Add MTEB eval results

README.md

@@ -4,6 +4,3849 @@ tags:
 - sentence-transformers
 - feature-extraction
 - sentence-similarity
+model-index:
+- name: SGPT-125M-weightedmean-nli-bitfit
+  results:
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/medrxiv-clustering-p2p
+      name: MTEB MedrxivClusteringP2P
+    metrics:
+    - type: v_measure
+      value: 0.28301902023313874
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts13-sts
+      name: MTEB STS13
+    metrics:
+    - type: cos_sim_pearson
+      value: 0.76401935081936
+    - type: cos_sim_spearman
+      value: 0.7723446219694267
+    - type: euclidean_pearson
+      value: 0.7461017160439877
+    - type: euclidean_spearman
+      value: 0.7585871531365609
+    - type: manhattan_pearson
+      value: 0.7483034779539725
+    - type: manhattan_spearman
+      value: 0.759594899358843
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/arxiv-clustering-p2p
+      name: MTEB ArxivClusteringP2P
+    metrics:
+    - type: v_measure
+      value: 0.3474248247787077
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_reviews_multi
+      name: MTEB AmazonReviewsClassification (en)
+    metrics:
+    - type: accuracy
+      value: 0.35098
+    - type: f1
+      value: 0.34732656514357263
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_reviews_multi
+      name: MTEB AmazonReviewsClassification (de)
+    metrics:
+    - type: accuracy
+      value: 0.24516
+    - type: f1
+      value: 0.2421748200448397
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_reviews_multi
+      name: MTEB AmazonReviewsClassification (es)
+    metrics:
+    - type: accuracy
+      value: 0.29097999999999996
+    - type: f1
+      value: 0.28620040162757093
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_reviews_multi
+      name: MTEB AmazonReviewsClassification (fr)
+    metrics:
+    - type: accuracy
+      value: 0.27396
+    - type: f1
+      value: 0.27146888644986283
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_reviews_multi
+      name: MTEB AmazonReviewsClassification (ja)
+    metrics:
+    - type: accuracy
+      value: 0.21724000000000002
+    - type: f1
+      value: 0.2137230564276654
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_reviews_multi
+      name: MTEB AmazonReviewsClassification (zh)
+    metrics:
+    - type: accuracy
+      value: 0.23975999999999997
+    - type: f1
+      value: 0.23741137981755484
+  - task:
+      type: BitextMining
+    dataset:
+      type: mteb/bucc-bitext-mining
+      name: MTEB BUCC (de-en)
+    metrics:
+    - type: accuracy
+      value: 0.010960334029227558
+    - type: f1
+      value: 0.01092553931802366
+    - type: precision
+      value: 0.010908141962421711
+    - type: recall
+      value: 0.010960334029227558
+  - task:
+      type: BitextMining
+    dataset:
+      type: mteb/bucc-bitext-mining
+      name: MTEB BUCC (fr-en)
+    metrics:
+    - type: accuracy
+      value: 0.00022011886418666079
+    - type: f1
+      value: 0.00022011886418666079
+    - type: precision
+      value: 0.00022011886418666079
+    - type: recall
+      value: 0.00022011886418666079
+  - task:
+      type: BitextMining
+    dataset:
+      type: mteb/bucc-bitext-mining
+      name: MTEB BUCC (ru-en)
+    metrics:
+    - type: accuracy
+      value: 0.0
+    - type: f1
+      value: 0.0
+    - type: precision
+      value: 0.0
+    - type: recall
+      value: 0.0
+  - task:
+      type: BitextMining
+    dataset:
+      type: mteb/bucc-bitext-mining
+      name: MTEB BUCC (zh-en)
+    metrics:
+    - type: accuracy
+      value: 0.0
+    - type: f1
+      value: 0.0
+    - type: precision
+      value: 0.0
+    - type: recall
+      value: 0.0
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_domain
+      name: MTEB MTOPDomainClassification (en)
+    metrics:
+    - type: accuracy
+      value: 0.8151846785225718
+    - type: f1
+      value: 0.81648869152345
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_domain
+      name: MTEB MTOPDomainClassification (de)
+    metrics:
+    - type: accuracy
+      value: 0.6037475345167653
+    - type: f1
+      value: 0.5845264937551703
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_domain
+      name: MTEB MTOPDomainClassification (es)
+    metrics:
+    - type: accuracy
+      value: 0.6736824549699799
+    - type: f1
+      value: 0.6535927434998515
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_domain
+      name: MTEB MTOPDomainClassification (fr)
+    metrics:
+    - type: accuracy
+      value: 0.6312871907297212
+    - type: f1
+      value: 0.6137620329272278
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_domain
+      name: MTEB MTOPDomainClassification (hi)
+    metrics:
+    - type: accuracy
+      value: 0.47045536034420943
+    - type: f1
+      value: 0.46203899126445613
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_domain
+      name: MTEB MTOPDomainClassification (th)
+    metrics:
+    - type: accuracy
+      value: 0.5228209764918625
+    - type: f1
+      value: 0.5075489206473579
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackMathematicaRetrieval
+    metrics:
+    - type: map_at_1
+      value: 0.0808
+    - type: map_at_10
+      value: 0.11691
+    - type: map_at_100
+      value: 0.12312
+    - type: map_at_1000
+      value: 0.12439
+    - type: map_at_3
+      value: 0.10344
+    - type: map_at_5
+      value: 0.10996
+    - type: ndcg_at_1
+      value: 0.10697
+    - type: ndcg_at_10
+      value: 0.1448
+    - type: ndcg_at_100
+      value: 0.18161
+    - type: ndcg_at_1000
+      value: 0.21886
+    - type: ndcg_at_3
+      value: 0.11872
+    - type: ndcg_at_5
+      value: 0.12834
+    - type: precision_at_1
+      value: 0.10697
+    - type: precision_at_10
+      value: 0.02811
+    - type: precision_at_100
+      value: 0.00551
+    - type: precision_at_1000
+      value: 0.00102
+    - type: precision_at_3
+      value: 0.05804
+    - type: precision_at_5
+      value: 0.04154
+    - type: recall_at_1
+      value: 0.0808
+    - type: recall_at_10
+      value: 0.20235
+    - type: recall_at_100
+      value: 0.37526
+    - type: recall_at_1000
+      value: 0.65106
+    - type: recall_at_3
+      value: 0.12804
+    - type: recall_at_5
+      value: 0.15499
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_counterfactual
+      name: MTEB AmazonCounterfactualClassification (en)
+    metrics:
+    - type: accuracy
+      value: 0.6588059701492537
+    - type: ap
+      value: 0.28685493163579784
+    - type: f1
+      value: 0.5979951005816335
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_counterfactual
+      name: MTEB AmazonCounterfactualClassification (de)
+    metrics:
+    - type: accuracy
+      value: 0.5907922912205568
+    - type: ap
+      value: 0.7391887421019034
+    - type: f1
+      value: 0.566316368658711
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_counterfactual
+      name: MTEB AmazonCounterfactualClassification (en-ext)
+    metrics:
+    - type: accuracy
+      value: 0.6491754122938531
+    - type: ap
+      value: 0.16360681214864226
+    - type: f1
+      value: 0.5312659206152377
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_counterfactual
+      name: MTEB AmazonCounterfactualClassification (ja)
+    metrics:
+    - type: accuracy
+      value: 0.56423982869379
+    - type: ap
+      value: 0.12143003571907898
+    - type: f1
+      value: 0.45763637779874716
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackTexRetrieval
+    metrics:
+    - type: map_at_1
+      value: 0.06496
+    - type: map_at_10
+      value: 0.09243
+    - type: map_at_100
+      value: 0.09841
+    - type: map_at_1000
+      value: 0.09946
+    - type: map_at_3
+      value: 0.08395
+    - type: map_at_5
+      value: 0.08872
+    - type: ndcg_at_1
+      value: 0.08224
+    - type: ndcg_at_10
+      value: 0.1124
+    - type: ndcg_at_100
+      value: 0.14525
+    - type: ndcg_at_1000
+      value: 0.17686
+    - type: ndcg_at_3
+      value: 0.09617
+    - type: ndcg_at_5
+      value: 0.1037
+    - type: precision_at_1
+      value: 0.08224
+    - type: precision_at_10
+      value: 0.02082
+    - type: precision_at_100
+      value: 0.00443
+    - type: precision_at_1000
+      value: 0.00085
+    - type: precision_at_3
+      value: 0.04623
+    - type: precision_at_5
+      value: 0.03331
+    - type: recall_at_1
+      value: 0.06496
+    - type: recall_at_10
+      value: 0.1531
+    - type: recall_at_100
+      value: 0.3068
+    - type: recall_at_1000
+      value: 0.54335
+    - type: recall_at_3
+      value: 0.10691
+    - type: recall_at_5
+      value: 0.12688
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/mind_small
+      name: MTEB MindSmallReranking
+    metrics:
+    - type: map
+      value: 0.2926934104146833
+    - type: mrr
+      value: 0.3013214087687572
+  - task:
+      type: Retrieval
+    dataset:
+      type: nfcorpus
+      name: MTEB NFCorpus
+    metrics:
+    - type: map_at_1
+      value: 0.01227
+    - type: map_at_10
+      value: 0.03081
+    - type: map_at_100
+      value: 0.04104
+    - type: map_at_1000
+      value: 0.04989
+    - type: map_at_3
+      value: 0.02221
+    - type: map_at_5
+      value: 0.02535
+    - type: ndcg_at_1
+      value: 0.15015
+    - type: ndcg_at_10
+      value: 0.11805
+    - type: ndcg_at_100
+      value: 0.12452
+    - type: ndcg_at_1000
+      value: 0.22284
+    - type: ndcg_at_3
+      value: 0.13257
+    - type: ndcg_at_5
+      value: 0.12199
+    - type: precision_at_1
+      value: 0.16409
+    - type: precision_at_10
+      value: 0.09102
+    - type: precision_at_100
+      value: 0.03678
+    - type: precision_at_1000
+      value: 0.01609
+    - type: precision_at_3
+      value: 0.12797
+    - type: precision_at_5
+      value: 0.10464
+    - type: recall_at_1
+      value: 0.01227
+    - type: recall_at_10
+      value: 0.05838
+    - type: recall_at_100
+      value: 0.15716
+    - type: recall_at_1000
+      value: 0.48837
+    - type: recall_at_3
+      value: 0.02828
+    - type: recall_at_5
+      value: 0.03697
+  - task:
+      type: Retrieval
+    dataset:
+      type: msmarco
+      name: MTEB MSMARCO
+    metrics:
+    - type: map_at_1
+      value: 0.0288
+    - type: map_at_10
+      value: 0.04914
+    - type: map_at_100
+      value: 0.05459
+    - type: map_at_1000
+      value: 0.05538
+    - type: map_at_3
+      value: 0.04087
+    - type: map_at_5
+      value: 0.04518
+    - type: ndcg_at_1
+      value: 0.02937
+    - type: ndcg_at_10
+      value: 0.06273
+    - type: ndcg_at_100
+      value: 0.09426
+    - type: ndcg_at_1000
+      value: 0.12033
+    - type: ndcg_at_3
+      value: 0.04513
+    - type: ndcg_at_5
+      value: 0.05292
+    - type: precision_at_1
+      value: 0.02937
+    - type: precision_at_10
+      value: 0.01089
+    - type: precision_at_100
+      value: 0.00277
