| ---
|
| tags:
|
| - mteb
|
| model-index:
|
| - name: Solon-embeddings-large-0.1
|
| results:
|
| - task:
|
| type: sentence-similarity
|
| name: Passage Retrieval
|
| dataset:
|
| type: unicamp-dl/mmarco
|
| name: mMARCO-fr
|
| config: french
|
| split: validation
|
| metrics:
|
| - type: recall_at_500
|
| name: Recall@500
|
| value: 92.7
|
| - type: recall_at_100
|
| name: Recall@100
|
| value: 82.7
|
| - type: recall_at_10
|
| name: Recall@10
|
| value: 55.5
|
| - type: map_at_10
|
| name: MAP@10
|
| value: 29.4
|
| - type: ndcg_at_10
|
| name: nDCG@10
|
| value: 35.8
|
| - type: mrr_at_10
|
| name: MRR@10
|
| value: 29.9
|
| - task:
|
| type: Clustering
|
| dataset:
|
| type: lyon-nlp/alloprof
|
| name: MTEB AlloProfClusteringP2P
|
| config: default
|
| split: test
|
| revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b
|
| metrics:
|
| - type: v_measure
|
| value: 64.16942168287153
|
| - task:
|
| type: Clustering
|
| dataset:
|
| type: lyon-nlp/alloprof
|
| name: MTEB AlloProfClusteringS2S
|
| config: default
|
| split: test
|
| revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b
|
| metrics:
|
| - type: v_measure
|
| value: 38.17076313383054
|
| - task:
|
| type: Reranking
|
| dataset:
|
| type: lyon-nlp/mteb-fr-reranking-alloprof-s2p
|
| name: MTEB AlloprofReranking
|
| config: default
|
| split: test
|
| revision: 666fdacebe0291776e86f29345663dfaf80a0db9
|
| metrics:
|
| - type: map
|
| value: 64.8770878097632
|
| - type: mrr
|
| value: 66.39132423169396
|
| - task:
|
| type: Retrieval
|
| dataset:
|
| type: lyon-nlp/alloprof
|
| name: MTEB AlloprofRetrieval
|
| config: default
|
| split: test
|
| revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b
|
| metrics:
|
| - type: map_at_1
|
| value: 29.62
|
| - type: map_at_10
|
| value: 40.963
|
| - type: map_at_100
|
| value: 41.894
|
| - type: map_at_1000
|
| value: 41.939
|
| - type: map_at_3
|
| value: 37.708999999999996
|
| - type: map_at_5
|
| value: 39.696999999999996
|
| - type: mrr_at_1
|
| value: 29.62
|
| - type: mrr_at_10
|
| value: 40.963
|
| - type: mrr_at_100
|
| value: 41.894
|
| - type: mrr_at_1000
|
| value: 41.939
|
| - type: mrr_at_3
|
| value: 37.708999999999996
|
| - type: mrr_at_5
|
| value: 39.696999999999996
|
| - type: ndcg_at_1
|
| value: 29.62
|
| - type: ndcg_at_10
|
| value: 46.942
|
| - type: ndcg_at_100
|
| value: 51.629999999999995
|
| - type: ndcg_at_1000
|
| value: 52.927
|
| - type: ndcg_at_3
|
| value: 40.333999999999996
|
| - type: ndcg_at_5
|
| value: 43.922
|
| - type: precision_at_1
|
| value: 29.62
|
| - type: precision_at_10
|
| value: 6.589
|
| - type: precision_at_100
|
| value: 0.882
|
| - type: precision_at_1000
|
| value: 0.099
|
| - type: precision_at_3
|
| value: 15.976
|
| - type: precision_at_5
|
| value: 11.33
|
| - type: recall_at_1
|
| value: 29.62
|
| - type: recall_at_10
|
| value: 65.889
|
| - type: recall_at_100
|
| value: 88.212
|
| - type: recall_at_1000
|
| value: 98.575
|
| - type: recall_at_3
|
| value: 47.927
|
| - type: recall_at_5
|
| value: 56.64900000000001
|
| - task:
|
| type: Classification
|
| dataset:
|
| type: mteb/amazon_reviews_multi
|
| name: MTEB AmazonReviewsClassification (fr)
|
| config: fr
|
| split: test
|
| revision: 1399c76144fd37290681b995c656ef9b2e06e26d
|
| metrics:
|
| - type: accuracy
