr_at_1
value: 63.5
- type: mrr_at_10
value: 72.938
- type: mrr_at_100
value: 73.248
- type: mrr_at_1000
value: 73.25500000000001
- type: mrr_at_3
value: 70.917
- type: mrr_at_5
value: 72.317
- type: ndcg_at_1
value: 52.75
- type: ndcg_at_10
value: 39.837
- type: ndcg_at_100
value: 44.204
- type: ndcg_at_1000
value: 51.514
- type: ndcg_at_3
value: 44.178
- type: ndcg_at_5
value: 41.703
- type: precision_at_1
value: 63.5
- type: precision_at_10
value: 31.5
- type: precision_at_100
value: 10.152999999999999
- type: precision_at_1000
value: 1.9929999999999999
- type: precision_at_3
value: 46.916999999999994
- type: precision_at_5
value: 39.85
- type: recall_at_1
value: 8.709
- type: recall_at_10
value: 23.595
- type: recall_at_100
value: 50.244
- type: recall_at_1000
value: 73.193
- type: recall_at_3
value: 14.504
- type: recall_at_5
value: 18.137
- task:
type: Classification
dataset:
type: mteb/emotion
name: MTEB EmotionClassification
config: default
split: test
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
metrics:
- type: accuracy
value: 50.154999999999994
- type: f1
value: 43.57245108706806
- task:
type: Retrieval
dataset:
type: fiqa
name: MTEB FiQA2018
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 20.968999999999998
- type: map_at_10
value: 33.664
- type: map_at_100
value: 35.471000000000004
- type: map_at_1000
value: 35.65
- type: map_at_3
value: 29.997
- type: map_at_5
value: 31.921
- type: mrr_at_1
value: 42.13
- type: mrr_at_10
value: 50.475
- type: mrr_at_100
value: 51.23799999999999
- type: mrr_at_1000
value: 51.281
- type: mrr_at_3
value: 48.687999999999995
- type: mrr_at_5
value: 49.591
- type: ndcg_at_1
value: 42.284
- type: ndcg_at_10
value: 41.365
- type: ndcg_at_100
value: 47.863
- type: ndcg_at_1000
value: 50.971999999999994
- type: ndcg_at_3
value: 38.84
- type: ndcg_at_5
value: 39.184000000000005
- type: precision_at_1
value: 42.284
- type: precision_at_10
value: 11.265
- type: precision_at_100
value: 1.7850000000000001
- type: precision_at_1000
value: 0.23500000000000001
- type: precision_at_3
value: 25.977
- type: precision_at_5
value: 18.426000000000002
- type: recall_at_1
value: 20.968999999999998
- type: recall_at_10
value: 47.239
- type: recall_at_100
value: 71.334
- type: recall_at_1000
value: 89.916
- type: recall_at_3
value: 35.38
- type: recall_at_5
value: 39.965
- task:
type: Classification
dataset:
type: mteb/imdb
name: MTEB ImdbClassification
config: default
split: test
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
metrics:
- type: accuracy
value: 87.80999999999999
- type: ap
value: 82.64452124367875
- type: f1
value: 87.79250775511873
- task:
type: Classification
dataset:
type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (en)
config: en
split: test
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
metrics:
- type: accuracy
value: 93.3766529867761
- type: f1
value: 93.07516766462871
- task:
type: Classification
dataset:
type: mteb/mtop_intent
name: MTEB MTOPIntentClassification (en)
config: en
split: test
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
metrics:
- type: accuracy
value: 66.59598723210213
- type: f1
value: 47.047272522163624
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (en)
config: en
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 71.06926698049764
- type: f1
value: 69.13014185231128
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (en)
config: en
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 76.66442501681236
- type: f1
value: 75.63836848136394
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-p2p
name: MTEB MedrxivClusteringP2P
config: default
split: test
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
metrics:
- type: v_measure
value: 30.23749152164288
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-s2s
name: MTEB MedrxivClusteringS2S
config: default
split: test
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
metrics:
- type: v_measure
value: 26.083238688599486
- task:
type: Retrieval
dataset:
type: nfcorpus
name: MTEB NFCorpus
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 5.272
- type: map_at_10
value: 11.716999999999999
- type: map_at_100
value: 14.402999999999999
- type: map_at_1000
value: 15.664
- type: map_at_3
value: 8.956
- type: map_at_5
value: 10.249
- type: mrr_at_1
value: 43.963
- type: mrr_at_10
value: 52.553000000000004
- type: mrr_at_100
value: 53.176
- type: mrr_at_1000
value: 53.222
- type: mrr_at_3
value: 51.135
- type: mrr_at_5
value: 51.94
- type: ndcg_at_1
value: 41.486000000000004
- type: ndcg_at_10
value: 31.342
- type: ndcg_at_100
value: 28.471999999999998
- type: ndcg_at_1000
value: 37.102000000000004
- type: ndcg_at_3
value: 37.736
- type: ndcg_at_5
value: 35.105
- type: precision_at_1
value: 43.344
- type: precision_at_10
value: 22.786
- type: precision_at_100
value: 7.093000000000001
- type: precision_at_1000
value: 1.9539999999999997
- type: precision_at_3
value: 35.707
- type: precision_at_5
value: 30.217
- type: recall_at_1
value: 5.272
- type: recall_at_10
value: 14.671999999999999
- type: recall_at_100
value: 28.308
- type: recall_at_1000
value: 59.11300000000001
- type: recall_at_3
value: 10.07
- type: recall_at_5
value: 11.99
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering
name: MTEB RedditClustering
config: default
split: test
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
metrics:
- type: v_measure
value: 45.473096154259935
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering-p2p
name: MTEB RedditClusteringP2P
config: default
split: test
revision: 282350215ef01743dc01b456c7f5241fa8937f16
metrics:
- type: v_measure
value: 57.54220073389692
- task:
type: Reranking
dataset:
type: mteb/scidocs-reranking
name: MTEB SciDocsRR
config: default
split: test
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
metrics:
- type: map
value: 77.38133262065693
