metadata
base_model: TaylorAI/gte-tiny
license: mit
library_name: sentence-transformers
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- gte
- mteb
datasets:
- Mihaiii/qa-assistant
model-index:
- name: Ivysaur
results:
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en)
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
- type: accuracy
value: 72.1044776119403
- type: ap
value: 35.09105788324913
- type: f1
value: 66.26967715703572
- task:
type: Classification
dataset:
type: mteb/amazon_polarity
name: MTEB AmazonPolarityClassification
config: default
split: test
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
metrics:
- type: accuracy
value: 86.686075
- type: ap
value: 81.92716581685914
- type: f1
value: 86.65902299160209
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (en)
config: en
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy
value: 42.698
- type: f1
value: 42.287785312461885
- task:
type: Retrieval
dataset:
type: mteb/arguana
name: MTEB ArguAna
config: default
split: test
revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
metrics:
- type: map_at_1
value: 30.441000000000003
- type: map_at_10
value: 46.951
- type: map_at_100
value: 47.788000000000004
- type: map_at_1000
value: 47.794
- type: map_at_20
value: 47.621
- type: map_at_3
value: 42.295
- type: map_at_5
value: 45.126
- type: mrr_at_1
value: 31.65
- type: mrr_at_10
value: 47.394999999999996
- type: mrr_at_100
value: 48.238
- type: mrr_at_1000
value: 48.245
- type: mrr_at_20
value: 48.069
- type: mrr_at_3
value: 42.852000000000004
- type: mrr_at_5
value: 45.58
- type: ndcg_at_1
value: 30.441000000000003
- type: ndcg_at_10
value: 55.783
- type: ndcg_at_100
value: 59.227
- type: ndcg_at_1000
value: 59.376
- type: ndcg_at_20
value: 58.18
- type: ndcg_at_3
value: 46.291
- type: ndcg_at_5
value: 51.405
- type: precision_at_1
value: 30.441000000000003
- type: precision_at_10
value: 8.378
- type: precision_at_100
value: 0.985
- type: precision_at_1000
value: 0.1
- type: precision_at_20
value: 4.659
- type: precision_at_3
value: 19.298000000000002
- type: precision_at_5
value: 14.068
- type: recall_at_1
value: 30.441000000000003
- type: recall_at_10
value: 83.784
- type: recall_at_100
value: 98.506
- type: recall_at_1000
value: 99.644
- type: recall_at_20
value: 93.172
- type: recall_at_3
value: 57.894999999999996
- type: recall_at_5
value: 70.341
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-p2p
name: MTEB ArxivClusteringP2P
config: default
split: test
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
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value: 46.39249132731755
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- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-s2s
name: MTEB ArxivClusteringS2S
config: default
split: test
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
metrics:
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type: Reranking
dataset:
type: mteb/askubuntudupquestions-reranking
name: MTEB AskUbuntuDupQuestions
config: default
split: test
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
metrics:
- type: map
value: 59.69637278242267
- type: mrr
value: 74.02948159873367
- task:
type: STS
dataset:
type: mteb/biosses-sts
name: MTEB BIOSSES
config: default
split: test
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
metrics:
- type: cos_sim_pearson
value: 87.14461604689758
- type: cos_sim_spearman
value: 87.31584497244751
- type: euclidean_pearson
value: 84.78141750973201
- type: euclidean_spearman
value: 87.05017626840346
- type: manhattan_pearson
value: 84.35436632710646
- type: manhattan_spearman
value: 86.49534434907336
- task:
type: Classification
dataset:
type: mteb/banking77
name: MTEB Banking77Classification
config: default
split: test
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
metrics:
- type: accuracy
value: 81.91558441558439
- type: f1
value: 81.88197959191479
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-p2p
name: MTEB BiorxivClusteringP2P
config: default
split: test
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
metrics:
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value: 38.97808934568377
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- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-s2s
name: MTEB BiorxivClusteringS2S
config: default
split: test
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
metrics:
- type: v_measure
value: 31.7412250739116
- type: v_measures
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- 0.31626398941398964
- 0.3327295496031667
- 0.31156273517579985
- 0.31497713177719505
- 0.3211720123203406
- 0.30456845682253647
- 0.3152485096373301
- 0.32328632147728803
- 0.3114059814606084
- 0.32290781970290505
- 0.31626398941398964
- 0.3327295496031667
- 0.31156273517579985
- 0.31497713177719505
- 0.3211720123203406
- 0.30456845682253647
- 0.3152485096373301
- 0.32328632147728803
- 0.3114059814606084
- 0.32290781970290505
- 0.31626398941398964
- 0.3327295496031667
- 0.31156273517579985
- 0.31497713177719505
- 0.3211720123203406
- 0.30456845682253647
- 0.3152485096373301
- 0.32328632147728803
- 0.3114059814606084
- 0.32290781970290505
- 0.31626398941398964
- 0.3327295496031667
- 0.31156273517579985
- 0.31497713177719505
- 0.3211720123203406
- 0.30456845682253647
- 0.3152485096373301
- 0.32328632147728803
- 0.3114059814606084
- 0.32290781970290505
- 0.31626398941398964
- 0.3327295496031667
- task:
type: Reranking
dataset:
type: mteb/mind_small
name: MTEB MindSmallReranking
config: default
split: test
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
metrics:
- type: map
value: 31.7776266029616
- type: mrr
value: 32.9057970138914
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack
name: MTEB CQADupstackRetrieval
config: default
split: test
revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
metrics:
- type: map_at_1
value: 24.78675
- type: map_at_10
value: 33.18391666666666
- type: map_at_100
value: 34.34583333333333
- type: map_at_1000
value: 34.46825
- type: map_at_20
value: 33.819
- type: map_at_3
value: 30.636500000000005
- type: map_at_5
value: 32.02091666666667
- type: mrr_at_1
value: 29.478749999999998
- type: mrr_at_10
value: 37.385
- type: mrr_at_100
value: 38.23491666666667
- type: mrr_at_1000
value: 38.298833333333334
- type: mrr_at_20
value: 37.87508333333333
- type: mrr_at_3
value: 35.089666666666666
- type: mrr_at_5
value: 36.36816666666667
- type: ndcg_at_1
value: 29.478749999999998
- type: ndcg_at_10
value: 38.2035
- type: ndcg_at_100
value: 43.301083333333324
- type: ndcg_at_1000
value: 45.758666666666656
- type: ndcg_at_20
value: 40.15116666666667
- type: ndcg_at_3
value: 33.86033333333334
- type: ndcg_at_5
value: 35.81266666666666
- type: precision_at_1
value: 29.478749999999998
- type: precision_at_10
value: 6.642833333333334
- type: precision_at_100
value: 1.08425
- type: precision_at_1000
value: 0.14850000000000002
- type: precision_at_20
value: 3.948083333333334
- type: precision_at_3
value: 15.511
- type: precision_at_5
value: 10.929833333333333
- type: recall_at_1
value: 24.78675
- type: recall_at_10
value: 48.9305
- type: recall_at_100
value: 71.49416666666666
- type: recall_at_1000
value: 88.54375
- type: recall_at_20
value: 56.06475
- type: recall_at_3
value: 36.66891666666666
- type: recall_at_5
value: 41.790499999999994
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-android
name: MTEB CQADupstackAndroidRetrieval
config: default
split: test
revision: f46a197baaae43b4f621051089b82a364682dfeb
metrics:
- type: map_at_1
value: 30.793
- type: map_at_10
value: 42.254000000000005
