diff --git "a/README.md" "b/README.md"
--- "a/README.md"
+++ "b/README.md"
@@ -101,6 +101,21419 @@ language:
   - zh
 inference: false
 library_name: transformers
+model-index:
+- name: jina-embeddings-v3
+  results:
+  - dataset:
+      config: default
+      name: MTEB AFQMC (default)
+      revision: b44c3b011063adb25877c13823db83bb193913c4
+      split: validation
+      type: C-MTEB/AFQMC
+    metrics:
+    - type: cosine_pearson
+      value: 41.74237700998808
+    - type: cosine_spearman
+      value: 43.4726782647566
+    - type: euclidean_pearson
+      value: 42.244585459479964
+    - type: euclidean_spearman
+      value: 43.525070045169606
+    - type: main_score
+      value: 43.4726782647566
+    - type: manhattan_pearson
+      value: 42.04616728224863
+    - type: manhattan_spearman
+      value: 43.308828270754645
+    - type: pearson
+      value: 41.74237700998808
+    - type: spearman
+      value: 43.4726782647566
+    task:
+      type: STS
+  - dataset:
+      config: default
+      name: MTEB ATEC (default)
+      revision: 0f319b1142f28d00e055a6770f3f726ae9b7d865
+      split: test
+      type: C-MTEB/ATEC
+    metrics:
+    - type: cosine_pearson
+      value: 47.541497334563296
+    - type: cosine_spearman
+      value: 49.06268944206629
+    - type: euclidean_pearson
+      value: 51.838926748581635
+    - type: euclidean_spearman
+      value: 48.930697157135356
+    - type: main_score
+      value: 49.06268944206629
+    - type: manhattan_pearson
+      value: 51.835306769406365
+    - type: manhattan_spearman
+      value: 48.86135493444834
+    - type: pearson
+      value: 47.541497334563296
+    - type: spearman
+      value: 49.06268944206629
+    task:
+      type: STS
+  - dataset:
+      config: default
+      name: MTEB AllegroReviews (default)
+      revision: b89853e6de927b0e3bfa8ecc0e56fe4e02ceafc6
+      split: test
+      type: PL-MTEB/allegro-reviews
+    metrics:
+    - type: accuracy
+      value: 49.51292246520874
+    - type: f1
+      value: 44.14350234332397
+    - type: f1_weighted
+      value: 51.65508998354552
+    - type: main_score
+      value: 49.51292246520874
+    task:
+      type: Classification
+  - dataset:
+      config: default
+      name: MTEB AlloProfClusteringP2P (default)
+      revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b
+      split: test
+      type: lyon-nlp/alloprof
+    metrics:
+    - type: main_score
+      value: 63.883383458621665
+    - type: v_measure
+      value: 63.883383458621665
+    - type: v_measure_std
+      value: 2.693666879958465
+    task:
+      type: Clustering
+  - dataset:
+      config: default
+      name: MTEB AlloProfClusteringS2S (default)
+      revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b
+      split: test
+      type: lyon-nlp/alloprof
+    metrics:
+    - type: main_score
+      value: 46.85924588755251
+    - type: v_measure
+      value: 46.85924588755251
+    - type: v_measure_std
+      value: 2.1918258880872377
+    task:
+      type: Clustering
+  - dataset:
+      config: default
+      name: MTEB AlloprofReranking (default)
+      revision: e40c8a63ce02da43200eccb5b0846fcaa888f562
+      split: test
+      type: lyon-nlp/mteb-fr-reranking-alloprof-s2p
+    metrics:
+    - type: map
+      value: 66.39013753839347
+    - type: mrr
+      value: 67.68045617786551
+    - type: main_score
+      value: 66.39013753839347
+    task:
+      type: Reranking
+  - dataset:
+      config: default
+      name: MTEB AlloprofRetrieval (default)
+      revision: fcf295ea64c750f41fadbaa37b9b861558e1bfbd
+      split: test
+      type: lyon-nlp/alloprof
+    metrics:
+    - type: main_score
+      value: 54.284
+    - type: map_at_1
+      value: 37.047000000000004
+    - type: map_at_10
+      value: 48.53
+    - type: map_at_100
+      value: 49.357
+    - type: map_at_1000
+      value: 49.39
+    - type: map_at_20
+      value: 49.064
+    - type: map_at_3
+      value: 45.675
+    - type: map_at_5
+      value: 47.441
+    - type: mrr_at_1
+      value: 37.04663212435233
+    - type: mrr_at_10
+      value: 48.5300326232969
+    - type: mrr_at_100
+      value: 49.35708199037581
+    - type: mrr_at_1000
+      value: 49.39005824603193
+    - type: mrr_at_20
+      value: 49.06417416464799
+    - type: mrr_at_3
+      value: 45.67501439263105
+    - type: mrr_at_5
+      value: 47.44099021301103
+    - type: nauc_map_at_1000_diff1
+      value: 43.32474221868009
+    - type: nauc_map_at_1000_max
+      value: 39.407334029058575
+    - type: nauc_map_at_1000_std
+      value: -2.3728154448932606
+    - type: nauc_map_at_100_diff1
+      value: 43.32336300929909
+    - type: nauc_map_at_100_max
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+    - type: nauc_map_at_100_std
+      value: -2.356396922384349
+    - type: nauc_map_at_10_diff1
+      value: 43.1606520154482
+    - type: nauc_map_at_10_max
+      value: 39.33734650558226
+    - type: nauc_map_at_10_std
+      value: -2.5156222475075256
+    - type: nauc_map_at_1_diff1
+      value: 46.2178975214499