|
| value: 42.077999999999996
|
| - type: f1
|
| value: 40.64511241732637
|
| - task:
|
| type: Retrieval
|
| dataset:
|
| type: maastrichtlawtech/bsard
|
| name: MTEB BSARDRetrieval
|
| config: default
|
| split: test
|
| revision: 5effa1b9b5fa3b0f9e12523e6e43e5f86a6e6d59
|
| metrics:
|
| - type: map_at_1
|
| value: 0.901
|
| - type: map_at_10
|
| value: 1.524
|
| - type: map_at_100
|
| value: 1.833
|
| - type: map_at_1000
|
| value: 1.916
|
| - type: map_at_3
|
| value: 1.276
|
| - type: map_at_5
|
| value: 1.276
|
| - type: mrr_at_1
|
| value: 0.901
|
| - type: mrr_at_10
|
| value: 1.524
|
| - type: mrr_at_100
|
| value: 1.833
|
| - type: mrr_at_1000
|
| value: 1.916
|
| - type: mrr_at_3
|
| value: 1.276
|
| - type: mrr_at_5
|
| value: 1.276
|
| - type: ndcg_at_1
|
| value: 0.901
|
| - type: ndcg_at_10
|
| value: 2.085
|
| - type: ndcg_at_100
|
| value: 3.805
|
| - type: ndcg_at_1000
|
| value: 6.704000000000001
|
| - type: ndcg_at_3
|
| value: 1.41
|
| - type: ndcg_at_5
|
| value: 1.41
|
| - type: precision_at_1
|
| value: 0.901
|
| - type: precision_at_10
|
| value: 0.40499999999999997
|
| - type: precision_at_100
|
| value: 0.126
|
| - type: precision_at_1000
|
| value: 0.037
|
| - type: precision_at_3
|
| value: 0.601
|
| - type: precision_at_5
|
| value: 0.36
|
| - type: recall_at_1
|
| value: 0.901
|
| - type: recall_at_10
|
| value: 4.054
|
| - type: recall_at_100
|
| value: 12.613
|
| - type: recall_at_1000
|
| value: 36.937
|
| - type: recall_at_3
|
| value: 1.802
|
| - type: recall_at_5
|
| value: 1.802
|
| - task:
|
| type: BitextMining
|
| dataset:
|
| type: rbawden/DiaBLa
|
| name: MTEB DiaBLaBitextMining (fr-en)
|
| config: fr-en
|
| split: test
|
| revision: 5345895c56a601afe1a98519ce3199be60a27dba
|
| metrics:
|
| - type: accuracy
|
| value: 88.90048712595686
|
| - type: f1
|
| value: 86.94952864886115
|
| - type: precision
|
| value: 86.20344379175826
|
| - type: recall
|
| value: 88.90048712595686
|
| - task:
|
| type: Clustering
|
| dataset:
|
| type: lyon-nlp/clustering-hal-s2s
|
| name: MTEB HALClusteringS2S
|
| config: default
|
| split: test
|
| revision: e06ebbbb123f8144bef1a5d18796f3dec9ae2915
|
| metrics:
|
| - type: v_measure
|
| value: 24.087988843991155
|
| - task:
|
| type: Clustering
|
| dataset:
|
| type: mlsum
|
| name: MTEB MLSUMClusteringP2P
|
| config: default
|
| split: test
|
| revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7
|
| metrics:
|
| - type: v_measure
|
| value: 43.79603865728535
|
| - task:
|
| type: Clustering
|
| dataset:
|
| type: mlsum
|
| name: MTEB MLSUMClusteringS2S
|
| config: default
|
| split: test
|
| revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7
|
| metrics:
|
| - type: v_measure
|
| value: 37.746550373003
|
| - task:
|
| type: Classification
|
| dataset:
|
| type: mteb/mtop_domain
|
| name: MTEB MTOPDomainClassification (fr)
|
| config: fr
|
| split: test
|
| revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
|
| metrics:
|
| - type: accuracy
|
| value: 89.26088318196052
|
| - type: f1
|
| value: 88.95811185929033
|
| - task:
|
| type: Classification
|
| dataset:
|
| type: mteb/mtop_intent
|
| name: MTEB MTOPIntentClassification (fr)
|
| config: fr
|
| split: test
|
| revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
|
| metrics:
|
| - type: accuracy
|