- type: map_at_100
value: 43.569
- type: map_at_1000
value: 43.714999999999996
- type: map_at_20
value: 42.994
- type: map_at_3
value: 39.007999999999996
- type: map_at_5
value: 40.488
- type: mrr_at_1
value: 38.34
- type: mrr_at_10
value: 48.274
- type: mrr_at_100
value: 48.946
- type: mrr_at_1000
value: 49.001
- type: mrr_at_20
value: 48.701
- type: mrr_at_3
value: 45.756
- type: mrr_at_5
value: 47.036
- type: ndcg_at_1
value: 38.34
- type: ndcg_at_10
value: 48.622
- type: ndcg_at_100
value: 53.288999999999994
- type: ndcg_at_1000
value: 55.614
- type: ndcg_at_20
value: 50.495000000000005
- type: ndcg_at_3
value: 43.852999999999994
- type: ndcg_at_5
value: 45.442
- type: precision_at_1
value: 38.34
- type: precision_at_10
value: 9.413
- type: precision_at_100
value: 1.4749999999999999
- type: precision_at_1000
value: 0.19499999999999998
- type: precision_at_20
value: 5.494000000000001
- type: precision_at_3
value: 20.935000000000002
- type: precision_at_5
value: 14.735000000000001
- type: recall_at_1
value: 30.793
- type: recall_at_10
value: 60.455000000000005
- type: recall_at_100
value: 80.061
- type: recall_at_1000
value: 95.322
- type: recall_at_20
value: 67.27
- type: recall_at_3
value: 46.296
- type: recall_at_5
value: 51.139
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-english
name: MTEB CQADupstackEnglishRetrieval
config: default
split: test
revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
metrics:
- type: map_at_1
value: 27.93
- type: map_at_10
value: 36.085
- type: map_at_100
value: 37.192
- type: map_at_1000
value: 37.324
- type: map_at_20
value: 36.614999999999995
- type: map_at_3
value: 33.452
- type: map_at_5
value: 35.088
- type: mrr_at_1
value: 34.777
- type: mrr_at_10
value: 41.865
- type: mrr_at_100
value: 42.518
- type: mrr_at_1000
value: 42.571
- type: mrr_at_20
value: 42.219
- type: mrr_at_3
value: 39.628
- type: mrr_at_5
value: 41.038999999999994
- type: ndcg_at_1
value: 34.777
- type: ndcg_at_10
value: 41.095
- type: ndcg_at_100
value: 45.286
- type: ndcg_at_1000
value: 47.656
- type: ndcg_at_20
value: 42.472
- type: ndcg_at_3
value: 37.349
- type: ndcg_at_5
value: 39.318
- type: precision_at_1
value: 34.777
- type: precision_at_10
value: 7.617999999999999
- type: precision_at_100
value: 1.242
- type: precision_at_1000
value: 0.173
- type: precision_at_20
value: 4.481
- type: precision_at_3
value: 17.771
- type: precision_at_5
value: 12.687999999999999
- type: recall_at_1
value: 27.93
- type: recall_at_10
value: 49.464000000000006
- type: recall_at_100
value: 67.64099999999999
- type: recall_at_1000
value: 83.066
- type: recall_at_20
value: 54.452999999999996
- type: recall_at_3
value: 38.157000000000004
- type: recall_at_5
value: 43.829
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-gaming
name: MTEB CQADupstackGamingRetrieval
config: default
split: test
revision: 4885aa143210c98657558c04aaf3dc47cfb54340
metrics:
- type: map_at_1
value: 37.332
- type: map_at_10
value: 49.146
- type: map_at_100
value: 50.222
- type: map_at_1000
value: 50.281
- type: map_at_20
value: 49.802
- type: map_at_3
value: 46.264
- type: map_at_5
value: 47.912
- type: mrr_at_1
value: 43.009
- type: mrr_at_10
value: 52.586999999999996
- type: mrr_at_100
value: 53.323
- type: mrr_at_1000
value: 53.352999999999994
- type: mrr_at_20
value: 53.04299999999999
- type: mrr_at_3
value: 50.261
- type: mrr_at_5
value: 51.615
- type: ndcg_at_1
value: 43.009
- type: ndcg_at_10
value: 54.652
- type: ndcg_at_100
value: 58.918000000000006
- type: ndcg_at_1000
value: 60.172000000000004
- type: ndcg_at_20
value: 56.554
- type: ndcg_at_3
value: 49.757
- type: ndcg_at_5
value: 52.169
- type: precision_at_1
value: 43.009
- type: precision_at_10
value: 8.715
- type: precision_at_100
value: 1.1780000000000002
- type: precision_at_1000
value: 0.133
- type: precision_at_20
value: 4.931
- type: precision_at_3
value: 22.153
- type: precision_at_5
value: 15.146999999999998
- type: recall_at_1
value: 37.332
- type: recall_at_10
value: 67.55600000000001
- type: recall_at_100
value: 85.885
- type: recall_at_1000
value: 94.87400000000001
- type: recall_at_20
value: 74.568
- type: recall_at_3
value: 54.419
- type: recall_at_5
value: 60.288
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-gis
name: MTEB CQADupstackGisRetrieval
config: default
split: test
revision: 5003b3064772da1887988e05400cf3806fe491f2
metrics:
- type: map_at_1
value: 24.09
- type: map_at_10
value: 32.608
- type: map_at_100
value: 33.571
- type: map_at_1000
value: 33.668
- type: map_at_20
value: 33.181
- type: map_at_3
value: 30.091
- type: map_at_5
value: 31.518
- type: mrr_at_1
value: 25.763
- type: mrr_at_10
value: 34.25
- type: mrr_at_100
value: 35.134
- type: mrr_at_1000
value: 35.207
- type: mrr_at_20
value: 34.78
- type: mrr_at_3
value: 31.807999999999996
- type: mrr_at_5
value: 33.198
- type: ndcg_at_1
value: 25.763
- type: ndcg_at_10
value: 37.305
- type: ndcg_at_100
value: 42.114000000000004
- type: ndcg_at_1000
value: 44.467
- type: ndcg_at_20
value: 39.272
- type: ndcg_at_3
value: 32.405
- type: ndcg_at_5
value: 34.775
- type: precision_at_1
value: 25.763
- type: precision_at_10
value: 5.729
- type: precision_at_100
value: 0.853
- type: precision_at_1000
value: 0.109
- type: precision_at_20
value: 3.3329999999999997
- type: precision_at_3
value: 13.71
- type: precision_at_5
value: 9.65
- type: recall_at_1
value: 24.09
- type: recall_at_10
value: 50.161
- type: recall_at_100
value: 72.419
- type: recall_at_1000
value: 89.983
- type: recall_at_20
value: 57.53
- type: recall_at_3
value: 36.961
- type: recall_at_5
value: 42.568
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-mathematica
name: MTEB CQADupstackMathematicaRetrieval
config: default
split: test
revision: 90fceea13679c63fe563ded68f3b6f06e50061de
metrics:
- type: map_at_1
value: 16.333000000000002
- type: map_at_10
value: 23.352999999999998
- type: map_at_100
value: 24.618000000000002
- type: map_at_1000
value: 24.743000000000002
- type: map_at_20
value: 24.117
- type: map_at_3
value: 21.013
- type: map_at_5
value: 22.259
- type: mrr_at_1
value: 20.398
- type: mrr_at_10
value: 28.28
- type: mrr_at_100
value: 29.307
- type: mrr_at_1000
value: 29.381
- type: mrr_at_20
value: 28.955
- type: mrr_at_3
value: 25.933
- type: mrr_at_5
value: 27.114
- type: ndcg_at_1
value: 20.398
- type: ndcg_at_10
value: 28.359
- type: ndcg_at_100
value: 34.178999999999995
- type: ndcg_at_1000
value: 37.112
- type: ndcg_at_20
value: 30.982
- type: ndcg_at_3
value: 24.104999999999997
- type: ndcg_at_5
value: 25.877
- type: precision_at_1
value: 20.398
- type: precision_at_10
value: 5.2490000000000006
- type: precision_at_100
value: 0.927
- type: precision_at_1000
value: 0.131
- type: precision_at_20
value: 3.3520000000000003
- type: precision_at_3
value: 11.733
- type: precision_at_5
value: 8.433
- type: recall_at_1
value: 16.333000000000002
- type: recall_at_10
value: 39.082
- type: recall_at_100
value: 64.269
- type: recall_at_1000
value: 85.103
- type: recall_at_20
value: 48.625
- type: recall_at_3
value: 26.740000000000002
- type: recall_at_5
value: 31.519000000000002
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-physics
name: MTEB CQADupstackPhysicsRetrieval
config: default
split: test
revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
metrics:
- type: map_at_1
value: 26.857999999999997
- type: map_at_10
value: 36.258
- type: map_at_100
value: 37.556
- type: map_at_1000
value: 37.669999999999995
- type: map_at_20
value: 36.937
- type: map_at_3
value: 33.306000000000004
- type: map_at_5
value: 35.004999999999995
- type: mrr_at_1
value: 33.397
