Update README.md

README.md

@@ -1,2966 +1,4 @@
 ---
-tags:
-- mteb
-model-index:
-- name: mmarco-sentence-flare-it
-  results:
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/amazon_counterfactual
-      name: MTEB AmazonCounterfactualClassification (en)
-      config: en
-      split: test
-      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
-    metrics:
-    - type: accuracy
-      value: 66.28358208955223
-    - type: ap
-      value: 28.583712225399804
-    - type: f1
-      value: 59.773975520814645
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/amazon_counterfactual
-      name: MTEB AmazonCounterfactualClassification (de)
-      config: de
-      split: test
-      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
-    metrics:
-    - type: accuracy
-      value: 49.28265524625267
-    - type: ap
-      value: 70.12705711793366
-    - type: f1
-      value: 46.9152621753021
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/amazon_counterfactual
-      name: MTEB AmazonCounterfactualClassification (en-ext)
-      config: en-ext
-      split: test
-      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
-    metrics:
-    - type: accuracy
-      value: 61.13943028485757
-    - type: ap
-      value: 15.393299134540122
-    - type: f1
-      value: 50.441499676740754
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/amazon_counterfactual
-      name: MTEB AmazonCounterfactualClassification (ja)
-      config: ja
-      split: test
-      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
-    metrics:
-    - type: accuracy
-      value: 44.85010706638115
-    - type: ap
-      value: 11.24959111812915
-    - type: f1
-      value: 38.4896899038441
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/amazon_polarity
-      name: MTEB AmazonPolarityClassification
-      config: default
-      split: test
-      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
-    metrics:
-    - type: accuracy
-      value: 53.786350000000006
-    - type: ap
-      value: 52.711619488611895
-    - type: f1
-      value: 52.08639681443221
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/amazon_reviews_multi
-      name: MTEB AmazonReviewsClassification (en)
-      config: en
-      split: test
-      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
-    metrics:
-    - type: accuracy
-      value: 22.954
-    - type: f1
-      value: 20.895324325359304
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/amazon_reviews_multi
-      name: MTEB AmazonReviewsClassification (de)
-      config: de
-      split: test
-      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
-    metrics:
-    - type: accuracy
-      value: 22.016
-    - type: f1
-      value: 20.141551433471214
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/amazon_reviews_multi
-      name: MTEB AmazonReviewsClassification (es)
-      config: es
-      split: test
-      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
-    metrics:
-    - type: accuracy
-      value: 23.842000000000002
-    - type: f1
-      value: 22.360764368564414
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/amazon_reviews_multi
-      name: MTEB AmazonReviewsClassification (fr)
-      config: fr
-      split: test
-      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
-    metrics:
-    - type: accuracy
-      value: 24.534000000000002
-    - type: f1
-      value: 23.348432665500937
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/amazon_reviews_multi
-      name: MTEB AmazonReviewsClassification (ja)
-      config: ja
-      split: test
-      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
-    metrics:
-    - type: accuracy
-      value: 20.183999999999997
-    - type: f1
-      value: 17.025753479408394
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/amazon_reviews_multi
-      name: MTEB AmazonReviewsClassification (zh)
-      config: zh
-      split: test
-      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
-    metrics:
-    - type: accuracy
-      value: 20.226000000000003
-    - type: f1
-      value: 17.949454130689396
-  - task:
-      type: Retrieval
-    dataset:
-      type: arguana
-      name: MTEB ArguAna
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 0.64
-    - type: map_at_10
-      value: 1.109
-    - type: map_at_100
-      value: 1.214
-    - type: map_at_1000
-      value: 1.273
-    - type: map_at_3
-      value: 0.936
-    - type: map_at_5
-      value: 1.032
-    - type: mrr_at_1
-      value: 0.64
-    - type: mrr_at_10
-      value: 1.109
-    - type: mrr_at_100
-      value: 1.214
-    - type: mrr_at_1000
-      value: 1.273
-    - type: mrr_at_3
-      value: 0.936
-    - type: mrr_at_5
-      value: 1.032
-    - type: ndcg_at_1
-      value: 0.64
-    - type: ndcg_at_10
-      value: 1.401
-    - type: ndcg_at_100
-      value: 2.106
-    - type: ndcg_at_1000
-      value: 4.484
-    - type: ndcg_at_3
-      value: 1.042
-    - type: ndcg_at_5
-      value: 1.217
-    - type: precision_at_1
-      value: 0.64
-    - type: precision_at_10
-      value: 0.23500000000000001
-    - type: precision_at_100
-      value: 0.061
-    - type: precision_at_1000
-      value: 0.027
-    - type: precision_at_3
-      value: 0.44999999999999996
-    - type: precision_at_5
-      value: 0.356
-    - type: recall_at_1
-      value: 0.64
-    - type: recall_at_10
-      value: 2.347
-    - type: recall_at_100
-      value: 6.117
-    - type: recall_at_1000
-      value: 26.671
-    - type: recall_at_3
-      value: 1.351
-    - type: recall_at_5
-      value: 1.778
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/arxiv-clustering-p2p
-      name: MTEB ArxivClusteringP2P
-      config: default
-      split: test
-      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
-    metrics:
-    - type: v_measure
-      value: 10.337297492580117
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/arxiv-clustering-s2s
-      name: MTEB ArxivClusteringS2S
-      config: default
-      split: test
-      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
-    metrics:
-    - type: v_measure
-      value: 8.41067718068448
-  - task:
-      type: Reranking
-    dataset:
-      type: mteb/askubuntudupquestions-reranking
-      name: MTEB AskUbuntuDupQuestions
-      config: default
-      split: test
-      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
-    metrics:
-    - type: map
-      value: 39.45372039138711
-    - type: mrr
-      value: 49.48005979861936
-  - task:
-      type: STS
-    dataset:
-      type: mteb/biosses-sts
-      name: MTEB BIOSSES
-      config: default
-      split: test
-      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
-    metrics:
-    - type: cos_sim_pearson
-      value: 2.1060056434908527
-    - type: cos_sim_spearman
-      value: -6.396531291473412
-    - type: euclidean_pearson
-      value: -1.0319749731423296
-    - type: euclidean_spearman
-      value: -5.283855335987313
-    - type: manhattan_pearson
-      value: -5.66609061890471
-    - type: manhattan_spearman
-      value: -7.173055009189482
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/banking77
-      name: MTEB Banking77Classification
-      config: default
-      split: test
-      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
-    metrics:
-    - type: accuracy
-      value: 17.435064935064933
-    - type: f1
-      value: 15.631665237965379
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/biorxiv-clustering-p2p
-      name: MTEB BiorxivClusteringP2P
-      config: default
-      split: test
-      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
-    metrics:
-    - type: v_measure
-      value: 4.01285243931824
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/biorxiv-clustering-s2s
-      name: MTEB BiorxivClusteringS2S
-      config: default
-      split: test
-      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
-    metrics:
-    - type: v_measure
-      value: 3.0046123718115685
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackAndroidRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 0.001
-    - type: map_at_10
-      value: 0.023
-    - type: map_at_100
-      value: 0.034999999999999996
-    - type: map_at_1000
-      value: 0.042
-    - type: map_at_3
-      value: 0.001
-    - type: map_at_5
-      value: 0.001
-    - type: mrr_at_1
-      value: 0.14300000000000002
-    - type: mrr_at_10
-      value: 0.173
-    - type: mrr_at_100
-      value: 0.203
-    - type: mrr_at_1000
-      value: 0.216
-    - type: mrr_at_3
-      value: 0.14300000000000002
-    - type: mrr_at_5
-      value: 0.14300000000000002
-    - type: ndcg_at_1
-      value: 0.14300000000000002
-    - type: ndcg_at_10
-      value: 0.11
-    - type: ndcg_at_100
-      value: 0.174
-    - type: ndcg_at_1000