+    - type: precision_at_1000
+      value: 0.00051
+    - type: precision_at_3
+      value: 0.01929
+    - type: precision_at_5
+      value: 0.01547
+    - type: recall_at_1
+      value: 0.0288
+    - type: recall_at_10
+      value: 0.10578
+    - type: recall_at_100
+      value: 0.26267
+    - type: recall_at_1000
+      value: 0.4759
+    - type: recall_at_3
+      value: 0.05673
+    - type: recall_at_5
+      value: 0.07545
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackUnixRetrieval
+    metrics:
+    - type: map_at_1
+      value: 0.13843
+    - type: map_at_10
+      value: 0.17496
+    - type: map_at_100
+      value: 0.18304
+    - type: map_at_1000
+      value: 0.18426
+    - type: map_at_3
+      value: 0.16225
+    - type: map_at_5
+      value: 0.1683
+    - type: ndcg_at_1
+      value: 0.16698
+    - type: ndcg_at_10
+      value: 0.20301
+    - type: ndcg_at_100
+      value: 0.24523
+    - type: ndcg_at_1000
+      value: 0.27784
+    - type: ndcg_at_3
+      value: 0.17822
+    - type: ndcg_at_5
+      value: 0.18794
+    - type: precision_at_1
+      value: 0.16698
+    - type: precision_at_10
+      value: 0.03358
+    - type: precision_at_100
+      value: 0.00618
+    - type: precision_at_1000
+      value: 0.00101
+    - type: precision_at_3
+      value: 0.07898
+    - type: precision_at_5
+      value: 0.05429
+    - type: recall_at_1
+      value: 0.13843
+    - type: recall_at_10
+      value: 0.25888
+    - type: recall_at_100
+      value: 0.45028
+    - type: recall_at_1000
+      value: 0.68991
+    - type: recall_at_3
+      value: 0.18851
+    - type: recall_at_5
+      value: 0.21462
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts12-sts
+      name: MTEB STS12
+    metrics:
+    - type: cos_sim_pearson
+      value: 0.8020938796088339
+    - type: cos_sim_spearman
+      value: 0.6916914010333395
+    - type: euclidean_pearson
+      value: 0.7933415250097545
+    - type: euclidean_spearman
+      value: 0.7146707320292746
+    - type: manhattan_pearson
+      value: 0.7973669837981976
+    - type: manhattan_spearman
+      value: 0.7187919511134903
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/stackexchange-clustering
+      name: MTEB StackExchangeClustering
+    metrics:
+    - type: v_measure
+      value: 0.4459127540530939
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/scidocs-reranking
+      name: MTEB SciDocsRR
+    metrics:
+    - type: map
+      value: 0.6835710819755543
+    - type: mrr
+      value: 0.8805442832403617
+  - task:
+      type: Retrieval
+    dataset:
+      type: arguana
+      name: MTEB ArguAna
+    metrics:
+    - type: map_at_1
+      value: 0.13442
+    - type: map_at_10
+      value: 0.24275
+    - type: map_at_100
+      value: 0.25588
+    - type: map_at_1000
+      value: 0.25659
+    - type: map_at_3
+      value: 0.20092
+    - type: map_at_5
+      value: 0.2244
+    - type: ndcg_at_1
+      value: 0.13442
+    - type: ndcg_at_10
+      value: 0.3104
+    - type: ndcg_at_100
+      value: 0.37529
+    - type: ndcg_at_1000
+      value: 0.39348
+    - type: ndcg_at_3
+      value: 0.22342
+    - type: ndcg_at_5
+      value: 0.26596
+    - type: precision_at_1
+      value: 0.13442
+    - type: precision_at_10
+      value: 0.05299
+    - type: precision_at_100
+      value: 0.00836
+    - type: precision_at_1000
+      value: 0.00098
+    - type: precision_at_3
+      value: 0.09625
+    - type: precision_at_5
+      value: 0.07852
+    - type: recall_at_1
+      value: 0.13442
+    - type: recall_at_10
+      value: 0.52987
+    - type: recall_at_100
+      value: 0.83642
+    - type: recall_at_1000
+      value: 0.97795
+    - type: recall_at_3
+      value: 0.28876
+    - type: recall_at_5
+      value: 0.3926
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/askubuntudupquestions-reranking
+      name: MTEB AskUbuntuDupQuestions
+    metrics:
+    - type: map
+      value: 0.5263439984994702
+    - type: mrr
+      value: 0.6575704612408213
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/tweet_sentiment_extraction
+      name: MTEB TweetSentimentExtractionClassification
+    metrics:
+    - type: accuracy
+      value: 0.5482173174872665
+    - type: f1
+      value: 0.5514729314789282
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/arxiv-clustering-s2s
+      name: MTEB ArxivClusteringS2S
+    metrics:
+    - type: v_measure
+      value: 0.2467870651472156
+  - task:
+      type: Retrieval
+    dataset:
+      type: hotpotqa
+      name: MTEB HotpotQA
+    metrics:
+    - type: map_at_1
+      value: 0.09676
+    - type: map_at_10
+      value: 0.13351
+    - type: map_at_100
+      value: 0.13919
+    - type: map_at_1000
+      value: 0.1401
+    - type: map_at_3
+      value: 0.12223
+    - type: map_at_5
+      value: 0.12812
+    - type: ndcg_at_1
+      value: 0.19352
+    - type: ndcg_at_10
+      value: 0.17727
+    - type: ndcg_at_100
+      value: 0.20837
+    - type: ndcg_at_1000
+      value: 0.23412
+    - type: ndcg_at_3
+      value: 0.15317
+    - type: ndcg_at_5
+      value: 0.16436
+    - type: precision_at_1
+      value: 0.19352
+    - type: precision_at_10
+      value: 0.03993
+    - type: precision_at_100
+      value: 0.00651
+    - type: precision_at_1000
+      value: 0.001
+    - type: precision_at_3
+      value: 0.09669
+    - type: precision_at_5
+      value: 0.0669
+    - type: recall_at_1
+      value: 0.09676
+    - type: recall_at_10
+      value: 0.19966
+    - type: recall_at_100
+      value: 0.32573
+    - type: recall_at_1000
+      value: 0.49905
+    - type: recall_at_3
+      value: 0.14504
+    - type: recall_at_5
+      value: 0.16725
+  - task:
+      type: Retrieval
+    dataset:
+      type: webis-touche2020
+      name: MTEB Touche2020
+    metrics:
+    - type: map_at_1
+      value: 0.00645
+    - type: map_at_10
+      value: 0.04116
+    - type: map_at_100
+      value: 0.07527
+    - type: map_at_1000
+      value: 0.08678
+    - type: map_at_3
+      value: 0.01602
+    - type: map_at_5
+      value: 0.026
+    - type: ndcg_at_1
+      value: 0.10204
+    - type: ndcg_at_10
+      value: 0.1227
+    - type: ndcg_at_100
+      value: 0.22461
+    - type: ndcg_at_1000
+      value: 0.33543
+    - type: ndcg_at_3
+      value: 0.09982
+    - type: ndcg_at_5
+      value: 0.11498
+    - type: precision_at_1
+      value: 0.10204
+    - type: precision_at_10
+      value: 0.12245
+    - type: precision_at_100
+      value: 0.05286
+    - type: precision_at_1000
+      value: 0.01263
+    - type: precision_at_3
+      value: 0.10884
+    - type: precision_at_5
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+    - type: recall_at_1
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+    - type: recall_at_10
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+    - type: recall_at_1000
+      value: 0.67704
+    - type: recall_at_3
+      value: 0.02504
+    - type: recall_at_5
+      value: 0.0495
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackAndroidRetrieval
+    metrics:
+    - type: map_at_1
+      value: 0.18222
+    - type: map_at_10
+      value: 0.24506
+    - type: map_at_100
+      value: 0.25611
+    - type: map_at_1000
+      value: 0.25758
+    - type: map_at_3
+      value: 0.22265
+    - type: map_at_5
+      value: 0.23698
+    - type: ndcg_at_1
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+    - type: ndcg_at_10
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+    - type: ndcg_at_100
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+    - type: ndcg_at_1000
+      value: 0.37056
+    - type: ndcg_at_3
+      value: 0.2524
+    - type: ndcg_at_5
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+    - type: precision_at_1
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+    - type: precision_at_10
+      value: 0.05408
+    - type: precision_at_100
+      value: 0.01004
+    - type: precision_at_1000
+      value: 0.00158
+    - type: precision_at_3
+      value: 0.11874
+    - type: precision_at_5
+      value: 0.08927
+    - type: recall_at_1
+      value: 0.18222
+    - type: recall_at_10
+      value: 0.36355
+    - type: recall_at_100
+      value: 0.58724
+    - type: recall_at_1000
+      value: 0.81335
+    - type: recall_at_3
+      value: 0.26334
+    - type: recall_at_5
+      value: 0.314
+  - task:
+      type: Summarization
+    dataset:
+      type: mteb/summeval
+      name: MTEB SummEval
+    metrics:
+    - type: cos_sim_pearson
+      value: 0.3056303767714449
+    - type: cos_sim_spearman
+      value: 0.30256847004390486
+    - type: dot_pearson
+      value: 0.29453520030995006
+    - type: dot_spearman
+      value: 0.2956173255092678
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/imdb
+      name: MTEB ImdbClassification
+    metrics:
+    - type: accuracy
+      value: 0.62896
+    - type: ap
+      value: 0.5847769349850157
+    - type: f1
+      value: 0.6267885149592086
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts15-sts
+      name: MTEB STS15
+    metrics:
+    - type: cos_sim_pearson
+      value: 0.7905293131911804
+    - type: cos_sim_spearman
+      value: 0.7973794782598049
+    - type: euclidean_pearson
+      value: 0.7817016171851057
+    - type: euclidean_spearman
+      value: 0.7876038607583106
+    - type: manhattan_pearson
+      value: 0.784994607532332
+    - type: manhattan_spearman
+      value: 0.7913026720132872
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/medrxiv-clustering-s2s
+      name: MTEB MedrxivClusteringS2S
+    metrics:
+    - type: v_measure
+      value: 0.24932123582259286
+  - task:
+      type: Retrieval
+    dataset:
+      type: climate-fever
+      name: MTEB ClimateFEVER
+    metrics:
+    - type: map_at_1
+      value: 0.03714
+    - type: map_at_10
+      value: 0.06926
+    - type: map_at_100
+      value: 0.07879
+    - type: map_at_1000
+      value: 0.08032
+    - type: map_at_3
+      value: 0.05504
+    - type: map_at_5
+      value: 0.06357
+    - type: ndcg_at_1
+      value: 0.0886
+    - type: ndcg_at_10
+      value: 0.11007
+    - type: ndcg_at_100
+      value: 0.16154
+    - type: ndcg_at_1000
+      value: 0.19668
+    - type: ndcg_at_3
+      value: 0.08103
+    - type: ndcg_at_5
+      value: 0.09456
+    - type: precision_at_1
+      value: 0.0886
+    - type: precision_at_10
+      value: 0.0372
+    - type: precision_at_100
+      value: 0.00917
+    - type: precision_at_1000
+      value: 0.00156
+    - type: precision_at_3
+      value: 0.06254
+    - type: precision_at_5
+      value: 0.05381
+    - type: recall_at_1
+      value: 0.03714
+    - type: recall_at_10
+      value: 0.14382
+    - type: recall_at_100
+      value: 0.33166
+    - type: recall_at_1000
+      value: 0.53444
+    - type: recall_at_3
+      value: 0.07523
+    - type: recall_at_5
+      value: 0.1091
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts14-sts
+      name: MTEB STS14