- type: mrr
value: 93.20244479558205
- task:
type: PairClassification
dataset:
type: mteb/sprintduplicatequestions-pairclassification
name: MTEB SprintDuplicateQuestions
config: default
split: test
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
metrics:
- type: cos_sim_accuracy
value: 99.87722772277228
- type: cos_sim_ap
value: 97.32321748519148
- type: cos_sim_f1
value: 93.74369323915236
- type: cos_sim_precision
value: 94.60285132382892
- type: cos_sim_recall
value: 92.9
- type: dot_accuracy
value: 99.87722772277228
- type: dot_ap
value: 97.31598992113545
- type: dot_f1
value: 93.74369323915236
- type: dot_precision
value: 94.60285132382892
- type: dot_recall
value: 92.9
- type: euclidean_accuracy
value: 99.87722772277228
- type: euclidean_ap
value: 97.32307655128027
- type: euclidean_f1
value: 93.74369323915236
- type: euclidean_precision
value: 94.60285132382892
- type: euclidean_recall
value: 92.9
- type: manhattan_accuracy
value: 99.87524752475248
- type: manhattan_ap
value: 97.2914492164419
- type: manhattan_f1
value: 93.58074222668003
- type: manhattan_precision
value: 93.86317907444668
- type: manhattan_recall
value: 93.30000000000001
- type: max_accuracy
value: 99.87722772277228
- type: max_ap
value: 97.32321748519148
- type: max_f1
value: 93.74369323915236
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering
name: MTEB StackExchangeClustering
config: default
split: test
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
metrics:
- type: v_measure
value: 55.615368500858054
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering-p2p
name: MTEB StackExchangeClusteringP2P
config: default
split: test
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
metrics:
- type: v_measure
value: 31.827358732957318
- task:
type: Reranking
dataset:
type: mteb/stackoverflowdupquestions-reranking
name: MTEB StackOverflowDupQuestions
config: default
split: test
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
metrics:
- type: map
value: 51.58195276065337
- type: mrr
value: 52.538900029708856
- task:
type: Classification
dataset:
type: mteb/toxic_conversations_50k
name: MTEB ToxicConversationsClassification
config: default
split: test
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
metrics:
- type: accuracy
value: 72.5814
- type: ap
value: 15.705026098892539
- type: f1
value: 56.287318053086665
- task:
type: Classification
dataset:
type: mteb/tweet_sentiment_extraction
name: MTEB TweetSentimentExtractionClassification
config: default
split: test
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
metrics:
- type: accuracy
value: 63.7040181097906
- type: f1
value: 63.536790312918676
- task:
type: Clustering
dataset:
type: mteb/twentynewsgroups-clustering
name: MTEB TwentyNewsgroupsClustering
config: default
split: test
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
metrics:
- type: v_measure
value: 37.0755355816832
- task:
type: PairClassification
dataset:
type: mteb/twittersemeval2015-pairclassification
name: MTEB TwitterSemEval2015
config: default
split: test
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
metrics:
- type: cos_sim_accuracy
value: 85.09268641592656
- type: cos_sim_ap
value: 70.26996907384613
- type: cos_sim_f1
value: 65.01384676249505
- type: cos_sim_precision
value: 64.98813604007381
- type: cos_sim_recall
value: 65.03957783641161
- type: dot_accuracy
value: 85.09268641592656
- type: dot_ap
value: 70.21842436196593
- type: dot_f1
value: 64.98002663115845
- type: dot_precision
value: 65.59139784946237
- type: dot_recall
value: 64.37994722955145
- type: euclidean_accuracy
value: 85.09268641592656
- type: euclidean_ap
value: 70.2701643775076
- type: euclidean_f1
value: 65.02177068214804
- type: euclidean_precision
value: 65.03035101609923
- type: euclidean_recall
value: 65.0131926121372
- type: manhattan_accuracy
value: 85.027120462538
- type: manhattan_ap
value: 70.04080344828975
- type: manhattan_f1
value: 64.59036898061288
- type: manhattan_precision
value: 61.40309155766944
- type: manhattan_recall
value: 68.12664907651715
- type: max_accuracy
value: 85.09268641592656
- type: max_ap
value: 70.2701643775076
- type: max_f1
value: 65.02177068214804
- task:
type: PairClassification
dataset:
type: mteb/twitterurlcorpus-pairclassification
name: MTEB TwitterURLCorpus
config: default
split: test
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
metrics:
- type: cos_sim_accuracy
value: 88.99949547871309
- type: cos_sim_ap
value: 85.82630890007624
- type: cos_sim_f1
value: 78.36594626168225
- type: cos_sim_precision
value: 74.51402388225493
- type: cos_sim_recall
value: 82.63781952571605
- type: dot_accuracy
value: 88.99561454573679
- type: dot_ap
value: 85.80051087301636
- type: dot_f1
value: 78.36163544931128
- type: dot_precision
value: 74.38771274387713
- type: dot_recall
value: 82.78410840776101
- type: euclidean_accuracy
value: 89.00531687817751
- type: euclidean_ap
value: 85.82673451926944
- type: euclidean_f1
value: 78.36308545978899
- type: euclidean_precision
value: 74.50885109337035
- type: euclidean_recall
value: 82.63781952571605
- type: manhattan_accuracy
value: 88.9781503473435
- type: manhattan_ap
value: 85.7726134330323
- type: manhattan_f1
value: 78.3766878840281
- type: manhattan_precision
value: 75.05461207807765
- type: manhattan_recall
value: 82.00646750846936
- type: max_accuracy
value: 89.00531687817751
- type: max_ap
value: 85.82673451926944
- type: max_f1
value: 78.3766878840281
Thanks @michaelfeil for running the benchmarks. Looks promising! I think the main question that many ask themselves with FlagEmbeddings is whether to use https://huggingface.co/BAAI/bge-base-en-v1.5 or the newer https://huggingface.co/BAAI/bge-m3 as it's really versatile, multilingual and has a larger context. @Shitao do you maybe have general recommendations here what model to choose when?