-      value: 0.526
-    - type: ndcg_at_3
-      value: 0.067
-    - type: ndcg_at_5
-      value: 0.049
-    - type: precision_at_1
-      value: 0.14300000000000002
-    - type: precision_at_10
-      value: 0.056999999999999995
-    - type: precision_at_100
-      value: 0.02
-    - type: precision_at_1000
-      value: 0.01
-    - type: precision_at_3
-      value: 0.048
-    - type: precision_at_5
-      value: 0.029
-    - type: recall_at_1
-      value: 0.001
-    - type: recall_at_10
-      value: 0.216
-    - type: recall_at_100
-      value: 0.629
-    - type: recall_at_1000
-      value: 3.1940000000000004
-    - type: recall_at_3
-      value: 0.001
-    - type: recall_at_5
-      value: 0.001
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackEnglishRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 0.0
-    - type: map_at_10
-      value: 0.04
-    - type: map_at_100
-      value: 0.058
-    - type: map_at_1000
-      value: 0.065
-    - type: map_at_3
-      value: 0.033
-    - type: map_at_5
-      value: 0.04
-    - type: mrr_at_1
-      value: 0.0
-    - type: mrr_at_10
-      value: 0.066
-    - type: mrr_at_100
-      value: 0.099
-    - type: mrr_at_1000
-      value: 0.11
-    - type: mrr_at_3
-      value: 0.053
-    - type: mrr_at_5
-      value: 0.066
-    - type: ndcg_at_1
-      value: 0.0
-    - type: ndcg_at_10
-      value: 0.062
-    - type: ndcg_at_100
-      value: 0.182
-    - type: ndcg_at_1000
-      value: 0.494
-    - type: ndcg_at_3
-      value: 0.055
-    - type: ndcg_at_5
-      value: 0.066
-    - type: precision_at_1
-      value: 0.0
-    - type: precision_at_10
-      value: 0.019
-    - type: precision_at_100
-      value: 0.012
-    - type: precision_at_1000
-      value: 0.006
-    - type: precision_at_3
-      value: 0.042
-    - type: precision_at_5
-      value: 0.038
-    - type: recall_at_1
-      value: 0.0
-    - type: recall_at_10
-      value: 0.1
-    - type: recall_at_100
-      value: 0.626
-    - type: recall_at_1000
-      value: 3.012
-    - type: recall_at_3
-      value: 0.068
-    - type: recall_at_5
-      value: 0.1
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackGamingRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 0.0
-    - type: map_at_10
-      value: 0.01
-    - type: map_at_100
-      value: 0.019
-    - type: map_at_1000
-      value: 0.026
-    - type: map_at_3
-      value: 0.0
-    - type: map_at_5
-      value: 0.0
-    - type: mrr_at_1
-      value: 0.0
-    - type: mrr_at_10
-      value: 0.01
-    - type: mrr_at_100
-      value: 0.019
-    - type: mrr_at_1000
-      value: 0.027
-    - type: mrr_at_3
-      value: 0.0
-    - type: mrr_at_5
-      value: 0.0
-    - type: ndcg_at_1
-      value: 0.0
-    - type: ndcg_at_10
-      value: 0.022000000000000002
-    - type: ndcg_at_100
-      value: 0.09
-    - type: ndcg_at_1000
-      value: 0.35500000000000004
-    - type: ndcg_at_3
-      value: 0.0
-    - type: ndcg_at_5
-      value: 0.0
-    - type: precision_at_1
-      value: 0.0
-    - type: precision_at_10
-      value: 0.006
-    - type: precision_at_100
-      value: 0.004
-    - type: precision_at_1000
-      value: 0.003
-    - type: precision_at_3
-      value: 0.0
-    - type: precision_at_5
-      value: 0.0
-    - type: recall_at_1
-      value: 0.0
-    - type: recall_at_10
-      value: 0.063
-    - type: recall_at_100
-      value: 0.439
-    - type: recall_at_1000
-      value: 2.576
-    - type: recall_at_3
-      value: 0.0
-    - type: recall_at_5
-      value: 0.0
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackGisRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 0.22599999999999998
-    - type: map_at_10
-      value: 0.22599999999999998
-    - type: map_at_100
-      value: 0.23500000000000001
-    - type: map_at_1000
-      value: 0.241
-    - type: map_at_3
-      value: 0.22599999999999998
-    - type: map_at_5
-      value: 0.22599999999999998
-    - type: mrr_at_1
-      value: 0.22599999999999998
-    - type: mrr_at_10
-      value: 0.22599999999999998
-    - type: mrr_at_100
-      value: 0.23800000000000002
-    - type: mrr_at_1000
-      value: 0.244
-    - type: mrr_at_3
-      value: 0.22599999999999998
-    - type: mrr_at_5
-      value: 0.22599999999999998
-    - type: ndcg_at_1
-      value: 0.22599999999999998
-    - type: ndcg_at_10
-      value: 0.22599999999999998
-    - type: ndcg_at_100
-      value: 0.317
-    - type: ndcg_at_1000
-      value: 0.584
-    - type: ndcg_at_3
-      value: 0.22599999999999998
-    - type: ndcg_at_5
-      value: 0.22599999999999998
-    - type: precision_at_1
-      value: 0.22599999999999998
-    - type: precision_at_10
-      value: 0.023
-    - type: precision_at_100
-      value: 0.009000000000000001
-    - type: precision_at_1000
-      value: 0.004
-    - type: precision_at_3
-      value: 0.075
-    - type: precision_at_5
-      value: 0.045
-    - type: recall_at_1
-      value: 0.22599999999999998
-    - type: recall_at_10
-      value: 0.22599999999999998
-    - type: recall_at_100
-      value: 0.732
-    - type: recall_at_1000
-      value: 2.951
-    - type: recall_at_3
-      value: 0.22599999999999998
-    - type: recall_at_5
-      value: 0.22599999999999998
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackMathematicaRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 0.062
-    - type: map_at_10
-      value: 0.062
-    - type: map_at_100
-      value: 0.08800000000000001
-    - type: map_at_1000
-      value: 0.1
-    - type: map_at_3
-      value: 0.062
-    - type: map_at_5
-      value: 0.062
-    - type: mrr_at_1
-      value: 0.124
-    - type: mrr_at_10
-      value: 0.124
-    - type: mrr_at_100
-      value: 0.173
-    - type: mrr_at_1000
-      value: 0.191
-    - type: mrr_at_3
-      value: 0.124
-    - type: mrr_at_5
-      value: 0.124
-    - type: ndcg_at_1
-      value: 0.124
-    - type: ndcg_at_10
-      value: 0.076
-    - type: ndcg_at_100
-      value: 0.27
-    - type: ndcg_at_1000
-      value: 0.7849999999999999
-    - type: ndcg_at_3
-      value: 0.076
-    - type: ndcg_at_5
-      value: 0.076
-    - type: precision_at_1
-      value: 0.124
-    - type: precision_at_10
-      value: 0.012
-    - type: precision_at_100
-      value: 0.02
-    - type: precision_at_1000
-      value: 0.009000000000000001
-    - type: precision_at_3
-      value: 0.041
-    - type: precision_at_5
-      value: 0.025
-    - type: recall_at_1
-      value: 0.062
-    - type: recall_at_10
-      value: 0.062
-    - type: recall_at_100
-      value: 0.9119999999999999
-    - type: recall_at_1000
-      value: 4.809
-    - type: recall_at_3
-      value: 0.062
-    - type: recall_at_5
-      value: 0.062
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackPhysicsRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 0.0
-    - type: map_at_10
-      value: 0.043
-    - type: map_at_100
-      value: 0.061
-    - type: map_at_1000
-      value: 0.06999999999999999
-    - type: map_at_3
-      value: 0.0
-    - type: map_at_5
-      value: 0.043
-    - type: mrr_at_1
-      value: 0.0
-    - type: mrr_at_10
-      value: 0.043
-    - type: mrr_at_100
-      value: 0.06899999999999999
-    - type: mrr_at_1000
-      value: 0.079
-    - type: mrr_at_3
-      value: 0.0
-    - type: mrr_at_5
-      value: 0.043
-    - type: ndcg_at_1
-      value: 0.0
-    - type: ndcg_at_10
-      value: 0.079
-    - type: ndcg_at_100
-      value: 0.22599999999999998
-    - type: ndcg_at_1000
-      value: 0.5579999999999999
-    - type: ndcg_at_3
-      value: 0.0
-    - type: ndcg_at_5
-      value: 0.079
-    - type: precision_at_1
-      value: 0.0
-    - type: precision_at_10
-      value: 0.019
-    - type: precision_at_100
-      value: 0.013
-    - type: precision_at_1000
-      value: 0.005
-    - type: precision_at_3
-      value: 0.0
-    - type: precision_at_5
-      value: 0.038
-    - type: recall_at_1
-      value: 0.0
-    - type: recall_at_10
-      value: 0.192
-    - type: recall_at_100
-      value: 0.918
-    - type: recall_at_1000
-      value: 3.5909999999999997
-    - type: recall_at_3
-      value: 0.0
-    - type: recall_at_5
-      value: 0.192
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackProgrammersRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 0.0
-    - type: map_at_10
-      value: 0.04
-    - type: map_at_100
-      value: 0.044000000000000004
-    - type: map_at_1000
-      value: 0.052
-    - type: map_at_3
-      value: 0.038
-    - type: map_at_5
-      value: 0.038
-    - type: mrr_at_1
-      value: 0.0
-    - type: mrr_at_10
-      value: 0.054
-    - type: mrr_at_100
-      value: 0.07200000000000001
-    - type: mrr_at_1000
-      value: 0.084
-    - type: mrr_at_3
-      value: 0.038
-    - type: mrr_at_5