| value: 68.55308487316003
|
| - type: f1
|
| value: 48.2936682439785
|
| - task:
|
| type: Classification
|
| dataset:
|
| type: masakhane/masakhanews
|
| name: MTEB MasakhaNEWSClassification (fra)
|
| config: fra
|
| split: test
|
| revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
|
| metrics:
|
| - type: accuracy
|
| value: 81.51658767772511
|
| - type: f1
|
| value: 77.695234448912
|
| - task:
|
| type: Clustering
|
| dataset:
|
| type: masakhane/masakhanews
|
| name: MTEB MasakhaNEWSClusteringP2P (fra)
|
| config: fra
|
| split: test
|
| revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
|
| metrics:
|
| - type: v_measure
|
| value: 40.80377094681114
|
| - task:
|
| type: Clustering
|
| dataset:
|
| type: masakhane/masakhanews
|
| name: MTEB MasakhaNEWSClusteringS2S (fra)
|
| config: fra
|
| split: test
|
| revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
|
| metrics:
|
| - type: v_measure
|
| value: 28.79703837416241
|
| - task:
|
| type: Classification
|
| dataset:
|
| type: mteb/amazon_massive_intent
|
| name: MTEB MassiveIntentClassification (fr)
|
| config: fr
|
| split: test
|
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
|
| metrics:
|
| - type: accuracy
|
| value: 67.40080699394755
|
| - type: f1
|
| value: 65.60793135686376
|
| - task:
|
| type: Classification
|
| dataset:
|
| type: mteb/amazon_massive_scenario
|
| name: MTEB MassiveScenarioClassification (fr)
|
| config: fr
|
| split: test
|
| revision: 7d571f92784cd94a019292a1f45445077d0ef634
|
| metrics:
|
| - type: accuracy
|
| value: 71.29455279085406
|
| - type: f1
|
| value: 70.80876673828983
|
| - task:
|
| type: Retrieval
|
| dataset:
|
| type: jinaai/mintakaqa
|
| name: MTEB MintakaRetrieval (fr)
|
| config: fr
|
| split: test
|
| revision: efa78cc2f74bbcd21eff2261f9e13aebe40b814e
|
| metrics:
|
| - type: map_at_1
|
| value: 16.625999999999998
|
| - type: map_at_10
|
| value: 25.224999999999998
|
| - type: map_at_100
|
| value: 26.291999999999998
|
| - type: map_at_1000
|
| value: 26.395000000000003
|
| - type: map_at_3
|
| value: 22.378999999999998
|
| - type: map_at_5
|
| value: 24.009
|
| - type: mrr_at_1
|
| value: 16.625999999999998
|
| - type: mrr_at_10
|
| value: 25.224999999999998
|
| - type: mrr_at_100
|
| value: 26.291999999999998
|
| - type: mrr_at_1000
|
| value: 26.395000000000003
|
| - type: mrr_at_3
|
| value: 22.378999999999998
|
| - type: mrr_at_5
|
| value: 24.009
|
| - type: ndcg_at_1
|
| value: 16.625999999999998
|
| - type: ndcg_at_10
|
| value: 30.074
|
| - type: ndcg_at_100
|
| value: 35.683
|
| - type: ndcg_at_1000
|
| value: 38.714999999999996
|
| - type: ndcg_at_3
|
| value: 24.188000000000002
|
| - type: ndcg_at_5
|
| value: 27.124
|
| - type: precision_at_1
|
| value: 16.625999999999998
|
| - type: precision_at_10
|
| value: 4.566
|
| - type: precision_at_100
|
| value: 0.729
|
| - type: precision_at_1000
|
| value: 0.097
|
| - type: precision_at_3
|
| value: 9.801
|
| - type: precision_at_5
|
| value: 7.305000000000001
|
| - type: recall_at_1
|
| value: 16.625999999999998
|
| - type: recall_at_10
|
| value: 45.659
|
| - type: recall_at_100
|
| value: 72.85000000000001
|
| - type: recall_at_1000
|
| value: 97.42
|
| - type: recall_at_3
|
| value: 29.402
|
| - type: recall_at_5
|
| value: 36.527
|
| - task:
|
