metadata
tags:
- mteb
- sentence-transformers
- transformers
- Qwen
- sentence-similarity
- llama-cpp
- gguf-my-repo
model-index:
- name: gte-qwen1.5-7b
results:
- task:
type: Classification
dataset:
name: MTEB AmazonCounterfactualClassification (en)
type: mteb/amazon_counterfactual
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
- type: accuracy
value: 83.16417910447761
- type: ap
value: 49.37655308937739
- type: f1
value: 77.52987230462615
- task:
type: Classification
dataset:
name: MTEB AmazonPolarityClassification
type: mteb/amazon_polarity
config: default
split: test
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
metrics:
- type: accuracy
value: 96.6959
- type: ap
value: 94.90885739242472
- type: f1
value: 96.69477648952649
- task:
type: Classification
dataset:
name: MTEB AmazonReviewsClassification (en)
type: mteb/amazon_reviews_multi
config: en
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy
value: 62.168
- type: f1
value: 60.411431278343755
- task:
type: Retrieval
dataset:
name: MTEB ArguAna
type: mteb/arguana
config: default
split: test
revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
metrics:
- type: map_at_1
value: 36.415
- type: map_at_10
value: 53.505
- type: map_at_100
value: 54.013
- type: map_at_1000
value: 54.013
- type: map_at_3
value: 48.459
- type: map_at_5
value: 51.524
- type: mrr_at_1
value: 36.842000000000006
- type: mrr_at_10
value: 53.679
- type: mrr_at_100
value: 54.17999999999999
- type: mrr_at_1000
value: 54.17999999999999
- type: mrr_at_3
value: 48.613
- type: mrr_at_5
value: 51.696
- type: ndcg_at_1
value: 36.415
- type: ndcg_at_10
value: 62.644999999999996
- type: ndcg_at_100
value: 64.60000000000001
- type: ndcg_at_1000
value: 64.60000000000001
- type: ndcg_at_3
value: 52.44799999999999
- type: ndcg_at_5
value: 57.964000000000006
- type: precision_at_1
value: 36.415
- type: precision_at_10
value: 9.161
- type: precision_at_100
value: 0.996
- type: precision_at_1000
value: 0.1
- type: precision_at_3
value: 21.337
- type: precision_at_5
value: 15.476999999999999
- type: recall_at_1
value: 36.415
- type: recall_at_10
value: 91.607
- type: recall_at_100
value: 99.644
- type: recall_at_1000
value: 99.644
- type: recall_at_3
value: 64.011
- type: recall_at_5
value: 77.383
- task:
type: Clustering
dataset:
name: MTEB ArxivClusteringP2P
type: mteb/arxiv-clustering-p2p
config: default
split: test
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
metrics:
- type: v_measure
value: 56.40183100758549
- task:
type: Clustering
dataset:
name: MTEB ArxivClusteringS2S
type: mteb/arxiv-clustering-s2s
config: default
split: test
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
metrics:
- type: v_measure
value: 51.44814171373338
- task:
type: Reranking
dataset:
name: MTEB AskUbuntuDupQuestions
type: mteb/askubuntudupquestions-reranking
config: default
split: test
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
metrics:
- type: map
value: 66.00208703259058
- type: mrr
value: 78.95165545442553
- task:
type: STS
dataset:
name: MTEB BIOSSES
type: mteb/biosses-sts
config: default
split: test
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
metrics:
- type: cos_sim_pearson
value: 82.12591694410098
- type: cos_sim_spearman
value: 81.11570369802254
- type: euclidean_pearson
value: 80.91709076204458
- type: euclidean_spearman
value: 81.11570369802254
- type: manhattan_pearson
value: 80.71719561024605
- type: manhattan_spearman
value: 81.21510355327713
- task:
type: Classification
dataset:
name: MTEB Banking77Classification
type: mteb/banking77
config: default
split: test
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
metrics:
- type: accuracy
value: 81.67857142857142
- type: f1
value: 80.84103272994895
- task:
type: Clustering
dataset:
name: MTEB BiorxivClusteringP2P
type: mteb/biorxiv-clustering-p2p
config: default
split: test
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
metrics:
- type: v_measure
value: 49.008657468552016
- task:
type: Clustering
dataset:
name: MTEB BiorxivClusteringS2S
type: mteb/biorxiv-clustering-s2s
config: default
split: test
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
metrics:
- type: v_measure
value: 45.05901064421589
- task:
type: Retrieval
dataset:
name: MTEB CQADupstackAndroidRetrieval
type: BeIR/cqadupstack
config: default
split: test
revision: f46a197baaae43b4f621051089b82a364682dfeb
metrics:
- type: map_at_1
value: 32.694
- type: map_at_10
value: 43.895
- type: map_at_100
value: 45.797
- type: map_at_1000
value: 45.922000000000004
- type: map_at_3
value: 40.141
- type: map_at_5
value: 42.077
- type: mrr_at_1
value: 40.2
- type: mrr_at_10
value: 50.11
- type: mrr_at_100
value: 51.101
- type: mrr_at_1000
value: 51.13100000000001
- type: mrr_at_3
value: 47.735
- type: mrr_at_5
value: 48.922
- type: ndcg_at_1
value: 40.2
- type: ndcg_at_10
value: 50.449999999999996
- type: ndcg_at_100
value: 56.85
- type: ndcg_at_1000
value: 58.345
- type: ndcg_at_3
value: 45.261
- type: ndcg_at_5
value: 47.298
- type: precision_at_1
value: 40.2
- type: precision_at_10
value: 9.742
- type: precision_at_100
value: 1.6480000000000001
- type: precision_at_1000
value: 0.214
- type: precision_at_3
value: 21.841
- type: precision_at_5
value: 15.68
- type: recall_at_1
value: 32.694
- type: recall_at_10
value: 62.751999999999995
- type: recall_at_100
value: 88.619
- type: recall_at_1000
value: 97.386
- type: recall_at_3
value: 47.087
- type: recall_at_5
value: 53.108999999999995
- task:
type: Retrieval
dataset:
name: MTEB CQADupstackEnglishRetrieval
type: BeIR/cqadupstack
config: default
split: test
revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
metrics:
- type: map_at_1
value: 27.849
- type: map_at_10
value: 37.938
- type: map_at_100
value: 39.211
- type: map_at_1000
value: 39.333
- type: map_at_3
value: 35.314
- type: map_at_5
value: 36.666
- type: mrr_at_1
value: 34.904
- type: mrr_at_10
value: 43.869
- type: mrr_at_100
value: 44.614
- type: mrr_at_1000
value: 44.662
- type: mrr_at_3
value: 41.815000000000005
- type: mrr_at_5
value: 42.943
- type: ndcg_at_1
value: 34.904
- type: ndcg_at_10
value: 43.605
- type: ndcg_at_100
value: 48.339999999999996
- type: ndcg_at_1000
value: 50.470000000000006
- type: ndcg_at_3
value: 39.835
- type: ndcg_at_5
value: 41.364000000000004
- type: precision_at_1
value: 34.904
- type: precision_at_10
value: 8.222999999999999
- type: precision_at_100
value: 1.332
- type: precision_at_1000
value: 0.183
- type: precision_at_3
value: 19.575
- type: precision_at_5
value: 13.58
- type: recall_at_1
value: 27.849
- type: recall_at_10
value: 53.635
- type: recall_at_100
value: 73.932
- type: recall_at_1000
value: 87.29599999999999
- type: recall_at_3
value: 42.019
- type: recall_at_5
value: 46.58
- task:
type: Retrieval
dataset:
name: MTEB CQADupstackGamingRetrieval
type: BeIR/cqadupstack
config: default
split: test
revision: 4885aa143210c98657558c04aaf3dc47cfb54340
metrics:
- type: map_at_1
value: 29.182999999999996
- type: map_at_10
value: 41.233
- type: map_at_100
value: 42.52
- type: map_at_1000
value: 42.589
- type: map_at_3
value: 37.284
- type: map_at_5
value: 39.586
- type: mrr_at_1
value: 33.793
- type: mrr_at_10
value: 44.572
- type: mrr_at_100
value: 45.456
- type: mrr_at_1000
value: 45.497
- type: mrr_at_3
value: 41.275
- type: mrr_at_5
value: 43.278
- type: ndcg_at_1
value: 33.793
- type: ndcg_at_10
value: 47.823
- type: ndcg_at_100
value: 52.994
- type: ndcg_at_1000
value: 54.400000000000006
- type: ndcg_at_3
value: 40.82
- type: ndcg_at_5
value: 44.426
- type: precision_at_1
value: 33.793
- type: precision_at_10
value: 8.312999999999999
- type: precision_at_100
value: 1.191
- type: precision_at_1000
value: 0.136
- type: precision_at_3
value: 18.662
- type: precision_at_5
value: 13.668
- type: recall_at_1
value: 29.182999999999996
- type: recall_at_10
value: 64.14999999999999
- type: recall_at_100
value: 86.533
- type: recall_at_1000
value: 96.492
- type: recall_at_3
value: 45.7
- type: recall_at_5
value: 54.330999999999996
- task:
type: Retrieval
dataset:
name: MTEB CQADupstackGisRetrieval
type: BeIR/cqadupstack
config: default
split: test
revision: 5003b3064772da1887988e05400cf3806fe491f2
metrics:
- type: map_at_1
value: 24.389
- type: map_at_10
value: 33.858
- type: map_at_100
value: 35.081
- type: map_at_1000
value: 35.161
- type: map_at_3
value: 30.793
- type: map_at_5
value: 32.336
- type: mrr_at_1
value: 27.006000000000004
- type: mrr_at_10
value: 36.378
- type: mrr_at_100
value: 37.345
- type: mrr_at_1000
value: 37.405
- type: mrr_at_3
value: 33.578
- type: mrr_at_5
value: 34.991
- type: ndcg_at_1
value: 27.006000000000004
- type: ndcg_at_10
value: 39.612
- type: ndcg_at_100
value: 45.216
- type: ndcg_at_1000
value: 47.12
- type: ndcg_at_3
value: 33.566
- type: ndcg_at_5
value: 36.105
- type: precision_at_1
value: 27.006000000000004
- type: precision_at_10
value: 6.372999999999999
- type: precision_at_100
value: 0.968
- type: precision_at_1000
value: 0.11800000000000001
- type: precision_at_3