Ran around 50% of MTEB, here are some scores for orientation.
tags:
- mteb
model-index:
- name: bge-m3
results:
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en)
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
- type: accuracy
value: 75.61194029850746
- type: ap
value: 39.4441857734361
- type: f1
value: 69.97034098944273
- task:
type: Classification
dataset:
type: mteb/amazon_polarity
name: MTEB AmazonPolarityClassification
config: default
split: test
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
metrics:
- type: accuracy
value: 91.005775
- type: ap
value: 87.2965129654928
- type: f1
value: 90.99368816155456
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (en)
config: en
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy
value: 46.976
- type: f1
value: 44.92055541556327
- task:
type: Retrieval
dataset:
type: arguana
name: MTEB ArguAna
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 28.733999999999998
- type: map_at_10
value: 45.134
- type: map_at_100
value: 46.04
- type: map_at_1000
value: 46.047
- type: map_at_3
value: 40.149
- type: map_at_5
value: 43.24
- type: mrr_at_1
value: 29.587000000000003
- type: mrr_at_10
value: 45.428000000000004
- type: mrr_at_100
value: 46.336
- type: mrr_at_1000
value: 46.343
- type: mrr_at_3
value: 40.505
- type: mrr_at_5
value: 43.531
- type: ndcg_at_1
value: 28.733999999999998
- type: ndcg_at_10
value: 53.994
- type: ndcg_at_100
value: 57.742000000000004
- type: ndcg_at_1000
value: 57.908
- type: ndcg_at_3
value: 43.901
- type: ndcg_at_5
value: 49.437999999999995
- type: precision_at_1
value: 28.733999999999998
- type: precision_at_10
value: 8.215
- type: precision_at_100
value: 0.9820000000000001
- type: precision_at_1000
value: 0.1
- type: precision_at_3
value: 18.255
- type: precision_at_5
value: 13.627
- type: recall_at_1
value: 28.733999999999998
- type: recall_at_10
value: 82.148
- type: recall_at_100
value: 98.222
- type: recall_at_1000
value: 99.502
- type: recall_at_3
value: 54.765
- type: recall_at_5
value: 68.137
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-p2p
name: MTEB ArxivClusteringP2P
config: default
split: test
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
metrics:
- type: v_measure
value: 39.418453651259746
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-s2s
name: MTEB ArxivClusteringS2S
config: default
split: test
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
metrics:
- type: v_measure
value: 27.769780397780057
- task:
type: Reranking
dataset:
type: mteb/askubuntudupquestions-reranking
name: MTEB AskUbuntuDupQuestions
config: default
split: test
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
metrics:
- type: map
value: 61.47747150445644
- type: mrr
value: 74.28241656773513
- task:
type: BitextMining
dataset:
type: mteb/bucc-bitext-mining
name: MTEB BUCC (de-en)
config: de-en
split: test
revision: d51519689f32196a32af33b075a01d0e7c51e252
metrics:
- type: accuracy
value: 99.53027139874739
- type: f1
value: 99.45720250521921
- type: precision
value: 99.42066805845512
- type: recall
value: 99.53027139874739
- task:
type: BitextMining
dataset:
type: mteb/bucc-bitext-mining
name: MTEB BUCC (fr-en)
config: fr-en
split: test
revision: d51519689f32196a32af33b075a01d0e7c51e252
metrics:
- type: accuracy
value: 98.72331058771738
- type: f1
value: 98.55088414410449
- type: precision
value: 98.46650524616628
- type: recall
value: 98.72331058771738
- task:
type: BitextMining
dataset:
type: mteb/bucc-bitext-mining
name: MTEB BUCC (ru-en)
config: ru-en
split: test
revision: d51519689f32196a32af33b075a01d0e7c51e252
metrics:
- type: accuracy
value: 97.90093522687911
- type: f1
value: 97.64923219027827
- type: precision
value: 97.52338067197783
- type: recall
value: 97.90093522687911
- task:
type: BitextMining
dataset:
type: mteb/bucc-bitext-mining
name: MTEB BUCC (zh-en)
config: zh-en
split: test
revision: d51519689f32196a32af33b075a01d0e7c51e252
metrics:
- type: accuracy
value: 99.0521327014218
- type: f1
value: 98.99947340705634
- type: precision
value: 98.97314375987362
- type: recall
value: 99.0521327014218
- task:
type: Classification
dataset:
type: mteb/banking77
name: MTEB Banking77Classification
config: default
split: test
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
metrics:
- type: accuracy
value: 81.93181818181819
- type: f1
value: 81.0852312152688
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-p2p
name: MTEB BiorxivClusteringP2P
config: default
split: test
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
metrics:
- type: v_measure
value: 32.856148672160444
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-s2s
name: MTEB BiorxivClusteringS2S
config: default
split: test
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
metrics:
- type: v_measure
value: 25.729734227390967
- task:
type: BitextMining
dataset:
type: strombergnlp/bornholmsk_parallel
name: MTEB BornholmBitextMining
config: default
split: test
revision: 3bc5cfb4ec514264fe2db5615fac9016f7251552
metrics:
- type: accuracy
value: 52.6
- type: f1
value: 44.05714285714286
- type: precision
value: 40.93380952380952
- type: recall
value: 52.6
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackAndroidRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 31.1