+    metrics:
+    - type: cos_sim_pearson
+      value: 0.7535551963935667
+    - type: cos_sim_spearman
+      value: 0.7098892671568665
+    - type: euclidean_pearson
+      value: 0.7324467338564629
+    - type: euclidean_spearman
+      value: 0.7197533151639425
+    - type: manhattan_pearson
+      value: 0.7327765593599381
+    - type: manhattan_spearman
+      value: 0.722221421456084
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackEnglishRetrieval
+    metrics:
+    - type: map_at_1
+      value: 0.12058
+    - type: map_at_10
+      value: 0.16051
+    - type: map_at_100
+      value: 0.16772
+    - type: map_at_1000
+      value: 0.16871
+    - type: map_at_3
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+    - type: map_at_5
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+    - type: ndcg_at_1
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+    - type: ndcg_at_10
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+    - type: ndcg_at_100
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+    - type: ndcg_at_1000
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+    - type: ndcg_at_3
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+    - type: ndcg_at_5
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+    - type: precision_at_1
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+    - type: precision_at_1000
+      value: 0.00111
+    - type: precision_at_3
+      value: 0.07983
+    - type: precision_at_5
+      value: 0.05656
+    - type: recall_at_1
+      value: 0.12058
+    - type: recall_at_10
+      value: 0.23644
+    - type: recall_at_100
+      value: 0.3976
+    - type: recall_at_1000
+      value: 0.5856
+    - type: recall_at_3
+      value: 0.17542
+    - type: recall_at_5
+      value: 0.20232
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackGamingRetrieval
+    metrics:
+    - type: map_at_1
+      value: 0.21183
+    - type: map_at_10
+      value: 0.289
+    - type: map_at_100
+      value: 0.29858
+    - type: map_at_1000
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+    - type: map_at_3
+      value: 0.2658
+    - type: map_at_5
+      value: 0.27912
+    - type: ndcg_at_1
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+    - type: ndcg_at_10
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+    - type: ndcg_at_100
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+    - type: ndcg_at_1000
+      value: 0.40416
+    - type: ndcg_at_3
+      value: 0.29045
+    - type: ndcg_at_5
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+    - type: precision_at_1
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+    - type: precision_at_10
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+    - type: precision_at_100
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+    - type: precision_at_1000
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+    - type: precision_at_3
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+    - type: precision_at_5
+      value: 0.09367
+    - type: recall_at_1
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+      value: 0.43875
+    - type: recall_at_100
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+    - type: recall_at_1000
+      value: 0.83017
+    - type: recall_at_3
+      value: 0.32232
+    - type: recall_at_5
+      value: 0.37308
+  - task:
+      type: Retrieval
+    dataset:
+      type: fiqa
+      name: MTEB FiQA2018
+    metrics:
+    - type: map_at_1
+      value: 0.03637
+    - type: map_at_10
+      value: 0.06084
+    - type: map_at_100
+      value: 0.06919
+    - type: map_at_1000
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+    - type: map_at_3
+      value: 0.05071
+    - type: map_at_5
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+    - type: ndcg_at_1
+      value: 0.07407
+    - type: ndcg_at_10
+      value: 0.0894
+    - type: ndcg_at_100
+      value: 0.13595
+    - type: ndcg_at_1000
+      value: 0.1829
+    - type: ndcg_at_3
+      value: 0.07393
+    - type: ndcg_at_5
+      value: 0.07854
+    - type: precision_at_1
+      value: 0.07407
+    - type: precision_at_10
+      value: 0.02778
+    - type: precision_at_100
+      value: 0.0075
+    - type: precision_at_1000
+      value: 0.00154
+    - type: precision_at_3
+      value: 0.05144
+    - type: precision_at_5
+      value: 0.03981
+    - type: recall_at_1
+      value: 0.03637
+    - type: recall_at_10
+      value: 0.11821
+    - type: recall_at_100
+      value: 0.3018
+    - type: recall_at_1000
+      value: 0.60207
+    - type: recall_at_3
+      value: 0.06839
+    - type: recall_at_5
+      value: 0.08649
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (af)
+    metrics:
+    - type: accuracy
+      value: 0.3779421654337593
+    - type: f1
+      value: 0.3681580701507746
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (am)
+    metrics:
+    - type: accuracy
+      value: 0.23722259583053126
+    - type: f1
+      value: 0.23235269695764274
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (ar)
+    metrics:
+    - type: accuracy
+      value: 0.2964021519838601
+    - type: f1
+      value: 0.28273175327650135
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (az)
+    metrics:
+    - type: accuracy
+      value: 0.39475453934095495
+    - type: f1
+      value: 0.39259973614151206
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (bn)
+    metrics:
+    - type: accuracy
+      value: 0.26550100874243443
+    - type: f1
+      value: 0.25607924873522975
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (cy)
+    metrics:
+    - type: accuracy
+      value: 0.38782784129119036
+    - type: f1
+      value: 0.3764180582626517
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (da)
+    metrics:
+    - type: accuracy
+      value: 0.43557498318762605
+    - type: f1
+      value: 0.4135305173800667
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (de)
+    metrics:
+    - type: accuracy
+      value: 0.4039340954942838
+    - type: f1
+      value: 0.38333932195289344
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (el)
+    metrics:
+    - type: accuracy
+      value: 0.3728648285137861
+    - type: f1
+      value: 0.36640059066802844
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (en)
+    metrics:
+    - type: accuracy
+      value: 0.5808002689979825
+    - type: f1
+      value: 0.5649243881660991
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (es)
+    metrics:
+    - type: accuracy
+      value: 0.411768661735037
+    - type: f1
+      value: 0.4066779962225799
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (fa)
+    metrics:
+    - type: accuracy
+      value: 0.36422326832548757
+    - type: f1
+      value: 0.34644173804288503
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (fi)
+    metrics:
+    - type: accuracy
+      value: 0.3875588433086752
+    - type: f1
+      value: 0.3726725894668694
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (fr)
+    metrics:
+    - type: accuracy
+      value: 0.43671822461331533
+    - type: f1
+      value: 0.423518466245666
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (he)
+    metrics:
+    - type: accuracy
+      value: 0.3198049764626766
+    - type: f1
+      value: 0.3055792887280901
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (hi)
+    metrics:
+    - type: accuracy
+      value: 0.2803967720242098
+    - type: f1
+      value: 0.28428418145508305
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (hu)
+    metrics:
+    - type: accuracy
+      value: 0.3813718897108272
+    - type: f1
+      value: 0.3705740698819687
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (hy)
+    metrics:
+    - type: accuracy
+      value: 0.2605245460659045
+    - type: f1
+      value: 0.2525483953344816
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (id)
+    metrics:
+    - type: accuracy
+      value: 0.41156691324815065
+    - type: f1
+      value: 0.40837150332476047
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (is)
+    metrics:
+    - type: accuracy
+      value: 0.38628110289172835
+    - type: f1
+      value: 0.37676919012460314
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (it)
+    metrics:
+    - type: accuracy
+      value: 0.440383322125084
+    - type: f1
+      value: 0.43772590108774556
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (ja)
+    metrics:
+    - type: accuracy
+      value: 0.46207128446536655
+    - type: f1
+      value: 0.44666328759408236
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (jv)
+    metrics:
+    - type: accuracy
+      value: 0.3760591795561533
+    - type: f1
+      value: 0.36581071742378013
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (ka)
+    metrics:
+    - type: accuracy
+      value: 0.24472091459314052
+    - type: f1
+      value: 0.24238209697895607
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (km)
+    metrics:
+    - type: accuracy
+      value: 0.2623739071956961
+    - type: f1
+      value: 0.2537878315084505
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (kn)
+    metrics:
+    - type: accuracy
+      value: 0.17831203765971754
+    - type: f1
+      value: 0.17275078420466344
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (ko)
+    metrics:
+    - type: accuracy
+      value: 0.37266308002689974
+    - type: f1
+      value: 0.3692473791708214
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (lv)
+    metrics:
+    - type: accuracy
+      value: 0.4093140551445864
+    - type: f1
+      value: 0.4082522788964197
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (ml)
+    metrics:
+    - type: accuracy
+      value: 0.1788500336247478
+    - type: f1
+      value: 0.17621569082971816
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (mn)
+    metrics:
+    - type: accuracy
+      value: 0.3297579018157364
+    - type: f1
+      value: 0.33402014633349664
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (ms)
+    metrics:
+    - type: accuracy
+      value: 0.40911230665770015
+    - type: f1
+      value: 0.4009538559124075
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (my)
+    metrics:
+    - type: accuracy
+      value: 0.17834566240753194
+    - type: f1
+      value: 0.17006381849454313
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (nb)
+    metrics:
+    - type: accuracy
+      value: 0.3947881640887693
+    - type: f1
+      value: 0.37819934317839304
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (nl)
+    metrics:
+    - type: accuracy
+      value: 0.4176193678547412
+    - type: f1
+      value: 0.40281991759509694
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (pl)
+    metrics:
+    - type: accuracy
+      value: 0.4261936785474109
+    - type: f1
+      value: 0.40836739146499046
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (pt)
+    metrics:
+    - type: accuracy
+      value: 0.44542703429724273
+    - type: f1