value: 14.501
- type: precision_at_5
value: 10.169
- type: recall_at_1
value: 24.389
- type: recall_at_10
value: 55.131
- type: recall_at_100
value: 80.315
- type: recall_at_1000
value: 94.284
- type: recall_at_3
value: 38.643
- type: recall_at_5
value: 44.725
- task:
type: Retrieval
dataset:
name: MTEB CQADupstackMathematicaRetrieval
type: BeIR/cqadupstack
config: default
split: test
revision: 90fceea13679c63fe563ded68f3b6f06e50061de
metrics:
- type: map_at_1
value: 15.845999999999998
- type: map_at_10
value: 25.019000000000002
- type: map_at_100
value: 26.478
- type: map_at_1000
value: 26.598
- type: map_at_3
value: 21.595
- type: map_at_5
value: 23.335
- type: mrr_at_1
value: 20.274
- type: mrr_at_10
value: 29.221000000000004
- type: mrr_at_100
value: 30.354999999999997
- type: mrr_at_1000
value: 30.419
- type: mrr_at_3
value: 26.161
- type: mrr_at_5
value: 27.61
- type: ndcg_at_1
value: 20.274
- type: ndcg_at_10
value: 31.014000000000003
- type: ndcg_at_100
value: 37.699
- type: ndcg_at_1000
value: 40.363
- type: ndcg_at_3
value: 24.701999999999998
- type: ndcg_at_5
value: 27.261999999999997
- type: precision_at_1
value: 20.274
- type: precision_at_10
value: 6.219
- type: precision_at_100
value: 1.101
- type: precision_at_1000
value: 0.146
- type: precision_at_3
value: 12.231
- type: precision_at_5
value: 9.129
- type: recall_at_1
value: 15.845999999999998
- type: recall_at_10
value: 45.358
- type: recall_at_100
value: 74.232
- type: recall_at_1000
value: 92.985
- type: recall_at_3
value: 28.050000000000004
- type: recall_at_5
value: 34.588
- task:
type: Retrieval
dataset:
name: MTEB CQADupstackPhysicsRetrieval
type: BeIR/cqadupstack
config: default
split: test
revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
metrics:
- type: map_at_1
value: 33.808
- type: map_at_10
value: 46.86
- type: map_at_100
value: 48.237
- type: map_at_1000
value: 48.331
- type: map_at_3
value: 42.784
- type: map_at_5
value: 45.015
- type: mrr_at_1
value: 41.771
- type: mrr_at_10
value: 52.35300000000001
- type: mrr_at_100
value: 53.102000000000004
- type: mrr_at_1000
value: 53.132999999999996
- type: mrr_at_3
value: 49.663000000000004
- type: mrr_at_5
value: 51.27
- type: ndcg_at_1
value: 41.771
- type: ndcg_at_10
value: 53.562
- type: ndcg_at_100
value: 58.809999999999995
- type: ndcg_at_1000
value: 60.23
- type: ndcg_at_3
value: 47.514
- type: ndcg_at_5
value: 50.358999999999995
- type: precision_at_1
value: 41.771
- type: precision_at_10
value: 10.038
- type: precision_at_100
value: 1.473
- type: precision_at_1000
value: 0.17600000000000002
- type: precision_at_3
value: 22.875
- type: precision_at_5
value: 16.477
- type: recall_at_1
value: 33.808
- type: recall_at_10
value: 67.721
- type: recall_at_100
value: 89.261
- type: recall_at_1000
value: 98.042
- type: recall_at_3
value: 50.807
- type: recall_at_5
value: 58.162000000000006
- task:
type: Retrieval
dataset:
name: MTEB CQADupstackProgrammersRetrieval
type: BeIR/cqadupstack
config: default
split: test
revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
metrics:
- type: map_at_1
value: 28.105000000000004
- type: map_at_10
value: 40.354
- type: map_at_100
value: 41.921
- type: map_at_1000
value: 42.021
- type: map_at_3
value: 36.532
- type: map_at_5
value: 38.671
- type: mrr_at_1
value: 34.475
- type: mrr_at_10
value: 45.342
- type: mrr_at_100
value: 46.300000000000004
- type: mrr_at_1000
value: 46.343
- type: mrr_at_3
value: 42.637
- type: mrr_at_5
value: 44.207
- type: ndcg_at_1
value: 34.475
- type: ndcg_at_10
value: 46.945
- type: ndcg_at_100
value: 52.939
- type: ndcg_at_1000
value: 54.645999999999994
- type: ndcg_at_3
value: 41.065000000000005
- type: ndcg_at_5
value: 43.832
- type: precision_at_1
value: 34.475
- type: precision_at_10
value: 8.892999999999999
- type: precision_at_100
value: 1.377
- type: precision_at_1000
value: 0.17099999999999999
- type: precision_at_3
value: 20.091
- type: precision_at_5
value: 14.452000000000002
- type: recall_at_1
value: 28.105000000000004
- type: recall_at_10
value: 61.253
- type: recall_at_100
value: 85.92
- type: recall_at_1000
value: 96.799
- type: recall_at_3
value: 45.094
- type: recall_at_5
value: 52.455
- task:
type: Retrieval
dataset:
name: MTEB CQADupstackRetrieval
type: BeIR/cqadupstack
config: default
split: test
revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
metrics:
- type: map_at_1
value: 24.613833333333332
- type: map_at_10
value: 34.763
- type: map_at_100
value: 36.17066666666667
- type: map_at_1000
value: 36.2905
- type: map_at_3
value: 31.53541666666666
- type: map_at_5
value: 33.29216666666667
- type: mrr_at_1
value: 29.48725
- type: mrr_at_10
value: 38.92066666666667
- type: mrr_at_100
value: 39.88725000000001
- type: mrr_at_1000
value: 39.9435
- type: mrr_at_3
value: 36.284083333333335
- type: mrr_at_5
value: 37.73941666666667
- type: ndcg_at_1
value: 29.48725
- type: ndcg_at_10
value: 40.635083333333334
- type: ndcg_at_100
value: 46.479416666666665
- type: ndcg_at_1000
value: 48.63308333333334
- type: ndcg_at_3
value: 35.19483333333333
- type: ndcg_at_5
value: 37.68016666666667
- type: precision_at_1
value: 29.48725
- type: precision_at_10
value: 7.406499999999998
- type: precision_at_100
value: 1.2225833333333334
- type: precision_at_1000
value: 0.16108333333333336
- type: precision_at_3
value: 16.53375
- type: precision_at_5
value: 11.919416666666665
- type: recall_at_1
value: 24.613833333333332
- type: recall_at_10
value: 53.91766666666666
- type: recall_at_100
value: 79.18
- type: recall_at_1000
value: 93.85133333333333
- type: recall_at_3
value: 38.866166666666665
- type: recall_at_5
value: 45.21275000000001
- type: map_at_1
value: 12.328999999999999
- type: map_at_10
value: 20.078
- type: map_at_100
value: 21.166999999999998
- type: map_at_1000
value: 21.308
- type: map_at_3
value: 17.702
- type: map_at_5
value: 18.725
- type: mrr_at_1
value: 13.678
- type: mrr_at_10
value: 21.859
- type: mrr_at_100
value: 22.816
- type: mrr_at_1000
value: 22.926
- type: mrr_at_3
value: 19.378
- type: mrr_at_5
value: 20.385
- type: ndcg_at_1
value: 13.678
- type: ndcg_at_10
value: 24.993000000000002
- type: ndcg_at_100
value: 30.464999999999996
- type: ndcg_at_1000
value: 33.916000000000004
- type: ndcg_at_3
value: 19.966
- type: ndcg_at_5
value: 21.712999999999997
- type: precision_at_1
value: 13.678
- type: precision_at_10
value: 4.473
- type: precision_at_100
value: 0.784
- type: precision_at_1000
value: 0.116
- type: precision_at_3
value: 9.181000000000001
- type: precision_at_5
value: 6.506
- type: recall_at_1
value: 12.328999999999999
- type: recall_at_10
value: 38.592
- type: recall_at_100
value: 63.817
- type: recall_at_1000
value: 89.67500000000001
- type: recall_at_3
value: 24.726
- type: recall_at_5
value: 28.959000000000003
- task:
type: Retrieval
dataset:
name: MTEB CQADupstackStatsRetrieval
type: BeIR/cqadupstack
config: default
split: test
revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
metrics:
- type: map_at_1
value: 25.106
- type: map_at_10
value: 33.367999999999995
- type: map_at_100
value: 34.586
- type: map_at_1000
value: 34.681
- type: map_at_3
value: 31.022
- type: map_at_5
value: 32.548
- type: mrr_at_1
value: 28.374
- type: mrr_at_10
value: 36.521
- type: mrr_at_100
value: 37.55
- type: mrr_at_1000
value: 37.614999999999995
- type: mrr_at_3
value: 34.509
- type: mrr_at_5
value: 35.836
- type: ndcg_at_1
value: 28.374
- type: ndcg_at_10
value: 37.893
- type: ndcg_at_100
value: 43.694
- type: ndcg_at_1000
value: 46.001999999999995
- type: ndcg_at_3
value: 33.825
- type: ndcg_at_5
value: 36.201
- type: precision_at_1
value: 28.374
- type: precision_at_10
value: 5.966
- type: precision_at_100
value: 0.9650000000000001
- type: precision_at_1000
value: 0.124
- type: precision_at_3
value: 14.774999999999999
- type: precision_at_5
value: 10.459999999999999
- type: recall_at_1
value: 25.106
- type: recall_at_10
value: 48.607
- type: recall_at_100
value: 74.66000000000001
- type: recall_at_1000
value: 91.562
- type: recall_at_3
value: 37.669999999999995
- type: recall_at_5
value: 43.484
- task:
type: Retrieval
dataset:
name: MTEB CQADupstackTexRetrieval
type: BeIR/cqadupstack
config: default
split: test
revision: 46989137a86843e03a6195de44b09deda022eec7
metrics:
- type: map_at_1
value: 13.755
- type: map_at_10
value: 20.756
- type: map_at_100
value: 22.05
- type: map_at_1000
value: 22.201
- type: map_at_3
value: 18.243000000000002
- type: map_at_5
value: 19.512
- type: mrr_at_1
value: 16.93
- type: mrr_at_10
value: 24.276
- type: mrr_at_100
value: 25.349
- type: mrr_at_1000
value: 25.441000000000003
- type: mrr_at_3
value: 21.897
- type: mrr_at_5
value: 23.134
- type: ndcg_at_1
value: 16.93
- type: ndcg_at_10
value: 25.508999999999997
- type: ndcg_at_100
value: 31.777
- type: ndcg_at_1000
value: 35.112
- type: ndcg_at_3
value: 20.896
- type: ndcg_at_5
value: 22.857
- type: precision_at_1
value: 16.93
- type: precision_at_10
value: 4.972
- type: precision_at_100
value: 0.963
- type: precision_at_1000