- type: map_at_10
value: 42.028
- type: map_at_100
value: 43.57
- type: map_at_1000
value: 43.683
- type: map_at_3
value: 38.479
- type: map_at_5
value: 40.502
- type: mrr_at_1
value: 38.054
- type: mrr_at_10
value: 48.073
- type: mrr_at_100
value: 48.824
- type: mrr_at_1000
value: 48.856
- type: mrr_at_3
value: 45.231
- type: mrr_at_5
value: 46.941
- type: ndcg_at_1
value: 37.911
- type: ndcg_at_10
value: 48.406
- type: ndcg_at_100
value: 54.057
- type: ndcg_at_1000
value: 55.81700000000001
- type: ndcg_at_3
value: 42.988
- type: ndcg_at_5
value: 45.686
- type: precision_at_1
value: 37.911
- type: precision_at_10
value: 9.285
- type: precision_at_100
value: 1.498
- type: precision_at_1000
value: 0.196
- type: precision_at_3
value: 20.41
- type: precision_at_5
value: 14.907
- type: recall_at_1
value: 31.1
- type: recall_at_10
value: 60.50299999999999
- type: recall_at_100
value: 84.313
- type: recall_at_1000
value: 95.44500000000001
- type: recall_at_3
value: 45.550000000000004
- type: recall_at_5
value: 52.735
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackEnglishRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 28.720000000000002
- type: map_at_10
value: 38.87
- type: map_at_100
value: 40.141
- type: map_at_1000
value: 40.27
- type: map_at_3
value: 36.064
- type: map_at_5
value: 37.659
- type: mrr_at_1
value: 35.86
- type: mrr_at_10
value: 44.458
- type: mrr_at_100
value: 45.221000000000004
- type: mrr_at_1000
value: 45.266
- type: mrr_at_3
value: 42.335
- type: mrr_at_5
value: 43.59
- type: ndcg_at_1
value: 35.86
- type: ndcg_at_10
value: 44.397
- type: ndcg_at_100
value: 48.924
- type: ndcg_at_1000
value: 50.949
- type: ndcg_at_3
value: 40.382
- type: ndcg_at_5
value: 42.308
- type: precision_at_1
value: 35.86
- type: precision_at_10
value: 8.369
- type: precision_at_100
value: 1.369
- type: precision_at_1000
value: 0.181
- type: precision_at_3
value: 19.448
- type: precision_at_5
value: 13.783000000000001
- type: recall_at_1
value: 28.720000000000002
- type: recall_at_10
value: 54.057
- type: recall_at_100
value: 73.015
- type: recall_at_1000
value: 85.90100000000001
- type: recall_at_3
value: 42.561
- type: recall_at_5
value: 47.827999999999996
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackGamingRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 37.798
- type: map_at_10
value: 49.559999999999995
- type: map_at_100
value: 50.586
- type: map_at_1000
value: 50.64300000000001
- type: map_at_3
value: 46.686
- type: map_at_5
value: 48.292
- type: mrr_at_1
value: 42.884
- type: mrr_at_10
value: 52.864999999999995
- type: mrr_at_100
value: 53.549
- type: mrr_at_1000
value: 53.583000000000006
- type: mrr_at_3
value: 50.658
- type: mrr_at_5
value: 51.834
- type: ndcg_at_1
value: 42.884
- type: ndcg_at_10
value: 55.147
- type: ndcg_at_100
value: 59.205
- type: ndcg_at_1000
value: 60.431999999999995
- type: ndcg_at_3
value: 50.268
- type: ndcg_at_5
value: 52.595000000000006
- type: precision_at_1
value: 42.884
- type: precision_at_10
value: 8.802999999999999
- type: precision_at_100
value: 1.1769999999999998
- type: precision_at_1000
value: 0.133
- type: precision_at_3
value: 22.299
- type: precision_at_5
value: 15.160000000000002
- type: recall_at_1
value: 37.798
- type: recall_at_10
value: 68.28
- type: recall_at_100
value: 85.697
- type: recall_at_1000
value: 94.447
- type: recall_at_3
value: 55.184999999999995
- type: recall_at_5
value: 60.940000000000005
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackGisRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 24.935
- type: map_at_10
value: 32.757999999999996
- type: map_at_100
value: 33.633
- type: map_at_1000
value: 33.716
- type: map_at_3
value: 30.168
- type: map_at_5
value: 31.513999999999996
- type: mrr_at_1
value: 27.119
- type: mrr_at_10
value: 34.885
- type: mrr_at_100
value: 35.674
- type: mrr_at_1000
value: 35.739
- type: mrr_at_3
value: 32.505
- type: mrr_at_5
value: 33.714
- type: ndcg_at_1
value: 27.006000000000004
- type: ndcg_at_10
value: 37.56
- type: ndcg_at_100
value: 42.025
- type: ndcg_at_1000
value: 44.297
- type: ndcg_at_3
value: 32.408
- type: ndcg_at_5
value: 34.64
- type: precision_at_1
value: 27.006000000000004
- type: precision_at_10
value: 5.774
- type: precision_at_100
value: 0.844
- type: precision_at_1000
value: 0.108
- type: precision_at_3
value: 13.635
- type: precision_at_5
value: 9.424000000000001
- type: recall_at_1
value: 24.935
- type: recall_at_10
value: 50.608
- type: recall_at_100
value: 71.344
- type: recall_at_1000
value: 88.67699999999999
- type: recall_at_3
value: 36.368
- type: recall_at_5
value: 41.81
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackMathematicaRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 15.723
- type: map_at_10
value: 22.159000000000002
- type: map_at_100
value: 23.399
- type: map_at_1000
value: 23.513
- type: map_at_3
value: 19.792
- type: map_at_5
value: 21.102999999999998
- type: mrr_at_1
value: 19.527
- type: mrr_at_10
value: 26.346999999999998
- type: mrr_at_100
value: 27.48
- type: mrr_at_1000
value: 27.544999999999998
- type: mrr_at_3
value: 23.983999999999998
- type: mrr_at_5
value: 25.178
- type: ndcg_at_1