- type: mrr_at_10
value: 42.089
- type: mrr_at_100
value: 42.864999999999995
- type: mrr_at_1000
value: 42.915
- type: mrr_at_20
value: 42.510999999999996
- type: mrr_at_3
value: 39.413
- type: mrr_at_5
value: 40.905
- type: ndcg_at_1
value: 33.397
- type: ndcg_at_10
value: 42.062
- type: ndcg_at_100
value: 47.620000000000005
- type: ndcg_at_1000
value: 49.816
- type: ndcg_at_20
value: 44.096999999999994
- type: ndcg_at_3
value: 37.165
- type: ndcg_at_5
value: 39.493
- type: precision_at_1
value: 33.397
- type: precision_at_10
value: 7.5649999999999995
- type: precision_at_100
value: 1.224
- type: precision_at_1000
value: 0.16
- type: precision_at_20
value: 4.495
- type: precision_at_3
value: 17.613
- type: precision_at_5
value: 12.589
- type: recall_at_1
value: 26.857999999999997
- type: recall_at_10
value: 53.900000000000006
- type: recall_at_100
value: 77.595
- type: recall_at_1000
value: 92.116
- type: recall_at_20
value: 60.962
- type: recall_at_3
value: 39.799
- type: recall_at_5
value: 45.961
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-programmers
name: MTEB CQADupstackProgrammersRetrieval
config: default
split: test
revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
metrics:
- type: map_at_1
value: 24.131
- type: map_at_10
value: 33.016
- type: map_at_100
value: 34.263
- type: map_at_1000
value: 34.39
- type: map_at_20
value: 33.703
- type: map_at_3
value: 30.055
- type: map_at_5
value: 31.651
- type: mrr_at_1
value: 30.593999999999998
- type: mrr_at_10
value: 38.786
- type: mrr_at_100
value: 39.674
- type: mrr_at_1000
value: 39.739000000000004
- type: mrr_at_20
value: 39.322
- type: mrr_at_3
value: 36.32
- type: mrr_at_5
value: 37.787
- type: ndcg_at_1
value: 30.593999999999998
- type: ndcg_at_10
value: 38.606
- type: ndcg_at_100
value: 44.116
- type: ndcg_at_1000
value: 46.772999999999996
- type: ndcg_at_20
value: 40.775
- type: ndcg_at_3
value: 33.854
- type: ndcg_at_5
value: 35.957
- type: precision_at_1
value: 30.593999999999998
- type: precision_at_10
value: 7.112
- type: precision_at_100
value: 1.154
- type: precision_at_1000
value: 0.155
- type: precision_at_20
value: 4.2410000000000005
- type: precision_at_3
value: 16.323999999999998
- type: precision_at_5
value: 11.644
- type: recall_at_1
value: 24.131
- type: recall_at_10
value: 49.767
- type: recall_at_100
value: 73.57000000000001
- type: recall_at_1000
value: 91.842
- type: recall_at_20
value: 57.498000000000005
- type: recall_at_3
value: 35.888
- type: recall_at_5
value: 41.801
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-stats
name: MTEB CQADupstackStatsRetrieval
config: default
split: test
revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
metrics:
- type: map_at_1
value: 23.075000000000003
- type: map_at_10
value: 29.584
- type: map_at_100
value: 30.4
- type: map_at_1000
value: 30.501
- type: map_at_20
value: 30.051
- type: map_at_3
value: 27.561000000000003
- type: map_at_5
value: 28.603
- type: mrr_at_1
value: 26.227
- type: mrr_at_10
value: 32.647
- type: mrr_at_100
value: 33.391999999999996
- type: mrr_at_1000
value: 33.469
- type: mrr_at_20
value: 33.053
- type: mrr_at_3
value: 30.776999999999997
- type: mrr_at_5
value: 31.828
- type: ndcg_at_1
value: 26.227
- type: ndcg_at_10
value: 33.582
- type: ndcg_at_100
value: 37.814
- type: ndcg_at_1000
value: 40.444
- type: ndcg_at_20
value: 35.163
- type: ndcg_at_3
value: 29.874000000000002
- type: ndcg_at_5
value: 31.53
- type: precision_at_1
value: 26.227
- type: precision_at_10
value: 5.244999999999999
- type: precision_at_100
value: 0.788
- type: precision_at_1000
value: 0.11100000000000002
- type: precision_at_20
value: 3.006
- type: precision_at_3
value: 12.73
- type: precision_at_5
value: 8.741999999999999
- type: recall_at_1
value: 23.075000000000003
- type: recall_at_10
value: 42.894
- type: recall_at_100
value: 62.721000000000004
- type: recall_at_1000
value: 81.858
- type: recall_at_20
value: 48.842
- type: recall_at_3
value: 32.783
- type: recall_at_5
value: 36.949
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-tex
name: MTEB CQADupstackTexRetrieval
config: default
split: test
revision: 46989137a86843e03a6195de44b09deda022eec7
metrics:
- type: map_at_1
value: 17.028
- type: map_at_10
value: 23.377
- type: map_at_100
value: 24.399
- type: map_at_1000
value: 24.524
- type: map_at_20
value: 23.863
- type: map_at_3
value: 21.274
- type: map_at_5
value: 22.431
- type: mrr_at_1
value: 20.578
- type: mrr_at_10
value: 27.009
- type: mrr_at_100
value: 27.889999999999997
- type: mrr_at_1000
value: 27.969
- type: mrr_at_20
value: 27.46
- type: mrr_at_3
value: 24.959999999999997
- type: mrr_at_5
value: 26.113999999999997
- type: ndcg_at_1
value: 20.578
- type: ndcg_at_10
value: 27.522999999999996
- type: ndcg_at_100
value: 32.601
- type: ndcg_at_1000
value: 35.636
- type: ndcg_at_20
value: 29.132
- type: ndcg_at_3
value: 23.771
- type: ndcg_at_5
value: 25.539
- type: precision_at_1
value: 20.578
- type: precision_at_10
value: 4.962
- type: precision_at_100
value: 0.8880000000000001
- type: precision_at_1000
value: 0.132
- type: precision_at_20
value: 2.959
- type: precision_at_3
value: 11.068999999999999
- type: precision_at_5
value: 8.052
- type: recall_at_1
value: 17.028
- type: recall_at_10
value: 36.266
- type: recall_at_100
value: 59.556
- type: recall_at_1000
value: 81.416
- type: recall_at_20
value: 42.303000000000004
- type: recall_at_3
value: 25.858999999999998
- type: recall_at_5
value: 30.422
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-unix
name: MTEB CQADupstackUnixRetrieval
config: default
split: test
revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
metrics:
- type: map_at_1
value: 25.863000000000003
- type: map_at_10
value: 33.586
- type: map_at_100
value: 34.682
- type: map_at_1000
value: 34.791
- type: map_at_20
value: 34.182
- type: map_at_3
value: 31.044
- type: map_at_5
value: 32.507000000000005
- type: mrr_at_1
value: 30.131000000000004
- type: mrr_at_10
value: 37.518
- type: mrr_at_100
value: 38.355
- type: mrr_at_1000
value: 38.425
- type: mrr_at_20
value: 37.961
- type: mrr_at_3
value: 35.059000000000005
- type: mrr_at_5
value: 36.528
- type: ndcg_at_1
value: 30.131000000000004
- type: ndcg_at_10
value: 38.387
- type: ndcg_at_100
value: 43.617
- type: ndcg_at_1000
value: 46.038000000000004
- type: ndcg_at_20
value: 40.261
- type: ndcg_at_3
value: 33.722
- type: ndcg_at_5
value: 36.013
- type: precision_at_1
value: 30.131000000000004
- type: precision_at_10
value: 6.297
- type: precision_at_100
value: 1.008
- type: precision_at_1000
value: 0.132
- type: precision_at_20
value: 3.689
- type: precision_at_3
value: 15.049999999999999
- type: precision_at_5
value: 10.634
- type: recall_at_1
value: 25.863000000000003
- type: recall_at_10
value: 49.101
- type: recall_at_100
value: 72.286
- type: recall_at_1000
value: 89.14
- type: recall_at_20
value: 55.742999999999995
- type: recall_at_3
value: 36.513
- type: recall_at_5
value: 42.204
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-webmasters
name: MTEB CQADupstackWebmastersRetrieval
config: default
split: test
revision: 160c094312a0e1facb97e55eeddb698c0abe3571
metrics:
- type: map_at_1
value: 24.747
- type: map_at_10
value: 32.067
- type: map_at_100
value: 33.739999999999995
- type: map_at_1000
value: 33.952
- type: map_at_20
value: 32.927
- type: map_at_3
value: 29.736
- type: map_at_5
value: 30.996000000000002
- type: mrr_at_1
value: 29.644
- type: mrr_at_10
value: 36.683
- type: mrr_at_100
value: 37.808
- type: mrr_at_1000
value: 37.858999999999995
- type: mrr_at_20
value: 37.326
- type: mrr_at_3