-      value: 0.038
-    - type: ndcg_at_1
-      value: 0.0
-    - type: ndcg_at_10
-      value: 0.067
-    - type: ndcg_at_100
-      value: 0.10300000000000001
-    - type: ndcg_at_1000
-      value: 0.488
-    - type: ndcg_at_3
-      value: 0.056999999999999995
-    - type: ndcg_at_5
-      value: 0.056999999999999995
-    - type: precision_at_1
-      value: 0.0
-    - type: precision_at_10
-      value: 0.023
-    - type: precision_at_100
-      value: 0.006999999999999999
-    - type: precision_at_1000
-      value: 0.006
-    - type: precision_at_3
-      value: 0.038
-    - type: precision_at_5
-      value: 0.023
-    - type: recall_at_1
-      value: 0.0
-    - type: recall_at_10
-      value: 0.128
-    - type: recall_at_100
-      value: 0.248
-    - type: recall_at_1000
-      value: 3.36
-    - type: recall_at_3
-      value: 0.11399999999999999
-    - type: recall_at_5
-      value: 0.11399999999999999
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackStatsRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 0.0
-    - type: map_at_10
-      value: 0.0
-    - type: map_at_100
-      value: 0.013999999999999999
-    - type: map_at_1000
-      value: 0.023
-    - type: map_at_3
-      value: 0.0
-    - type: map_at_5
-      value: 0.0
-    - type: mrr_at_1
-      value: 0.0
-    - type: mrr_at_10
-      value: 0.0
-    - type: mrr_at_100
-      value: 0.03
-    - type: mrr_at_1000
-      value: 0.045
-    - type: mrr_at_3
-      value: 0.0
-    - type: mrr_at_5
-      value: 0.0
-    - type: ndcg_at_1
-      value: 0.0
-    - type: ndcg_at_10
-      value: 0.0
-    - type: ndcg_at_100
-      value: 0.066
-    - type: ndcg_at_1000
-      value: 0.445
-    - type: ndcg_at_3
-      value: 0.0
-    - type: ndcg_at_5
-      value: 0.0
-    - type: precision_at_1
-      value: 0.0
-    - type: precision_at_10
-      value: 0.0
-    - type: precision_at_100
-      value: 0.005
-    - type: precision_at_1000
-      value: 0.005
-    - type: precision_at_3
-      value: 0.0
-    - type: precision_at_5
-      value: 0.0
-    - type: recall_at_1
-      value: 0.0
-    - type: recall_at_10
-      value: 0.0
-    - type: recall_at_100
-      value: 0.24
-    - type: recall_at_1000
-      value: 3.1559999999999997
-    - type: recall_at_3
-      value: 0.0
-    - type: recall_at_5
-      value: 0.0
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackTexRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 0.0
-    - type: map_at_10
-      value: 0.0
-    - type: map_at_100
-      value: 0.006999999999999999
-    - type: map_at_1000
-      value: 0.012
-    - type: map_at_3
-      value: 0.0
-    - type: map_at_5
-      value: 0.0
-    - type: mrr_at_1
-      value: 0.0
-    - type: mrr_at_10
-      value: 0.0
-    - type: mrr_at_100
-      value: 0.011000000000000001
-    - type: mrr_at_1000
-      value: 0.018000000000000002
-    - type: mrr_at_3
-      value: 0.0
-    - type: mrr_at_5
-      value: 0.0
-    - type: ndcg_at_1
-      value: 0.0
-    - type: ndcg_at_10
-      value: 0.0
-    - type: ndcg_at_100
-      value: 0.055
-    - type: ndcg_at_1000
-      value: 0.254
-    - type: ndcg_at_3
-      value: 0.0
-    - type: ndcg_at_5
-      value: 0.0
-    - type: precision_at_1
-      value: 0.0
-    - type: precision_at_10
-      value: 0.0
-    - type: precision_at_100
-      value: 0.004
-    - type: precision_at_1000
-      value: 0.003
-    - type: precision_at_3
-      value: 0.0
-    - type: precision_at_5
-      value: 0.0
-    - type: recall_at_1
-      value: 0.0
-    - type: recall_at_10
-      value: 0.0
-    - type: recall_at_100
-      value: 0.27599999999999997
-    - type: recall_at_1000
-      value: 1.828
-    - type: recall_at_3
-      value: 0.0
-    - type: recall_at_5
-      value: 0.0
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackUnixRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 0.0
-    - type: map_at_10
-      value: 0.023
-    - type: map_at_100
-      value: 0.031
-    - type: map_at_1000
-      value: 0.038
-    - type: map_at_3
-      value: 0.0
-    - type: map_at_5
-      value: 0.023
-    - type: mrr_at_1
-      value: 0.0
-    - type: mrr_at_10
-      value: 0.023
-    - type: mrr_at_100
-      value: 0.039
-    - type: mrr_at_1000
-      value: 0.048
-    - type: mrr_at_3
-      value: 0.0
-    - type: mrr_at_5
-      value: 0.023
-    - type: ndcg_at_1
-      value: 0.0
-    - type: ndcg_at_10
-      value: 0.04
-    - type: ndcg_at_100
-      value: 0.133
-    - type: ndcg_at_1000
-      value: 0.395
-    - type: ndcg_at_3
-      value: 0.0
-    - type: ndcg_at_5
-      value: 0.04
-    - type: precision_at_1
-      value: 0.0
-    - type: precision_at_10
-      value: 0.009000000000000001
-    - type: precision_at_100
-      value: 0.009000000000000001
-    - type: precision_at_1000
-      value: 0.004
-    - type: precision_at_3
-      value: 0.0
-    - type: precision_at_5
-      value: 0.019
-    - type: recall_at_1
-      value: 0.0
-    - type: recall_at_10
-      value: 0.093
-    - type: recall_at_100
-      value: 0.598
-    - type: recall_at_1000
-      value: 2.59
-    - type: recall_at_3
-      value: 0.0
-    - type: recall_at_5
-      value: 0.093
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackWebmastersRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 0.0
-    - type: map_at_10
-      value: 0.0
-    - type: map_at_100
-      value: 0.015
-    - type: map_at_1000
-      value: 0.03
-    - type: map_at_3
-      value: 0.0
-    - type: map_at_5
-      value: 0.0
-    - type: mrr_at_1
-      value: 0.0
-    - type: mrr_at_10
-      value: 0.0
-    - type: mrr_at_100
-      value: 0.062
-    - type: mrr_at_1000
-      value: 0.083
-    - type: mrr_at_3
-      value: 0.0
-    - type: mrr_at_5
-      value: 0.0
-    - type: ndcg_at_1
-      value: 0.0
-    - type: ndcg_at_10
-      value: 0.0
-    - type: ndcg_at_100
-      value: 0.17700000000000002
-    - type: ndcg_at_1000
-      value: 0.9299999999999999
-    - type: ndcg_at_3
-      value: 0.0
-    - type: ndcg_at_5
-      value: 0.0
-    - type: precision_at_1
-      value: 0.0
-    - type: precision_at_10
-      value: 0.0
-    - type: precision_at_100
-      value: 0.027999999999999997
-    - type: precision_at_1000
-      value: 0.023
-    - type: precision_at_3
-      value: 0.0
-    - type: precision_at_5
-      value: 0.0
-    - type: recall_at_1
-      value: 0.0
-    - type: recall_at_10
-      value: 0.0
-    - type: recall_at_100
-      value: 0.894
-    - type: recall_at_1000
-      value: 6.639
-    - type: recall_at_3
-      value: 0.0
-    - type: recall_at_5
-      value: 0.0
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackWordpressRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 0.0
-    - type: map_at_10
-      value: 0.0
-    - type: map_at_100
-      value: 0.0
-    - type: map_at_1000
-      value: 0.006999999999999999
-    - type: map_at_3
-      value: 0.0
-    - type: map_at_5
-      value: 0.0
-    - type: mrr_at_1
-      value: 0.0
-    - type: mrr_at_10
-      value: 0.0
-    - type: mrr_at_100
-      value: 0.0
-    - type: mrr_at_1000
-      value: 0.009000000000000001
-    - type: mrr_at_3
-      value: 0.0
-    - type: mrr_at_5
-      value: 0.0
-    - type: ndcg_at_1
-      value: 0.0
-    - type: ndcg_at_10
-      value: 0.0
-    - type: ndcg_at_100
-      value: 0.0
-    - type: ndcg_at_1000
-      value: 0.35200000000000004
-    - type: ndcg_at_3
-      value: 0.0
-    - type: ndcg_at_5
-      value: 0.0
-    - type: precision_at_1
-      value: 0.0
-    - type: precision_at_10
-      value: 0.0
-    - type: precision_at_100
-      value: 0.0
-    - type: precision_at_1000
-      value: 0.004
-    - type: precision_at_3
-      value: 0.0
-    - type: precision_at_5
-      value: 0.0
-    - type: recall_at_1
-      value: 0.0
-    - type: recall_at_10
-      value: 0.0
-    - type: recall_at_100
-      value: 0.0
-    - type: recall_at_1000
-      value: 2.864
-    - type: recall_at_3
-      value: 0.0
-    - type: recall_at_5
-      value: 0.0
-  - task:
-      type: Retrieval
-    dataset:
-      type: climate-fever
-      name: MTEB ClimateFEVER
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 0.033
-    - type: map_at_10
-      value: 0.034
-    - type: map_at_100
-      value: 0.037
-    - type: map_at_1000
-      value: 0.039
-    - type: map_at_3
-      value: 0.033
-    - type: map_at_5
-      value: 0.033
-    - type: mrr_at_1
-      value: 0.065
-    - type: mrr_at_10
-      value: 0.07200000000000001
-    - type: mrr_at_100
-      value: 0.08
-    - type: mrr_at_1000
-      value: 0.086
-    - type: mrr_at_3
-      value: 0.065
-    - type: mrr_at_5
-      value: 0.065
-    - type: ndcg_at_1
-      value: 0.065
-    - type: ndcg_at_10
-      value: 0.047
-    - type: ndcg_at_100