| type: PairClassification
|
| dataset:
|
| type: GEM/opusparcus
|
| name: MTEB OpusparcusPC (fr)
|
| config: fr
|
| split: test
|
| revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
|
| metrics:
|
| - type: cos_sim_accuracy
|
| value: 83.58310626702998
|
| - type: cos_sim_ap
|
| value: 94.01979957812989
|
| - type: cos_sim_f1
|
| value: 88.70135958743555
|
| - type: cos_sim_precision
|
| value: 84.01420959147424
|
| - type: cos_sim_recall
|
| value: 93.94240317775571
|
| - type: dot_accuracy
|
| value: 83.58310626702998
|
| - type: dot_ap
|
| value: 94.01979957812989
|
| - type: dot_f1
|
| value: 88.70135958743555
|
| - type: dot_precision
|
| value: 84.01420959147424
|
| - type: dot_recall
|
| value: 93.94240317775571
|
| - type: euclidean_accuracy
|
| value: 83.58310626702998
|
| - type: euclidean_ap
|
| value: 94.01979957812989
|
| - type: euclidean_f1
|
| value: 88.70135958743555
|
| - type: euclidean_precision
|
| value: 84.01420959147424
|
| - type: euclidean_recall
|
| value: 93.94240317775571
|
| - type: manhattan_accuracy
|
| value: 83.58310626702998
|
| - type: manhattan_ap
|
| value: 93.99936024003892
|
| - type: manhattan_f1
|
| value: 88.6924150767799
|
| - type: manhattan_precision
|
| value: 83.45008756567425
|
| - type: manhattan_recall
|
| value: 94.63753723932473
|
| - type: max_accuracy
|
| value: 83.58310626702998
|
| - type: max_ap
|
| value: 94.01979957812989
|
| - type: max_f1
|
| value: 88.70135958743555
|
| - task:
|
| type: PairClassification
|
| dataset:
|
| type: paws-x
|
| name: MTEB PawsX (fr)
|
| config: fr
|
| split: test
|
| revision: 8a04d940a42cd40658986fdd8e3da561533a3646
|
| metrics:
|
| - type: cos_sim_accuracy
|
| value: 60.6
|
| - type: cos_sim_ap
|
| value: 60.18915797975459
|
| - type: cos_sim_f1
|
| value: 62.491349480968864
|
| - type: cos_sim_precision
|
| value: 45.44539506794162
|
| - type: cos_sim_recall
|
| value: 100
|
| - type: dot_accuracy
|
| value: 60.6
|
| - type: dot_ap
|
| value: 60.091135216056024
|
| - type: dot_f1
|
| value: 62.491349480968864
|
| - type: dot_precision
|
| value: 45.44539506794162
|
| - type: dot_recall
|
| value: 100
|
| - type: euclidean_accuracy
|
| value: 60.6
|
| - type: euclidean_ap
|
| value: 60.18915797975459
|
| - type: euclidean_f1
|
| value: 62.491349480968864
|
| - type: euclidean_precision
|
| value: 45.44539506794162
|
| - type: euclidean_recall
|
| value: 100
|
| - type: manhattan_accuracy
|
| value: 60.650000000000006
|
| - type: manhattan_ap
|
| value: 60.2082343915352
|
| - type: manhattan_f1
|
| value: 62.491349480968864
|
| - type: manhattan_precision
|
| value: 45.44539506794162
|
| - type: manhattan_recall
|
| value: 100
|
| - type: max_accuracy
|
| value: 60.650000000000006
|
| - type: max_ap
|
| value: 60.2082343915352
|
| - type: max_f1
|
| value: 62.491349480968864
|
| - task:
|
| type: STS
|
| dataset:
|
| type: Lajavaness/SICK-fr
|
| name: MTEB SICKFr
|
| config: default
|
| split: test
|
| revision: e077ab4cf4774a1e36d86d593b150422fafd8e8a
|
| metrics:
|
| - type: cos_sim_pearson
|
| value: 79.77067200230256
|
| - type: cos_sim_spearman
|
| value: 76.7445532523278
|
| - type: euclidean_pearson
|
| value: 76.34017074673956
|
| - type: euclidean_spearman
|
| value: 76.7453011027832
|
| - type: manhattan_pearson
|
| value: 76.19578084197778
|