value: 34.42
- type: mrr_at_5
value: 35.626000000000005
- type: ndcg_at_1
value: 29.644
- type: ndcg_at_10
value: 36.989
- type: ndcg_at_100
value: 43.589
- type: ndcg_at_1000
value: 46.133
- type: ndcg_at_20
value: 39.403
- type: ndcg_at_3
value: 33.273
- type: ndcg_at_5
value: 34.853
- type: precision_at_1
value: 29.644
- type: precision_at_10
value: 6.8180000000000005
- type: precision_at_100
value: 1.4529999999999998
- type: precision_at_1000
value: 0.23500000000000001
- type: precision_at_20
value: 4.457
- type: precision_at_3
value: 15.152
- type: precision_at_5
value: 10.711
- type: recall_at_1
value: 24.747
- type: recall_at_10
value: 45.714
- type: recall_at_100
value: 75.212
- type: recall_at_1000
value: 90.884
- type: recall_at_20
value: 54.777
- type: recall_at_3
value: 34.821999999999996
- type: recall_at_5
value: 39.278999999999996
- task:
type: Retrieval
dataset:
type: mteb/cqadupstack-wordpress
name: MTEB CQADupstackWordpressRetrieval
config: default
split: test
revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
metrics:
- type: map_at_1
value: 19.261
- type: map_at_10
value: 26.873
- type: map_at_100
value: 27.938000000000002
- type: map_at_1000
value: 28.060000000000002
- type: map_at_20
value: 27.456000000000003
- type: map_at_3
value: 24.834
- type: map_at_5
value: 25.793
- type: mrr_at_1
value: 20.887
- type: mrr_at_10
value: 28.634999999999998
- type: mrr_at_100
value: 29.609
- type: mrr_at_1000
value: 29.698999999999998
- type: mrr_at_20
value: 29.173
- type: mrr_at_3
value: 26.741
- type: mrr_at_5
value: 27.628000000000004
- type: ndcg_at_1
value: 20.887
- type: ndcg_at_10
value: 31.261
- type: ndcg_at_100
value: 36.471
- type: ndcg_at_1000
value: 39.245000000000005
- type: ndcg_at_20
value: 33.209
- type: ndcg_at_3
value: 27.195999999999998
- type: ndcg_at_5
value: 28.786
- type: precision_at_1
value: 20.887
- type: precision_at_10
value: 4.9910000000000005
- type: precision_at_100
value: 0.8210000000000001
- type: precision_at_1000
value: 0.116
- type: precision_at_20
value: 2.939
- type: precision_at_3
value: 11.892
- type: precision_at_5
value: 8.133
- type: recall_at_1
value: 19.261
- type: recall_at_10
value: 42.806
- type: recall_at_100
value: 66.715
- type: recall_at_1000
value: 86.921
- type: recall_at_20
value: 50.205999999999996
- type: recall_at_3
value: 31.790000000000003
- type: recall_at_5
value: 35.527
- task:
type: Retrieval
dataset:
type: mteb/climate-fever
name: MTEB ClimateFEVER
config: default
split: test
revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
metrics:
- type: map_at_1
value: 9.009
- type: map_at_10
value: 14.629
- type: map_at_100
value: 16.092000000000002
- type: map_at_1000
value: 16.267
- type: map_at_20
value: 15.384999999999998
- type: map_at_3
value: 12.280000000000001
- type: map_at_5
value: 13.442000000000002
- type: mrr_at_1
value: 20
- type: mrr_at_10
value: 29.298000000000002
- type: mrr_at_100
value: 30.375999999999998
- type: mrr_at_1000
value: 30.436999999999998
- type: mrr_at_20
value: 29.956
- type: mrr_at_3
value: 26.362999999999996
- type: mrr_at_5
value: 28.021
- type: ndcg_at_1
value: 20
- type: ndcg_at_10
value: 21.234
- type: ndcg_at_100
value: 27.687
- type: ndcg_at_1000
value: 31.325999999999997
- type: ndcg_at_20
value: 23.631
- type: ndcg_at_3
value: 17.101
- type: ndcg_at_5
value: 18.501
- type: precision_at_1
value: 20
- type: precision_at_10
value: 6.651
- type: precision_at_100
value: 1.347
- type: precision_at_1000
value: 0.201
- type: precision_at_20
value: 4.316
- type: precision_at_3
value: 12.53
- type: precision_at_5
value: 9.707
- type: recall_at_1
value: 9.009
- type: recall_at_10
value: 25.824
- type: recall_at_100
value: 48.535000000000004
- type: recall_at_1000
value: 69.44399999999999
- type: recall_at_20
value: 32.78
- type: recall_at_3
value: 15.693999999999999
- type: recall_at_5
value: 19.59
- task:
type: Retrieval
dataset:
type: mteb/dbpedia
name: MTEB DBPedia
config: default
split: test
revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
metrics:
- type: map_at_1
value: 7.454
- type: map_at_10
value: 15.675
- type: map_at_100
value: 21.335
- type: map_at_1000
value: 22.639
- type: map_at_20
value: 17.822
- type: map_at_3
value: 11.609
- type: map_at_5
value: 13.342
- type: mrr_at_1
value: 56.25
- type: mrr_at_10
value: 65.30799999999999
- type: mrr_at_100
value: 65.90599999999999
- type: mrr_at_1000
value: 65.92099999999999
- type: mrr_at_20
value: 65.74600000000001
- type: mrr_at_3
value: 63.333
- type: mrr_at_5
value: 64.521
- type: ndcg_at_1
value: 44.625
- type: ndcg_at_10
value: 33.881
- type: ndcg_at_100
value: 37.775999999999996
- type: ndcg_at_1000
value: 44.956
- type: ndcg_at_20
value: 33.451
- type: ndcg_at_3
value: 37.72
- type: ndcg_at_5
value: 35.811
- type: precision_at_1
value: 56.25
- type: precision_at_10
value: 27.175
- type: precision_at_100
value: 8.448
- type: precision_at_1000
value: 1.809
- type: precision_at_20
value: 20.262
- type: precision_at_3
value: 41.333
- type: precision_at_5
value: 35.199999999999996
- type: recall_at_1
value: 7.454
- type: recall_at_10
value: 20.355999999999998
- type: recall_at_100
value: 43.168
- type: recall_at_1000
value: 66.559
- type: recall_at_20
value: 26.785999999999998
- type: recall_at_3
value: 13.052
- type: recall_at_5
value: 15.733
- task:
type: Classification
dataset:
type: mteb/emotion
name: MTEB EmotionClassification
config: default
split: test
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
metrics:
- type: accuracy
value: 45.44499999999999
- type: f1
value: 40.581418056070994
- task:
type: Retrieval
dataset:
type: mteb/fever
name: MTEB FEVER
config: default
split: test
revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
metrics:
- type: map_at_1
value: 46.339000000000006
- type: map_at_10
value: 57.87
- type: map_at_100
value: 58.447
- type: map_at_1000
value: 58.474000000000004
- type: map_at_20
value: 58.241
- type: map_at_3
value: 55.336
- type: map_at_5
value: 56.879000000000005
- type: mrr_at_1
value: 49.91
- type: mrr_at_10
value: 61.55199999999999
- type: mrr_at_100
value: 62.07
- type: mrr_at_1000
value: 62.086
- type: mrr_at_20
value: 61.899
- type: mrr_at_3
value: 59.108000000000004
- type: mrr_at_5
value: 60.622
- type: ndcg_at_1
value: 49.91
- type: ndcg_at_10
value: 63.970000000000006
- type: ndcg_at_100
value: 66.625
- type: ndcg_at_1000
value: 67.221
- type: ndcg_at_20
value: 65.261
- type: ndcg_at_3
value: 59.059
- type: ndcg_at_5
value: 61.68900000000001
- type: precision_at_1
value: 49.91
- type: precision_at_10
value: 8.699
- type: precision_at_100
value: 1.015
- type: precision_at_1000
value: 0.108
- type: precision_at_20
value: 4.6370000000000005
- type: precision_at_3
value: 23.942
- type: precision_at_5
value: 15.815000000000001
- type: recall_at_1
value: 46.339000000000006
- type: recall_at_10
value: 79.28
- type: recall_at_100
value: 91.148
- type: recall_at_1000
value: 95.438
- type: recall_at_20
value: 84.187
- type: recall_at_3
value: 66.019
- type: recall_at_5
value: 72.394
- task:
type: Retrieval
dataset:
type: mteb/fiqa
name: MTEB FiQA2018
config: default
split: test
revision: 27a168819829fe9bcd655c2df245fb19452e8e06
metrics:
- type: map_at_1
value: 14.504
- type: map_at_10
value: 24.099999999999998
- type: map_at_100
value: 25.820999999999998
- type: map_at_1000
value: 25.997999999999998
- type: map_at_20
value: 25.003999999999998
- type: map_at_3
value: 21.218999999999998
- type: map_at_5
value: 22.744
- type: mrr_at_1
value: 29.475
- type: mrr_at_10
value: 38.072
- type: mrr_at_100
value: 39.196999999999996
- type: mrr_at_1000