value: 0.145
- type: precision_at_3
value: 10.14
- type: precision_at_5
value: 7.536
- type: recall_at_1
value: 13.755
- type: recall_at_10
value: 36.46
- type: recall_at_100
value: 64.786
- type: recall_at_1000
value: 88.287
- type: recall_at_3
value: 23.681
- type: recall_at_5
value: 28.615000000000002
- task:
type: Retrieval
dataset:
name: MTEB CQADupstackUnixRetrieval
type: BeIR/cqadupstack
config: default
split: test
revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
metrics:
- type: map_at_1
value: 26.99
- type: map_at_10
value: 38.009
- type: map_at_100
value: 39.384
- type: map_at_1000
value: 39.481
- type: map_at_3
value: 34.593
- type: map_at_5
value: 36.449999999999996
- type: mrr_at_1
value: 31.81
- type: mrr_at_10
value: 41.943000000000005
- type: mrr_at_100
value: 42.914
- type: mrr_at_1000
value: 42.962
- type: mrr_at_3
value: 39.179
- type: mrr_at_5
value: 40.798
- type: ndcg_at_1
value: 31.81
- type: ndcg_at_10
value: 44.086
- type: ndcg_at_100
value: 50.026
- type: ndcg_at_1000
value: 51.903999999999996
- type: ndcg_at_3
value: 38.23
- type: ndcg_at_5
value: 40.926
- type: precision_at_1
value: 31.81
- type: precision_at_10
value: 7.761
- type: precision_at_100
value: 1.205
- type: precision_at_1000
value: 0.148
- type: precision_at_3
value: 17.537
- type: precision_at_5
value: 12.649
- type: recall_at_1
value: 26.99
- type: recall_at_10
value: 58.467
- type: recall_at_100
value: 83.93
- type: recall_at_1000
value: 96.452
- type: recall_at_3
value: 42.685
- type: recall_at_5
value: 49.341
- task:
type: Retrieval
dataset:
name: MTEB CQADupstackWebmastersRetrieval
type: BeIR/cqadupstack
config: default
split: test
revision: 160c094312a0e1facb97e55eeddb698c0abe3571
metrics:
- type: map_at_1
value: 25.312
- type: map_at_10
value: 35.788
- type: map_at_100
value: 37.616
- type: map_at_1000
value: 37.86
- type: map_at_3
value: 32.422000000000004
- type: map_at_5
value: 34.585
- type: mrr_at_1
value: 30.631999999999998
- type: mrr_at_10
value: 40.604
- type: mrr_at_100
value: 41.745
- type: mrr_at_1000
value: 41.788
- type: mrr_at_3
value: 37.582
- type: mrr_at_5
value: 39.499
- type: ndcg_at_1
value: 30.631999999999998
- type: ndcg_at_10
value: 42.129
- type: ndcg_at_100
value: 48.943
- type: ndcg_at_1000
value: 51.089
- type: ndcg_at_3
value: 36.658
- type: ndcg_at_5
value: 39.818999999999996
- type: precision_at_1
value: 30.631999999999998
- type: precision_at_10
value: 7.904999999999999
- type: precision_at_100
value: 1.664
- type: precision_at_1000
value: 0.256
- type: precision_at_3
value: 16.996
- type: precision_at_5
value: 12.727
- type: recall_at_1
value: 25.312
- type: recall_at_10
value: 54.886
- type: recall_at_100
value: 84.155
- type: recall_at_1000
value: 96.956
- type: recall_at_3
value: 40.232
- type: recall_at_5
value: 48.204
- task:
type: Retrieval
dataset:
name: MTEB ClimateFEVER
type: mteb/climate-fever
config: default
split: test
revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
metrics:
- type: map_at_1
value: 19.147
- type: map_at_10
value: 33.509
- type: map_at_100
value: 35.573
- type: map_at_1000
value: 35.769
- type: map_at_3
value: 27.983999999999998
- type: map_at_5
value: 31.012
- type: mrr_at_1
value: 43.844
- type: mrr_at_10
value: 56.24
- type: mrr_at_100
value: 56.801
- type: mrr_at_1000
value: 56.826
- type: mrr_at_3
value: 53.290000000000006
- type: mrr_at_5
value: 55.13
- type: ndcg_at_1
value: 43.844
- type: ndcg_at_10
value: 43.996
- type: ndcg_at_100
value: 50.965
- type: ndcg_at_1000
value: 53.927
- type: ndcg_at_3
value: 37.263000000000005
- type: ndcg_at_5
value: 39.553
- type: precision_at_1
value: 43.844
- type: precision_at_10
value: 13.687
- type: precision_at_100
value: 2.139
- type: precision_at_1000
value: 0.269
- type: precision_at_3
value: 28.122000000000003
- type: precision_at_5
value: 21.303
- type: recall_at_1
value: 19.147
- type: recall_at_10
value: 50.449999999999996
- type: recall_at_100
value: 74.00099999999999
- type: recall_at_1000
value: 90.098
- type: recall_at_3
value: 33.343
- type: recall_at_5
value: 40.744
- task:
type: Retrieval
dataset:
name: MTEB DBPedia
type: mteb/dbpedia
config: default
split: test
revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
metrics:
- type: map_at_1
value: 8.773
- type: map_at_10
value: 21.172
- type: map_at_100
value: 30.244
- type: map_at_1000
value: 32.127
- type: map_at_3
value: 14.510000000000002
- type: map_at_5
value: 17.483
- type: mrr_at_1
value: 68.25
- type: mrr_at_10
value: 77.33
- type: mrr_at_100
value: 77.529
- type: mrr_at_1000
value: 77.536
- type: mrr_at_3
value: 75.708
- type: mrr_at_5
value: 76.72099999999999
- type: ndcg_at_1
value: 60
- type: ndcg_at_10
value: 48.045
- type: ndcg_at_100
value: 51.620999999999995
- type: ndcg_at_1000
value: 58.843999999999994
- type: ndcg_at_3
value: 52.922000000000004
- type: ndcg_at_5
value: 50.27
- type: precision_at_1
value: 68.25
- type: precision_at_10
value: 37.625
- type: precision_at_100
value: 11.774999999999999
- type: precision_at_1000
value: 2.395
- type: precision_at_3
value: 55.25
- type: precision_at_5
value: 47.599999999999994
- type: recall_at_1
value: 8.773
- type: recall_at_10
value: 27.332
- type: recall_at_100
value: 55.48499999999999
- type: recall_at_1000
value: 79.886
- type: recall_at_3
value: 15.823
- type: recall_at_5
value: 20.523
- task:
type: Classification
dataset:
name: MTEB EmotionClassification
type: mteb/emotion
config: default
split: test
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
metrics:
- type: accuracy
value: 54.52999999999999
- type: f1
value: 47.396628088963645
- task:
type: Retrieval
dataset:
name: MTEB FEVER
type: mteb/fever
config: default
split: test
revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
metrics:
- type: map_at_1
value: 85.397
- type: map_at_10
value: 90.917
- type: map_at_100
value: 91.109
- type: map_at_1000
value: 91.121
- type: map_at_3
value: 90.045
- type: map_at_5
value: 90.602
- type: mrr_at_1
value: 92.00399999999999
- type: mrr_at_10
value: 95.39999999999999
- type: mrr_at_100
value: 95.41
- type: mrr_at_1000
value: 95.41
- type: mrr_at_3
value: 95.165
- type: mrr_at_5
value: 95.348
- type: ndcg_at_1
value: 92.00399999999999
- type: ndcg_at_10
value: 93.345
- type: ndcg_at_100
value: 93.934
- type: ndcg_at_1000
value: 94.108
- type: ndcg_at_3
value: 92.32000000000001
- type: ndcg_at_5
value: 92.899
- type: precision_at_1
value: 92.00399999999999
- type: precision_at_10
value: 10.839
- type: precision_at_100
value: 1.1440000000000001
- type: precision_at_1000
value: 0.117
- type: precision_at_3
value: 34.298
- type: precision_at_5
value: 21.128
- type: recall_at_1
value: 85.397
- type: recall_at_10
value: 96.375
- type: recall_at_100
value: 98.518
- type: recall_at_1000
value: 99.515
- type: recall_at_3
value: 93.59100000000001
- type: recall_at_5
value: 95.134
- task:
type: Retrieval
dataset:
name: MTEB FiQA2018
type: mteb/fiqa
config: default
split: test
revision: 27a168819829fe9bcd655c2df245fb19452e8e06
metrics:
- type: map_at_1
value: 27.36
- type: map_at_10
value: 46.847
- type: map_at_100
value: 49.259
- type: map_at_1000
value: 49.389
- type: map_at_3
value: 41.095
- type: map_at_5
value: 44.084
- type: mrr_at_1
value: 51.852
- type: mrr_at_10
value: 61.67
- type: mrr_at_100
value: 62.395999999999994
- type: mrr_at_1000
value: 62.414
- type: mrr_at_3
value: 59.465
- type: mrr_at_5
value: 60.584
- type: ndcg_at_1
value: 51.852
- type: ndcg_at_10
value: 55.311
- type: ndcg_at_100
value: 62.6
- type: ndcg_at_1000
value: 64.206
- type: ndcg_at_3
value: 51.159
- type: ndcg_at_5
value: 52.038
- type: precision_at_1
value: 51.852
- type: precision_at_10
value: 15.370000000000001
- type: precision_at_100
value: 2.282
- type: precision_at_1000
value: 0.258
- type: precision_at_3
value: 34.721999999999994
- type: precision_at_5
value: 24.846
- type: recall_at_1
value: 27.36
- type: recall_at_10
value: 63.932
- type: recall_at_100
value: 89.824
- type: recall_at_1000
value: 98.556
- type: recall_at_3
value: 47.227999999999994
- type: recall_at_5
value: 53.724000000000004
- task:
type: Retrieval
dataset:
name: MTEB HotpotQA
type: mteb/hotpotqa
config: default
split: test
revision: ab518f4d6fcca38d87c25209f94beba119d02014
metrics:
- type: map_at_1
value: 40.655
- type: map_at_10
value: 63.824999999999996
- type: map_at_100
value: 64.793
- type: map_at_1000
value: 64.848
- type: map_at_3
value: 60.221000000000004
- type: map_at_5
value: 62.474
- type: mrr_at_1
value: 81.31
- type: mrr_at_10
value: 86.509
- type: mrr_at_100
value: 86.677
- type: mrr_at_1000
value: 86.682
- type: mrr_at_3
value: 85.717
- type: mrr_at_5
value: 86.21
- type: ndcg_at_1
value: 81.31
- type: ndcg_at_10
value: 72.251
- type: ndcg_at_100
value: 75.536
- type: ndcg_at_1000
value: 76.558
- type: ndcg_at_3
value: 67.291
- type: ndcg_at_5
value: 70.045
- type: precision_at_1
value: 81.31
- type: precision_at_10
value: 15.082999999999998
- type: precision_at_100
value: 1.764