value: 19.403000000000002
- type: ndcg_at_10
value: 26.789
- type: ndcg_at_100
value: 32.791
- type: ndcg_at_1000
value: 35.58
- type: ndcg_at_3
value: 22.235
- type: ndcg_at_5
value: 24.27
- type: precision_at_1
value: 19.403000000000002
- type: precision_at_10
value: 4.913
- type: precision_at_100
value: 0.903
- type: precision_at_1000
value: 0.128
- type: precision_at_3
value: 10.488999999999999
- type: precision_at_5
value: 7.710999999999999
- type: recall_at_1
value: 15.723
- type: recall_at_10
value: 37.143
- type: recall_at_100
value: 63.402
- type: recall_at_1000
value: 83.291
- type: recall_at_3
value: 24.446
- type: recall_at_5
value: 29.544999999999998
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackPhysicsRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 26.606
- type: map_at_10
value: 36.495
- type: map_at_100
value: 37.759
- type: map_at_1000
value: 37.877
- type: map_at_3
value: 33.542
- type: map_at_5
value: 35.256
- type: mrr_at_1
value: 32.435
- type: mrr_at_10
value: 42.126999999999995
- type: mrr_at_100
value: 42.96
- type: mrr_at_1000
value: 43.006
- type: mrr_at_3
value: 39.75
- type: mrr_at_5
value: 41.169
- type: ndcg_at_1
value: 32.531
- type: ndcg_at_10
value: 42.382
- type: ndcg_at_100
value: 47.721000000000004
- type: ndcg_at_1000
value: 49.888
- type: ndcg_at_3
value: 37.687
- type: ndcg_at_5
value: 39.987
- type: precision_at_1
value: 32.531
- type: precision_at_10
value: 7.7
- type: precision_at_100
value: 1.209
- type: precision_at_1000
value: 0.159
- type: precision_at_3
value: 18.062
- type: precision_at_5
value: 12.723999999999998
- type: recall_at_1
value: 26.606
- type: recall_at_10
value: 54.277
- type: recall_at_100
value: 76.91
- type: recall_at_1000
value: 90.979
- type: recall_at_3
value: 40.692
- type: recall_at_5
value: 46.949999999999996
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackProgrammersRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 25.306
- type: map_at_10
value: 34.676
- type: map_at_100
value: 35.939
- type: map_at_1000
value: 36.044
- type: map_at_3
value: 31.418000000000003
- type: map_at_5
value: 33.323
- type: mrr_at_1
value: 31.507
- type: mrr_at_10
value: 39.893
- type: mrr_at_100
value: 40.808
- type: mrr_at_1000
value: 40.859
- type: mrr_at_3
value: 37.080999999999996
- type: mrr_at_5
value: 38.708
- type: ndcg_at_1
value: 31.392999999999997
- type: ndcg_at_10
value: 40.357
- type: ndcg_at_100
value: 45.878
- type: ndcg_at_1000
value: 48.101
- type: ndcg_at_3
value: 34.914
- type: ndcg_at_5
value: 37.476
- type: precision_at_1
value: 31.392999999999997
- type: precision_at_10
value: 7.352
- type: precision_at_100
value: 1.1769999999999998
- type: precision_at_1000
value: 0.153
- type: precision_at_3
value: 16.476
- type: precision_at_5
value: 11.918
- type: recall_at_1
value: 25.306
- type: recall_at_10
value: 52.528
- type: recall_at_100
value: 76.069
- type: recall_at_1000
value: 91.106
- type: recall_at_3
value: 37.275000000000006
- type: recall_at_5
value: 44.080999999999996
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackStatsRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 23.159
- type: map_at_10
value: 29.647000000000002
- type: map_at_100
value: 30.441000000000003
- type: map_at_1000
value: 30.531999999999996
- type: map_at_3
value: 27.076
- type: map_at_5
value: 28.792
- type: mrr_at_1
value: 25.613000000000003
- type: mrr_at_10
value: 32.123000000000005
- type: mrr_at_100
value: 32.814
- type: mrr_at_1000
value: 32.883
- type: mrr_at_3
value: 29.755
- type: mrr_at_5
value: 31.296000000000003
- type: ndcg_at_1
value: 25.613000000000003
- type: ndcg_at_10
value: 33.707
- type: ndcg_at_100
value: 37.62
- type: ndcg_at_1000
value: 40.042
- type: ndcg_at_3
value: 29.086000000000002
- type: ndcg_at_5
value: 31.823
- type: precision_at_1
value: 25.613000000000003
- type: precision_at_10
value: 5.2909999999999995
- type: precision_at_100
value: 0.7849999999999999
- type: precision_at_1000
value: 0.107
- type: precision_at_3
value: 12.27
- type: precision_at_5
value: 9.11
- type: recall_at_1
value: 23.159
- type: recall_at_10
value: 43.795
- type: recall_at_100
value: 61.436
- type: recall_at_1000
value: 79.511
- type: recall_at_3
value: 31.394
- type: recall_at_5
value: 38.002
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackTexRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 17.523
- type: map_at_10
value: 24.34
- type: map_at_100
value: 25.318
- type: map_at_1000
value: 25.432
- type: map_at_3
value: 22.31
- type: map_at_5
value: 23.406
- type: mrr_at_1
value: 21.163
- type: mrr_at_10
value: 27.907
- type: mrr_at_100
value: 28.816000000000003
- type: mrr_at_1000
value: 28.89
- type: mrr_at_3
value: 26.015
- type: mrr_at_5
value: 27.046
- type: ndcg_at_1
value: 21.129
- type: ndcg_at_10
value: 28.542
- type: ndcg_at_100
value: 33.465
- type: ndcg_at_1000
value: 36.339
- type: ndcg_at_3
value: 24.905
- type: ndcg_at_5
value: 26.489
- type: precision_at_1
value: 21.129
- type: precision_at_10
value: 5.045
- type: precision_at_100
value: 0.8699999999999999
- type: precision_at_1000
value: 0.129
- type: precision_at_3
value: 11.643
- type: precision_at_5
value: 8.245
- type: recall_at_1
value: 17.523
- type: recall_at_10