+      value: 0.43452431642784484
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (ro)
+    metrics:
+    - type: accuracy
+      value: 0.3996973772696705
+    - type: f1
+      value: 0.3874209466530094
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (ru)
+    metrics:
+    - type: accuracy
+      value: 0.37461331540013454
+    - type: f1
+      value: 0.3691132021821187
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (sl)
+    metrics:
+    - type: accuracy
+      value: 0.3828850033624748
+    - type: f1
+      value: 0.3737259394049676
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (sq)
+    metrics:
+    - type: accuracy
+      value: 0.4095494283792872
+    - type: f1
+      value: 0.3976770790286908
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (sv)
+    metrics:
+    - type: accuracy
+      value: 0.4185272360457296
+    - type: f1
+      value: 0.4042848260365438
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (sw)
+    metrics:
+    - type: accuracy
+      value: 0.3832885003362475
+    - type: f1
+      value: 0.3690334596675622
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (ta)
+    metrics:
+    - type: accuracy
+      value: 0.19031607262945527
+    - type: f1
+      value: 0.18665103063257613
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (te)
+    metrics:
+    - type: accuracy
+      value: 0.1938466711499664
+    - type: f1
+      value: 0.19186399376652535
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (th)
+    metrics:
+    - type: accuracy
+      value: 0.34088769334229996
+    - type: f1
+      value: 0.3420383086009429
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (tl)
+    metrics:
+    - type: accuracy
+      value: 0.40285810356422325
+    - type: f1
+      value: 0.39361500249640413
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (tr)
+    metrics:
+    - type: accuracy
+      value: 0.38860121049092133
+    - type: f1
+      value: 0.3781916859627235
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (ur)
+    metrics:
+    - type: accuracy
+      value: 0.27834566240753195
+    - type: f1
+      value: 0.26898389386106486
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (vi)
+    metrics:
+    - type: accuracy
+      value: 0.38705447209145927
+    - type: f1
+      value: 0.3828002644202441
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (zh-CN)
+    metrics:
+    - type: accuracy
+      value: 0.45780094149293876
+    - type: f1
+      value: 0.4421526778674136
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (zh-TW)
+    metrics:
+    - type: accuracy
+      value: 0.4232010759919301
+    - type: f1
+      value: 0.4225772977490916
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_polarity
+      name: MTEB AmazonPolarityClassification
+    metrics:
+    - type: accuracy
+      value: 0.74938225
+    - type: ap
+      value: 0.6958187110320567
+    - type: f1
+      value: 0.7472744058439321
+  - task:
+      type: Retrieval
+    dataset:
+      type: dbpedia-entity
+      name: MTEB DBPedia
+    metrics:
+    - type: map_at_1
+      value: 0.01764
+    - type: map_at_10
+      value: 0.0386
+    - type: map_at_100
+      value: 0.05457
+    - type: map_at_1000
+      value: 0.05938
+    - type: map_at_3
+      value: 0.02667
+    - type: map_at_5
+      value: 0.0322
+    - type: ndcg_at_1
+      value: 0.14
+    - type: ndcg_at_10
+      value: 0.10868
+    - type: ndcg_at_100
+      value: 0.12866
+    - type: ndcg_at_1000
+      value: 0.1743
+    - type: ndcg_at_3
+      value: 0.11943
+    - type: ndcg_at_5
+      value: 0.1166
+    - type: precision_at_1
+      value: 0.1925
+    - type: precision_at_10
+      value: 0.10275
+    - type: precision_at_100
+      value: 0.03527
+    - type: precision_at_1000
+      value: 0.00912
+    - type: precision_at_3
+      value: 0.14917
+    - type: precision_at_5
+      value: 0.135
+    - type: recall_at_1
+      value: 0.01764
+    - type: recall_at_10
+      value: 0.06609
+    - type: recall_at_100
+      value: 0.17616
+    - type: recall_at_1000
+      value: 0.33085
+    - type: recall_at_3
+      value: 0.03115
+    - type: recall_at_5
+      value: 0.04605
+  - task:
+      type: Retrieval
+    dataset:
+      type: fever
+      name: MTEB FEVER
+    metrics:
+    - type: map_at_1
+      value: 0.11497
+    - type: map_at_10
+      value: 0.15744
+    - type: map_at_100
+      value: 0.163
+    - type: map_at_1000
+      value: 0.16365
+    - type: map_at_3
+      value: 0.1444
+    - type: map_at_5
+      value: 0.1518
+    - type: ndcg_at_1
+      value: 0.12346
+    - type: ndcg_at_10
+      value: 0.18399
+    - type: ndcg_at_100
+      value: 0.21399
+    - type: ndcg_at_1000
+      value: 0.23442
+    - type: ndcg_at_3
+      value: 0.15695
+    - type: ndcg_at_5
+      value: 0.17027
+    - type: precision_at_1
+      value: 0.12346
+    - type: precision_at_10
+      value: 0.02798
+    - type: precision_at_100
+      value: 0.00445
+    - type: precision_at_1000
+      value: 0.00063
+    - type: precision_at_3
+      value: 0.06586
+    - type: precision_at_5
+      value: 0.04665
+    - type: recall_at_1
+      value: 0.11497
+    - type: recall_at_10
+      value: 0.25636
+    - type: recall_at_100
+      value: 0.39894
+    - type: recall_at_1000
+      value: 0.56181
+    - type: recall_at_3
+      value: 0.18273
+    - type: recall_at_5
+      value: 0.21474
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackProgrammersRetrieval
+    metrics:
+    - type: map_at_1
+      value: 0.12598
+    - type: map_at_10
+      value: 0.17304
+    - type: map_at_100
+      value: 0.18209
+    - type: map_at_1000
+      value: 0.18328
+    - type: map_at_3
+      value: 0.15784
+    - type: map_at_5
+      value: 0.1667
+    - type: ndcg_at_1
+      value: 0.15868
+    - type: ndcg_at_10
+      value: 0.20623
+    - type: ndcg_at_100
+      value: 0.25093
+    - type: ndcg_at_1000
+      value: 0.28498
+    - type: ndcg_at_3
+      value: 0.17912
+    - type: ndcg_at_5
+      value: 0.19198
+    - type: precision_at_1
+      value: 0.15868
+    - type: precision_at_10
+      value: 0.03767
+    - type: precision_at_100
+      value: 0.00716
+    - type: precision_at_1000
+      value: 0.00118
+    - type: precision_at_3
+      value: 0.08638
+    - type: precision_at_5
+      value: 0.0621
+    - type: recall_at_1
+      value: 0.12598
+    - type: recall_at_10
+      value: 0.27144
+    - type: recall_at_100
+      value: 0.46817
+    - type: recall_at_1000
+      value: 0.71861
+    - type: recall_at_3
+      value: 0.19231
+    - type: recall_at_5
+      value: 0.22716
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (en)
+    metrics:
+    - type: cos_sim_pearson
+      value: 0.5917638344661753
+    - type: cos_sim_spearman
+      value: 0.5963676007113087
+    - type: euclidean_pearson
+      value: 0.5668753290255448
+    - type: euclidean_spearman
+      value: 0.5761328025857448
+    - type: manhattan_pearson
+      value: 0.5692312052723706
+    - type: manhattan_spearman
+      value: 0.5776774918418505
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (de)
+    metrics:
+    - type: cos_sim_pearson
+      value: 0.10322254716987457
+    - type: cos_sim_spearman
+      value: 0.110033092996862
+    - type: euclidean_pearson
+      value: 0.06006926471684402
+    - type: euclidean_spearman
+      value: 0.10972140246688376
+    - type: manhattan_pearson
+      value: 0.05933298751861177
+    - type: manhattan_spearman
+      value: 0.11030111585680233
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (es)
+    metrics:
+    - type: cos_sim_pearson
+      value: 0.4338031880545056
+    - type: cos_sim_spearman
+      value: 0.4305358201410913
+    - type: euclidean_pearson
+      value: 0.42723271963625525
+    - type: euclidean_spearman
+      value: 0.4255163899944477
+    - type: manhattan_pearson
+      value: 0.44015574997805873
+    - type: manhattan_spearman
+      value: 0.43124732216158546
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (pl)
+    metrics:
+    - type: cos_sim_pearson
+      value: 0.042912905043631364
+    - type: cos_sim_spearman
+      value: 0.1491272748789348
+    - type: euclidean_pearson
+      value: 0.032855132112394485
+    - type: euclidean_spearman
+      value: 0.16575204463951024
+    - type: manhattan_pearson
+      value: 0.03239877672346581
+    - type: manhattan_spearman
+      value: 0.16841985772913856
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (tr)
+    metrics:
+    - type: cos_sim_pearson
+      value: 0.041027394985558165
+    - type: cos_sim_spearman
+      value: 0.03818238576547375
+    - type: euclidean_pearson
+      value: 0.023181033496453556
+    - type: euclidean_spearman
+      value: 0.051826811802703564
+    - type: manhattan_pearson
+      value: 0.04800617926525645
+    - type: manhattan_spearman
+      value: 0.06738401400306251
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (ar)
+    metrics:
+    - type: cos_sim_pearson
+      value: 0.0238765395226737
+    - type: cos_sim_spearman
+      value: 0.051738993911623274
+    - type: euclidean_pearson
+      value: 0.030710263954769824
+    - type: euclidean_spearman
+      value: 0.050492229090398195
+    - type: manhattan_pearson
+      value: 0.0378263141098617
+    - type: manhattan_spearman
+      value: 0.05042238232170212
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (ru)
+    metrics:
+    - type: cos_sim_pearson
+      value: 0.07673549067267635
+    - type: cos_sim_spearman
+      value: 0.03363121525687889
+    - type: euclidean_pearson
+      value: 0.0464331702652217
+    - type: euclidean_spearman
+      value: 0.036129205171334326
+    - type: manhattan_pearson
+      value: 0.040112317360761963
+    - type: manhattan_spearman
+      value: 0.03233959766173701
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (zh)
+    metrics:
+    - type: cos_sim_pearson
+      value: 0.0006167614416104335
+    - type: cos_sim_spearman
+      value: 0.06521685391703255
+    - type: euclidean_pearson
+      value: 0.048845725790690325
+    - type: euclidean_spearman
+      value: 0.0559058032900239
+    - type: manhattan_pearson
+      value: 0.06139838096573896
+    - type: manhattan_spearman
+      value: 0.050060884837066215
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (fr)
+    metrics:
+    - type: cos_sim_pearson
+      value: 0.5319490347682836
+    - type: cos_sim_spearman
+      value: 0.5456055727079527
+    - type: euclidean_pearson
+      value: 0.5255574442039842
+    - type: euclidean_spearman
+      value: 0.5294640154371587
+    - type: manhattan_pearson
+      value: 0.532759930404542
+    - type: manhattan_spearman
+      value: 0.5317456150351015
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (de-en)
+    metrics:
+    - type: cos_sim_pearson
+      value: 0.5115115853012214
+    - type: cos_sim_spearman
+      value: 0.5392692508173665