- type: precision_at_1000
value: 0.19
- type: precision_at_3
value: 42.971
- type: precision_at_5
value: 27.956999999999997
- type: recall_at_1
value: 40.655
- type: recall_at_10
value: 75.41499999999999
- type: recall_at_100
value: 88.224
- type: recall_at_1000
value: 94.943
- type: recall_at_3
value: 64.456
- type: recall_at_5
value: 69.892
- task:
type: Classification
dataset:
name: MTEB ImdbClassification
type: mteb/imdb
config: default
split: test
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
metrics:
- type: accuracy
value: 95.58120000000001
- type: ap
value: 93.0407063004784
- type: f1
value: 95.57849992996822
- task:
type: Retrieval
dataset:
name: MTEB MSMARCO
type: mteb/msmarco
config: default
split: dev
revision: c5a29a104738b98a9e76336939199e264163d4a0
metrics:
- type: map_at_1
value: 22.031
- type: map_at_10
value: 34.628
- type: map_at_100
value: 35.833
- type: map_at_1000
value: 35.881
- type: map_at_3
value: 30.619000000000003
- type: map_at_5
value: 32.982
- type: mrr_at_1
value: 22.736
- type: mrr_at_10
value: 35.24
- type: mrr_at_100
value: 36.381
- type: mrr_at_1000
value: 36.424
- type: mrr_at_3
value: 31.287
- type: mrr_at_5
value: 33.617000000000004
- type: ndcg_at_1
value: 22.736
- type: ndcg_at_10
value: 41.681000000000004
- type: ndcg_at_100
value: 47.371
- type: ndcg_at_1000
value: 48.555
- type: ndcg_at_3
value: 33.553
- type: ndcg_at_5
value: 37.771
- type: precision_at_1
value: 22.736
- type: precision_at_10
value: 6.625
- type: precision_at_100
value: 0.9450000000000001
- type: precision_at_1000
value: 0.105
- type: precision_at_3
value: 14.331
- type: precision_at_5
value: 10.734
- type: recall_at_1
value: 22.031
- type: recall_at_10
value: 63.378
- type: recall_at_100
value: 89.47699999999999
- type: recall_at_1000
value: 98.48400000000001
- type: recall_at_3
value: 41.388000000000005
- type: recall_at_5
value: 51.522999999999996
- task:
type: Classification
dataset:
name: MTEB MTOPDomainClassification (en)
type: mteb/mtop_domain
config: en
split: test
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
metrics:
- type: accuracy
value: 95.75239398084815
- type: f1
value: 95.51228043205194
- task:
type: Classification
dataset:
name: MTEB MTOPIntentClassification (en)
type: mteb/mtop_intent
config: en
split: test
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
metrics:
- type: accuracy
value: 84.25900592795259
- type: f1
value: 62.14790420114562
- task:
type: Classification
dataset:
name: MTEB MassiveIntentClassification (en)
type: mteb/amazon_massive_intent
config: en
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 78.47007397444519
- type: f1
value: 76.92133583932912
- task:
type: Classification
dataset:
name: MTEB MassiveScenarioClassification (en)
type: mteb/amazon_massive_scenario
config: en
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 78.19098856758575
- type: f1
value: 78.10820805879119
- task:
type: Clustering
dataset:
name: MTEB MedrxivClusteringP2P
type: mteb/medrxiv-clustering-p2p
config: default
split: test
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
metrics:
- type: v_measure
value: 44.37013684222983
- task:
type: Clustering
dataset:
name: MTEB MedrxivClusteringS2S
type: mteb/medrxiv-clustering-s2s
config: default
split: test
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
metrics:
- type: v_measure
value: 42.003012591979704
- task:
type: Reranking
dataset:
name: MTEB MindSmallReranking
type: mteb/mind_small
config: default
split: test
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
metrics:
- type: map
value: 32.70743071063257
- type: mrr
value: 33.938337390083994
- task:
type: Retrieval
dataset:
name: MTEB NFCorpus
type: mteb/nfcorpus
config: default
split: test
revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
metrics:
- type: map_at_1
value: 6.369
- type: map_at_10
value: 14.313
- type: map_at_100
value: 18.329
- type: map_at_1000
value: 20.017
- type: map_at_3
value: 10.257
- type: map_at_5
value: 12.264999999999999
- type: mrr_at_1
value: 49.536
- type: mrr_at_10
value: 58.464000000000006
- type: mrr_at_100
value: 59.016000000000005
- type: mrr_at_1000
value: 59.053
- type: mrr_at_3
value: 56.294999999999995
- type: mrr_at_5
value: 57.766
- type: ndcg_at_1
value: 47.678
- type: ndcg_at_10
value: 38.246
- type: ndcg_at_100
value: 35.370000000000005
- type: ndcg_at_1000
value: 44.517
- type: ndcg_at_3
value: 43.368
- type: ndcg_at_5
value: 41.892
- type: precision_at_1
value: 49.536
- type: precision_at_10
value: 28.235
- type: precision_at_100
value: 9.014999999999999
- type: precision_at_1000
value: 2.257
- type: precision_at_3
value: 40.557
- type: precision_at_5
value: 36.409000000000006
- type: recall_at_1
value: 6.369
- type: recall_at_10
value: 19.195999999999998
- type: recall_at_100
value: 37.042
- type: recall_at_1000
value: 69.203
- type: recall_at_3
value: 11.564
- type: recall_at_5
value: 15.264
- task:
type: Retrieval
dataset:
name: MTEB NQ
type: mteb/nq
config: default
split: test
revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
metrics:
- type: map_at_1
value: 39.323
- type: map_at_10
value: 54.608999999999995
- type: map_at_100
value: 55.523
- type: map_at_1000
value: 55.544000000000004
- type: map_at_3
value: 50.580000000000005
- type: map_at_5
value: 53.064
- type: mrr_at_1
value: 44.263999999999996
- type: mrr_at_10
value: 57.416
- type: mrr_at_100
value: 58.037000000000006
- type: mrr_at_1000
value: 58.05200000000001
- type: mrr_at_3
value: 54.330999999999996
- type: mrr_at_5
value: 56.302
- type: ndcg_at_1
value: 44.263999999999996
- type: ndcg_at_10
value: 61.785999999999994
- type: ndcg_at_100
value: 65.40599999999999
- type: ndcg_at_1000
value: 65.859
- type: ndcg_at_3
value: 54.518
- type: ndcg_at_5
value: 58.53699999999999
- type: precision_at_1
value: 44.263999999999996
- type: precision_at_10
value: 9.652
- type: precision_at_100
value: 1.169
- type: precision_at_1000
value: 0.121
- type: precision_at_3
value: 24.15
- type: precision_at_5
value: 16.848
- type: recall_at_1
value: 39.323
- type: recall_at_10
value: 80.663
- type: recall_at_100
value: 96.072
- type: recall_at_1000
value: 99.37700000000001
- type: recall_at_3
value: 62.23
- type: recall_at_5
value: 71.379
- task:
type: Retrieval
dataset:
name: MTEB QuoraRetrieval
type: mteb/quora
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 72.02499999999999
- type: map_at_10
value: 86.14500000000001
- type: map_at_100
value: 86.764
- type: map_at_1000
value: 86.776
- type: map_at_3
value: 83.249
- type: map_at_5
value: 85.083
- type: mrr_at_1
value: 82.83
- type: mrr_at_10
value: 88.70599999999999
- type: mrr_at_100
value: 88.791
- type: mrr_at_1000
value: 88.791
- type: mrr_at_3
value: 87.815
- type: mrr_at_5
value: 88.435
- type: ndcg_at_1
value: 82.84
- type: ndcg_at_10
value: 89.61200000000001
- type: ndcg_at_100
value: 90.693
- type: ndcg_at_1000
value: 90.752
- type: ndcg_at_3
value: 86.96199999999999
- type: ndcg_at_5
value: 88.454
- type: precision_at_1
value: 82.84
- type: precision_at_10
value: 13.600000000000001
- type: precision_at_100
value: 1.543
- type: precision_at_1000
value: 0.157
- type: precision_at_3
value: 38.092999999999996
- type: precision_at_5
value: 25.024
- type: recall_at_1
value: 72.02499999999999
- type: recall_at_10
value: 96.21600000000001
- type: recall_at_100
value: 99.76
- type: recall_at_1000
value: 99.996
- type: recall_at_3
value: 88.57000000000001
- type: recall_at_5
value: 92.814
- task:
type: Clustering
dataset:
name: MTEB RedditClustering
type: mteb/reddit-clustering
config: default
split: test
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
metrics:
- type: v_measure
value: 73.37297191949929
- task:
type: Clustering
dataset:
name: MTEB RedditClusteringP2P
type: mteb/reddit-clustering-p2p
config: default
split: test
revision: 282350215ef01743dc01b456c7f5241fa8937f16
metrics:
- type: v_measure
value: 72.50752304246946
- task:
type: Retrieval
dataset:
name: MTEB SCIDOCS
type: mteb/scidocs
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 6.4479999999999995
- type: map_at_10
value: 17.268
- type: map_at_100
value: 20.502000000000002
- type: map_at_1000
value: 20.904
- type: map_at_3
value: 11.951
- type: map_at_5
value: 14.494000000000002
- type: mrr_at_1
value: 31.900000000000002
- type: mrr_at_10
value: 45.084999999999994
- type: mrr_at_100
value: 46.145
- type: mrr_at_1000
value: 46.164
- type: mrr_at_3
value: 41.6
- type: mrr_at_5
value: 43.76
- type: ndcg_at_1
value: 31.900000000000002
- type: ndcg_at_10
value: 27.694000000000003
- type: ndcg_at_100
value: 39.016
- type: ndcg_at_1000
value: 44.448
- type: ndcg_at_3
value: 26.279999999999998
- type: ndcg_at_5
value: 22.93
- type: precision_at_1
value: 31.900000000000002
- type: precision_at_10
value: 14.399999999999999
- type: precision_at_100
value: 3.082
- type: precision_at_1000
value: 0.436
- type: precision_at_3
value: 24.667
- type: precision_at_5
value: 20.200000000000003
- type: recall_at_1
value: 6.4479999999999995