value: 37.682
- type: recall_at_100
value: 60.111000000000004
- type: recall_at_1000
value: 80.766
- type: recall_at_3
value: 27.412
- type: recall_at_5
value: 31.518
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackUnixRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 26.284000000000002
- type: map_at_10
value: 34.435
- type: map_at_100
value: 35.545
- type: map_at_1000
value: 35.644
- type: map_at_3
value: 32.036
- type: map_at_5
value: 33.335
- type: mrr_at_1
value: 30.784
- type: mrr_at_10
value: 38.261
- type: mrr_at_100
value: 39.153
- type: mrr_at_1000
value: 39.208999999999996
- type: mrr_at_3
value: 36.022999999999996
- type: mrr_at_5
value: 37.282
- type: ndcg_at_1
value: 30.784
- type: ndcg_at_10
value: 39.091
- type: ndcg_at_100
value: 44.391999999999996
- type: ndcg_at_1000
value: 46.681
- type: ndcg_at_3
value: 34.778
- type: ndcg_at_5
value: 36.664
- type: precision_at_1
value: 30.784
- type: precision_at_10
value: 6.446000000000001
- type: precision_at_100
value: 1.014
- type: precision_at_1000
value: 0.132
- type: precision_at_3
value: 15.672
- type: precision_at_5
value: 10.84
- type: recall_at_1
value: 26.284000000000002
- type: recall_at_10
value: 49.467
- type: recall_at_100
value: 73.039
- type: recall_at_1000
value: 89.037
- type: recall_at_3
value: 37.519999999999996
- type: recall_at_5
value: 42.435
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackWebmastersRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 25.263999999999996
- type: map_at_10
value: 34.665
- type: map_at_100
value: 36.137
- type: map_at_1000
value: 36.354
- type: map_at_3
value: 32.137
- type: map_at_5
value: 33.371
- type: mrr_at_1
value: 31.225
- type: mrr_at_10
value: 39.948
- type: mrr_at_100
value: 40.794999999999995
- type: mrr_at_1000
value: 40.858
- type: mrr_at_3
value: 37.879000000000005
- type: mrr_at_5
value: 39.035
- type: ndcg_at_1
value: 30.830000000000002
- type: ndcg_at_10
value: 40.516000000000005
- type: ndcg_at_100
value: 45.7
- type: ndcg_at_1000
value: 48.446
- type: ndcg_at_3
value: 36.603
- type: ndcg_at_5
value: 38.098
- type: precision_at_1
value: 30.830000000000002
- type: precision_at_10
value: 7.767
- type: precision_at_100
value: 1.48
- type: precision_at_1000
value: 0.23800000000000002
- type: precision_at_3
value: 17.391000000000002
- type: precision_at_5
value: 12.292
- type: recall_at_1
value: 25.263999999999996
- type: recall_at_10
value: 51.034
- type: recall_at_100
value: 74.493
- type: recall_at_1000
value: 92.15100000000001
- type: recall_at_3
value: 39.519999999999996
- type: recall_at_5
value: 43.74
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackWordpressRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 20.4
- type: map_at_10
value: 27.72
- type: map_at_100
value: 28.57
- type: map_at_1000
value: 28.682999999999996
- type: map_at_3
value: 25.365
- type: map_at_5
value: 26.773000000000003
- type: mrr_at_1
value: 22.551
- type: mrr_at_10
value: 29.829
- type: mrr_at_100
value: 30.604
- type: mrr_at_1000
value: 30.691000000000003
- type: mrr_at_3
value: 27.695999999999998
- type: mrr_at_5
value: 28.962
- type: ndcg_at_1
value: 22.551
- type: ndcg_at_10
value: 32.096999999999994
- type: ndcg_at_100
value: 36.518
- type: ndcg_at_1000
value: 39.487
- type: ndcg_at_3
value: 27.655
- type: ndcg_at_5
value: 29.975
- type: precision_at_1
value: 22.551
- type: precision_at_10
value: 5.083
- type: precision_at_100
value: 0.787
- type: precision_at_1000
value: 0.117
- type: precision_at_3
value: 11.83
- type: precision_at_5
value: 8.577
- type: recall_at_1
value: 20.4
- type: recall_at_10
value: 43.444
- type: recall_at_100
value: 64.19500000000001
- type: recall_at_1000
value: 86.586
- type: recall_at_3
value: 31.75
- type: recall_at_5
value: 37.214999999999996
- task:
type: Retrieval
dataset:
type: dbpedia-entity
name: MTEB DBPedia
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 8.709
- type: map_at_10
value: 18.137
- type: map_at_100
value: 25.337
- type: map_at_1000
value: 26.929
- type: map_at_3
value: 13.164000000000001
- type: map_at_5
value: 15.332
- type: mrr_at_1
value: 63.5
- type: mrr_at_10
value: 72.938
- type: mrr_at_100
value: 73.248
- type: mrr_at_1000
value: 73.25500000000001
- type: mrr_at_3
value: 70.917
- type: mrr_at_5
value: 72.317
- type: ndcg_at_1
value: 52.75
- type: ndcg_at_10
value: 39.837
- type: ndcg_at_100
value: 44.204
- type: ndcg_at_1000
value: 51.514
- type: ndcg_at_3
value: 44.178
- type: ndcg_at_5
value: 41.703
- type: precision_at_1
value: 63.5
- type: precision_at_10
value: 31.5
- type: precision_at_100
value: 10.152999999999999
- type: precision_at_1000
value: 1.9929999999999999
- type: precision_at_3
value: 46.916999999999994
- type: precision_at_5
value: 39.85
- type: recall_at_1
value: 8.709
- type: recall_at_10
value: 23.595
- type: recall_at_100
value: 50.244
- type: recall_at_1000
value: 73.193
- type: recall_at_3
value: 14.504
- type: recall_at_5
value: 18.137
- task:
type: Classification
dataset:
type: mteb/emotion
name: MTEB EmotionClassification
config: default
split: test
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
metrics:
- type: accuracy
value: 50.154999999999994
- type: f1
value: 43.57245108706806