| - type: manhattan_spearman
|
| value: 76.56293456459228
|
| - task:
|
| type: STS
|
| dataset:
|
| type: mteb/sts22-crosslingual-sts
|
| name: MTEB STS22 (fr)
|
| config: fr
|
| split: test
|
| revision: eea2b4fe26a775864c896887d910b76a8098ad3f
|
| metrics:
|
| - type: cos_sim_pearson
|
| value: 81.2564160237984
|
| - type: cos_sim_spearman
|
| value: 83.30552085410882
|
| - type: euclidean_pearson
|
| value: 82.00494560507786
|
| - type: euclidean_spearman
|
| value: 83.30552085410882
|
| - type: manhattan_pearson
|
| value: 81.93132229157803
|
| - type: manhattan_spearman
|
| value: 83.04357992939353
|
| - task:
|
| type: STS
|
| dataset:
|
| type: stsb_multi_mt
|
| name: MTEB STSBenchmarkMultilingualSTS (fr)
|
| config: fr
|
| split: test
|
| revision: 93d57ef91790589e3ce9c365164337a8a78b7632
|
| metrics:
|
| - type: cos_sim_pearson
|
| value: 80.34931905288978
|
| - type: cos_sim_spearman
|
| value: 79.99372771100049
|
| - type: euclidean_pearson
|
| value: 78.37976845123443
|
| - type: euclidean_spearman
|
| value: 79.99452356550658
|
| - type: manhattan_pearson
|
| value: 78.24434042082316
|
| - type: manhattan_spearman
|
| value: 79.87248340061164
|
| - task:
|
| type: Summarization
|
| dataset:
|
| type: lyon-nlp/summarization-summeval-fr-p2p
|
| name: MTEB SummEvalFr
|
| config: default
|
| split: test
|
| revision: b385812de6a9577b6f4d0f88c6a6e35395a94054
|
| metrics:
|
| - type: cos_sim_pearson
|
| value: 30.476001473421586
|
| - type: cos_sim_spearman
|
| value: 29.687350195905456
|
| - type: dot_pearson
|
| value: 30.476000875190685
|
| - type: dot_spearman
|
| value: 29.662224660056562
|
| - task:
|
| type: Reranking
|
| dataset:
|
| type: lyon-nlp/mteb-fr-reranking-syntec-s2p
|
| name: MTEB SyntecReranking
|
| config: default
|
| split: test
|
| revision: b205c5084a0934ce8af14338bf03feb19499c84d
|
| metrics:
|
| - type: map
|
| value: 88.28333333333333
|
| - type: mrr
|
| value: 88.28333333333333
|
| - task:
|
| type: Retrieval
|
| dataset:
|
| type: lyon-nlp/mteb-fr-retrieval-syntec-s2p
|
| name: MTEB SyntecRetrieval
|
| config: default
|
| split: test
|
| revision: 77f7e271bf4a92b24fce5119f3486b583ca016ff
|
| metrics:
|
| - type: map_at_1
|
| value: 69
|
| - type: map_at_10
|
| value: 79.906
|
| - type: map_at_100
|
| value: 79.982
|
| - type: map_at_1000
|
| value: 79.982
|
| - type: map_at_3
|
| value: 77.667
|
| - type: map_at_5
|
| value: 79.51700000000001
|
| - type: mrr_at_1
|
| value: 69
|
| - type: mrr_at_10
|
| value: 79.906
|
| - type: mrr_at_100
|
| value: 79.982
|
| - type: mrr_at_1000
|
| value: 79.982
|
| - type: mrr_at_3
|
| value: 77.667
|
| - type: mrr_at_5
|
| value: 79.51700000000001
|
| - type: ndcg_at_1
|
| value: 69
|
| - type: ndcg_at_10
|
| value: 84.60499999999999
|
| - type: ndcg_at_100
|
| value: 84.868
|
| - type: ndcg_at_1000
|
| value: 84.868
|
| - type: ndcg_at_3
|
| value: 80.333
|
| - type: ndcg_at_5
|
| value: 83.647
|
| - type: precision_at_1
|
| value: 69
|
| - type: precision_at_10
|
| value: 9.9
|
| - type: precision_at_100
|
| value: 1
|
| - type: precision_at_1000
|
| value: 0.1
|
| - type: precision_at_3
|
| value: 29.333
|
| - type: precision_at_5
|
| value: 19.2
|
| - type: recall_at_1
|
| value: 69
|
| - type: recall_at_10
|
| value: 99
|
| - type: recall_at_100
|
| value: 100
|