value: 39.249
- type: mrr_at_20
value: 38.757999999999996
- type: mrr_at_3
value: 36.214
- type: mrr_at_5
value: 37.094
- type: ndcg_at_1
value: 29.475
- type: ndcg_at_10
value: 30.708999999999996
- type: ndcg_at_100
value: 37.744
- type: ndcg_at_1000
value: 41.215
- type: ndcg_at_20
value: 33.336
- type: ndcg_at_3
value: 28.243000000000002
- type: ndcg_at_5
value: 28.62
- type: precision_at_1
value: 29.475
- type: precision_at_10
value: 8.596
- type: precision_at_100
value: 1.562
- type: precision_at_1000
value: 0.219
- type: precision_at_20
value: 5.394
- type: precision_at_3
value: 19.084
- type: precision_at_5
value: 13.672999999999998
- type: recall_at_1
value: 14.504
- type: recall_at_10
value: 36.232
- type: recall_at_100
value: 62.712
- type: recall_at_1000
value: 83.864
- type: recall_at_20
value: 44.357
- type: recall_at_3
value: 26.029000000000003
- type: recall_at_5
value: 29.909000000000002
- task:
type: Retrieval
dataset:
type: mteb/hotpotqa
name: MTEB HotpotQA
config: default
split: test
revision: ab518f4d6fcca38d87c25209f94beba119d02014
metrics:
- type: map_at_1
value: 31.634
- type: map_at_10
value: 45.007000000000005
- type: map_at_100
value: 45.963
- type: map_at_1000
value: 46.052
- type: map_at_20
value: 45.550000000000004
- type: map_at_3
value: 42.092
- type: map_at_5
value: 43.832
- type: mrr_at_1
value: 63.268
- type: mrr_at_10
value: 70.691
- type: mrr_at_100
value: 71.063
- type: mrr_at_1000
value: 71.082
- type: mrr_at_20
value: 70.917
- type: mrr_at_3
value: 69.176
- type: mrr_at_5
value: 70.132
- type: ndcg_at_1
value: 63.268
- type: ndcg_at_10
value: 54.205000000000005
- type: ndcg_at_100
value: 57.847
- type: ndcg_at_1000
value: 59.64
- type: ndcg_at_20
value: 55.663
- type: ndcg_at_3
value: 49.613
- type: ndcg_at_5
value: 52.054
- type: precision_at_1
value: 63.268
- type: precision_at_10
value: 11.357000000000001
- type: precision_at_100
value: 1.423
- type: precision_at_1000
value: 0.166
- type: precision_at_20
value: 6.148
- type: precision_at_3
value: 31.041999999999998
- type: precision_at_5
value: 20.551
- type: recall_at_1
value: 31.634
- type: recall_at_10
value: 56.786
- type: recall_at_100
value: 71.128
- type: recall_at_1000
value: 82.97099999999999
- type: recall_at_20
value: 61.47899999999999
- type: recall_at_3
value: 46.563
- type: recall_at_5
value: 51.376999999999995
- task:
type: Classification
dataset:
type: mteb/imdb
name: MTEB ImdbClassification
config: default
split: test
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
metrics:
- type: accuracy
value: 80.7996
- type: ap
value: 74.98592172204835
- type: f1
value: 80.77161545117626
- task:
type: Retrieval
dataset:
type: mteb/msmarco
name: MTEB MSMARCO
config: default
split: dev
revision: c5a29a104738b98a9e76336939199e264163d4a0
metrics:
- type: map_at_1
value: 16.637
- type: map_at_10
value: 27.331
- type: map_at_100
value: 28.518
- type: map_at_1000
value: 28.583
- type: map_at_20
value: 28.031
- type: map_at_3
value: 23.715
- type: map_at_5
value: 25.758
- type: mrr_at_1
value: 17.077
- type: mrr_at_10
value: 27.807
- type: mrr_at_100
value: 28.965999999999998
- type: mrr_at_1000
value: 29.025000000000002
- type: mrr_at_20
value: 28.499999999999996
- type: mrr_at_3
value: 24.234
- type: mrr_at_5
value: 26.257
- type: ndcg_at_1
value: 17.077
- type: ndcg_at_10
value: 33.607
- type: ndcg_at_100
value: 39.593
- type: ndcg_at_1000
value: 41.317
- type: ndcg_at_20
value: 36.118
- type: ndcg_at_3
value: 26.204
- type: ndcg_at_5
value: 29.862
- type: precision_at_1
value: 17.077
- type: precision_at_10
value: 5.54
- type: precision_at_100
value: 0.857
- type: precision_at_1000
value: 0.101
- type: precision_at_20
value: 3.2870000000000004
- type: precision_at_3
value: 11.361
- type: precision_at_5
value: 8.673
- type: recall_at_1
value: 16.637
- type: recall_at_10
value: 53.077
- type: recall_at_100
value: 81.306
- type: recall_at_1000
value: 94.72699999999999
- type: recall_at_20
value: 62.855000000000004
- type: recall_at_3
value: 32.897999999999996
- type: recall_at_5
value: 41.697
- task:
type: Classification
dataset:
type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (en)
config: en
split: test
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
metrics:
- type: accuracy
value: 92.12494300045599
- type: f1
value: 91.6522604757574
- task:
type: Classification
dataset:
type: mteb/mtop_intent
name: MTEB MTOPIntentClassification (en)
config: en
split: test
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
metrics:
- type: accuracy
value: 71.86046511627907
- type: f1
value: 53.8926541769729
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (en)
config: en
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy
value: 70.34633490248824
- type: f1
value: 67.94196699295675
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (en)
config: en
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy
value: 74.88903833221251
- type: f1
value: 74.54991713265153
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-p2p
name: MTEB MedrxivClusteringP2P
config: default
split: test
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
metrics:
- type: v_measure
value: 33.129785771060526
- type: v_measures
value:
- 0.3116408980465631
- 0.31900622847630045
- 0.31934151231927727
- 0.3186791563176499
- 0.32750328333726775
- 0.3510627418495332
- 0.33347506212887845
- 0.35025343435496104
- 0.3417862644568677
- 0.3402299958187535
- 0.3116408980465631
- 0.31900622847630045
- 0.31934151231927727
- 0.3186791563176499
- 0.32750328333726775
- 0.3510627418495332
- 0.33347506212887845
- 0.35025343435496104
- 0.3417862644568677
- 0.3402299958187535
- 0.3116408980465631
- 0.31900622847630045
- 0.31934151231927727
- 0.3186791563176499
- 0.32750328333726775
- 0.3510627418495332
- 0.33347506212887845
- 0.35025343435496104
- 0.3417862644568677
- 0.3402299958187535
- 0.3116408980465631
- 0.31900622847630045
- 0.31934151231927727
- 0.3186791563176499
- 0.32750328333726775
- 0.3510627418495332
- 0.33347506212887845
- 0.35025343435496104
- 0.3417862644568677
- 0.3402299958187535
- 0.3116408980465631
- 0.31900622847630045
- 0.31934151231927727
- 0.3186791563176499
- 0.32750328333726775
- 0.3510627418495332
- 0.33347506212887845
- 0.35025343435496104
- 0.3417862644568677
- 0.3402299958187535
- 0.3116408980465631
- 0.31900622847630045
- 0.31934151231927727
- 0.3186791563176499
- 0.32750328333726775
- 0.3510627418495332
- 0.33347506212887845
- 0.35025343435496104
- 0.3417862644568677
- 0.3402299958187535
- 0.3116408980465631
- 0.31900622847630045
- 0.31934151231927727
- 0.3186791563176499
- 0.32750328333726775
- 0.3510627418495332
- 0.33347506212887845
- 0.35025343435496104
- 0.3417862644568677
- 0.3402299958187535
- 0.3116408980465631
- 0.31900622847630045
- 0.31934151231927727
- 0.3186791563176499
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- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-s2s
name: MTEB MedrxivClusteringS2S
config: default
split: test
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
metrics:
- type: v_measure
value: 30.29367725266166
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- task:
type: Retrieval
dataset:
type: mteb/nfcorpus
name: MTEB NFCorpus
config: default
split: test
revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
metrics:
- type: map_at_1
value: 5.542
- type: map_at_10
value: 11.734
- type: map_at_100
value: 14.812
- type: map_at_1000
value: 16.184
- type: map_at_20
value: 13.045000000000002
- type: map_at_3
value: 8.859
- type: map_at_5
value: 10.162
- type: mrr_at_1
value: 43.963
- type: mrr_at_10
value: 51.914