+    - type: euclidean_pearson
+      value: 0.4455629287737235
+    - type: euclidean_spearman
+      value: 0.46222372143731383
+    - type: manhattan_pearson
+      value: 0.42831322151459006
+    - type: manhattan_spearman
+      value: 0.4570991764985799
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (es-en)
+    metrics:
+    - type: cos_sim_pearson
+      value: 0.30361948851267917
+    - type: cos_sim_spearman
+      value: 0.32739632941633834
+    - type: euclidean_pearson
+      value: 0.2983135800843496
+    - type: euclidean_spearman
+      value: 0.3111440600132692
+    - type: manhattan_pearson
+      value: 0.31264502938148286
+    - type: manhattan_spearman
+      value: 0.33311204075347495
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (it)
+    metrics:
+    - type: cos_sim_pearson
+      value: 0.3523883630335275
+    - type: cos_sim_spearman
+      value: 0.33677970820867037
+    - type: euclidean_pearson
+      value: 0.34878640693874546
+    - type: euclidean_spearman
+      value: 0.33525189235133496
+    - type: manhattan_pearson
+      value: 0.3422761246389947
+    - type: manhattan_spearman
+      value: 0.32713218497609176
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (pl-en)
+    metrics:
+    - type: cos_sim_pearson
+      value: 0.19809302548119545
+    - type: cos_sim_spearman
+      value: 0.205403702021155
+    - type: euclidean_pearson
+      value: 0.23006803962133016
+    - type: euclidean_spearman
+      value: 0.2296270653079511
+    - type: manhattan_pearson
+      value: 0.2540168317585851
+    - type: manhattan_spearman
+      value: 0.25421508137540866
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (zh-en)
+    metrics:
+    - type: cos_sim_pearson
+      value: 0.20393500955410487
+    - type: cos_sim_spearman
+      value: 0.267057136930116
+    - type: euclidean_pearson
+      value: 0.18168376767724584
+    - type: euclidean_spearman
+      value: 0.19260826601517245
+    - type: manhattan_pearson
+      value: 0.18302619990671526
+    - type: manhattan_spearman
+      value: 0.194691037846159
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (es-it)
+    metrics:
+    - type: cos_sim_pearson
+      value: 0.36589199830751484
+    - type: cos_sim_spearman
+      value: 0.3598972209997404
+    - type: euclidean_pearson
+      value: 0.4104511254757421
+    - type: euclidean_spearman
+      value: 0.39322301680629834
+    - type: manhattan_pearson
+      value: 0.4136802503205308
+    - type: manhattan_spearman
+      value: 0.4076270030293609
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (de-fr)
+    metrics:
+    - type: cos_sim_pearson
+      value: 0.26350936227950084
+    - type: cos_sim_spearman
+      value: 0.25108218032460344
+    - type: euclidean_pearson
+      value: 0.2861681094744849
+    - type: euclidean_spearman
+      value: 0.2735099020394359
+    - type: manhattan_pearson
+      value: 0.30527977072984513
+    - type: manhattan_spearman
+      value: 0.2640333999064081
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (de-pl)
+    metrics:
+    - type: cos_sim_pearson
+      value: 0.20056269198600324
+    - type: cos_sim_spearman
+      value: 0.20939990379746756
+    - type: euclidean_pearson
+      value: 0.18942765438962197
+    - type: euclidean_spearman
+      value: 0.21709842967237447
+    - type: manhattan_pearson
+      value: 0.23643909798655122
+    - type: manhattan_spearman
+      value: 0.2358828328071473
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (fr-pl)
+    metrics:
+    - type: cos_sim_pearson
+      value: 0.19563740271419394
+    - type: cos_sim_spearman
+      value: 0.05634361698190111
+    - type: euclidean_pearson
+      value: 0.16833522619239474
+    - type: euclidean_spearman
+      value: 0.16903085094570333
+    - type: manhattan_pearson
+      value: 0.058053927126608146
+    - type: manhattan_spearman
+      value: 0.16903085094570333
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (af)
+    metrics:
+    - type: accuracy
+      value: 0.40245460659045057
+    - type: f1
+      value: 0.3879924050989544
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (am)
+    metrics:
+    - type: accuracy
+      value: 0.2568930733019502
+    - type: f1
+      value: 0.2548816627916271
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (ar)
+    metrics:
+    - type: accuracy
+      value: 0.3239744451916611
+    - type: f1
+      value: 0.31863029579075774
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (az)
+    metrics:
+    - type: accuracy
+      value: 0.4053127101546738
+    - type: f1
+      value: 0.39707079033948933
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (bn)
+    metrics:
+    - type: accuracy
+      value: 0.2723268325487559
+    - type: f1
+      value: 0.2644365328185879
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (cy)
+    metrics:
+    - type: accuracy
+      value: 0.3869872225958305
+    - type: f1
+      value: 0.3655930387892567
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (da)
+    metrics:
+    - type: accuracy
+      value: 0.4475453934095494
+    - type: f1
+      value: 0.4287356484024154
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (de)
+    metrics:
+    - type: accuracy
+      value: 0.41355077336919976
+    - type: f1
+      value: 0.3982365179458047
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (el)
+    metrics:
+    - type: accuracy
+      value: 0.3843981170141224
+    - type: f1
+      value: 0.3702538368296387
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (en)
+    metrics:
+    - type: accuracy
+      value: 0.6633826496301277
+    - type: f1
+      value: 0.6589634765029931
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (es)
+    metrics:
+    - type: accuracy
+      value: 0.4417955615332885
+    - type: f1
+      value: 0.4310228811620319
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (fa)
+    metrics:
+    - type: accuracy
+      value: 0.3482851378614661
+    - type: f1
+      value: 0.33959524415028025
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (fi)
+    metrics:
+    - type: accuracy
+      value: 0.40561533288500334
+    - type: f1
+      value: 0.38049390117336274
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (fr)
+    metrics:
+    - type: accuracy
+      value: 0.45917955615332884
+    - type: f1
+      value: 0.4465741971572902
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (he)
+    metrics:
+    - type: accuracy
+      value: 0.3208473436449227
+    - type: f1
+      value: 0.2953932929808133
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (hi)
+    metrics:
+    - type: accuracy
+      value: 0.28369199731002015
+    - type: f1
+      value: 0.2752902837981212
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (hu)
+    metrics:
+    - type: accuracy
+      value: 0.3949226630800269
+    - type: f1
+      value: 0.37327234047050406
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (hy)
+    metrics:
+    - type: accuracy
+      value: 0.2590450571620713
+    - type: f1
+      value: 0.24547396574853445
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (id)
+    metrics:
+    - type: accuracy
+      value: 0.4095830531271016
+    - type: f1
+      value: 0.40177843177422223
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (is)
+    metrics:
+    - type: accuracy
+      value: 0.38564223268325487
+    - type: f1
+      value: 0.3735307758495248
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (it)
+    metrics:
+    - type: accuracy
+      value: 0.4658708809683928
+    - type: f1
+      value: 0.44103900526804984
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (ja)
+    metrics:
+    - type: accuracy
+      value: 0.4624747814391393
+    - type: f1
+      value: 0.454107101796664
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (jv)
+    metrics:
+    - type: accuracy
+      value: 0.396570275722932
+    - type: f1
+      value: 0.3882737576832412
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (ka)
+    metrics:
+    - type: accuracy
+      value: 0.2527908540685945
+    - type: f1
+      value: 0.23662661686788491
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (km)
+    metrics:
+    - type: accuracy
+      value: 0.2897108271687962
+    - type: f1
+      value: 0.27195758324189245
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (kn)
+    metrics:
+    - type: accuracy
+      value: 0.1927370544720915
+    - type: f1
+      value: 0.18694271924323635
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (ko)
+    metrics:
+    - type: accuracy
+      value: 0.3572965702757229
+    - type: f1
+      value: 0.3438287006177308
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (lv)
+    metrics:
+    - type: accuracy
+      value: 0.3957296570275723
+    - type: f1
+      value: 0.38074945140886923
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (ml)
+    metrics:
+    - type: accuracy
+      value: 0.19895763281775386
+    - type: f1
+      value: 0.20009313648468288
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (mn)
+    metrics:
+    - type: accuracy
+      value: 0.32431069266980495
+    - type: f1
+      value: 0.31395958664782575
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (ms)
+    metrics:
+    - type: accuracy
+      value: 0.42323470073974445
+    - type: f1
+      value: 0.4081374026314701
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (my)
+    metrics:
+    - type: accuracy
+      value: 0.20864156018829857
+    - type: f1
+      value: 0.20409870408935435
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (nb)
+    metrics:
+    - type: accuracy
+      value: 0.4047074646940148
+    - type: f1
+      value: 0.3919044149415904
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (nl)
+    metrics:
+    - type: accuracy
+      value: 0.43591123066577
+    - type: f1
+      value: 0.4143420363064241
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (pl)
+    metrics:
+    - type: accuracy
+      value: 0.41876260928043046
+    - type: f1
+      value: 0.4119211767666761
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (pt)
+    metrics:
+    - type: accuracy
+      value: 0.46308002689979827
+    - type: f1
+      value: 0.4525536730126799
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (ro)
+    metrics:
+    - type: accuracy
+      value: 0.4252521856086079
+    - type: f1
+      value: 0.4102418109296485
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (ru)
+    metrics:
+    - type: accuracy
+      value: 0.3594821788836584
+    - type: f1
+      value: 0.3508598314806566
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (sl)
+    metrics:
+    - type: accuracy
+      value: 0.3869199731002017
+    - type: f1
+      value: 0.3768119408674127
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (sq)
+    metrics:
+    - type: accuracy
+      value: 0.4047410894418292
+    - type: f1