-      value: 0.079
-    - type: ndcg_at_1000
-      value: 0.19
-    - type: ndcg_at_3
-      value: 0.04
-    - type: ndcg_at_5
-      value: 0.04
-    - type: precision_at_1
-      value: 0.065
-    - type: precision_at_10
-      value: 0.013
-    - type: precision_at_100
-      value: 0.005
-    - type: precision_at_1000
-      value: 0.002
-    - type: precision_at_3
-      value: 0.022000000000000002
-    - type: precision_at_5
-      value: 0.013
-    - type: recall_at_1
-      value: 0.033
-    - type: recall_at_10
-      value: 0.049
-    - type: recall_at_100
-      value: 0.186
-    - type: recall_at_1000
-      value: 0.9199999999999999
-    - type: recall_at_3
-      value: 0.033
-    - type: recall_at_5
-      value: 0.033
-  - task:
-      type: Retrieval
-    dataset:
-      type: dbpedia-entity
-      name: MTEB DBPedia
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 0.0
-    - type: map_at_10
-      value: 0.0
-    - type: map_at_100
-      value: 0.008
-    - type: map_at_1000
-      value: 0.008
-    - type: map_at_3
-      value: 0.0
-    - type: map_at_5
-      value: 0.0
-    - type: mrr_at_1
-      value: 0.0
-    - type: mrr_at_10
-      value: 0.0
-    - type: mrr_at_100
-      value: 0.066
-    - type: mrr_at_1000
-      value: 0.077
-    - type: mrr_at_3
-      value: 0.0
-    - type: mrr_at_5
-      value: 0.0
-    - type: ndcg_at_1
-      value: 0.0
-    - type: ndcg_at_10
-      value: 0.0
-    - type: ndcg_at_100
-      value: 0.08
-    - type: ndcg_at_1000
-      value: 0.131
-    - type: ndcg_at_3
-      value: 0.0
-    - type: ndcg_at_5
-      value: 0.0
-    - type: precision_at_1
-      value: 0.0
-    - type: precision_at_10
-      value: 0.0
-    - type: precision_at_100
-      value: 0.018000000000000002
-    - type: precision_at_1000
-      value: 0.006999999999999999
-    - type: precision_at_3
-      value: 0.0
-    - type: precision_at_5
-      value: 0.0
-    - type: recall_at_1
-      value: 0.0
-    - type: recall_at_10
-      value: 0.0
-    - type: recall_at_100
-      value: 0.133
-    - type: recall_at_1000
-      value: 0.293
-    - type: recall_at_3
-      value: 0.0
-    - type: recall_at_5
-      value: 0.0
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/emotion
-      name: MTEB EmotionClassification
-      config: default
-      split: test
-      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
-    metrics:
-    - type: accuracy
-      value: 19.57
-    - type: f1
-      value: 16.51103261738041
-  - task:
-      type: Retrieval
-    dataset:
-      type: fever
-      name: MTEB FEVER
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 0.068
-    - type: map_at_10
-      value: 0.104
-    - type: map_at_100
-      value: 0.11
-    - type: map_at_1000
-      value: 0.11299999999999999
-    - type: map_at_3
-      value: 0.095
-    - type: map_at_5
-      value: 0.098
-    - type: mrr_at_1
-      value: 0.075
-    - type: mrr_at_10
-      value: 0.11299999999999999
-    - type: mrr_at_100
-      value: 0.11900000000000001
-    - type: mrr_at_1000
-      value: 0.123
-    - type: mrr_at_3
-      value: 0.10300000000000001
-    - type: mrr_at_5
-      value: 0.106
-    - type: ndcg_at_1
-      value: 0.075
-    - type: ndcg_at_10
-      value: 0.128
-    - type: ndcg_at_100
-      value: 0.167
-    - type: ndcg_at_1000
-      value: 0.291
-    - type: ndcg_at_3
-      value: 0.105
-    - type: ndcg_at_5
-      value: 0.11100000000000002
-    - type: precision_at_1
-      value: 0.075
-    - type: precision_at_10
-      value: 0.021
-    - type: precision_at_100
-      value: 0.004
-    - type: precision_at_1000
-      value: 0.002
-    - type: precision_at_3
-      value: 0.045
-    - type: precision_at_5
-      value: 0.03
-    - type: recall_at_1
-      value: 0.068
-    - type: recall_at_10
-      value: 0.19499999999999998
-    - type: recall_at_100
-      value: 0.40299999999999997
-    - type: recall_at_1000
-      value: 1.448
-    - type: recall_at_3
-      value: 0.128
-    - type: recall_at_5
-      value: 0.14300000000000002
-  - task:
-      type: Retrieval
-    dataset:
-      type: fiqa
-      name: MTEB FiQA2018
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 0.0
-    - type: map_at_10
-      value: 0.0
-    - type: map_at_100
-      value: 0.005
-    - type: map_at_1000
-      value: 0.01
-    - type: map_at_3
-      value: 0.0
-    - type: map_at_5
-      value: 0.0
-    - type: mrr_at_1
-      value: 0.0
-    - type: mrr_at_10
-      value: 0.0
-    - type: mrr_at_100
-      value: 0.011000000000000001
-    - type: mrr_at_1000
-      value: 0.026
-    - type: mrr_at_3
-      value: 0.0
-    - type: mrr_at_5
-      value: 0.0
-    - type: ndcg_at_1
-      value: 0.0
-    - type: ndcg_at_10
-      value: 0.0
-    - type: ndcg_at_100
-      value: 0.06999999999999999
-    - type: ndcg_at_1000
-      value: 0.38899999999999996
-    - type: ndcg_at_3
-      value: 0.0
-    - type: ndcg_at_5
-      value: 0.0
-    - type: precision_at_1
-      value: 0.0
-    - type: precision_at_10
-      value: 0.0
-    - type: precision_at_100
-      value: 0.008
-    - type: precision_at_1000
-      value: 0.006999999999999999
-    - type: precision_at_3
-      value: 0.0
-    - type: precision_at_5
-      value: 0.0
-    - type: recall_at_1
-      value: 0.0
-    - type: recall_at_10
-      value: 0.0
-    - type: recall_at_100
-      value: 0.383
-    - type: recall_at_1000
-      value: 2.435
-    - type: recall_at_3
-      value: 0.0
-    - type: recall_at_5
-      value: 0.0
-  - task:
-      type: Retrieval
-    dataset:
-      type: hotpotqa
-      name: MTEB HotpotQA
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 0.013999999999999999
-    - type: map_at_10
-      value: 0.018000000000000002
-    - type: map_at_100
-      value: 0.019
-    - type: map_at_1000
-      value: 0.02
-    - type: map_at_3
-      value: 0.016
-    - type: map_at_5
-      value: 0.016
-    - type: mrr_at_1
-      value: 0.027
-    - type: mrr_at_10
-      value: 0.034999999999999996
-    - type: mrr_at_100
-      value: 0.038
-    - type: mrr_at_1000
-      value: 0.039
-    - type: mrr_at_3
-      value: 0.032
-    - type: mrr_at_5
-      value: 0.032
-    - type: ndcg_at_1
-      value: 0.027
-    - type: ndcg_at_10
-      value: 0.026
-    - type: ndcg_at_100
-      value: 0.038
-    - type: ndcg_at_1000
-      value: 0.064
-    - type: ndcg_at_3
-      value: 0.021
-    - type: ndcg_at_5
-      value: 0.021
-    - type: precision_at_1
-      value: 0.027
-    - type: precision_at_10
-      value: 0.006999999999999999
-    - type: precision_at_100
-      value: 0.002
-    - type: precision_at_1000
-      value: 0.001
-    - type: precision_at_3
-      value: 0.013999999999999999
-    - type: precision_at_5
-      value: 0.008
-    - type: recall_at_1
-      value: 0.013999999999999999
-    - type: recall_at_10
-      value: 0.034
-    - type: recall_at_100
-      value: 0.08800000000000001
-    - type: recall_at_1000
-      value: 0.27
-    - type: recall_at_3
-      value: 0.02
-    - type: recall_at_5
-      value: 0.02
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/imdb
-      name: MTEB ImdbClassification
-      config: default
-      split: test
-      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
-    metrics:
-    - type: accuracy
-      value: 55.4624
-    - type: ap
-      value: 53.20545827965495
-    - type: f1
-      value: 54.40019244805333
-  - task:
-      type: Retrieval
-    dataset:
-      type: msmarco
-      name: MTEB MSMARCO
-      config: default
-      split: dev
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 0.086
-    - type: map_at_10
-      value: 0.109
-    - type: map_at_100
-      value: 0.11499999999999999
-    - type: map_at_1000
-      value: 0.11800000000000001
-    - type: map_at_3
-      value: 0.091
-    - type: map_at_5
-      value: 0.101
-    - type: mrr_at_1
-      value: 0.086
-    - type: mrr_at_10
-      value: 0.109
-    - type: mrr_at_100
-      value: 0.11499999999999999
-    - type: mrr_at_1000
-      value: 0.11800000000000001
-    - type: mrr_at_3
-      value: 0.091
-    - type: mrr_at_5
-      value: 0.101
-    - type: ndcg_at_1
-      value: 0.086
-    - type: ndcg_at_10
-      value: 0.133
-    - type: ndcg_at_100
-      value: 0.168
-    - type: ndcg_at_1000
-      value: 0.259
-    - type: ndcg_at_3
-      value: 0.093
-    - type: ndcg_at_5
-      value: 0.11100000000000002
-    - type: precision_at_1
-      value: 0.086
-    - type: precision_at_10
-      value: 0.021
-    - type: precision_at_100
-      value: 0.004
-    - type: precision_at_1000
-      value: 0.001
-    - type: precision_at_3
-      value: 0.033
-    - type: precision_at_5
-      value: 0.029
-    - type: recall_at_1
-      value: 0.086
-    - type: recall_at_10
-      value: 0.215