- type: recall_at_10
value: 29.243000000000002
- type: recall_at_100
value: 62.547
- type: recall_at_1000
value: 88.40299999999999
- type: recall_at_3
value: 14.988000000000001
- type: recall_at_5
value: 20.485
- task:
type: STS
dataset:
name: MTEB SICK-R
type: mteb/sickr-sts
config: default
split: test
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
metrics:
- type: cos_sim_pearson
value: 80.37839336866843
- type: cos_sim_spearman
value: 79.14737320486729
- type: euclidean_pearson
value: 78.74010870392799
- type: euclidean_spearman
value: 79.1472505448557
- type: manhattan_pearson
value: 78.76735626972086
- type: manhattan_spearman
value: 79.18509055331465
- task:
type: STS
dataset:
name: MTEB STS12
type: mteb/sts12-sts
config: default
split: test
revision: a0d554a64d88156834ff5ae9920b964011b16384
metrics:
- type: cos_sim_pearson
value: 84.98947740740309
- type: cos_sim_spearman
value: 76.52068694652895
- type: euclidean_pearson
value: 81.10952542010847
- type: euclidean_spearman
value: 76.52162808897668
- type: manhattan_pearson
value: 81.13752577872523
- type: manhattan_spearman
value: 76.55073892851847
- type: cos_sim_pearson
value: 84.99292517797305
- type: cos_sim_spearman
value: 76.52287451692155
- type: euclidean_pearson
value: 81.11616055544546
- type: euclidean_spearman
value: 76.525387473028
- type: manhattan_pearson
value: 81.14367598670032
- type: manhattan_spearman
value: 76.55571799438607
- task:
type: STS
dataset:
name: MTEB STS13
type: mteb/sts13-sts
config: default
split: test
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
metrics:
- type: cos_sim_pearson
value: 88.14795728641734
- type: cos_sim_spearman
value: 88.62720469210905
- type: euclidean_pearson
value: 87.96160445129142
- type: euclidean_spearman
value: 88.62615925428736
- type: manhattan_pearson
value: 87.86760858379527
- type: manhattan_spearman
value: 88.5613166629411
- task:
type: STS
dataset:
name: MTEB STS14
type: mteb/sts14-sts
config: default
split: test
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
metrics:
- type: cos_sim_pearson
value: 85.06444249948838
- type: cos_sim_spearman
value: 83.32346434965837
- type: euclidean_pearson
value: 83.86264166785146
- type: euclidean_spearman
value: 83.32323156068114
- type: manhattan_pearson
value: 83.87253909108084
- type: manhattan_spearman
value: 83.42760090819642
- task:
type: STS
dataset:
name: MTEB STS15
type: mteb/sts15-sts
config: default
split: test
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
metrics:
- type: cos_sim_pearson
value: 87.00847937091636
- type: cos_sim_spearman
value: 87.50432670473445
- type: euclidean_pearson
value: 87.21611485565168
- type: euclidean_spearman
value: 87.50387351928698
- type: manhattan_pearson
value: 87.30690660623411
- type: manhattan_spearman
value: 87.61147161393255
- task:
type: STS
dataset:
name: MTEB STS16
type: mteb/sts16-sts
config: default
split: test
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
metrics:
- type: cos_sim_pearson
value: 85.51456553517488
- type: cos_sim_spearman
value: 86.39208323626035
- type: euclidean_pearson
value: 85.74698473006475
- type: euclidean_spearman
value: 86.3892506146807
- type: manhattan_pearson
value: 85.77493611949014
- type: manhattan_spearman
value: 86.42961510735024
- task:
type: STS
dataset:
name: MTEB STS17 (en-en)
type: mteb/sts17-crosslingual-sts
config: en-en
split: test
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
metrics:
- type: cos_sim_pearson
value: 88.63402051628222
- type: cos_sim_spearman
value: 87.78994504115502
- type: euclidean_pearson
value: 88.44861926968403
- type: euclidean_spearman
value: 87.80670473078185
- type: manhattan_pearson
value: 88.4773722010208
- type: manhattan_spearman
value: 87.85175600656768
- task:
type: STS
dataset:
name: MTEB STS22 (en)
type: mteb/sts22-crosslingual-sts
config: en
split: test
revision: eea2b4fe26a775864c896887d910b76a8098ad3f
metrics:
- type: cos_sim_pearson
value: 65.9659729672951
- type: cos_sim_spearman
value: 66.39891735341361
- type: euclidean_pearson
value: 68.040150710449
- type: euclidean_spearman
value: 66.41777234484414
- type: manhattan_pearson
value: 68.16264809387305
- type: manhattan_spearman
value: 66.31608161700346
- task:
type: STS
dataset:
name: MTEB STSBenchmark
type: mteb/stsbenchmark-sts
config: default
split: test
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
metrics:
- type: cos_sim_pearson
value: 86.91024857159385
- type: cos_sim_spearman
value: 87.35031011815016
- type: euclidean_pearson
value: 86.94569462996033
- type: euclidean_spearman
value: 87.34929703462852
- type: manhattan_pearson
value: 86.94404111225616
- type: manhattan_spearman
value: 87.37827218003393
- task:
type: Reranking
dataset:
name: MTEB SciDocsRR
type: mteb/scidocs-reranking
config: default
split: test
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
metrics:
- type: map
value: 87.89077927002596
- type: mrr
value: 96.94650937297997
- task:
type: Retrieval
dataset:
name: MTEB SciFact
type: mteb/scifact
config: default
split: test
revision: 0228b52cf27578f30900b9e5271d331663a030d7
metrics:
- type: map_at_1
value: 57.994
- type: map_at_10
value: 70.07100000000001
- type: map_at_100
value: 70.578
- type: map_at_1000
value: 70.588
- type: map_at_3
value: 67.228
- type: map_at_5
value: 68.695
- type: mrr_at_1
value: 61.333000000000006
- type: mrr_at_10
value: 71.342
- type: mrr_at_100
value: 71.739
- type: mrr_at_1000
value: 71.75
- type: mrr_at_3
value: 69.389
- type: mrr_at_5
value: 70.322
- type: ndcg_at_1
value: 61.333000000000006
- type: ndcg_at_10
value: 75.312
- type: ndcg_at_100
value: 77.312
- type: ndcg_at_1000
value: 77.50200000000001
- type: ndcg_at_3
value: 70.72
- type: ndcg_at_5
value: 72.616
- type: precision_at_1
value: 61.333000000000006
- type: precision_at_10
value: 10.167
- type: precision_at_100
value: 1.117
- type: precision_at_1000
value: 0.11299999999999999
- type: precision_at_3
value: 28.111000000000004
- type: precision_at_5
value: 18.333
- type: recall_at_1
value: 57.994
- type: recall_at_10
value: 89.944
- type: recall_at_100
value: 98.667
- type: recall_at_1000
value: 100
- type: recall_at_3
value: 77.694
- type: recall_at_5
value: 82.339
- task:
type: PairClassification
dataset:
name: MTEB SprintDuplicateQuestions
type: mteb/sprintduplicatequestions-pairclassification
config: default
split: test
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
metrics:
- type: cos_sim_accuracy
value: 99.81485148514851
- type: cos_sim_ap
value: 95.99339654021689
- type: cos_sim_f1
value: 90.45971329708354
- type: cos_sim_precision
value: 89.44281524926686
- type: cos_sim_recall
value: 91.5
- type: dot_accuracy
value: 99.81485148514851
- type: dot_ap
value: 95.990792367539
- type: dot_f1
value: 90.54187192118228
- type: dot_precision
value: 89.2233009708738
- type: dot_recall
value: 91.9
- type: euclidean_accuracy
value: 99.81386138613861
- type: euclidean_ap
value: 95.99403827746491
- type: euclidean_f1
value: 90.45971329708354
- type: euclidean_precision
value: 89.44281524926686
- type: euclidean_recall
value: 91.5
- type: manhattan_accuracy
value: 99.81485148514851
- type: manhattan_ap
value: 96.06741547889861
- type: manhattan_f1
value: 90.55666003976144
- type: manhattan_precision
value: 90.01976284584981
- type: manhattan_recall
value: 91.10000000000001
- type: max_accuracy
value: 99.81485148514851
- type: max_ap
value: 96.06741547889861
- type: max_f1
value: 90.55666003976144
- task:
type: Clustering
dataset:
name: MTEB StackExchangeClustering
type: mteb/stackexchange-clustering
config: default
split: test
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
metrics:
- type: v_measure
value: 79.0667992003181
- task:
type: Clustering
dataset:
name: MTEB StackExchangeClusteringP2P
type: mteb/stackexchange-clustering-p2p
config: default
split: test
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
metrics:
- type: v_measure
value: 49.57086425048946
- task:
type: Reranking
dataset:
name: MTEB StackOverflowDupQuestions
type: mteb/stackoverflowdupquestions-reranking
config: default
split: test
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
metrics:
- type: map
value: 53.929415255105894
- type: mrr
value: 54.93889790764791
- task:
type: Summarization
dataset:
name: MTEB SummEval
type: mteb/summeval
config: default
split: test
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
metrics:
- type: cos_sim_pearson
value: 31.050700527286658
- type: cos_sim_spearman
value: 31.46077656458546
- type: dot_pearson
value: 31.056448416258263
- type: dot_spearman
value: 31.435272601921042
- task:
type: Retrieval
dataset:
name: MTEB TRECCOVID
type: mteb/trec-covid
config: default
split: test
revision: None
metrics:
- type: map_at_1
value: 0.23500000000000001
- type: map_at_10
value: 1.812
- type: map_at_100
value: 10.041
- type: map_at_1000
value: 24.095
- type: map_at_3
value: 0.643
- type: map_at_5
value: 1
- type: mrr_at_1
value: 86
- type: mrr_at_10
value: 92
- type: mrr_at_100
value: 92
- type: mrr_at_1000