- type: mrr_at_100
value: 52.422000000000004
- type: mrr_at_1000
value: 52.479
- type: mrr_at_20
value: 52.215
- type: mrr_at_3
value: 49.897000000000006
- type: mrr_at_5
value: 50.965
- type: ndcg_at_1
value: 42.105
- type: ndcg_at_10
value: 32.035000000000004
- type: ndcg_at_100
value: 29.487999999999996
- type: ndcg_at_1000
value: 38.316
- type: ndcg_at_20
value: 30.255
- type: ndcg_at_3
value: 37.098
- type: ndcg_at_5
value: 34.98
- type: precision_at_1
value: 43.344
- type: precision_at_10
value: 23.313
- type: precision_at_100
value: 7.591
- type: precision_at_1000
value: 2.023
- type: precision_at_20
value: 17.755000000000003
- type: precision_at_3
value: 33.745999999999995
- type: precision_at_5
value: 29.474
- type: recall_at_1
value: 5.542
- type: recall_at_10
value: 15.61
- type: recall_at_100
value: 29.413
- type: recall_at_1000
value: 61.926
- type: recall_at_20
value: 19.517
- type: recall_at_3
value: 9.669
- type: recall_at_5
value: 11.772
- task:
type: Retrieval
dataset:
type: mteb/nq
name: MTEB NQ
config: default
split: test
revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
metrics:
- type: map_at_1
value: 21.590999999999998
- type: map_at_10
value: 35.088
- type: map_at_100
value: 36.386
- type: map_at_1000
value: 36.439
- type: map_at_20
value: 35.93
- type: map_at_3
value: 30.985000000000003
- type: map_at_5
value: 33.322
- type: mrr_at_1
value: 24.189
- type: mrr_at_10
value: 37.395
- type: mrr_at_100
value: 38.449
- type: mrr_at_1000
value: 38.486
- type: mrr_at_20
value: 38.092999999999996
- type: mrr_at_3
value: 33.686
- type: mrr_at_5
value: 35.861
- type: ndcg_at_1
value: 24.189
- type: ndcg_at_10
value: 42.471
- type: ndcg_at_100
value: 48.150999999999996
- type: ndcg_at_1000
value: 49.342000000000006
- type: ndcg_at_20
value: 45.245000000000005
- type: ndcg_at_3
value: 34.483000000000004
- type: ndcg_at_5
value: 38.505
- type: precision_at_1
value: 24.189
- type: precision_at_10
value: 7.3870000000000005
- type: precision_at_100
value: 1.056
- type: precision_at_1000
value: 0.117
- type: precision_at_20
value: 4.35
- type: precision_at_3
value: 16.009999999999998
- type: precision_at_5
value: 11.883000000000001
- type: recall_at_1
value: 21.590999999999998
- type: recall_at_10
value: 62.79
- type: recall_at_100
value: 87.71
- type: recall_at_1000
value: 96.418
- type: recall_at_20
value: 73.042
- type: recall_at_3
value: 41.876999999999995
- type: recall_at_5
value: 51.205
- task:
type: Retrieval
dataset:
type: mteb/quora
name: MTEB QuoraRetrieval
config: default
split: test
revision: e4e08e0b7dbe3c8700f0daef558ff32256715259
metrics:
- type: map_at_1
value: 68.31099999999999
- type: map_at_10
value: 81.845
- type: map_at_100
value: 82.518
- type: map_at_1000
value: 82.541
- type: map_at_20
value: 82.292
- type: map_at_3
value: 78.827
- type: map_at_5
value: 80.715
- type: mrr_at_1
value: 78.62
- type: mrr_at_10
value: 85.42
- type: mrr_at_100
value: 85.54899999999999
- type: mrr_at_1000
value: 85.55
- type: mrr_at_20
value: 85.516
- type: mrr_at_3
value: 84.265
- type: mrr_at_5
value: 85.021
- type: ndcg_at_1
value: 78.63
- type: ndcg_at_10
value: 86.032
- type: ndcg_at_100
value: 87.50099999999999
- type: ndcg_at_1000
value: 87.67200000000001
- type: ndcg_at_20
value: 86.822
- type: ndcg_at_3
value: 82.813
- type: ndcg_at_5
value: 84.555
- type: precision_at_1
value: 78.63
- type: precision_at_10
value: 13.025999999999998
- type: precision_at_100
value: 1.504
- type: precision_at_1000
value: 0.156
- type: precision_at_20
value: 6.944999999999999
- type: precision_at_3
value: 36.013
- type: precision_at_5
value: 23.788
- type: recall_at_1
value: 68.31099999999999
- type: recall_at_10
value: 94.003
- type: recall_at_100
value: 99.11999999999999
- type: recall_at_1000
value: 99.923
- type: recall_at_20
value: 96.55799999999999
- type: recall_at_3
value: 84.836
- type: recall_at_5
value: 89.655
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering
name: MTEB RedditClustering
config: default
split: test
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
metrics:
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value: 47.52530454226057
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- task:
type: Clustering
dataset:
type: mteb/reddit-clustering-p2p
name: MTEB RedditClusteringP2P
config: default
split: test
revision: 385e3cb46b4cfa89021f56c4380204149d0efe33
metrics:
- type: v_measure
value: 56.028612066452
- type: v_measures
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- task:
type: Retrieval
dataset:
type: mteb/scidocs
name: MTEB SCIDOCS
config: default
split: test
revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88
metrics:
- type: map_at_1
value: 4.108
- type: map_at_10
value: 10.953
- type: map_at_100
value: 13.004
- type: map_at_1000
value: 13.303
- type: map_at_20
value: 12.004
- type: map_at_3
value: 7.754999999999999
- type: map_at_5
value: 9.19
- type: mrr_at_1
value: 20.200000000000003
- type: mrr_at_10
value: 31.069999999999997
- type: mrr_at_100
value: 32.222
- type: mrr_at_1000
value: 32.277
- type: mrr_at_20
value: 31.761
- type: mrr_at_3
value: 27.717000000000002
- type: mrr_at_5
value: 29.416999999999998
- type: ndcg_at_1
value: 20.200000000000003
- type: ndcg_at_10
value: 18.636
- type: ndcg_at_100
value: 26.442
- type: ndcg_at_1000
value: 31.828
- type: ndcg_at_20
value: 21.441
- type: ndcg_at_3
value: 17.323
- type: ndcg_at_5
value: 15.010000000000002
- type: precision_at_1
value: 20.200000000000003
- type: precision_at_10
value: 9.9
- type: precision_at_100
value: 2.106
- type: precision_at_1000
value: 0.33999999999999997
- type: precision_at_20
value: 6.575
- type: precision_at_3
value: 16.367
- type: precision_at_5
value: 13.200000000000001
- type: recall_at_1
value: 4.108
- type: recall_at_10
value: 20.052
- type: recall_at_100
value: 42.723
- type: recall_at_1000
value: 69.118
- type: recall_at_20
value: 26.662999999999997
- type: recall_at_3
value: 9.963
- type: recall_at_5
value: 13.377
- task:
type: STS
dataset:
type: mteb/sickr-sts
name: MTEB SICK-R
config: default
split: test
revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
metrics:
- type: cos_sim_pearson
value: 81.73133871784073
- type: cos_sim_spearman
value: 75.63155962642634
- type: euclidean_pearson
value: 78.84721858652286
- type: euclidean_spearman
value: 75.52150847464515
- type: manhattan_pearson
value: 78.65433033180727
- type: manhattan_spearman
value: 75.30995832884881
- task:
type: STS
dataset:
type: mteb/sts12-sts
name: MTEB STS12
config: default
split: test
revision: a0d554a64d88156834ff5ae9920b964011b16384
metrics:
- type: cos_sim_pearson
value: 75.66063073145264
- type: cos_sim_spearman
value: 68.58158236004101
- type: euclidean_pearson
value: 72.54019756825143
- type: euclidean_spearman
value: 69.05526621955067
- type: manhattan_pearson
value: 72.69442494173272
- type: manhattan_spearman
value: 69.24310689645435
- task:
type: STS
dataset:
type: mteb/sts13-sts
name: MTEB STS13
config: default
split: test
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
metrics:
- type: cos_sim_pearson
value: 79.93061145846976
- type: cos_sim_spearman
value: 80.54473705232682
- type: euclidean_pearson
value: 80.25598213392439
- type: euclidean_spearman
value: 80.57639468906437
- type: manhattan_pearson
value: 80.04739474388745
- type: manhattan_spearman
value: 80.35672978503159
- task:
type: STS
dataset:
type: mteb/sts14-sts
name: MTEB STS14
config: default
split: test
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
metrics:
- type: cos_sim_pearson
value: 80.63106651366024
- type: cos_sim_spearman
value: 77.628680514703