+      value: 0.39480530387013596
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (sv)
+    metrics:
+    - type: accuracy
+      value: 0.41523201075991933
+    - type: f1
+      value: 0.40200979960243827
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (sw)
+    metrics:
+    - type: accuracy
+      value: 0.39549428379287155
+    - type: f1
+      value: 0.3818556124333806
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (ta)
+    metrics:
+    - type: accuracy
+      value: 0.228782784129119
+    - type: f1
+      value: 0.22239467186721457
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (te)
+    metrics:
+    - type: accuracy
+      value: 0.2051445864156019
+    - type: f1
+      value: 0.1999904788553022
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (th)
+    metrics:
+    - type: accuracy
+      value: 0.34926025554808343
+    - type: f1
+      value: 0.33240167172157226
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (tl)
+    metrics:
+    - type: accuracy
+      value: 0.4074983187626093
+    - type: f1
+      value: 0.3930274328728882
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (tr)
+    metrics:
+    - type: accuracy
+      value: 0.3906859448554136
+    - type: f1
+      value: 0.39215420396629713
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (ur)
+    metrics:
+    - type: accuracy
+      value: 0.29747814391392063
+    - type: f1
+      value: 0.2826183689222045
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (vi)
+    metrics:
+    - type: accuracy
+      value: 0.3802286482851379
+    - type: f1
+      value: 0.37874243860869694
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (zh-CN)
+    metrics:
+    - type: accuracy
+      value: 0.48550773369199723
+    - type: f1
+      value: 0.46739962588264905
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (zh-TW)
+    metrics:
+    - type: accuracy
+      value: 0.45178211163416276
+    - type: f1
+      value: 0.4484809741811729
+  - task:
+      type: Retrieval
+    dataset:
+      type: quora
+      name: MTEB QuoraRetrieval
+    metrics:
+    - type: map_at_1
+      value: 0.61697
+    - type: map_at_10
+      value: 0.74204
+    - type: map_at_100
+      value: 0.75023
+    - type: map_at_1000
+      value: 0.75059
+    - type: map_at_3
+      value: 0.71265
+    - type: map_at_5
+      value: 0.73001
+    - type: ndcg_at_1
+      value: 0.7095
+    - type: ndcg_at_10
+      value: 0.7896
+    - type: ndcg_at_100
+      value: 0.8126
+    - type: ndcg_at_1000
+      value: 0.81679
+    - type: ndcg_at_3
+      value: 0.75246
+    - type: ndcg_at_5
+      value: 0.77092
+    - type: precision_at_1
+      value: 0.7095
+    - type: precision_at_10
+      value: 0.11998
+    - type: precision_at_100
+      value: 0.01451
+    - type: precision_at_1000
+      value: 0.00154
+    - type: precision_at_3
+      value: 0.3263
+    - type: precision_at_5
+      value: 0.21574
+    - type: recall_at_1
+      value: 0.61697
+    - type: recall_at_10
+      value: 0.88233
+    - type: recall_at_100
+      value: 0.96961
+    - type: recall_at_1000
+      value: 0.99401
+    - type: recall_at_3
+      value: 0.77689
+    - type: recall_at_5
+      value: 0.82745
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sickr-sts
+      name: MTEB SICK-R
+    metrics:
+    - type: cos_sim_pearson
+      value: 0.8096286245858941
+    - type: cos_sim_spearman
+      value: 0.7457093488947429
+    - type: euclidean_pearson
+      value: 0.7550377970259401
+    - type: euclidean_spearman
+      value: 0.7174980046229991
+    - type: manhattan_pearson
+      value: 0.7532568360913819
+    - type: manhattan_spearman
+      value: 0.7180676733410375
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/twitterurlcorpus-pairclassification
+      name: MTEB TwitterURLCorpus
+    metrics:
+    - type: cos_sim_accuracy
+      value: 0.8663018589668956
+    - type: cos_sim_accuracy_threshold
+      value: 0.6738145351409912
+    - type: cos_sim_ap
+      value: 0.805106377126291
+    - type: cos_sim_f1
+      value: 0.7270810586950793
+    - type: cos_sim_f1_threshold
+      value: 0.6406128406524658
+    - type: cos_sim_precision
+      value: 0.7114123627790466
+    - type: cos_sim_recall
+      value: 0.743455497382199
+    - type: dot_accuracy
+      value: 0.8241743315092949
+    - type: dot_accuracy_threshold
+      value: 967.1823120117188
+    - type: dot_ap
+      value: 0.692393381283664
+    - type: dot_f1
+      value: 0.6561346624814597
+    - type: dot_f1_threshold
+      value: 831.1060791015625
+    - type: dot_precision
+      value: 0.5943260638630257
+    - type: dot_recall
+      value: 0.7322913458577148
+    - type: euclidean_accuracy
+      value: 0.8649435324251951
+    - type: euclidean_accuracy_threshold
+      value: 30.077878952026367
+    - type: euclidean_ap
+      value: 0.8028100477250927
+    - type: euclidean_f1
+      value: 0.7258242344489099
+    - type: euclidean_f1_threshold
+      value: 32.570228576660156
+    - type: euclidean_precision
+      value: 0.6744662568576906
+    - type: euclidean_recall
+      value: 0.7856482907299045
+    - type: manhattan_accuracy
+      value: 0.8659525749990298
+    - type: manhattan_accuracy_threshold
+      value: 625.0921020507812
+    - type: manhattan_ap
+      value: 0.8037850832566262
+    - type: manhattan_f1
+      value: 0.7259435321233073
+    - type: manhattan_f1_threshold
+      value: 679.8679809570312
+    - type: manhattan_precision
+      value: 0.6819350473612991
+    - type: manhattan_recall
+      value: 0.7760240221743148
+    - type: max_accuracy
+      value: 0.8663018589668956
+    - type: max_ap
+      value: 0.805106377126291
+    - type: max_f1
+      value: 0.7270810586950793
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/biorxiv-clustering-s2s
+      name: MTEB BiorxivClusteringS2S
+    metrics:
+    - type: v_measure
+      value: 0.23080939123955474
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts17-crosslingual-sts
+      name: MTEB STS17 (ko-ko)
+    metrics:
+    - type: cos_sim_pearson
+      value: 0.430464619152799
+    - type: cos_sim_spearman
+      value: 0.4565606588928089
+    - type: euclidean_pearson
+      value: 0.45694377883554993
+    - type: euclidean_spearman
+      value: 0.4508552742346606
+    - type: manhattan_pearson
+      value: 0.45871666989036813
+    - type: manhattan_spearman
+      value: 0.45155963016434164
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts17-crosslingual-sts
+      name: MTEB STS17 (ar-ar)
+    metrics:
+    - type: cos_sim_pearson
+      value: 0.5327469278912148
+    - type: cos_sim_spearman
+      value: 0.541611320762379
+    - type: euclidean_pearson
+      value: 0.5597026429327157
+    - type: euclidean_spearman
+      value: 0.5471320909074608
+    - type: manhattan_pearson
+      value: 0.5612511774278802
+    - type: manhattan_spearman
+      value: 0.5522875659158676
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts17-crosslingual-sts
+      name: MTEB STS17 (en-ar)
+    metrics:
+    - type: cos_sim_pearson
+      value: 0.015482997790039945
+    - type: cos_sim_spearman
+      value: 0.01720838634736358
+    - type: euclidean_pearson
+      value: -0.06727915670345885
+    - type: euclidean_spearman
+      value: -0.06112826908474543
+    - type: manhattan_pearson
+      value: -0.0494386093060865
+    - type: manhattan_spearman
+      value: -0.05018174110623732
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts17-crosslingual-sts
+      name: MTEB STS17 (en-de)
+    metrics:
+    - type: cos_sim_pearson
+      value: 0.275420218362265
+    - type: cos_sim_spearman
+      value: 0.2548383843103101
+    - type: euclidean_pearson
+      value: 0.06268684143856358
+    - type: euclidean_spearman
+      value: 0.058779614210916785
+    - type: manhattan_pearson
+      value: 0.026672377392278606
+    - type: manhattan_spearman
+      value: 0.025683839956554773
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts17-crosslingual-sts
+      name: MTEB STS17 (en-en)
+    metrics:
+    - type: cos_sim_pearson
+      value: 0.8532029757646663
+    - type: cos_sim_spearman
+      value: 0.8732720847297224
+    - type: euclidean_pearson
+      value: 0.8112594485791255
+    - type: euclidean_spearman
+      value: 0.811531079489332
+    - type: manhattan_pearson
+      value: 0.8132899414704019
+    - type: manhattan_spearman
+      value: 0.813897040261192
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts17-crosslingual-sts
+      name: MTEB STS17 (en-tr)
+    metrics:
+    - type: cos_sim_pearson
+      value: 0.0437162299241808
+    - type: cos_sim_spearman
+      value: 0.020879072561774542
+    - type: euclidean_pearson
+      value: -0.030725243785454597
+    - type: euclidean_spearman
+      value: -0.05372133927948353
+    - type: manhattan_pearson
+      value: -0.04867795293367359
+    - type: manhattan_spearman
+      value: -0.07939706984001878
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts17-crosslingual-sts
+      name: MTEB STS17 (es-en)
+    metrics:
+    - type: cos_sim_pearson
+      value: 0.20306030448858603
+    - type: cos_sim_spearman
+      value: 0.2193220782551375
+    - type: euclidean_pearson
+      value: 0.03878631934602361
+    - type: euclidean_spearman
+      value: 0.05171796902725965
+    - type: manhattan_pearson
+      value: 0.0713020644036815
+    - type: manhattan_spearman
+      value: 0.07707315591498748
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts17-crosslingual-sts
+      name: MTEB STS17 (es-es)
+    metrics:
+    - type: cos_sim_pearson
+      value: 0.6681873207478459
+    - type: cos_sim_spearman
+      value: 0.6780273445636502
+    - type: euclidean_pearson
+      value: 0.7060654682977268
+    - type: euclidean_spearman
+      value: 0.694566208379486
+    - type: manhattan_pearson
+      value: 0.7095484618966419
+    - type: manhattan_spearman
+      value: 0.6978323323058773
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts17-crosslingual-sts
+      name: MTEB STS17 (fr-en)
+    metrics:
+    - type: cos_sim_pearson
+      value: 0.21366487281202604
+    - type: cos_sim_spearman
+      value: 0.18906275286984808
+    - type: euclidean_pearson
+      value: -0.023390998579461995
+    - type: euclidean_spearman
+      value: -0.04151213674012541
+    - type: manhattan_pearson
+      value: -0.02234831868844863
+    - type: manhattan_spearman
+      value: -0.045552913285014415
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts17-crosslingual-sts
+      name: MTEB STS17 (it-en)
+    metrics:
+    - type: cos_sim_pearson
+      value: 0.20731531772510847
+    - type: cos_sim_spearman
+      value: 0.163855949033176
+    - type: euclidean_pearson
+      value: -0.08734648741714238
+    - type: euclidean_spearman
+      value: -0.1075672244732182
+    - type: manhattan_pearson
+      value: -0.07536654126608877
+    - type: manhattan_spearman