| - type: recall_at_1000
|
| value: 100
|
| - type: recall_at_3
|
| value: 88
|
| - type: recall_at_5
|
| value: 96
|
| - task:
|
| type: Retrieval
|
| dataset:
|
| type: jinaai/xpqa
|
| name: MTEB XPQARetrieval (fr)
|
| config: fr
|
| split: test
|
| revision: c99d599f0a6ab9b85b065da6f9d94f9cf731679f
|
| metrics:
|
| - type: map_at_1
|
| value: 42.027
|
| - type: map_at_10
|
| value: 64.331
|
| - type: map_at_100
|
| value: 65.657
|
| - type: map_at_1000
|
| value: 65.7
|
| - type: map_at_3
|
| value: 57.967999999999996
|
| - type: map_at_5
|
| value: 62.33800000000001
|
| - type: mrr_at_1
|
| value: 65.688
|
| - type: mrr_at_10
|
| value: 72.263
|
| - type: mrr_at_100
|
| value: 72.679
|
| - type: mrr_at_1000
|
| value: 72.69099999999999
|
| - type: mrr_at_3
|
| value: 70.405
|
| - type: mrr_at_5
|
| value: 71.587
|
| - type: ndcg_at_1
|
| value: 65.688
|
| - type: ndcg_at_10
|
| value: 70.221
|
| - type: ndcg_at_100
|
| value: 74.457
|
| - type: ndcg_at_1000
|
| value: 75.178
|
| - type: ndcg_at_3
|
| value: 65.423
|
| - type: ndcg_at_5
|
| value: 67.05499999999999
|
| - type: precision_at_1
|
| value: 65.688
|
| - type: precision_at_10
|
| value: 16.208
|
| - type: precision_at_100
|
| value: 1.975
|
| - type: precision_at_1000
|
| value: 0.207
|
| - type: precision_at_3
|
| value: 39.831
|
| - type: precision_at_5
|
| value: 28.652
|
| - type: recall_at_1
|
| value: 42.027
|
| - type: recall_at_10
|
| value: 78.803
|
| - type: recall_at_100
|
| value: 95.051
|
| - type: recall_at_1000
|
| value: 99.75500000000001
|
| - type: recall_at_3
|
| value: 62.62799999999999
|
| - type: recall_at_5
|
| value: 70.975
|
| license: mit
|
| language:
|
| - fr
|
| ---
|
|
|
| # Solon Embeddings — large 0.1
|
|
|
| SOTA Open source french embedding model.
|
|
|
| **Instructions :**
|
| Add "query : " before the *query* to retrieve to increase performance of retrieval.
|
| No instructions needed for *passages*.
|
|
|
|
|
| | Model | Mean Score |
|
| | --- | --- |
|
| | **OrdalieTech/Solon-embeddings-large-0.1** | 0.7490 |
|
| | cohere/embed-multilingual-v3 | 0.7402 |
|
| | **OrdalieTech/Solon-embeddings-base-0.1** | 0.7306 |
|
| | openai/ada-002 | 0.7290 |
|
| | cohere/embed-multilingual-light-v3 | 0.6945 |
|
| | antoinelouis/biencoder-camembert-base-mmarcoFR | 0.6826 |
|
| | dangvantuan/sentence-camembert-large | 0.6756 |
|
| | voyage/voyage-01 | 0.6753 |
|
| | intfloat/multilingual-e5-large | 0.6660 |
|
| | intfloat/multilingual-e5-base | 0.6597 |
|
| | Sbert/paraphrase-multilingual-mpnet-base-v2 | 0.5975 |
|
| | dangvantuan/sentence-camembert-base | 0.5456 |
|
| | EuropeanParliament/eubert_embedding_v1 | 0.5063 |
|
|
|
| These results have been obtained through 9 french benchmarks on a variety of text similarity tasks (classification, reranking, STS) :
|
| - AmazonReviewsClassification (MTEB)
|
| - MassiveIntentClassification (MTEB)
|
| - MassiveScenarioClassification (MTEB)
|
| - MTOPDomainClassification (MTEB)
|
| - MTOPIntentClassification (MTEB)
|
| - STS22 (MTEB)
|
| - MiraclFRRerank (Miracl)
|
| - OrdalieFRSTS (Ordalie)
|
| - OrdalieFRReranking (Ordalie)
|
|
|
| We created OrdalieFRSTS and OrdalieFRReranking to enhance the benchmarking capabilities of French STS and reranking assessments.
|
|
|
| (evaluation script available here : github.com/OrdalieTech/mteb) |