- type: euclidean_pearson
value: 79.88625241187461
- type: euclidean_spearman
value: 77.80535399731345
- type: manhattan_pearson
value: 79.78810133011544
- type: manhattan_spearman
value: 77.73028091841451
- task:
type: STS
dataset:
type: mteb/sts15-sts
name: MTEB STS15
config: default
split: test
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
metrics:
- type: cos_sim_pearson
value: 85.30832602658512
- type: cos_sim_spearman
value: 86.15687211744392
- type: euclidean_pearson
value: 85.94586990553746
- type: euclidean_spearman
value: 86.48157226860724
- type: manhattan_pearson
value: 85.88233798668581
- type: manhattan_spearman
value: 86.42359889540302
- task:
type: STS
dataset:
type: mteb/sts16-sts
name: MTEB STS16
config: default
split: test
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
metrics:
- type: cos_sim_pearson
value: 81.48207305822743
- type: cos_sim_spearman
value: 82.8229306585227
- type: euclidean_pearson
value: 82.3912454156615
- type: euclidean_spearman
value: 83.09865476559257
- type: manhattan_pearson
value: 82.30053520575876
- type: manhattan_spearman
value: 83.00392320200139
- task:
type: STS
dataset:
type: mteb/sts17-crosslingual-sts
name: MTEB STS17 (en-en)
config: en-en
split: test
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
metrics:
- type: cos_sim_pearson
value: 87.83517082969622
- type: cos_sim_spearman
value: 88.5704237984555
- type: euclidean_pearson
value: 88.15443024833176
- type: euclidean_spearman
value: 88.60313594495189
- type: manhattan_pearson
value: 87.99012996276818
- type: manhattan_spearman
value: 88.39306322978999
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (en)
config: en
split: test
revision: eea2b4fe26a775864c896887d910b76a8098ad3f
metrics:
- type: cos_sim_pearson
value: 67.62856734038614
- type: cos_sim_spearman
value: 67.38775280429276
- type: euclidean_pearson
value: 68.09416503472238
- type: euclidean_spearman
value: 67.45221088834498
- type: manhattan_pearson
value: 68.31811474137709
- type: manhattan_spearman
value: 67.75846817406287
- task:
type: STS
dataset:
type: mteb/stsbenchmark-sts
name: MTEB STSBenchmark
config: default
split: test
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
metrics:
- type: cos_sim_pearson
value: 84.13302836216701
- type: cos_sim_spearman
value: 84.24952159575491
- type: euclidean_pearson
value: 84.65017899273384
- type: euclidean_spearman
value: 84.43303793097236
- type: manhattan_pearson
value: 84.55589549879238
- type: manhattan_spearman
value: 84.42827667887977
- task:
type: Reranking
dataset:
type: mteb/scidocs-reranking
name: MTEB SciDocsRR
config: default
split: test
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
metrics:
- type: map
value: 80.03616790601166
- type: mrr
value: 94.31135132115524
- task:
type: Retrieval
dataset:
type: mteb/scifact
name: MTEB SciFact
config: default
split: test
revision: 0228b52cf27578f30900b9e5271d331663a030d7
metrics:
- type: map_at_1
value: 51.678000000000004
- type: map_at_10
value: 62.011
- type: map_at_100
value: 62.443000000000005
- type: map_at_1000
value: 62.468999999999994
- type: map_at_20
value: 62.226000000000006
- type: map_at_3
value: 58.443999999999996
- type: map_at_5
value: 60.550000000000004
- type: mrr_at_1
value: 54
- type: mrr_at_10
value: 63.27199999999999
- type: mrr_at_100
value: 63.596
- type: mrr_at_1000
value: 63.619
- type: mrr_at_20
value: 63.416
- type: mrr_at_3
value: 60.5
- type: mrr_at_5
value: 62.283
- type: ndcg_at_1
value: 54
- type: ndcg_at_10
value: 67.315
- type: ndcg_at_100
value: 69.372
- type: ndcg_at_1000
value: 70.15400000000001
- type: ndcg_at_20
value: 67.943
- type: ndcg_at_3
value: 61.121
- type: ndcg_at_5
value: 64.399
- type: precision_at_1
value: 54
- type: precision_at_10
value: 9.232999999999999
- type: precision_at_100
value: 1.047
- type: precision_at_1000
value: 0.11100000000000002
- type: precision_at_20
value: 4.7829999999999995
- type: precision_at_3
value: 23.666999999999998
- type: precision_at_5
value: 16.2
- type: recall_at_1
value: 51.678000000000004
- type: recall_at_10
value: 82.389
- type: recall_at_100
value: 92
- type: recall_at_1000
value: 98.333
- type: recall_at_20
value: 84.63300000000001
- type: recall_at_3
value: 66.05
- type: recall_at_5
value: 74.006
- task:
type: PairClassification
dataset:
type: mteb/sprintduplicatequestions-pairclassification
name: MTEB SprintDuplicateQuestions
config: default
split: test
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
metrics:
- type: cos_sim_accuracy
value: 99.82673267326733
- type: cos_sim_ap
value: 95.11999931294784
- type: cos_sim_f1
value: 91.0941475826972
- type: cos_sim_precision
value: 92.74611398963731
- type: cos_sim_recall
value: 89.5
- type: dot_accuracy
value: 99.73861386138614
- type: dot_ap
value: 92.76208671816435
- type: dot_f1
value: 86.5055387713998
- type: dot_precision
value: 87.11967545638946
- type: dot_recall
value: 85.9
- type: euclidean_accuracy
value: 99.82376237623762
- type: euclidean_ap
value: 95.02471241011084
- type: euclidean_f1
value: 90.97363083164299
- type: euclidean_precision
value: 92.28395061728395
- type: euclidean_recall
value: 89.7
- type: manhattan_accuracy
value: 99.82574257425742
- type: manhattan_ap
value: 95.08424842231868
- type: manhattan_f1
value: 91.10212335692619
- type: manhattan_precision
value: 92.12678936605317
- type: manhattan_recall
value: 90.10000000000001
- type: max_accuracy
value: 99.82673267326733
- type: max_ap
value: 95.11999931294784
- type: max_f1
value: 91.10212335692619
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering
name: MTEB StackExchangeClustering
config: default
split: test
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
metrics:
- type: v_measure
value: 53.870949746768424
- type: v_measures
value:
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- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering-p2p
name: MTEB StackExchangeClusteringP2P
config: default
split: test
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
metrics:
- type: v_measure
value: 33.56703823226784
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- task:
type: Reranking
dataset:
type: mteb/stackoverflowdupquestions-reranking
name: MTEB StackOverflowDupQuestions
config: default
split: test
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
metrics:
- type: map
value: 49.82873266157383
- type: mrr
value: 50.652096065699006
- task:
type: Summarization
dataset:
type: mteb/summeval
name: MTEB SummEval
config: default
split: test
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
metrics:
- type: cos_sim_pearson
value: 31.35739606124227
- type: cos_sim_spearman
value: 31.26775311472305
- type: dot_pearson
value: 29.421400993418278
- type: dot_spearman
value: 30.180472594773534
- task:
type: Retrieval
dataset:
type: mteb/trec-covid
name: MTEB TRECCOVID
config: default
split: test
revision: bb9466bac8153a0349341eb1b22e06409e78ef4e
metrics:
- type: map_at_1
value: 0.184
- type: map_at_10
value: 1.398
- type: map_at_100
value: 7.2090000000000005
- type: map_at_1000
value: 18.414
- type: map_at_20
value: 2.414
- type: map_at_3
value: 0.509
- type: map_at_5
value: 0.767
- type: mrr_at_1
value: 72
- type: mrr_at_10
value: 80.467
- type: mrr_at_100
value: 80.735
- type: mrr_at_1000
value: 80.735
- type: mrr_at_20
value: 80.735
- type: mrr_at_3
value: 79
- type: mrr_at_5
value: 79.80000000000001
- type: ndcg_at_1
value: 68
- type: ndcg_at_10
value: 60.324
- type: ndcg_at_100
value: 43.866
- type: ndcg_at_1000
value: 41.932
- type: ndcg_at_20
value: 56.013999999999996
- type: ndcg_at_3
value: 66.458