value: 92
- type: mrr_at_3
value: 91.667
- type: mrr_at_5
value: 91.667
- type: ndcg_at_1
value: 79
- type: ndcg_at_10
value: 72.72
- type: ndcg_at_100
value: 55.82899999999999
- type: ndcg_at_1000
value: 50.72
- type: ndcg_at_3
value: 77.715
- type: ndcg_at_5
value: 75.036
- type: precision_at_1
value: 86
- type: precision_at_10
value: 77.60000000000001
- type: precision_at_100
value: 56.46
- type: precision_at_1000
value: 22.23
- type: precision_at_3
value: 82.667
- type: precision_at_5
value: 80.4
- type: recall_at_1
value: 0.23500000000000001
- type: recall_at_10
value: 2.046
- type: recall_at_100
value: 13.708
- type: recall_at_1000
value: 47.451
- type: recall_at_3
value: 0.6709999999999999
- type: recall_at_5
value: 1.078
- task:
type: Retrieval
dataset:
name: MTEB Touche2020
type: mteb/touche2020
config: default
split: test
revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
metrics:
- type: map_at_1
value: 2.252
- type: map_at_10
value: 7.958
- type: map_at_100
value: 12.293
- type: map_at_1000
value: 13.832
- type: map_at_3
value: 4.299
- type: map_at_5
value: 5.514
- type: mrr_at_1
value: 30.612000000000002
- type: mrr_at_10
value: 42.329
- type: mrr_at_100
value: 43.506
- type: mrr_at_1000
value: 43.506
- type: mrr_at_3
value: 38.775999999999996
- type: mrr_at_5
value: 39.592
- type: ndcg_at_1
value: 28.571
- type: ndcg_at_10
value: 20.301
- type: ndcg_at_100
value: 30.703999999999997
- type: ndcg_at_1000
value: 43.155
- type: ndcg_at_3
value: 22.738
- type: ndcg_at_5
value: 20.515
- type: precision_at_1
value: 30.612000000000002
- type: precision_at_10
value: 17.347
- type: precision_at_100
value: 6.327000000000001
- type: precision_at_1000
value: 1.443
- type: precision_at_3
value: 22.448999999999998
- type: precision_at_5
value: 19.184
- type: recall_at_1
value: 2.252
- type: recall_at_10
value: 13.206999999999999
- type: recall_at_100
value: 40.372
- type: recall_at_1000
value: 78.071
- type: recall_at_3
value: 5.189
- type: recall_at_5
value: 7.338
- task:
type: Classification
dataset:
name: MTEB ToxicConversationsClassification
type: mteb/toxic_conversations_50k
config: default
split: test
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
metrics:
- type: accuracy
value: 78.75399999999999
- type: ap
value: 19.666483622175363
- type: f1
value: 61.575187470329176
- task:
type: Classification
dataset:
name: MTEB TweetSentimentExtractionClassification
type: mteb/tweet_sentiment_extraction
config: default
split: test
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
metrics:
- type: accuracy
value: 66.00452744765137
- type: f1
value: 66.18291586829227
- task:
type: Clustering
dataset:
name: MTEB TwentyNewsgroupsClustering
type: mteb/twentynewsgroups-clustering
config: default
split: test
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
metrics:
- type: v_measure
value: 51.308747717084316
- task:
type: PairClassification
dataset:
name: MTEB TwitterSemEval2015
type: mteb/twittersemeval2015-pairclassification
config: default
split: test
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
metrics:
- type: cos_sim_accuracy
value: 87.81069321094355
- type: cos_sim_ap
value: 79.3576921453847
- type: cos_sim_f1
value: 71.75811286328685
- type: cos_sim_precision
value: 70.89878959567345
- type: cos_sim_recall
value: 72.63852242744063
- type: dot_accuracy
value: 87.79877212850927
- type: dot_ap
value: 79.35550320857683
- type: dot_f1
value: 71.78153446033811
- type: dot_precision
value: 70.76923076923077
- type: dot_recall
value: 72.82321899736148
- type: euclidean_accuracy
value: 87.80473266972642
- type: euclidean_ap
value: 79.35792655436586
- type: euclidean_f1
value: 71.75672148264161
- type: euclidean_precision
value: 70.99690082644628
- type: euclidean_recall
value: 72.53298153034301
- type: manhattan_accuracy
value: 87.76300888120642
- type: manhattan_ap
value: 79.33615959143606
- type: manhattan_f1
value: 71.73219978746015
- type: manhattan_precision
value: 72.23113964686998
- type: manhattan_recall
value: 71.2401055408971
- type: max_accuracy
value: 87.81069321094355
- type: max_ap
value: 79.35792655436586
- type: max_f1
value: 71.78153446033811
- task:
type: PairClassification
dataset:
name: MTEB TwitterURLCorpus
type: mteb/twitterurlcorpus-pairclassification
config: default
split: test
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
metrics:
- type: cos_sim_accuracy
value: 89.3778864439011
- type: cos_sim_ap
value: 86.79005637312795
- type: cos_sim_f1
value: 79.14617791685293
- type: cos_sim_precision
value: 76.66714780600462
- type: cos_sim_recall
value: 81.79088389282414
- type: dot_accuracy
value: 89.37206504443668
- type: dot_ap
value: 86.78770290102123
- type: dot_f1
value: 79.14741392159786
- type: dot_precision
value: 76.6897746967071
- type: dot_recall
value: 81.76778564829073
- type: euclidean_accuracy
value: 89.37594597741297
- type: euclidean_ap
value: 86.7900899669397
- type: euclidean_f1
value: 79.13920845898953
- type: euclidean_precision
value: 76.62028692956528
- type: euclidean_recall
value: 81.8293809670465
- type: manhattan_accuracy
value: 89.38758877634183
- type: manhattan_ap
value: 86.78862564973224
- type: manhattan_f1
value: 79.1130985653065
- type: manhattan_precision
value: 76.6592041597458
- type: manhattan_recall
value: 81.72928857406838
- type: max_accuracy
value: 89.38758877634183
- type: max_ap
value: 86.7900899669397
- type: max_f1
value: 79.14741392159786
- task:
type: STS
dataset:
name: MTEB AFQMC
type: C-MTEB/AFQMC
config: default
split: validation
revision: b44c3b011063adb25877c13823db83bb193913c4
metrics:
- type: cos_sim_pearson
value: 50.01571015887356
- type: cos_sim_spearman
value: 58.47419994907958
- type: euclidean_pearson
value: 55.63582004345212
- type: euclidean_spearman
value: 58.47514484211099
- type: manhattan_pearson
value: 55.58487268871911
- type: manhattan_spearman
value: 58.411916843600075
- task:
type: STS
dataset:
name: MTEB ATEC
type: C-MTEB/ATEC
config: default
split: test
revision: 0f319b1142f28d00e055a6770f3f726ae9b7d865
metrics:
- type: cos_sim_pearson
value: 44.99231617937922
- type: cos_sim_spearman
value: 55.459227458516416
- type: euclidean_pearson
value: 52.98483376548224
- type: euclidean_spearman
value: 55.45938733128155
- type: manhattan_pearson
value: 52.946854805143964
- type: manhattan_spearman
value: 55.4272663113618
- task:
type: Classification
dataset:
name: MTEB AmazonReviewsClassification (zh)
type: mteb/amazon_reviews_multi
config: zh
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy
value: 52.946000000000005
- type: f1
value: 49.299873931232725
- task:
type: STS
dataset:
name: MTEB BQ
type: C-MTEB/BQ
config: default
split: test
revision: e3dda5e115e487b39ec7e618c0c6a29137052a55
metrics:
- type: cos_sim_pearson
value: 74.66979530294986
- type: cos_sim_spearman
value: 77.59153258548018
- type: euclidean_pearson
value: 76.5862988380262
- type: euclidean_spearman
value: 77.59094368703879
- type: manhattan_pearson
value: 76.6034419552102
- type: manhattan_spearman
value: 77.6000715948404
- task:
type: Clustering
dataset:
name: MTEB CLSClusteringP2P
type: C-MTEB/CLSClusteringP2P
config: default
split: test
revision: 4b6227591c6c1a73bc76b1055f3b7f3588e72476
metrics:
- type: v_measure
value: 47.20931915009524
- task:
type: Clustering
dataset:
name: MTEB CLSClusteringS2S
type: C-MTEB/CLSClusteringS2S
config: default
split: test
revision: e458b3f5414b62b7f9f83499ac1f5497ae2e869f
metrics:
- type: v_measure
value: 45.787353610995474
- task:
type: Reranking
dataset:
name: MTEB CMedQAv1
type: C-MTEB/CMedQAv1-reranking
config: default
split: test
revision: 8d7f1e942507dac42dc58017c1a001c3717da7df
metrics:
- type: map
value: 86.37146026784607
- type: mrr
value: 88.52309523809524
- task:
type: Reranking
dataset:
name: MTEB CMedQAv2
type: C-MTEB/CMedQAv2-reranking
config: default
split: test
revision: 23d186750531a14a0357ca22cd92d712fd512ea0
metrics:
- type: map
value: 87.40699302584699
- type: mrr
value: 89.51591269841269
- task:
type: Retrieval
dataset:
name: MTEB CmedqaRetrieval
type: C-MTEB/CmedqaRetrieval
config: default
split: dev
revision: cd540c506dae1cf9e9a59c3e06f42030d54e7301
metrics:
- type: map_at_1
value: 24.465
- type: map_at_10
value: 36.689
- type: map_at_100
value: 38.605000000000004
- type: map_at_1000
value: 38.718
- type: map_at_3
value: 32.399
- type: map_at_5
value: 34.784
- type: mrr_at_1
value: 37.234
- type: mrr_at_10
value: 45.634
- type: mrr_at_100
value: 46.676
- type: mrr_at_1000
value: 46.717
- type: mrr_at_3
value: 42.94
- type: mrr_at_5
value: 44.457
- type: ndcg_at_1
value: 37.234
- type: ndcg_at_10
value: 43.469
- type: ndcg_at_100
value: 51.048
- type: ndcg_at_1000
value: 52.925999999999995
- type: ndcg_at_3
value: 37.942
- type: ndcg_at_5
value: 40.253
- type: precision_at_1
value: 37.234
- type: precision_at_10
value: 9.745
- type: precision_at_100
value: 1.5879999999999999
- type: precision_at_1000
value: 0.183
- type: precision_at_3
value: 21.505
- type: precision_at_5