+      value: -0.08330065460047295
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts17-crosslingual-sts
+      name: MTEB STS17 (nl-en)
+    metrics:
+    - type: cos_sim_pearson
+      value: 0.2661843502408425
+    - type: cos_sim_spearman
+      value: 0.23488974089577816
+    - type: euclidean_pearson
+      value: -0.031310350304707864
+    - type: euclidean_spearman
+      value: -0.031242598481634666
+    - type: manhattan_pearson
+      value: -0.011096752982707007
+    - type: manhattan_spearman
+      value: -0.014591693078765849
+  - task:
+      type: Retrieval
+    dataset:
+      type: trec-covid
+      name: MTEB TRECCOVID
+    metrics:
+    - type: map_at_1
+      value: 0.00113
+    - type: map_at_10
+      value: 0.00733
+    - type: map_at_100
+      value: 0.03313
+    - type: map_at_1000
+      value: 0.07355
+    - type: map_at_3
+      value: 0.00282
+    - type: map_at_5
+      value: 0.00414
+    - type: ndcg_at_1
+      value: 0.42
+    - type: ndcg_at_10
+      value: 0.3931
+    - type: ndcg_at_100
+      value: 0.26904
+    - type: ndcg_at_1000
+      value: 0.23778
+    - type: ndcg_at_3
+      value: 0.42776
+    - type: ndcg_at_5
+      value: 0.41554
+    - type: precision_at_1
+      value: 0.48
+    - type: precision_at_10
+      value: 0.43
+    - type: precision_at_100
+      value: 0.2708
+    - type: precision_at_1000
+      value: 0.11014
+    - type: precision_at_3
+      value: 0.48
+    - type: precision_at_5
+      value: 0.456
+    - type: recall_at_1
+      value: 0.00113
+    - type: recall_at_10
+      value: 0.00976
+    - type: recall_at_100
+      value: 0.05888
+    - type: recall_at_1000
+      value: 0.22635
+    - type: recall_at_3
+      value: 0.00329
+    - type: recall_at_5
+      value: 0.00518
+  - task:
+      type: Retrieval
+    dataset:
+      type: scifact
+      name: MTEB SciFact
+    metrics:
+    - type: map_at_1
+      value: 0.21556
+    - type: map_at_10
+      value: 0.27982
+    - type: map_at_100
+      value: 0.28937
+    - type: map_at_1000
+      value: 0.29058
+    - type: map_at_3
+      value: 0.25644
+    - type: map_at_5
+      value: 0.26996
+    - type: ndcg_at_1
+      value: 0.23333
+    - type: ndcg_at_10
+      value: 0.31787
+    - type: ndcg_at_100
+      value: 0.36648
+    - type: ndcg_at_1000
+      value: 0.39936
+    - type: ndcg_at_3
+      value: 0.27299
+    - type: ndcg_at_5
+      value: 0.29659
+    - type: precision_at_1
+      value: 0.23333
+    - type: precision_at_10
+      value: 0.04867
+    - type: precision_at_100
+      value: 0.00743
+    - type: precision_at_1000
+      value: 0.00102
+    - type: precision_at_3
+      value: 0.11333
+    - type: precision_at_5
+      value: 0.08133
+    - type: recall_at_1
+      value: 0.21556
+    - type: recall_at_10
+      value: 0.42333
+    - type: recall_at_100
+      value: 0.65706
+    - type: recall_at_1000
+      value: 0.91489
+    - type: recall_at_3
+      value: 0.30361
+    - type: recall_at_5
+      value: 0.36222
+  - task:
+      type: Retrieval
+    dataset:
+      type: scidocs
+      name: MTEB SCIDOCS
+    metrics:
+    - type: map_at_1
+      value: 0.0172
+    - type: map_at_10
+      value: 0.03824
+    - type: map_at_100
+      value: 0.04727
+    - type: map_at_1000
+      value: 0.04932
+    - type: map_at_3
+      value: 0.02867
+    - type: map_at_5
+      value: 0.03323
+    - type: ndcg_at_1
+      value: 0.085
+    - type: ndcg_at_10
+      value: 0.07133
+    - type: ndcg_at_100
+      value: 0.11911
+    - type: ndcg_at_1000
+      value: 0.16962
+    - type: ndcg_at_3
+      value: 0.06763
+    - type: ndcg_at_5
+      value: 0.05832
+    - type: precision_at_1
+      value: 0.085
+    - type: precision_at_10
+      value: 0.0368
+    - type: precision_at_100
+      value: 0.01067
+    - type: precision_at_1000
+      value: 0.0023
+    - type: precision_at_3
+      value: 0.06233
+    - type: precision_at_5
+      value: 0.0502
+    - type: recall_at_1
+      value: 0.0172
+    - type: recall_at_10
+      value: 0.07487
+    - type: recall_at_100
+      value: 0.21683
+    - type: recall_at_1000
+      value: 0.46688
+    - type: recall_at_3
+      value: 0.03798
+    - type: recall_at_5
+      value: 0.05113
+  - task:
+      type: Retrieval
+    dataset:
+      type: nq
+      name: MTEB NQ
+    metrics:
+    - type: map_at_1
+      value: 0.03515
+    - type: map_at_10
+      value: 0.05884
+    - type: map_at_100
+      value: 0.0651
+    - type: map_at_1000
+      value: 0.06599
+    - type: map_at_3
+      value: 0.04892
+    - type: map_at_5
+      value: 0.05391
+    - type: ndcg_at_1
+      value: 0.04056
+    - type: ndcg_at_10
+      value: 0.07626
+    - type: ndcg_at_100
+      value: 0.1108
+    - type: ndcg_at_1000
+      value: 0.13793
+    - type: ndcg_at_3
+      value: 0.05537
+    - type: ndcg_at_5
+      value: 0.0645
+    - type: precision_at_1
+      value: 0.04056
+    - type: precision_at_10
+      value: 0.01457
+    - type: precision_at_100
+      value: 0.00347
+    - type: precision_at_1000
+      value: 0.00061
+    - type: precision_at_3
+      value: 0.02607
+    - type: precision_at_5
+      value: 0.02086
+    - type: recall_at_1
+      value: 0.03515
+    - type: recall_at_10
+      value: 0.12312
+    - type: recall_at_100
+      value: 0.28713
+    - type: recall_at_1000
+      value: 0.50027
+    - type: recall_at_3
+      value: 0.06701
+    - type: recall_at_5
+      value: 0.08816
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts16-sts
+      name: MTEB STS16
+    metrics:
+    - type: cos_sim_pearson
+      value: 0.7604750373932828
+    - type: cos_sim_spearman
+      value: 0.7793230986462234
+    - type: euclidean_pearson
+      value: 0.758320302521164
+    - type: euclidean_spearman
+      value: 0.7683154481579385
+    - type: manhattan_pearson
+      value: 0.7598713517720608
+    - type: manhattan_spearman
+      value: 0.7695479705521506
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/emotion
+      name: MTEB EmotionClassification
+    metrics:
+    - type: accuracy
+      value: 0.42225
+    - type: f1
+      value: 0.3756351654211211
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackWebmastersRetrieval
+    metrics:
+    - type: map_at_1
+      value: 0.13757
+    - type: map_at_10
+      value: 0.1927
+    - type: map_at_100
+      value: 0.20461
+    - type: map_at_1000
+      value: 0.20641
+    - type: map_at_3
+      value: 0.17865
+    - type: map_at_5
+      value: 0.18618
+    - type: ndcg_at_1
+      value: 0.16996
+    - type: ndcg_at_10
+      value: 0.22774
+    - type: ndcg_at_100
+      value: 0.27675
+    - type: ndcg_at_1000
+      value: 0.31145
+    - type: ndcg_at_3
+      value: 0.20691
+    - type: ndcg_at_5
+      value: 0.21741
+    - type: precision_at_1
+      value: 0.16996
+    - type: precision_at_10
+      value: 0.04545
+    - type: precision_at_100
+      value: 0.01036
+    - type: precision_at_1000
+      value: 0.00185
+    - type: precision_at_3
+      value: 0.10145
+    - type: precision_at_5
+      value: 0.07391
+    - type: recall_at_1
+      value: 0.13757
+    - type: recall_at_10
+      value: 0.28234
+    - type: recall_at_100
+      value: 0.51055
+    - type: recall_at_1000
+      value: 0.75353
+    - type: recall_at_3
+      value: 0.21794
+    - type: recall_at_5
+      value: 0.24614
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/reddit-clustering-p2p
+      name: MTEB RedditClusteringP2P
+    metrics:
+    - type: v_measure
+      value: 0.41007999100992665
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackGisRetrieval
+    metrics:
+    - type: map_at_1
+      value: 0.11351
+    - type: map_at_10
+      value: 0.14953
+    - type: map_at_100
+      value: 0.15623
+    - type: map_at_1000
+      value: 0.15716
+    - type: map_at_3
+      value: 0.13603
+    - type: map_at_5
+      value: 0.14343
+    - type: ndcg_at_1
+      value: 0.12429
+    - type: ndcg_at_10
+      value: 0.17319
+    - type: ndcg_at_100
+      value: 0.2099
+    - type: ndcg_at_1000
+      value: 0.23899
+    - type: ndcg_at_3
+      value: 0.14605
+    - type: ndcg_at_5
+      value: 0.1589
+    - type: precision_at_1
+      value: 0.12429
+    - type: precision_at_10
+      value: 0.02701
+    - type: precision_at_100
+      value: 0.00487
+    - type: precision_at_1000
+      value: 0.00078
+    - type: precision_at_3
+      value: 0.06026
+    - type: precision_at_5
+      value: 0.04384
+    - type: recall_at_1
+      value: 0.11351
+    - type: recall_at_10
+      value: 0.23536
+    - type: recall_at_100
+      value: 0.40942
+    - type: recall_at_1000
+      value: 0.6405
+    - type: recall_at_3
+      value: 0.16195
+    - type: recall_at_5
+      value: 0.19264
+  - task:
+      type: STS
+    dataset:
+      type: mteb/stsbenchmark-sts
+      name: MTEB STSBenchmark
+    metrics:
+    - type: cos_sim_pearson
+      value: 0.8000905671833967
+    - type: cos_sim_spearman
+      value: 0.7954269211027273
+    - type: euclidean_pearson
+      value: 0.7951954544247442
+    - type: euclidean_spearman
+      value: 0.7893670303434288
+    - type: manhattan_pearson
+      value: 0.7947610653340678
+    - type: manhattan_spearman
+      value: 0.7907344156719612
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/banking77
+      name: MTEB Banking77Classification
+    metrics:
+    - type: accuracy
+      value: 0.7467857142857142
+    - type: f1
+      value: 0.7461743413995573
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackStatsRetrieval
+    metrics:
+    - type: map_at_1
+      value: 0.12307
+    - type: map_at_10
+      value: 0.1544
+    - type: map_at_100
+      value: 0.16033
+    - type: map_at_1000
+      value: 0.1614
+    - type: map_at_3
+      value: 0.14393
+    - type: map_at_5
+      value: 0.14856
+    - type: ndcg_at_1
+      value: 0.14571
+    - type: ndcg_at_10
+      value: 0.17685
+    - type: ndcg_at_100
+      value: 0.20882
+    - type: ndcg_at_1000
+      value: 0.23888
+    - type: ndcg_at_3
+      value: 0.15739
+    - type: ndcg_at_5
+      value: 0.16391
+    - type: precision_at_1
+      value: 0.14571
+    - type: precision_at_10
+      value: 0.02883
+    - type: precision_at_100
+      value: 0.00491
+    - type: precision_at_1000
+      value: 0.0008
+    - type: precision_at_3
+      value: 0.07004
+    - type: precision_at_5
+      value: 0.04693
+    - type: recall_at_1
+      value: 0.12307
+    - type: recall_at_10
+      value: 0.22566
+    - type: recall_at_100
+      value: 0.37469
+    - type: recall_at_1000
+      value: 0.6055
+    - type: recall_at_3
+      value: 0.16742
+    - type: recall_at_5
+      value: 0.18634
+  - task:
+      type: STS
+    dataset:
+      type: mteb/biosses-sts
+      name: MTEB BIOSSES
+    metrics:
+    - type: cos_sim_pearson
+      value: 0.7278000135012542
+    - type: cos_sim_spearman