- type: ndcg_at_5
value: 63.048
- type: precision_at_1
value: 72
- type: precision_at_10
value: 64.2
- type: precision_at_100
value: 44.56
- type: precision_at_1000
value: 18.736
- type: precision_at_20
value: 59
- type: precision_at_3
value: 72
- type: precision_at_5
value: 67.2
- type: recall_at_1
value: 0.184
- type: recall_at_10
value: 1.649
- type: recall_at_100
value: 10.659
- type: recall_at_1000
value: 40.424
- type: recall_at_20
value: 3.0349999999999997
- type: recall_at_3
value: 0.5519999999999999
- type: recall_at_5
value: 0.852
- task:
type: Retrieval
dataset:
type: mteb/touche2020
name: MTEB Touche2020
config: default
split: test
revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
metrics:
- type: map_at_1
value: 1.252
- type: map_at_10
value: 8.029
- type: map_at_100
value: 13.504
- type: map_at_1000
value: 15.013000000000002
- type: map_at_20
value: 10.306
- type: map_at_3
value: 3.372
- type: map_at_5
value: 4.923
- type: mrr_at_1
value: 18.367
- type: mrr_at_10
value: 36.612
- type: mrr_at_100
value: 37.345
- type: mrr_at_1000
value: 37.345
- type: mrr_at_20
value: 36.955
- type: mrr_at_3
value: 32.993
- type: mrr_at_5
value: 33.912
- type: ndcg_at_1
value: 16.326999999999998
- type: ndcg_at_10
value: 21.124000000000002
- type: ndcg_at_100
value: 32.635
- type: ndcg_at_1000
value: 43.993
- type: ndcg_at_20
value: 22.429
- type: ndcg_at_3
value: 20.836
- type: ndcg_at_5
value: 20.437
- type: precision_at_1
value: 18.367
- type: precision_at_10
value: 21.02
- type: precision_at_100
value: 7.245
- type: precision_at_1000
value: 1.473
- type: precision_at_20
value: 15.714
- type: precision_at_3
value: 23.128999999999998
- type: precision_at_5
value: 22.448999999999998
- type: recall_at_1
value: 1.252
- type: recall_at_10
value: 15.312999999999999
- type: recall_at_100
value: 44.908
- type: recall_at_1000
value: 79.396
- type: recall_at_20
value: 22.647000000000002
- type: recall_at_3
value: 4.883
- type: recall_at_5
value: 7.917000000000001
- task:
type: Classification
dataset:
type: mteb/toxic_conversations_50k
name: MTEB ToxicConversationsClassification
config: default
split: test
revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
metrics:
- type: accuracy
value: 65.458984375
- type: ap
value: 12.013147326225168
- type: f1
value: 50.30981581053394
- task:
type: Classification
dataset:
type: mteb/tweet_sentiment_extraction
name: MTEB TweetSentimentExtractionClassification
config: default
split: test
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
metrics:
- type: accuracy
value: 58.658743633276735
- type: f1
value: 59.01001910848807
- task:
type: Clustering
dataset:
type: mteb/twentynewsgroups-clustering
name: MTEB TwentyNewsgroupsClustering
config: default
split: test
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
metrics:
- type: v_measure
value: 40.7719980016582
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- task:
type: PairClassification
dataset:
type: mteb/twittersemeval2015-pairclassification
name: MTEB TwitterSemEval2015
config: default
split: test
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
metrics:
- type: cos_sim_accuracy
value: 84.71717231924659
- type: cos_sim_ap
value: 69.78325722226528
- type: cos_sim_f1
value: 66.23786691615015
- type: cos_sim_precision
value: 59.483301827347205
- type: cos_sim_recall
value: 74.72295514511873
- type: dot_accuracy
value: 81.95148119449246
- type: dot_ap
value: 60.71125646179137
- type: dot_f1
value: 58.44781026182928
- type: dot_precision
value: 52.65496086312672
- type: dot_recall
value: 65.67282321899735
- type: euclidean_accuracy
value: 84.84830422602371
- type: euclidean_ap
value: 69.97192936786296
- type: euclidean_f1
value: 66.53649011471808
- type: euclidean_precision
value: 61.898274296094456
- type: euclidean_recall
value: 71.92612137203166
- type: manhattan_accuracy
value: 84.75889610776659
- type: manhattan_ap
value: 69.75691180376053
- type: manhattan_f1
value: 66.32788868723533
- type: manhattan_precision
value: 61.2513966480447
- type: manhattan_recall
value: 72.32189973614776
- type: max_accuracy
value: 84.84830422602371
- type: max_ap
value: 69.97192936786296
- type: max_f1
value: 66.53649011471808
- task:
type: PairClassification
dataset:
type: mteb/twitterurlcorpus-pairclassification
name: MTEB TwitterURLCorpus
config: default
split: test
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
metrics:
- type: cos_sim_accuracy
value: 88.43287926417511
- type: cos_sim_ap
value: 85.07378179191598
- type: cos_sim_f1
value: 77.50230244980658
- type: cos_sim_precision
value: 74.30246521155613
- type: cos_sim_recall
value: 80.99014474899907
- type: dot_accuracy
value: 86.946481934257
- type: dot_ap
value: 80.90485630835825
- type: dot_f1
value: 74.43342263413221
- type: dot_precision
value: 70.24736914035807
- type: dot_recall
value: 79.1499846011703
- type: euclidean_accuracy
value: 88.49303372530757
- type: euclidean_ap
value: 85.08920672765427
- type: euclidean_f1
value: 77.53514807059526
- type: euclidean_precision
value: 75.3707473102646
- type: euclidean_recall
value: 79.82753310748383
- type: manhattan_accuracy
value: 88.47168859393798
- type: manhattan_ap
value: 85.01816084029292
- type: manhattan_f1
value: 77.36513181524315
- type: manhattan_precision
value: 72.5057223643463
- type: manhattan_recall
value: 82.9226978749615
- type: max_accuracy
value: 88.49303372530757
- type: max_ap
value: 85.08920672765427
- type: max_f1
value: 77.53514807059526
Ivysaur
This is a fine-tune of gte-tiny using qa-assistant.
Intended purpose
This model is designed for use in semantic-autocomplete (click here for demo).
Usage (Sentence-Transformers) (same as gte-tiny)
Using this model becomes easy when you have sentence-transformers installed:
pip install -U sentence-transformers
Then you can use the model like this:
from sentence_transformers import SentenceTransformer
sentences = ["This is an example sentence", "Each sentence is converted"]
model = SentenceTransformer('Mihaiii/Ivysaur')
embeddings = model.encode(sentences)
print(embeddings)
Usage (HuggingFace Transformers) (same as gte-tiny)
Without sentence-transformers, you can use the model like this: First, you pass your input through the transformer model, then you have to apply the right pooling-operation on-top of the contextualized word embeddings.
from transformers import AutoTokenizer, AutoModel
import torch
#Mean Pooling - Take attention mask into account for correct averaging
def mean_pooling(model_output, attention_mask):
token_embeddings = model_output[0] #First element of model_output contains all token embeddings
input_mask_expanded = attention_mask.unsqueeze(-1).expand(token_embeddings.size()).float()
return torch.sum(token_embeddings * input_mask_expanded, 1) / torch.clamp(input_mask_expanded.sum(1), min=1e-9)
# Sentences we want sentence embeddings for
sentences = ['This is an example sentence', 'Each sentence is converted']
# Load model from HuggingFace Hub
tokenizer = AutoTokenizer.from_pretrained('Mihaiii/Ivysaur')
model = AutoModel.from_pretrained('Mihaiii/Ivysaur')
# Tokenize sentences
encoded_input = tokenizer(sentences, padding=True, truncation=True, return_tensors='pt')
# Compute token embeddings
with torch.no_grad():
model_output = model(**encoded_input)
# Perform pooling. In this case, mean pooling.
sentence_embeddings = mean_pooling(model_output, encoded_input['attention_mask'])
print("Sentence embeddings:")
print(sentence_embeddings)
Limitation (same as gte-small)
This model exclusively caters to English texts, and any lengthy texts will be truncated to a maximum of 512 tokens.