-    - type: recall_at_100
-      value: 0.387
-    - type: recall_at_1000
-      value: 1.1560000000000001
-    - type: recall_at_3
-      value: 0.1
-    - type: recall_at_5
-      value: 0.14300000000000002
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/mtop_domain
-      name: MTEB MTOPDomainClassification (en)
-      config: en
-      split: test
-      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
-    metrics:
-    - type: accuracy
-      value: 34.42544459644323
-    - type: f1
-      value: 33.610930846065315
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/mtop_domain
-      name: MTEB MTOPDomainClassification (de)
-      config: de
-      split: test
-      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
-    metrics:
-    - type: accuracy
-      value: 27.511975204282894
-    - type: f1
-      value: 25.84277270994464
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/mtop_domain
-      name: MTEB MTOPDomainClassification (es)
-      config: es
-      split: test
-      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
-    metrics:
-    - type: accuracy
-      value: 29.51967978652435
-    - type: f1
-      value: 27.67290779782277
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/mtop_domain
-      name: MTEB MTOPDomainClassification (fr)
-      config: fr
-      split: test
-      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
-    metrics:
-    - type: accuracy
-      value: 26.003758221108676
-    - type: f1
-      value: 23.831315642315282
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/mtop_domain
-      name: MTEB MTOPDomainClassification (hi)
-      config: hi
-      split: test
-      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
-    metrics:
-    - type: accuracy
-      value: 20.132664037289356
-    - type: f1
-      value: 16.737043939830457
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/mtop_domain
-      name: MTEB MTOPDomainClassification (th)
-      config: th
-      split: test
-      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
-    metrics:
-    - type: accuracy
-      value: 14.701627486437612
-    - type: f1
-      value: 10.849797498613762
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/mtop_intent
-      name: MTEB MTOPIntentClassification (en)
-      config: en
-      split: test
-      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
-    metrics:
-    - type: accuracy
-      value: 13.948928408572733
-    - type: f1
-      value: 8.562615846233708
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/mtop_intent
-      name: MTEB MTOPIntentClassification (de)
-      config: de
-      split: test
-      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
-    metrics:
-    - type: accuracy
-      value: 11.814595660749507
-    - type: f1
-      value: 5.353787568647624
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/mtop_intent
-      name: MTEB MTOPIntentClassification (es)
-      config: es
-      split: test
-      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
-    metrics:
-    - type: accuracy
-      value: 12.468312208138759
-    - type: f1
-      value: 7.566990405355253
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/mtop_intent
-      name: MTEB MTOPIntentClassification (fr)
-      config: fr
-      split: test
-      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
-    metrics:
-    - type: accuracy
-      value: 9.320388349514563
-    - type: f1
-      value: 5.916218245687591
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/mtop_intent
-      name: MTEB MTOPIntentClassification (hi)
-      config: hi
-      split: test
-      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
-    metrics:
-    - type: accuracy
-      value: 3.2377196127644314
-    - type: f1
-      value: 1.2053714075016808
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/mtop_intent
-      name: MTEB MTOPIntentClassification (th)
-      config: th
-      split: test
-      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
-    metrics:
-    - type: accuracy
-      value: 4.4159132007233275
-    - type: f1
-      value: 1.1992998118559788
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/amazon_massive_intent
-      name: MTEB MassiveIntentClassification (it)
-      config: it
-      split: test
-      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
-    metrics:
-    - type: accuracy
-      value: 22.299932750504368
-    - type: f1
-      value: 20.147804322480262
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/amazon_massive_scenario
-      name: MTEB MassiveScenarioClassification (it)
-      config: it
-      split: test
-      revision: 7d571f92784cd94a019292a1f45445077d0ef634
-    metrics:
-    - type: accuracy
-      value: 27.40753194351042
-    - type: f1
-      value: 25.187141587127705
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/medrxiv-clustering-p2p
-      name: MTEB MedrxivClusteringP2P
-      config: default
-      split: test
-      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
-    metrics:
-    - type: v_measure
-      value: 11.797082944399047
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/medrxiv-clustering-s2s
-      name: MTEB MedrxivClusteringS2S
-      config: default
-      split: test
-      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
-    metrics:
-    - type: v_measure
-      value: 11.059126362649126
-  - task:
-      type: Reranking
-    dataset:
-      type: mteb/mind_small
-      name: MTEB MindSmallReranking
-      config: default
-      split: test
-      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
-    metrics:
-    - type: map
-      value: 24.452301182586798
-    - type: mrr
-      value: 24.374807287562085
-  - task:
-      type: Retrieval
-    dataset:
-      type: nfcorpus
-      name: MTEB NFCorpus
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 0.03
-    - type: map_at_10
-      value: 0.075
-    - type: map_at_100
-      value: 0.208
-    - type: map_at_1000
-      value: 0.529
-    - type: map_at_3
-      value: 0.051000000000000004
-    - type: map_at_5
-      value: 0.055999999999999994
-    - type: mrr_at_1
-      value: 1.238
-    - type: mrr_at_10
-      value: 2.939
-    - type: mrr_at_100
-      value: 3.927
-    - type: mrr_at_1000
-      value: 4.117
-    - type: mrr_at_3
-      value: 1.806
-    - type: mrr_at_5
-      value: 2.286
-    - type: ndcg_at_1
-      value: 1.084
-    - type: ndcg_at_10
-      value: 1.133
-    - type: ndcg_at_100
-      value: 2.1399999999999997
-    - type: ndcg_at_1000
-      value: 9.362
-    - type: ndcg_at_3
-      value: 0.9299999999999999
-    - type: ndcg_at_5
-      value: 0.958
-    - type: precision_at_1
-      value: 1.238
-    - type: precision_at_10
-      value: 1.269
-    - type: precision_at_100
-      value: 1.155
-    - type: precision_at_1000
-      value: 1.0250000000000001
-    - type: precision_at_3
-      value: 1.032
-    - type: precision_at_5
-      value: 1.053
-    - type: recall_at_1
-      value: 0.03
-    - type: recall_at_10
-      value: 0.22200000000000003
-    - type: recall_at_100
-      value: 3.779
-    - type: recall_at_1000
-      value: 29.471000000000004
-    - type: recall_at_3
-      value: 0.087
-    - type: recall_at_5
-      value: 0.11199999999999999
-  - task:
-      type: Retrieval
-    dataset:
-      type: nq
-      name: MTEB NQ
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 0.0
-    - type: map_at_10
-      value: 0.012
-    - type: map_at_100
-      value: 0.025
-    - type: map_at_1000
-      value: 0.027
-    - type: map_at_3
-      value: 0.0
-    - type: map_at_5
-      value: 0.006999999999999999
-    - type: mrr_at_1
-      value: 0.0
-    - type: mrr_at_10
-      value: 0.012
-    - type: mrr_at_100
-      value: 0.026
-    - type: mrr_at_1000
-      value: 0.029
-    - type: mrr_at_3
-      value: 0.0
-    - type: mrr_at_5
-      value: 0.006999999999999999
-    - type: ndcg_at_1
-      value: 0.0
-    - type: ndcg_at_10
-      value: 0.023
-    - type: ndcg_at_100
-      value: 0.092
-    - type: ndcg_at_1000
-      value: 0.16999999999999998
-    - type: ndcg_at_3
-      value: 0.0
-    - type: ndcg_at_5
-      value: 0.012
-    - type: precision_at_1
-      value: 0.0
-    - type: precision_at_10
-      value: 0.006
-    - type: precision_at_100
-      value: 0.004
-    - type: precision_at_1000
-      value: 0.001
-    - type: precision_at_3
-      value: 0.0
-    - type: precision_at_5
-      value: 0.006
-    - type: recall_at_1
-      value: 0.0
-    - type: recall_at_10
-      value: 0.058
-    - type: recall_at_100
-      value: 0.377
-    - type: recall_at_1000
-      value: 1.009
-    - type: recall_at_3
-      value: 0.0
-    - type: recall_at_5
-      value: 0.029
-  - task:
-      type: Retrieval
-    dataset:
-      type: quora
-      name: MTEB QuoraRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 8.943
-    - type: map_at_10
-      value: 10.557
-    - type: map_at_100
-      value: 10.777000000000001
-    - type: map_at_1000
-      value: 10.812
-    - type: map_at_3
-      value: 10.137
-    - type: map_at_5
-      value: 10.351
-    - type: mrr_at_1
-      value: 10.51
-    - type: mrr_at_10
-      value: 12.229
-    - type: mrr_at_100
-      value: 12.468
-    - type: mrr_at_1000
-      value: 12.504999999999999
-    - type: mrr_at_3
-      value: 11.777
-    - type: mrr_at_5
-      value: 12.014
-    - type: ndcg_at_1
-      value: 10.5
-    - type: ndcg_at_10
-      value: 11.715
-    - type: ndcg_at_100
-      value: 12.925
-    - type: ndcg_at_1000
-      value: 14.163
-    - type: ndcg_at_3
-      value: 10.968
-    - type: ndcg_at_5
-      value: 11.264000000000001
-    - type: precision_at_1
-      value: 10.5
-    - type: precision_at_10
-      value: 1.696
-    - type: precision_at_100
-      value: 0.248
-    - type: precision_at_1000
-      value: 0.039
-    - type: precision_at_3
-      value: 4.623
-    - type: precision_at_5
-      value: 3.012
-    - type: recall_at_1
-      value: 8.943
-    - type: recall_at_10
-      value: 13.746
-    - type: recall_at_100
-      value: 19.521
-    - type: recall_at_1000
-      value: 29.255
-    - type: recall_at_3
-      value: 11.448
-    - type: recall_at_5
-      value: 12.332
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/reddit-clustering
-      name: MTEB RedditClustering
-      config: default
-      split: test
-      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
-    metrics:
-    - type: v_measure
-      value: 4.845410629021448
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/reddit-clustering-p2p
-      name: MTEB RedditClusteringP2P
-      config: default
-      split: test
-      revision: 282350215ef01743dc01b456c7f5241fa8937f16
-    metrics:
-    - type: v_measure
-      value: 11.661900277329933
-  - task:
-      type: Retrieval
-    dataset:
-      type: scidocs
-      name: MTEB SCIDOCS
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 0.02
-    - type: map_at_10
-      value: 0.036000000000000004
-    - type: map_at_100
-      value: 0.056999999999999995
-    - type: map_at_1000
-      value: 0.07200000000000001
-    - type: map_at_3
-      value: 0.03
-    - type: map_at_5
-      value: 0.03
-    - type: mrr_at_1
-      value: 0.1
-    - type: mrr_at_10
-      value: 0.181
-    - type: mrr_at_100
-      value: 0.27899999999999997
-    - type: mrr_at_1000
-      value: 0.335
-    - type: mrr_at_3
-      value: 0.15
-    - type: mrr_at_5
-      value: 0.15
-    - type: ndcg_at_1
-      value: 0.1
-    - type: ndcg_at_10
-      value: 0.079
-    - type: ndcg_at_100
-      value: 0.28200000000000003
-    - type: ndcg_at_1000
-      value: 1.228
-    - type: ndcg_at_3
-      value: 0.077
-    - type: ndcg_at_5
-      value: 0.055
-    - type: precision_at_1
-      value: 0.1
-    - type: precision_at_10
-      value: 0.04
-    - type: precision_at_100
-      value: 0.034
-    - type: precision_at_1000
-      value: 0.027999999999999997
-    - type: precision_at_3
-      value: 0.067
-    - type: precision_at_5
-      value: 0.04
-    - type: recall_at_1
-      value: 0.02
-    - type: recall_at_10
-      value: 0.08
-    - type: recall_at_100
-      value: 0.703
-    - type: recall_at_1000
-      value: 5.632000000000001
-    - type: recall_at_3
-      value: 0.04
-    - type: recall_at_5
-      value: 0.04
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sickr-sts
-      name: MTEB SICK-R
-      config: default
-      split: test
-      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
-    metrics:
-    - type: cos_sim_pearson
-      value: 22.985682461739827
-    - type: cos_sim_spearman
-      value: 36.63211990852576
-    - type: euclidean_pearson
-      value: 30.883409587497358
-    - type: euclidean_spearman
-      value: 36.94600975857584
-    - type: manhattan_pearson
-      value: 36.736693988156894
-    - type: manhattan_spearman
-      value: 38.98446799028811
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts12-sts
-      name: MTEB STS12
-      config: default
-      split: test
-      revision: a0d554a64d88156834ff5ae9920b964011b16384
-    metrics:
-    - type: cos_sim_pearson
-      value: 2.5604178523517063
-    - type: cos_sim_spearman
-      value: 13.628378324133767
-    - type: euclidean_pearson
-      value: 7.9904894312005865
-    - type: euclidean_spearman
-      value: 15.090689818973416
-    - type: manhattan_pearson
-      value: 14.011092205465575
-    - type: manhattan_spearman
-      value: 18.04386210573924
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts13-sts
-      name: MTEB STS13
-      config: default
-      split: test
-      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
-    metrics:
-    - type: cos_sim_pearson
-      value: 18.59414271348264
-    - type: cos_sim_spearman
-      value: 23.758346452530105
-    - type: euclidean_pearson
-      value: 22.985667268384162
-    - type: euclidean_spearman
-      value: 25.143580728437183
-    - type: manhattan_pearson
-      value: 28.109316236003
-    - type: manhattan_spearman
-      value: 29.403691387442727
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts14-sts
-      name: MTEB STS14
-      config: default
-      split: test
-      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
-    metrics:
-    - type: cos_sim_pearson
-      value: 8.292349216262673
-    - type: cos_sim_spearman
-      value: 15.648383623810028
-    - type: euclidean_pearson
-      value: 12.136605941196938
-    - type: euclidean_spearman
-      value: 16.37547051924145
-    - type: manhattan_pearson
-      value: 21.049918496319524
-    - type: manhattan_spearman
-      value: 22.168125518695295
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts15-sts
-      name: MTEB STS15
-      config: default
-      split: test
-      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
-    metrics:
-    - type: cos_sim_pearson
-      value: 21.0574858763695
-    - type: cos_sim_spearman
-      value: 28.24306393347735
-    - type: euclidean_pearson
-      value: 25.67620587891895
-    - type: euclidean_spearman
-      value: 28.802005577995292
-    - type: manhattan_pearson
-      value: 33.333168689238846
-    - type: manhattan_spearman
-      value: 33.7249701052437
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts16-sts
-      name: MTEB STS16
-      config: default
-      split: test
-      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
-    metrics:
-    - type: cos_sim_pearson
-      value: 23.345013082866608
-    - type: cos_sim_spearman
-      value: 32.08654087568418
-    - type: euclidean_pearson
-      value: 29.1302480053082
-    - type: euclidean_spearman
-      value: 32.723960824054224
-    - type: manhattan_pearson
-      value: 34.73363269084969
-    - type: manhattan_spearman
-      value: 35.946509333697016
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts17-crosslingual-sts
-      name: MTEB STS17 (ko-ko)
-      config: ko-ko
-      split: test
-      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
-    metrics:
-    - type: cos_sim_pearson
-      value: -1.0510693376748088
-    - type: cos_sim_spearman
-      value: 3.7330446273344897
-    - type: euclidean_pearson
-      value: -0.2108306777168949
-    - type: euclidean_spearman
-      value: 3.627369552634812
-    - type: manhattan_pearson
-      value: 1.5031538964733262
-    - type: manhattan_spearman
-      value: 5.004910973166412
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts17-crosslingual-sts
-      name: MTEB STS17 (ar-ar)
-      config: ar-ar
-      split: test
-      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
-    metrics:
-    - type: cos_sim_pearson
-      value: 11.578393453214481
-    - type: cos_sim_spearman
-      value: 21.790827126422034
-    - type: euclidean_pearson
-      value: 19.06071141618503
-    - type: euclidean_spearman
-      value: 22.161779839314196
-    - type: manhattan_pearson
-      value: 17.725623325242474
-    - type: manhattan_spearman
-      value: 20.43157514666076
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts17-crosslingual-sts
-      name: MTEB STS17 (en-ar)
-      config: en-ar
-      split: test
-      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
-    metrics:
-    - type: cos_sim_pearson
-      value: 17.29239442081278
-    - type: cos_sim_spearman
-      value: 16.292056207420202
-    - type: euclidean_pearson
-      value: 16.503491974377727
-    - type: euclidean_spearman
-      value: 15.541440440884651
-    - type: manhattan_pearson
-      value: 21.158901085317268
-    - type: manhattan_spearman