+      value: 0.7092812216947605
+    - type: euclidean_pearson
+      value: 0.771169214949292
+    - type: euclidean_spearman
+      value: 0.7710175681583312
+    - type: manhattan_pearson
+      value: 0.7684527031837596
+    - type: manhattan_spearman
+      value: 0.7707043080084379
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/biorxiv-clustering-p2p
+      name: MTEB BiorxivClusteringP2P
+    metrics:
+    - type: v_measure
+      value: 0.2893427045246491
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/stackexchange-clustering-p2p
+      name: MTEB StackExchangeClusteringP2P
+    metrics:
+    - type: v_measure
+      value: 0.28230204578753637
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/toxic_conversations_50k
+      name: MTEB ToxicConversationsClassification
+    metrics:
+    - type: accuracy
+      value: 0.627862
+    - type: ap
+      value: 0.10958454618347832
+    - type: f1
+      value: 0.48372434170467626
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/twentynewsgroups-clustering
+      name: MTEB TwentyNewsgroupsClustering
+    metrics:
+    - type: v_measure
+      value: 0.2824295128553035
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/twittersemeval2015-pairclassification
+      name: MTEB TwitterSemEval2015
+    metrics:
+    - type: cos_sim_accuracy
+      value: 0.815640460153782
+    - type: cos_sim_accuracy_threshold
+      value: 0.7118978500366211
+    - type: cos_sim_ap
+      value: 0.5709409536692154
+    - type: cos_sim_f1
+      value: 0.5529607083563918
+    - type: cos_sim_f1_threshold
+      value: 0.5981647968292236
+    - type: cos_sim_precision
+      value: 0.47626310772163966
+    - type: cos_sim_recall
+      value: 0.6591029023746702
+    - type: dot_accuracy
+      value: 0.788162365142755
+    - type: dot_accuracy_threshold
+      value: 1049.799072265625
+    - type: dot_ap
+      value: 0.4742989400382077
+    - type: dot_f1
+      value: 0.5125944584382871
+    - type: dot_f1_threshold
+      value: 723.3736572265625
+    - type: dot_precision
+      value: 0.4255838271174625
+    - type: dot_recall
+      value: 0.6443271767810026
+    - type: euclidean_accuracy
+      value: 0.8029445073612684
+    - type: euclidean_accuracy_threshold
+      value: 26.134265899658203
+    - type: euclidean_ap
+      value: 0.5342012231336148
+    - type: euclidean_f1
+      value: 0.5186778356350464
+    - type: euclidean_f1_threshold
+      value: 31.25627326965332
+    - type: euclidean_precision
+      value: 0.454203013481364
+    - type: euclidean_recall
+      value: 0.604485488126649
+    - type: manhattan_accuracy
+      value: 0.802884901949097
+    - type: manhattan_accuracy_threshold
+      value: 560.0760498046875
+    - type: manhattan_ap
+      value: 0.5343205271323233
+    - type: manhattan_f1
+      value: 0.520141655599823
+    - type: manhattan_f1_threshold
+      value: 658.3975830078125
+    - type: manhattan_precision
+      value: 0.44796035074342355
+    - type: manhattan_recall
+      value: 0.6200527704485488
+    - type: max_accuracy
+      value: 0.815640460153782
+    - type: max_ap
+      value: 0.5709409536692154
+    - type: max_f1
+      value: 0.5529607083563918
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_intent
+      name: MTEB MTOPIntentClassification (en)
+    metrics:
+    - type: accuracy
+      value: 0.582421340629275
+    - type: f1
+      value: 0.40116960466226426
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_intent
+      name: MTEB MTOPIntentClassification (de)
+    metrics:
+    - type: accuracy
+      value: 0.4506903353057199
+    - type: f1
+      value: 0.30468468273374966
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_intent
+      name: MTEB MTOPIntentClassification (es)
+    metrics:
+    - type: accuracy
+      value: 0.4880920613742495
+    - type: f1
+      value: 0.3265985375400447
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_intent
+      name: MTEB MTOPIntentClassification (fr)
+    metrics:
+    - type: accuracy
+      value: 0.4433761352959599
+    - type: f1
+      value: 0.2930204743560644
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_intent
+      name: MTEB MTOPIntentClassification (hi)
+    metrics:
+    - type: accuracy
+      value: 0.34198637504481894
+    - type: f1
+      value: 0.2206370603224841
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_intent
+      name: MTEB MTOPIntentClassification (th)
+    metrics:
+    - type: accuracy
+      value: 0.4311030741410488
+    - type: f1
+      value: 0.2692408933648504
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/reddit-clustering
+      name: MTEB RedditClustering
+    metrics:
+    - type: v_measure
+      value: 0.3375741018380938
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackPhysicsRetrieval
+    metrics:
+    - type: map_at_1
+      value: 0.13909
+    - type: map_at_10
+      value: 0.19256
+    - type: map_at_100
+      value: 0.20286
+    - type: map_at_1000
+      value: 0.20429
+    - type: map_at_3
+      value: 0.17399
+    - type: map_at_5
+      value: 0.18399
+    - type: ndcg_at_1
+      value: 0.17421
+    - type: ndcg_at_10
+      value: 0.23106
+    - type: ndcg_at_100
+      value: 0.28129
+    - type: ndcg_at_1000
+      value: 0.31481
+    - type: ndcg_at_3
+      value: 0.19789
+    - type: ndcg_at_5
+      value: 0.21237
+    - type: precision_at_1
+      value: 0.17421
+    - type: precision_at_10
+      value: 0.04331
+    - type: precision_at_100
+      value: 0.00839
+    - type: precision_at_1000
+      value: 0.00131
+    - type: precision_at_3
+      value: 0.094
+    - type: precision_at_5
+      value: 0.06776
+    - type: recall_at_1
+      value: 0.13909
+    - type: recall_at_10
+      value: 0.31087
+    - type: recall_at_100
+      value: 0.52946
+    - type: recall_at_1000
+      value: 0.76546
+    - type: recall_at_3
+      value: 0.21351
+    - type: recall_at_5
+      value: 0.25265
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/stackoverflowdupquestions-reranking
+      name: MTEB StackOverflowDupQuestions
+    metrics:
+    - type: map
+      value: 0.3996520488022785
+    - type: mrr
+      value: 0.40189248047703935
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackRetrieval
+    metrics:
+    - type: map_at_1
+      value: 0.12738416666666666
+    - type: map_at_10
+      value: 0.17235916666666667
+    - type: map_at_100
+      value: 0.1806333333333333
+    - type: map_at_1000
+      value: 0.18184333333333333
+    - type: map_at_3
+      value: 0.1574775
+    - type: map_at_5
+      value: 0.1657825
+    - type: ndcg_at_1
+      value: 0.15487416666666665
+    - type: ndcg_at_10
+      value: 0.20290166666666667
+    - type: ndcg_at_100
+      value: 0.24412916666666662
+    - type: ndcg_at_1000
+      value: 0.27586333333333335
+    - type: ndcg_at_3
+      value: 0.17622083333333333
+    - type: ndcg_at_5
+      value: 0.18859916666666668
+    - type: precision_at_1
+      value: 0.15487416666666665
+    - type: precision_at_10
+      value: 0.036226666666666664
+    - type: precision_at_100
+      value: 0.006820833333333333
+    - type: precision_at_1000
+      value: 0.0011216666666666666
+    - type: precision_at_3
+      value: 0.08163749999999999
+    - type: precision_at_5
+      value: 0.058654166666666674
+    - type: recall_at_1
+      value: 0.12738416666666666
+    - type: recall_at_10
+      value: 0.26599416666666664
+    - type: recall_at_100
+      value: 0.4541258333333334
+    - type: recall_at_1000
+      value: 0.687565
+    - type: recall_at_3
+      value: 0.19008166666666668
+    - type: recall_at_5
+      value: 0.2224991666666667
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/sprintduplicatequestions-pairclassification
+      name: MTEB SprintDuplicateQuestions
+    metrics:
+    - type: cos_sim_accuracy
+      value: 0.9949306930693069
+    - type: cos_sim_accuracy_threshold
+      value: 0.7870972752571106
+    - type: cos_sim_ap
+      value: 0.7773085502917281
+    - type: cos_sim_f1
+      value: 0.7178978681209718
+    - type: cos_sim_f1_threshold
+      value: 0.7572916746139526
+    - type: cos_sim_precision
+      value: 0.711897738446411
+    - type: cos_sim_recall
+      value: 0.724
+    - type: dot_accuracy
+      value: 0.9908118811881188
+    - type: dot_accuracy_threshold
+      value: 1571.5850830078125
+    - type: dot_ap
+      value: 0.30267748833368235
+    - type: dot_f1
+      value: 0.34335201222618444
+    - type: dot_f1_threshold
+      value: 1329.530029296875
+    - type: dot_precision
+      value: 0.34994807892004154
+    - type: dot_recall
+      value: 0.337
+    - type: euclidean_accuracy
+      value: 0.9951683168316832
+    - type: euclidean_accuracy_threshold
+      value: 25.715721130371094
+    - type: euclidean_ap
+      value: 0.7864498778235628
+    - type: euclidean_f1
+      value: 0.7309149972929074
+    - type: euclidean_f1_threshold
+      value: 26.336116790771484
+    - type: euclidean_precision
+      value: 0.7969303423848878
+    - type: euclidean_recall
+      value: 0.675
+    - type: manhattan_accuracy
+      value: 0.9953168316831683
+    - type: manhattan_accuracy_threshold
+      value: 534.224609375
+    - type: manhattan_ap
+      value: 0.7945274878693959
+    - type: manhattan_f1
+      value: 0.7419863373620599
+    - type: manhattan_f1_threshold
+      value: 562.244140625
+    - type: manhattan_precision
+      value: 0.7818383167220376
+    - type: manhattan_recall
+      value: 0.706
+    - type: max_accuracy
+      value: 0.9953168316831683
+    - type: max_ap
+      value: 0.7945274878693959
+    - type: max_f1
+      value: 0.7419863373620599
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackWordpressRetrieval
+    metrics:
+    - type: map_at_1
+      value: 0.09057
+    - type: map_at_10
+      value: 0.12721
+    - type: map_at_100
+      value: 0.1345
+    - type: map_at_1000
+      value: 0.13564
+    - type: map_at_3
+      value: 0.1134
+    - type: map_at_5
+      value: 0.12245
+    - type: ndcg_at_1
+      value: 0.09797
+    - type: ndcg_at_10
+      value: 0.15091
+    - type: ndcg_at_100
+      value: 0.18886
+    - type: ndcg_at_1000
+      value: 0.2229
+    - type: ndcg_at_3
+      value: 0.12365
+    - type: ndcg_at_5
+      value: 0.13931
+    - type: precision_at_1
+      value: 0.09797
+    - type: precision_at_10
+      value: 0.02477
+    - type: precision_at_100
+      value: 0.00466
+    - type: precision_at_1000
+      value: 0.00082
+    - type: precision_at_3
+      value: 0.05299
+    - type: precision_at_5
+      value: 0.04067
+    - type: recall_at_1
+      value: 0.09057
+    - type: recall_at_10
+      value: 0.21319
+    - type: recall_at_100
+      value: 0.38999
+    - type: recall_at_1000
+      value: 0.65374
+    - type: recall_at_3
+      value: 0.14331
+    - type: recall_at_5
+      value: 0.17917
 ---
 
 # SGPT-125M-weightedmean-nli-bitfit