value: 15.729000000000001
- type: recall_at_1
value: 24.465
- type: recall_at_10
value: 54.559999999999995
- type: recall_at_100
value: 85.97200000000001
- type: recall_at_1000
value: 98.32499999999999
- type: recall_at_3
value: 38.047
- type: recall_at_5
value: 45.08
- task:
type: PairClassification
dataset:
name: MTEB Cmnli
type: C-MTEB/CMNLI
config: default
split: validation
revision: 41bc36f332156f7adc9e38f53777c959b2ae9766
metrics:
- type: cos_sim_accuracy
value: 84.50992182802165
- type: cos_sim_ap
value: 91.81488661281966
- type: cos_sim_f1
value: 85.46855802524294
- type: cos_sim_precision
value: 81.82207014542344
- type: cos_sim_recall
value: 89.4552256254384
- type: dot_accuracy
value: 84.50992182802165
- type: dot_ap
value: 91.80547588176556
- type: dot_f1
value: 85.46492111446794
- type: dot_precision
value: 81.95278969957081
- type: dot_recall
value: 89.29155950432546
- type: euclidean_accuracy
value: 84.49789536981359
- type: euclidean_ap
value: 91.81495039620808
- type: euclidean_f1
value: 85.46817317373308
- type: euclidean_precision
value: 81.93908193908193
- type: euclidean_recall
value: 89.31494037877017
- type: manhattan_accuracy
value: 84.46181599518941
- type: manhattan_ap
value: 91.85400573633447
- type: manhattan_f1
value: 85.54283809312146
- type: manhattan_precision
value: 81.51207115628971
- type: manhattan_recall
value: 89.99298573766659
- type: max_accuracy
value: 84.50992182802165
- type: max_ap
value: 91.85400573633447
- type: max_f1
value: 85.54283809312146
- task:
type: Retrieval
dataset:
name: MTEB CovidRetrieval
type: C-MTEB/CovidRetrieval
config: default
split: dev
revision: 1271c7809071a13532e05f25fb53511ffce77117
metrics:
- type: map_at_1
value: 68.072
- type: map_at_10
value: 76.82900000000001
- type: map_at_100
value: 77.146
- type: map_at_1000
value: 77.14999999999999
- type: map_at_3
value: 74.939
- type: map_at_5
value: 76.009
- type: mrr_at_1
value: 68.282
- type: mrr_at_10
value: 76.818
- type: mrr_at_100
value: 77.13600000000001
- type: mrr_at_1000
value: 77.14
- type: mrr_at_3
value: 74.956
- type: mrr_at_5
value: 76.047
- type: ndcg_at_1
value: 68.282
- type: ndcg_at_10
value: 80.87299999999999
- type: ndcg_at_100
value: 82.191
- type: ndcg_at_1000
value: 82.286
- type: ndcg_at_3
value: 77.065
- type: ndcg_at_5
value: 78.965
- type: precision_at_1
value: 68.282
- type: precision_at_10
value: 9.452
- type: precision_at_100
value: 1.002
- type: precision_at_1000
value: 0.101
- type: precision_at_3
value: 27.889000000000003
- type: precision_at_5
value: 17.682000000000002
- type: recall_at_1
value: 68.072
- type: recall_at_10
value: 93.467
- type: recall_at_100
value: 99.157
- type: recall_at_1000
value: 99.895
- type: recall_at_3
value: 83.14
- type: recall_at_5
value: 87.67099999999999
- task:
type: Retrieval
dataset:
name: MTEB DuRetrieval
type: C-MTEB/DuRetrieval
config: default
split: dev
revision: a1a333e290fe30b10f3f56498e3a0d911a693ced
metrics:
- type: map_at_1
value: 26.107999999999997
- type: map_at_10
value: 78.384
- type: map_at_100
value: 81.341
- type: map_at_1000
value: 81.384
- type: map_at_3
value: 54.462999999999994
- type: map_at_5
value: 68.607
- type: mrr_at_1
value: 88.94999999999999
- type: mrr_at_10
value: 92.31
- type: mrr_at_100
value: 92.379
- type: mrr_at_1000
value: 92.38300000000001
- type: mrr_at_3
value: 91.85799999999999
- type: mrr_at_5
value: 92.146
- type: ndcg_at_1
value: 88.94999999999999
- type: ndcg_at_10
value: 86.00999999999999
- type: ndcg_at_100
value: 89.121
- type: ndcg_at_1000
value: 89.534
- type: ndcg_at_3
value: 84.69200000000001
- type: ndcg_at_5
value: 83.678
- type: precision_at_1
value: 88.94999999999999
- type: precision_at_10
value: 41.065000000000005
- type: precision_at_100
value: 4.781
- type: precision_at_1000
value: 0.488
- type: precision_at_3
value: 75.75
- type: precision_at_5
value: 63.93
- type: recall_at_1
value: 26.107999999999997
- type: recall_at_10
value: 87.349
- type: recall_at_100
value: 97.14699999999999
- type: recall_at_1000
value: 99.287
- type: recall_at_3
value: 56.601
- type: recall_at_5
value: 73.381
- task:
type: Retrieval
dataset:
name: MTEB EcomRetrieval
type: C-MTEB/EcomRetrieval
config: default
split: dev
revision: 687de13dc7294d6fd9be10c6945f9e8fec8166b9
metrics:
- type: map_at_1
value: 50.7
- type: map_at_10
value: 61.312999999999995
- type: map_at_100
value: 61.88399999999999
- type: map_at_1000
value: 61.9
- type: map_at_3
value: 58.983
- type: map_at_5
value: 60.238
- type: mrr_at_1
value: 50.7
- type: mrr_at_10
value: 61.312999999999995
- type: mrr_at_100
value: 61.88399999999999
- type: mrr_at_1000
value: 61.9
- type: mrr_at_3
value: 58.983
- type: mrr_at_5
value: 60.238
- type: ndcg_at_1
value: 50.7
- type: ndcg_at_10
value: 66.458
- type: ndcg_at_100
value: 69.098
- type: ndcg_at_1000
value: 69.539
- type: ndcg_at_3
value: 61.637
- type: ndcg_at_5
value: 63.92099999999999
- type: precision_at_1
value: 50.7
- type: precision_at_10
value: 8.260000000000002
- type: precision_at_100
value: 0.946
- type: precision_at_1000
value: 0.098
- type: precision_at_3
value: 23.1
- type: precision_at_5
value: 14.979999999999999
- type: recall_at_1
value: 50.7
- type: recall_at_10
value: 82.6
- type: recall_at_100
value: 94.6
- type: recall_at_1000
value: 98.1
- type: recall_at_3
value: 69.3
- type: recall_at_5
value: 74.9
- task:
type: Classification
dataset:
name: MTEB IFlyTek
type: C-MTEB/IFlyTek-classification
config: default
split: validation
revision: 421605374b29664c5fc098418fe20ada9bd55f8a
metrics:
- type: accuracy
value: 53.76683339746056
- type: f1
value: 40.026100192683714
- task:
type: Classification
dataset:
name: MTEB JDReview
type: C-MTEB/JDReview-classification
config: default
split: test
revision: b7c64bd89eb87f8ded463478346f76731f07bf8b
metrics:
- type: accuracy
value: 88.19887429643526
- type: ap
value: 59.02998120976959
- type: f1
value: 83.3659125921227
- task:
type: STS
dataset:
name: MTEB LCQMC
type: C-MTEB/LCQMC
config: default
split: test
revision: 17f9b096f80380fce5ed12a9be8be7784b337daf
metrics:
- type: cos_sim_pearson
value: 72.53955204856854
- type: cos_sim_spearman
value: 76.28996886746215
- type: euclidean_pearson
value: 75.31184890026394
- type: euclidean_spearman
value: 76.28984471300522
- type: manhattan_pearson
value: 75.36930361638623
- type: manhattan_spearman
value: 76.34021995551348
- task:
type: Reranking
dataset:
name: MTEB MMarcoReranking
type: C-MTEB/Mmarco-reranking
config: default
split: dev
revision: None
metrics:
- type: map
value: 23.63666512532725
- type: mrr
value: 22.49642857142857
- task:
type: Retrieval
dataset:
name: MTEB MMarcoRetrieval
type: C-MTEB/MMarcoRetrieval
config: default
split: dev
revision: 539bbde593d947e2a124ba72651aafc09eb33fc2
metrics:
- type: map_at_1
value: 60.645
- type: map_at_10
value: 69.733
- type: map_at_100
value: 70.11699999999999
- type: map_at_1000
value: 70.135
- type: map_at_3
value: 67.585
- type: map_at_5
value: 68.904
- type: mrr_at_1
value: 62.765
- type: mrr_at_10
value: 70.428
- type: mrr_at_100
value: 70.77
- type: mrr_at_1000
value: 70.785
- type: mrr_at_3
value: 68.498
- type: mrr_at_5
value: 69.69
- type: ndcg_at_1
value: 62.765
- type: ndcg_at_10
value: 73.83
- type: ndcg_at_100
value: 75.593
- type: ndcg_at_1000
value: 76.05199999999999
- type: ndcg_at_3
value: 69.66499999999999
- type: ndcg_at_5
value: 71.929
- type: precision_at_1
value: 62.765
- type: precision_at_10
value: 9.117
- type: precision_at_100
value: 1
- type: precision_at_1000
value: 0.104
- type: precision_at_3
value: 26.323
- type: precision_at_5
value: 16.971
- type: recall_at_1
value: 60.645
- type: recall_at_10
value: 85.907
- type: recall_at_100
value: 93.947
- type: recall_at_1000
value: 97.531
- type: recall_at_3
value: 74.773
- type: recall_at_5
value: 80.16799999999999
- task:
type: Classification
dataset:
name: MTEB MassiveIntentClassification (zh-CN)
type: mteb/amazon_massive_intent
config: zh-CN
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 76.25084061869536
- type: f1
value: 73.65064492827022
- task:
type: Classification
dataset:
name: MTEB MassiveScenarioClassification (zh-CN)
type: mteb/amazon_massive_scenario
config: zh-CN
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 77.2595830531271
- type: f1
value: 77.15217273559321
- task:
type: Retrieval
dataset:
name: MTEB MedicalRetrieval
type: C-MTEB/MedicalRetrieval
config: default
split: dev
revision: 2039188fb5800a9803ba5048df7b76e6fb151fc6
metrics:
- type: map_at_1
value: 52.400000000000006
- type: map_at_10
value: 58.367000000000004
- type: map_at_100
value: 58.913000000000004
- type: map_at_1000
value: 58.961
- type: map_at_3
value: 56.882999999999996
- type: map_at_5
value: 57.743
- type: mrr_at_1
value: 52.400000000000006
- type: mrr_at_10
value: 58.367000000000004
- type: mrr_at_100
value: 58.913000000000004
- type: mrr_at_1000
value: 58.961
- type: mrr_at_3
value: 56.882999999999996
- type: mrr_at_5
value: 57.743
- type: ndcg_at_1
value: 52.400000000000006