-      value: 21.781541830999963
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts17-crosslingual-sts
-      name: MTEB STS17 (en-de)
-      config: en-de
-      split: test
-      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
-    metrics:
-    - type: cos_sim_pearson
-      value: 22.589778414759955
-    - type: cos_sim_spearman
-      value: 18.997838545450612
-    - type: euclidean_pearson
-      value: 21.90016323186628
-    - type: euclidean_spearman
-      value: 18.905160536986692
-    - type: manhattan_pearson
-      value: 16.913499882046576
-    - type: manhattan_spearman
-      value: 15.669617887287327
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts17-crosslingual-sts
-      name: MTEB STS17 (en-en)
-      config: en-en
-      split: test
-      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
-    metrics:
-    - type: cos_sim_pearson
-      value: 33.05366168385912
-    - type: cos_sim_spearman
-      value: 37.781952608504135
-    - type: euclidean_pearson
-      value: 37.085941074268966
-    - type: euclidean_spearman
-      value: 37.8364215997913
-    - type: manhattan_pearson
-      value: 42.316206028770736
-    - type: manhattan_spearman
-      value: 41.74208275697782
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts17-crosslingual-sts
-      name: MTEB STS17 (en-tr)
-      config: en-tr
-      split: test
-      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
-    metrics:
-    - type: cos_sim_pearson
-      value: 23.991765076225654
-    - type: cos_sim_spearman
-      value: 20.588105042260104
-    - type: euclidean_pearson
-      value: 19.712724760717997
-    - type: euclidean_spearman
-      value: 19.253030106327383
-    - type: manhattan_pearson
-      value: 16.84198288544301
-    - type: manhattan_spearman
-      value: 17.61549197324614
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts17-crosslingual-sts
-      name: MTEB STS17 (es-en)
-      config: es-en
-      split: test
-      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
-    metrics:
-    - type: cos_sim_pearson
-      value: 24.968980346008365
-    - type: cos_sim_spearman
-      value: 27.252856647926286
-    - type: euclidean_pearson
-      value: 24.58496162769602
-    - type: euclidean_spearman
-      value: 26.034323771297824
-    - type: manhattan_pearson
-      value: 22.40058722998031
-    - type: manhattan_spearman
-      value: 24.459230575688714
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts17-crosslingual-sts
-      name: MTEB STS17 (es-es)
-      config: es-es
-      split: test
-      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
-    metrics:
-    - type: cos_sim_pearson
-      value: 32.94464820482554
-    - type: cos_sim_spearman
-      value: 40.462017863354085
-    - type: euclidean_pearson
-      value: 38.88676423326504
-    - type: euclidean_spearman
-      value: 40.47190508444464
-    - type: manhattan_pearson
-      value: 39.692234741895874
-    - type: manhattan_spearman
-      value: 39.478725017400166
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts17-crosslingual-sts
-      name: MTEB STS17 (fr-en)
-      config: fr-en
-      split: test
-      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
-    metrics:
-    - type: cos_sim_pearson
-      value: 23.342163445031748
-    - type: cos_sim_spearman
-      value: 27.27097487628386
-    - type: euclidean_pearson
-      value: 24.76789948947651
-    - type: euclidean_spearman
-      value: 25.81926286149811
-    - type: manhattan_pearson
-      value: 25.475723026689685
-    - type: manhattan_spearman
-      value: 25.813420033921787
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts17-crosslingual-sts
-      name: MTEB STS17 (it-en)
-      config: it-en
-      split: test
-      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
-    metrics:
-    - type: cos_sim_pearson
-      value: 7.717130622537516
-    - type: cos_sim_spearman
-      value: 9.437435044381033
-    - type: euclidean_pearson
-      value: 7.9423592614250555
-    - type: euclidean_spearman
-      value: 8.010785684725303
-    - type: manhattan_pearson
-      value: 8.217253457576026
-    - type: manhattan_spearman
-      value: 8.247881477427692
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts17-crosslingual-sts
-      name: MTEB STS17 (nl-en)
-      config: nl-en
-      split: test
-      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
-    metrics:
-    - type: cos_sim_pearson
-      value: 16.16499446427259
-    - type: cos_sim_spearman
-      value: 17.21754435880688
-    - type: euclidean_pearson
-      value: 16.325415307049443
-    - type: euclidean_spearman
-      value: 16.293339731059863
-    - type: manhattan_pearson
-      value: 19.410680542804005
-    - type: manhattan_spearman
-      value: 18.95736158862253
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts22-crosslingual-sts
-      name: MTEB STS22 (it)
-      config: it
-      split: test
-      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
-    metrics:
-    - type: cos_sim_pearson
-      value: 30.67175493186678
-    - type: cos_sim_spearman
-      value: 37.92638638971281
-    - type: euclidean_pearson
-      value: 37.47072224334179
-    - type: euclidean_spearman
-      value: 39.23036609148336
-    - type: manhattan_pearson
-      value: 42.92657347688227
-    - type: manhattan_spearman
-      value: 43.93955531904934
-  - task:
-      type: STS
-    dataset:
-      type: mteb/stsbenchmark-sts
-      name: MTEB STSBenchmark
-      config: default
-      split: test
-      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
-    metrics:
-    - type: cos_sim_pearson
-      value: 15.51842992576514
-    - type: cos_sim_spearman
-      value: 22.738964472371965
-    - type: euclidean_pearson
-      value: 20.68981398028433
-    - type: euclidean_spearman
-      value: 23.35518754871016
-    - type: manhattan_pearson
-      value: 26.488467867333142
-    - type: manhattan_spearman
-      value: 27.318174781418055
-  - task:
-      type: Reranking
-    dataset:
-      type: mteb/scidocs-reranking
-      name: MTEB SciDocsRR
-      config: default
-      split: test
-      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
-    metrics:
-    - type: map
-      value: 30.728870040728083
-    - type: mrr
-      value: 45.1852849401869
-  - task:
-      type: Retrieval
-    dataset:
-      type: scifact
-      name: MTEB SciFact
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 0.0
-    - type: map_at_10
-      value: 0.104
-    - type: map_at_100
-      value: 0.265
-    - type: map_at_1000
-      value: 0.334
-    - type: map_at_3
-      value: 0.0
-    - type: map_at_5
-      value: 0.067
-    - type: mrr_at_1
-      value: 0.0
-    - type: mrr_at_10
-      value: 0.104
-    - type: mrr_at_100
-      value: 0.27
-    - type: mrr_at_1000
-      value: 0.345
-    - type: mrr_at_3
-      value: 0.0
-    - type: mrr_at_5
-      value: 0.067
-    - type: ndcg_at_1
-      value: 0.0
-    - type: ndcg_at_10
-      value: 0.22899999999999998
-    - type: ndcg_at_100
-      value: 1.044
-    - type: ndcg_at_1000
-      value: 3.911
-    - type: ndcg_at_3
-      value: 0.0
-    - type: ndcg_at_5
-      value: 0.129
-    - type: precision_at_1
-      value: 0.0
-    - type: precision_at_10
-      value: 0.067
-    - type: precision_at_100
-      value: 0.05
-    - type: precision_at_1000
-      value: 0.032
-    - type: precision_at_3
-      value: 0.0
-    - type: precision_at_5
-      value: 0.067
-    - type: recall_at_1
-      value: 0.0
-    - type: recall_at_10
-      value: 0.6669999999999999
-    - type: recall_at_100
-      value: 4.583
-    - type: recall_at_1000
-      value: 28.910999999999998
-    - type: recall_at_3
-      value: 0.0
-    - type: recall_at_5
-      value: 0.333
-  - task:
-      type: PairClassification
-    dataset:
-      type: mteb/sprintduplicatequestions-pairclassification
-      name: MTEB SprintDuplicateQuestions
-      config: default
-      split: test
-      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
-    metrics:
-    - type: cos_sim_accuracy
-      value: 99.01089108910891
-    - type: cos_sim_ap
-      value: 2.649295518982714
-    - type: cos_sim_f1
-      value: 6.26322471434617
-    - type: cos_sim_precision
-      value: 3.972088030059045
-    - type: cos_sim_recall
-      value: 14.799999999999999
-    - type: dot_accuracy
-      value: 99.0089108910891
-    - type: dot_ap
-      value: 1.713700413108619
-    - type: dot_f1
-      value: 5.073705862187179
-    - type: dot_precision
-      value: 3.061646669424907
-    - type: dot_recall
-      value: 14.799999999999999
-    - type: euclidean_accuracy
-      value: 99.01089108910891
-    - type: euclidean_ap
-      value: 2.744099763470491
-    - type: euclidean_f1
-      value: 6.291706387035273