- task:
type: Retrieval
dataset:
type: fiqa
name: MTEB FiQA2018
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 20.968999999999998
- type: map_at_10
value: 33.664
- type: map_at_100
value: 35.471000000000004
- type: map_at_1000
value: 35.65
- type: map_at_3
value: 29.997
- type: map_at_5
value: 31.921
- type: mrr_at_1
value: 42.13
- type: mrr_at_10
value: 50.475
- type: mrr_at_100
value: 51.23799999999999
- type: mrr_at_1000
value: 51.281
- type: mrr_at_3
value: 48.687999999999995
- type: mrr_at_5
value: 49.591
- type: ndcg_at_1
value: 42.284
- type: ndcg_at_10
value: 41.365
- type: ndcg_at_100
value: 47.863
- type: ndcg_at_1000
value: 50.971999999999994
- type: ndcg_at_3
value: 38.84
- type: ndcg_at_5
value: 39.184000000000005
- type: precision_at_1
value: 42.284
- type: precision_at_10
value: 11.265
- type: precision_at_100
value: 1.7850000000000001
- type: precision_at_1000
value: 0.23500000000000001
- type: precision_at_3
value: 25.977
- type: precision_at_5
value: 18.426000000000002
- type: recall_at_1
value: 20.968999999999998
- type: recall_at_10
value: 47.239
- type: recall_at_100
value: 71.334
- type: recall_at_1000
value: 89.916
- type: recall_at_3
value: 35.38
- type: recall_at_5
value: 39.965
- task:
type: Classification
dataset:
type: mteb/imdb
name: MTEB ImdbClassification
config: default
split: test
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
metrics:
- type: accuracy
value: 87.80999999999999
- type: ap
value: 82.64452124367875
- type: f1
value: 87.79250775511873
- task:
type: Classification
dataset:
type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (en)
config: en
split: test
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
metrics:
- type: accuracy
value: 93.3766529867761
- type: f1
value: 93.07516766462871
- task:
type: Classification
dataset:
type: mteb/mtop_intent
name: MTEB MTOPIntentClassification (en)
config: en
split: test
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
metrics:
- type: accuracy
value: 66.59598723210213
- type: f1
value: 47.047272522163624
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (en)
config: en
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 71.06926698049764
- type: f1
value: 69.13014185231128
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (en)
config: en
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 76.66442501681236
- type: f1
value: 75.63836848136394
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-p2p
name: MTEB MedrxivClusteringP2P
config: default
split: test
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
metrics:
- type: v_measure
value: 30.23749152164288
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-s2s
name: MTEB MedrxivClusteringS2S
config: default
split: test
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
metrics:
- type: v_measure
value: 26.083238688599486
- task:
type: Retrieval
dataset:
type: nfcorpus
name: MTEB NFCorpus
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 5.272
- type: map_at_10
value: 11.716999999999999
- type: map_at_100
value: 14.402999999999999
- type: map_at_1000
value: 15.664
- type: map_at_3
value: 8.956
- type: map_at_5
value: 10.249
- type: mrr_at_1
value: 43.963
- type: mrr_at_10
value: 52.553000000000004
- type: mrr_at_100
value: 53.176
- type: mrr_at_1000
value: 53.222
- type: mrr_at_3
value: 51.135
- type: mrr_at_5
value: 51.94
- type: ndcg_at_1
value: 41.486000000000004
- type: ndcg_at_10
value: 31.342
- type: ndcg_at_100
value: 28.471999999999998
- type: ndcg_at_1000
value: 37.102000000000004
- type: ndcg_at_3
value: 37.736
- type: ndcg_at_5
value: 35.105
- type: precision_at_1
value: 43.344
- type: precision_at_10
value: 22.786
- type: precision_at_100
value: 7.093000000000001
- type: precision_at_1000
value: 1.9539999999999997
- type: precision_at_3
value: 35.707
- type: precision_at_5
value: 30.217
- type: recall_at_1
value: 5.272
- type: recall_at_10
value: 14.671999999999999
- type: recall_at_100
value: 28.308
- type: recall_at_1000
value: 59.11300000000001
- type: recall_at_3
value: 10.07
- type: recall_at_5
value: 11.99
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering
name: MTEB RedditClustering
config: default
split: test
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
metrics:
- type: v_measure
value: 45.473096154259935
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering-p2p
name: MTEB RedditClusteringP2P
config: default
split: test
revision: 282350215ef01743dc01b456c7f5241fa8937f16
metrics:
- type: v_measure
value: 57.54220073389692
- task:
type: Reranking
dataset:
type: mteb/scidocs-reranking
name: MTEB SciDocsRR
config: default
split: test
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
metrics:
- type: map
value: 77.38133262065693
- type: mrr
value: 93.20244479558205
- task:
type: PairClassification
dataset:
type: mteb/sprintduplicatequestions-pairclassification
name: MTEB SprintDuplicateQuestions
config: default
split: test
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
metrics:
- type: cos_sim_accuracy
value: 99.87722772277228
- type: cos_sim_ap
value: 97.32321748519148
- type: cos_sim_f1
value: 93.74369323915236
- type: cos_sim_precision
value: 94.60285132382892
- type: cos_sim_recall