- type: ndcg_at_10
value: 61.329
- type: ndcg_at_100
value: 64.264
- type: ndcg_at_1000
value: 65.669
- type: ndcg_at_3
value: 58.256
- type: ndcg_at_5
value: 59.813
- type: precision_at_1
value: 52.400000000000006
- type: precision_at_10
value: 7.07
- type: precision_at_100
value: 0.851
- type: precision_at_1000
value: 0.096
- type: precision_at_3
value: 20.732999999999997
- type: precision_at_5
value: 13.200000000000001
- type: recall_at_1
value: 52.400000000000006
- type: recall_at_10
value: 70.7
- type: recall_at_100
value: 85.1
- type: recall_at_1000
value: 96.39999999999999
- type: recall_at_3
value: 62.2
- type: recall_at_5
value: 66
- task:
type: Classification
dataset:
name: MTEB MultilingualSentiment
type: C-MTEB/MultilingualSentiment-classification
config: default
split: validation
revision: 46958b007a63fdbf239b7672c25d0bea67b5ea1a
metrics:
- type: accuracy
value: 77.42333333333333
- type: f1
value: 77.24849313989888
- task:
type: PairClassification
dataset:
name: MTEB Ocnli
type: C-MTEB/OCNLI
config: default
split: validation
revision: 66e76a618a34d6d565d5538088562851e6daa7ec
metrics:
- type: cos_sim_accuracy
value: 80.12994044396319
- type: cos_sim_ap
value: 85.21793541189636
- type: cos_sim_f1
value: 81.91489361702128
- type: cos_sim_precision
value: 75.55753791257806
- type: cos_sim_recall
value: 89.44033790918691
- type: dot_accuracy
value: 80.12994044396319
- type: dot_ap
value: 85.22568672443236
- type: dot_f1
value: 81.91489361702128
- type: dot_precision
value: 75.55753791257806
- type: dot_recall
value: 89.44033790918691
- type: euclidean_accuracy
value: 80.12994044396319
- type: euclidean_ap
value: 85.21643342357407
- type: euclidean_f1
value: 81.8830242510699
- type: euclidean_precision
value: 74.48096885813149
- type: euclidean_recall
value: 90.91869060190075
- type: manhattan_accuracy
value: 80.5630752571738
- type: manhattan_ap
value: 85.27682975032671
- type: manhattan_f1
value: 82.03883495145631
- type: manhattan_precision
value: 75.92093441150045
- type: manhattan_recall
value: 89.22914466737065
- type: max_accuracy
value: 80.5630752571738
- type: max_ap
value: 85.27682975032671
- type: max_f1
value: 82.03883495145631
- task:
type: Classification
dataset:
name: MTEB OnlineShopping
type: C-MTEB/OnlineShopping-classification
config: default
split: test
revision: e610f2ebd179a8fda30ae534c3878750a96db120
metrics:
- type: accuracy
value: 94.47999999999999
- type: ap
value: 92.81177660844013
- type: f1
value: 94.47045470502114
- task:
type: STS
dataset:
name: MTEB PAWSX
type: C-MTEB/PAWSX
config: default
split: test
revision: 9c6a90e430ac22b5779fb019a23e820b11a8b5e1
metrics:
- type: cos_sim_pearson
value: 46.13154582182421
- type: cos_sim_spearman
value: 50.21718723757444
- type: euclidean_pearson
value: 49.41535243569054
- type: euclidean_spearman
value: 50.21831909208907
- type: manhattan_pearson
value: 49.50756578601167
- type: manhattan_spearman
value: 50.229118655684566
- task:
type: STS
dataset:
name: MTEB QBQTC
type: C-MTEB/QBQTC
config: default
split: test
revision: 790b0510dc52b1553e8c49f3d2afb48c0e5c48b7
metrics:
- type: cos_sim_pearson
value: 30.787794367421956
- type: cos_sim_spearman
value: 31.81774306987836
- type: euclidean_pearson
value: 29.809436608089495
- type: euclidean_spearman
value: 31.817379098812165
- type: manhattan_pearson
value: 30.377027186607787
- type: manhattan_spearman
value: 32.42286865176827
- task:
type: STS
dataset:
name: MTEB STS22 (zh)
type: mteb/sts22-crosslingual-sts
config: zh
split: test
revision: eea2b4fe26a775864c896887d910b76a8098ad3f
metrics:
- type: cos_sim_pearson
value: 61.29839896616376
- type: cos_sim_spearman
value: 67.36328213286453
- type: euclidean_pearson
value: 64.33899267794008
- type: euclidean_spearman
value: 67.36552580196211
- type: manhattan_pearson
value: 65.20010308796022
- type: manhattan_spearman
value: 67.50982972902
- task:
type: STS
dataset:
name: MTEB STSB
type: C-MTEB/STSB
config: default
split: test
revision: 0cde68302b3541bb8b3c340dc0644b0b745b3dc0
metrics:
- type: cos_sim_pearson
value: 81.23278996774297
- type: cos_sim_spearman
value: 81.369375466486
- type: euclidean_pearson
value: 79.91030863727944
- type: euclidean_spearman
value: 81.36824495466793
- type: manhattan_pearson
value: 79.88047052896854
- type: manhattan_spearman
value: 81.3369604332008
- task:
type: Reranking
dataset:
name: MTEB T2Reranking
type: C-MTEB/T2Reranking
config: default
split: dev
revision: 76631901a18387f85eaa53e5450019b87ad58ef9
metrics:
- type: map
value: 68.109205221286
- type: mrr
value: 78.40703619520477
- task:
type: Retrieval
dataset:
name: MTEB T2Retrieval
type: C-MTEB/T2Retrieval
config: default
split: dev
revision: 8731a845f1bf500a4f111cf1070785c793d10e64
metrics:
- type: map_at_1
value: 26.704
- type: map_at_10
value: 75.739
- type: map_at_100
value: 79.606
- type: map_at_1000
value: 79.666
- type: map_at_3
value: 52.803
- type: map_at_5
value: 65.068
- type: mrr_at_1
value: 88.48899999999999
- type: mrr_at_10
value: 91.377
- type: mrr_at_100
value: 91.474
- type: mrr_at_1000
value: 91.47800000000001
- type: mrr_at_3
value: 90.846
- type: mrr_at_5
value: 91.18
- type: ndcg_at_1
value: 88.48899999999999
- type: ndcg_at_10
value: 83.581
- type: ndcg_at_100
value: 87.502
- type: ndcg_at_1000
value: 88.1
- type: ndcg_at_3
value: 84.433
- type: ndcg_at_5
value: 83.174
- type: precision_at_1
value: 88.48899999999999
- type: precision_at_10
value: 41.857
- type: precision_at_100
value: 5.039
- type: precision_at_1000
value: 0.517
- type: precision_at_3
value: 73.938
- type: precision_at_5
value: 62.163000000000004
- type: recall_at_1
value: 26.704
- type: recall_at_10
value: 83.092
- type: recall_at_100
value: 95.659
- type: recall_at_1000
value: 98.779
- type: recall_at_3
value: 54.678000000000004
- type: recall_at_5
value: 68.843
- task:
type: Classification
dataset:
name: MTEB TNews
type: C-MTEB/TNews-classification
config: default
split: validation
revision: 317f262bf1e6126357bbe89e875451e4b0938fe4
metrics:
- type: accuracy
value: 51.235
- type: f1
value: 48.14373844331604
- task:
type: Clustering
dataset:
name: MTEB ThuNewsClusteringP2P
type: C-MTEB/ThuNewsClusteringP2P
config: default
split: test
revision: 5798586b105c0434e4f0fe5e767abe619442cf93
metrics:
- type: v_measure
value: 87.42930040493792
- task:
type: Clustering
dataset:
name: MTEB ThuNewsClusteringS2S
type: C-MTEB/ThuNewsClusteringS2S
config: default
split: test
revision: 8a8b2caeda43f39e13c4bc5bea0f8a667896e10d
metrics:
- type: v_measure
value: 87.90254094650042
- task:
type: Retrieval
dataset:
name: MTEB VideoRetrieval
type: C-MTEB/VideoRetrieval
config: default
split: dev
revision: 58c2597a5943a2ba48f4668c3b90d796283c5639
metrics:
- type: map_at_1
value: 54.900000000000006
- type: map_at_10
value: 64.92
- type: map_at_100
value: 65.424
- type: map_at_1000
value: 65.43900000000001
- type: map_at_3
value: 63.132999999999996
- type: map_at_5
value: 64.208
- type: mrr_at_1
value: 54.900000000000006
- type: mrr_at_10
value: 64.92
- type: mrr_at_100
value: 65.424
- type: mrr_at_1000
value: 65.43900000000001
- type: mrr_at_3
value: 63.132999999999996
- type: mrr_at_5
value: 64.208
- type: ndcg_at_1
value: 54.900000000000006
- type: ndcg_at_10
value: 69.41199999999999
- type: ndcg_at_100
value: 71.824
- type: ndcg_at_1000
value: 72.301
- type: ndcg_at_3
value: 65.79700000000001
- type: ndcg_at_5
value: 67.713
- type: precision_at_1
value: 54.900000000000006
- type: precision_at_10
value: 8.33
- type: precision_at_100
value: 0.9450000000000001
- type: precision_at_1000
value: 0.098
- type: precision_at_3
value: 24.5
- type: precision_at_5
value: 15.620000000000001
- type: recall_at_1
value: 54.900000000000006
- type: recall_at_10
value: 83.3
- type: recall_at_100
value: 94.5
- type: recall_at_1000
value: 98.4
- type: recall_at_3
value: 73.5
- type: recall_at_5
value: 78.10000000000001
- task:
type: Classification
dataset:
name: MTEB Waimai
type: C-MTEB/waimai-classification
config: default
split: test
revision: 339287def212450dcaa9df8c22bf93e9980c7023
metrics:
- type: accuracy
value: 88.63
- type: ap
value: 73.78658340897097
- type: f1
value: 87.16764294033919
agier9/gte-Qwen1.5-7B-instruct-Q5_K_M-GGUF
This model was converted to GGUF format from Alibaba-NLP/gte-Qwen1.5-7B-instruct using llama.cpp via the ggml.ai's GGUF-my-repo space.
Refer to the original model card for more details on the model.
Use with llama.cpp
Install llama.cpp through brew.
brew install ggerganov/ggerganov/llama.cpp
Invoke the llama.cpp server or the CLI. CLI:
llama-cli --hf-repo agier9/gte-Qwen1.5-7B-instruct-Q5_K_M-GGUF --model gte-qwen1.5-7b-instruct-q5_k_m.gguf -p "The meaning to life and the universe is"
Server:
llama-server --hf-repo agier9/gte-Qwen1.5-7B-instruct-Q5_K_M-GGUF --model gte-qwen1.5-7b-instruct-q5_k_m.gguf -c 2048
Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.
git clone https://github.com/ggerganov/llama.cpp && \
cd llama.cpp && \
make && \
./main -m gte-qwen1.5-7b-instruct-q5_k_m.gguf -n 128