-    - type: euclidean_precision
-      value: 4.611085235211924
-    - type: euclidean_recall
-      value: 9.9
-    - type: manhattan_accuracy
-      value: 99.01089108910891
-    - type: manhattan_ap
-      value: 3.2781717730991327
-    - type: manhattan_f1
-      value: 7.68245838668374
-    - type: manhattan_precision
-      value: 10.676156583629894
-    - type: manhattan_recall
-      value: 6.0
-    - type: max_accuracy
-      value: 99.01089108910891
-    - type: max_ap
-      value: 3.2781717730991327
-    - type: max_f1
-      value: 7.68245838668374
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/stackexchange-clustering
-      name: MTEB StackExchangeClustering
-      config: default
-      split: test
-      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
-    metrics:
-    - type: v_measure
-      value: 8.602221384568187
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/stackexchange-clustering-p2p
-      name: MTEB StackExchangeClusteringP2P
-      config: default
-      split: test
-      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
-    metrics:
-    - type: v_measure
-      value: 25.619483506865205
-  - task:
-      type: Reranking
-    dataset:
-      type: mteb/stackoverflowdupquestions-reranking
-      name: MTEB StackOverflowDupQuestions
-      config: default
-      split: test
-      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
-    metrics:
-    - type: map
-      value: 20.02237719216371
-    - type: mrr
-      value: 18.132453739071387
-  - task:
-      type: Retrieval
-    dataset:
-      type: trec-covid
-      name: MTEB TRECCOVID
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 0.004
-    - type: map_at_10
-      value: 0.009000000000000001
-    - type: map_at_100
-      value: 0.011000000000000001
-    - type: map_at_1000
-      value: 0.016
-    - type: map_at_3
-      value: 0.004
-    - type: map_at_5
-      value: 0.006999999999999999
-    - type: mrr_at_1
-      value: 2.0
-    - type: mrr_at_10
-      value: 4.233
-    - type: mrr_at_100
-      value: 4.936
-    - type: mrr_at_1000
-      value: 5.103
-    - type: mrr_at_3
-      value: 2.0
-    - type: mrr_at_5
-      value: 3.9
-    - type: ndcg_at_1
-      value: 1.0
-    - type: ndcg_at_10
-      value: 1.1039999999999999
-    - type: ndcg_at_100
-      value: 0.486
-    - type: ndcg_at_1000
-      value: 0.666
-    - type: ndcg_at_3
-      value: 0.469
-    - type: ndcg_at_5
-      value: 1.347
-    - type: precision_at_1
-      value: 2.0
-    - type: precision_at_10
-      value: 1.4000000000000001
-    - type: precision_at_100
-      value: 0.52
-    - type: precision_at_1000
-      value: 0.37
-    - type: precision_at_3
-      value: 0.6669999999999999
-    - type: precision_at_5
-      value: 2.0
-    - type: recall_at_1
-      value: 0.004
-    - type: recall_at_10
-      value: 0.024
-    - type: recall_at_100
-      value: 0.09
-    - type: recall_at_1000
-      value: 0.807
-    - type: recall_at_3
-      value: 0.004
-    - type: recall_at_5
-      value: 0.016
-  - task:
-      type: Retrieval
-    dataset:
-      type: webis-touche2020
-      name: MTEB Touche2020
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 0.0
-    - type: map_at_10
-      value: 0.0
-    - type: map_at_100
-      value: 0.0
-    - type: map_at_1000
-      value: 0.0
-    - type: map_at_3
-      value: 0.0
-    - type: map_at_5
-      value: 0.0
-    - type: mrr_at_1
-      value: 0.0
-    - type: mrr_at_10
-      value: 0.0
-    - type: mrr_at_100
-      value: 0.0
-    - type: mrr_at_1000
-      value: 0.0
-    - type: mrr_at_3
-      value: 0.0
-    - type: mrr_at_5
-      value: 0.0
-    - type: ndcg_at_1
-      value: 0.0
-    - type: ndcg_at_10
-      value: 0.0
-    - type: ndcg_at_100
-      value: 0.0
-    - type: ndcg_at_1000
-      value: 0.0
-    - type: ndcg_at_3
-      value: 0.0
-    - type: ndcg_at_5
-      value: 0.0
-    - type: precision_at_1
-      value: 0.0
-    - type: precision_at_10
-      value: 0.0
-    - type: precision_at_100
-      value: 0.0
-    - type: precision_at_1000
-      value: 0.0
-    - type: precision_at_3
-      value: 0.0
-    - type: precision_at_5
-      value: 0.0
-    - type: recall_at_1
-      value: 0.0
-    - type: recall_at_10
-      value: 0.0
-    - type: recall_at_100
-      value: 0.0
-    - type: recall_at_1000
-      value: 0.0
-    - type: recall_at_3
-      value: 0.0
-    - type: recall_at_5
-      value: 0.0
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/toxic_conversations_50k
-      name: MTEB ToxicConversationsClassification
-      config: default
-      split: test
-      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
-    metrics:
-    - type: accuracy
-      value: 55.065799999999996
-    - type: ap
-      value: 8.3123142340845
-    - type: f1
-      value: 41.78797425886187
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/tweet_sentiment_extraction
-      name: MTEB TweetSentimentExtractionClassification
-      config: default
-      split: test
-      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
-    metrics:
-    - type: accuracy
-      value: 41.177136389360506
-    - type: f1
-      value: 40.882588170909244
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/twentynewsgroups-clustering
-      name: MTEB TwentyNewsgroupsClustering
-      config: default
-      split: test
-      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
-    metrics:
-    - type: v_measure
-      value: 10.046104242285523
-  - task:
-      type: PairClassification
-    dataset:
-      type: mteb/twittersemeval2015-pairclassification
-      name: MTEB TwitterSemEval2015
-      config: default
-      split: test
-      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
-    metrics:
-    - type: cos_sim_accuracy
-      value: 77.63604935328128
-    - type: cos_sim_ap
-      value: 32.380569186976906
-    - type: cos_sim_f1
-      value: 38.29160530191458
-    - type: cos_sim_precision
-      value: 27.110086708374492
-    - type: cos_sim_recall
-      value: 65.17150395778364
-    - type: dot_accuracy
-      value: 77.40954878702986
-    - type: dot_ap
-      value: 28.34039741384004
-    - type: dot_f1
-      value: 37.45059908412271
-    - type: dot_precision
-      value: 24.565879351493706
-    - type: dot_recall
-      value: 78.7598944591029
-    - type: euclidean_accuracy
-      value: 77.63604935328128
-    - type: euclidean_ap
-      value: 32.40705726976434
-    - type: euclidean_f1
-      value: 38.365584519430676
-    - type: euclidean_precision
-      value: 27.524093620927033
-    - type: euclidean_recall
-      value: 63.298153034300796
-    - type: manhattan_accuracy
-      value: 77.70757584788699
-    - type: manhattan_ap
-      value: 33.03410839977045
-    - type: manhattan_f1
-      value: 39.04353514063523
-    - type: manhattan_precision
-      value: 26.943524927274552
-    - type: manhattan_recall
-      value: 70.87071240105541
-    - type: max_accuracy
-      value: 77.70757584788699
-    - type: max_ap
-      value: 33.03410839977045
-    - type: max_f1
-      value: 39.04353514063523
-  - task:
-      type: PairClassification
-    dataset:
-      type: mteb/twitterurlcorpus-pairclassification
-      name: MTEB TwitterURLCorpus
-      config: default
-      split: test
-      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
-    metrics:
-    - type: cos_sim_accuracy
-      value: 75.80626382582373
-    - type: cos_sim_ap
-      value: 41.94768516713251
-    - type: cos_sim_f1
-      value: 44.69374385849984
-    - type: cos_sim_precision
-      value: 34.620263870094725
-    - type: cos_sim_recall
-      value: 63.035109331690784
-    - type: dot_accuracy
-      value: 74.79528078550084
-    - type: dot_ap
-      value: 33.69361208467778
-    - type: dot_f1
-      value: 44.620064092118845
-    - type: dot_precision
-      value: 34.467567340773684
-    - type: dot_recall
-      value: 63.250692947336006
-    - type: euclidean_accuracy
-      value: 75.98866767570924
-    - type: euclidean_ap
-      value: 42.65497342948604
-    - type: euclidean_f1
-      value: 44.794497753619176
-    - type: euclidean_precision
-      value: 35.006501950585175
-    - type: euclidean_recall
-      value: 62.180474283954425
-    - type: manhattan_accuracy
-      value: 76.37870143982613
-    - type: manhattan_ap
-      value: 46.65401496383161
-    - type: manhattan_f1
-      value: 48.14085011643678
-    - type: manhattan_precision
-      value: 36.0535091417839
-    - type: manhattan_recall
-      value: 72.42069602710194
-    - type: max_accuracy
-      value: 76.37870143982613
-    - type: max_ap
-      value: 46.65401496383161
-    - type: max_f1
-      value: 48.14085011643678
----
 pipeline_tag: sentence-similarity
 tags:
 - sentence-transformers