value: 92.9
- type: dot_accuracy
value: 99.87722772277228
- type: dot_ap
value: 97.31598992113545
- type: dot_f1
value: 93.74369323915236
- type: dot_precision
value: 94.60285132382892
- type: dot_recall
value: 92.9
- type: euclidean_accuracy
value: 99.87722772277228
- type: euclidean_ap
value: 97.32307655128027
- type: euclidean_f1
value: 93.74369323915236
- type: euclidean_precision
value: 94.60285132382892
- type: euclidean_recall
value: 92.9
- type: manhattan_accuracy
value: 99.87524752475248
- type: manhattan_ap
value: 97.2914492164419
- type: manhattan_f1
value: 93.58074222668003
- type: manhattan_precision
value: 93.86317907444668
- type: manhattan_recall
value: 93.30000000000001
- type: max_accuracy
value: 99.87722772277228
- type: max_ap
value: 97.32321748519148
- type: max_f1
value: 93.74369323915236
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering
name: MTEB StackExchangeClustering
config: default
split: test
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
metrics:
- type: v_measure
value: 55.615368500858054
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering-p2p
name: MTEB StackExchangeClusteringP2P
config: default
split: test
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
metrics:
- type: v_measure
value: 31.827358732957318
- task:
type: Reranking
dataset:
type: mteb/stackoverflowdupquestions-reranking
name: MTEB StackOverflowDupQuestions
config: default
split: test
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
metrics:
- type: map
value: 51.58195276065337
- type: mrr
value: 52.538900029708856
- task:
type: Classification
dataset:
type: mteb/toxic_conversations_50k
name: MTEB ToxicConversationsClassification
config: default
split: test
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
metrics:
- type: accuracy
value: 72.5814
- type: ap
value: 15.705026098892539
- type: f1
value: 56.287318053086665
- task:
type: Classification
dataset:
type: mteb/tweet_sentiment_extraction
name: MTEB TweetSentimentExtractionClassification
config: default
split: test
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
metrics:
- type: accuracy
value: 63.7040181097906
- type: f1
value: 63.536790312918676
- task:
type: Clustering
dataset:
type: mteb/twentynewsgroups-clustering
name: MTEB TwentyNewsgroupsClustering
config: default
split: test
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
metrics:
- type: v_measure
value: 37.0755355816832
- task:
type: PairClassification
dataset:
type: mteb/twittersemeval2015-pairclassification
name: MTEB TwitterSemEval2015
config: default
split: test
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
metrics:
- type: cos_sim_accuracy
value: 85.09268641592656
- type: cos_sim_ap
value: 70.26996907384613
- type: cos_sim_f1
value: 65.01384676249505
- type: cos_sim_precision
value: 64.98813604007381
- type: cos_sim_recall
value: 65.03957783641161
- type: dot_accuracy
value: 85.09268641592656
- type: dot_ap
value: 70.21842436196593
- type: dot_f1
value: 64.98002663115845
- type: dot_precision
value: 65.59139784946237
- type: dot_recall
value: 64.37994722955145
- type: euclidean_accuracy
value: 85.09268641592656
- type: euclidean_ap
value: 70.2701643775076
- type: euclidean_f1
value: 65.02177068214804
- type: euclidean_precision
value: 65.03035101609923
- type: euclidean_recall
value: 65.0131926121372
- type: manhattan_accuracy
value: 85.027120462538
- type: manhattan_ap
value: 70.04080344828975
- type: manhattan_f1
value: 64.59036898061288
- type: manhattan_precision
value: 61.40309155766944
- type: manhattan_recall
value: 68.12664907651715
- type: max_accuracy
value: 85.09268641592656
- type: max_ap
value: 70.2701643775076
- type: max_f1
value: 65.02177068214804
- task:
type: PairClassification
dataset:
type: mteb/twitterurlcorpus-pairclassification
name: MTEB TwitterURLCorpus
config: default
split: test
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
metrics:
- type: cos_sim_accuracy
value: 88.99949547871309
- type: cos_sim_ap
value: 85.82630890007624
- type: cos_sim_f1
value: 78.36594626168225
- type: cos_sim_precision
value: 74.51402388225493
- type: cos_sim_recall
value: 82.63781952571605
- type: dot_accuracy
value: 88.99561454573679
- type: dot_ap
value: 85.80051087301636
- type: dot_f1
value: 78.36163544931128
- type: dot_precision
value: 74.38771274387713
- type: dot_recall
value: 82.78410840776101
- type: euclidean_accuracy
value: 89.00531687817751
- type: euclidean_ap
value: 85.82673451926944
- type: euclidean_f1
value: 78.36308545978899
- type: euclidean_precision
value: 74.50885109337035
- type: euclidean_recall
value: 82.63781952571605
- type: manhattan_accuracy
value: 88.9781503473435
- type: manhattan_ap
value: 85.7726134330323
- type: manhattan_f1
value: 78.3766878840281
- type: manhattan_precision
value: 75.05461207807765
- type: manhattan_recall
value: 82.00646750846936
- type: max_accuracy
value: 89.00531687817751
- type: max_ap
value: 85.82673451926944
- type: max_f1
value: 78.3766878840281
Great work! thx for posting the results! I was also running the benchmark with bge-m3 but don't know why always basically all the tasks and datasets are skipped, only a few in classification had results. Did you run into the same issue before?