+    - type: nauc_map_at_1_max
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+      value: -2.3728154448932606
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+    - type: nauc_mrr_at_10_max
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+    - type: nauc_mrr_at_1_max
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+    - type: nauc_mrr_at_20_max
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+    - type: ndcg_at_1
+      value: 37.047000000000004
+    - type: ndcg_at_10
+      value: 54.284
+    - type: ndcg_at_100
+      value: 58.34
+    - type: ndcg_at_1000
+      value: 59.303
+    - type: ndcg_at_20
+      value: 56.235
+    - type: ndcg_at_3
+      value: 48.503
+    - type: ndcg_at_5
+      value: 51.686
+    - type: precision_at_1
+      value: 37.047000000000004
+    - type: precision_at_10
+      value: 7.237
+    - type: precision_at_100
+      value: 0.914
+    - type: precision_at_1000
+      value: 0.099
+    - type: precision_at_20
+      value: 4.005
+    - type: precision_at_3
+      value: 18.898
+    - type: precision_at_5
+      value: 12.884
+    - type: recall_at_1
+      value: 37.047000000000004
+    - type: recall_at_10
+      value: 72.366
+    - type: recall_at_100
+      value: 91.408
+    - type: recall_at_1000
+      value: 99.136
+    - type: recall_at_20
+      value: 80.095
+    - type: recall_at_3
+      value: 56.693000000000005
+    - type: recall_at_5
+      value: 64.42099999999999
+    task:
+      type: Retrieval
+  - dataset:
+      config: en
+      name: MTEB AmazonCounterfactualClassification (en)
+      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
+      split: test
+      type: mteb/amazon_counterfactual
+    metrics:
+    - type: accuracy
+      value: 89.49253731343283
+    - type: ap
+      value: 61.88098616359918
+    - type: ap_weighted
+      value: 61.88098616359918
+    - type: f1
+      value: 84.76516623679144
+    - type: f1_weighted
+      value: 89.92745276292968
+    - type: main_score
+      value: 89.49253731343283
+    task:
+      type: Classification
+  - dataset:
+      config: de
+      name: MTEB AmazonCounterfactualClassification (de)
+      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
+      split: test
+      type: mteb/amazon_counterfactual
+    metrics:
+    - type: accuracy
+      value: 89.61456102783727
+    - type: ap
+      value: 93.11816566733742
+    - type: ap_weighted
+      value: 93.11816566733742
+    - type: f1
+      value: 88.27635757733722
+    - type: f1_weighted
+      value: 89.82581568285453
+    - type: main_score
+      value: 89.61456102783727
+    task:
+      type: Classification
+  - dataset:
+      config: default
+      name: MTEB AmazonPolarityClassification (default)
+      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
+      split: test
+      type: mteb/amazon_polarity
+    metrics:
+    - type: accuracy
+      value: 95.3825
+    - type: ap
+      value: 93.393033869502
+    - type: ap_weighted
+      value: 93.393033869502
+    - type: f1
+      value: 95.38109007966307
+    - type: f1_weighted
+      value: 95.38109007966305
+    - type: main_score
+      value: 95.3825
+    task:
+      type: Classification
+  - dataset:
+      config: en
+      name: MTEB AmazonReviewsClassification (en)
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+      split: test
+      type: mteb/amazon_reviews_multi
+    metrics:
+    - type: accuracy
+      value: 49.768
+    - type: f1
+      value: 48.95084821944411
+    - type: f1_weighted
+      value: 48.9508482194441
+    - type: main_score
+      value: 49.768
+    task:
+      type: Classification
+  - dataset:
+      config: de
+      name: MTEB AmazonReviewsClassification (de)
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+      split: test
+      type: mteb/amazon_reviews_multi
+    metrics:
+    - type: accuracy
+      value: 48.071999999999996
+    - type: f1
+      value: 47.24171107487612
+    - type: f1_weighted
+      value: 47.24171107487612
+    - type: main_score
+      value: 48.071999999999996
+    task:
+      type: Classification
+  - dataset:
+      config: es
+      name: MTEB AmazonReviewsClassification (es)
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+      split: test
+      type: mteb/amazon_reviews_multi
+    metrics:
+    - type: accuracy
+      value: 48.102000000000004
+    - type: f1
+      value: 47.27193805278696
+    - type: f1_weighted
+      value: 47.27193805278696
+    - type: main_score
+      value: 48.102000000000004
+    task:
+      type: Classification
+  - dataset:
+      config: fr
+      name: MTEB AmazonReviewsClassification (fr)
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+      split: test
+      type: mteb/amazon_reviews_multi
+    metrics:
+    - type: accuracy
+      value: 47.30800000000001
+    - type: f1
+      value: 46.41683358017851
+    - type: f1_weighted
+      value: 46.41683358017851
+    - type: main_score
+      value: 47.30800000000001
+    task:
+      type: Classification
+  - dataset:
+      config: zh
+      name: MTEB AmazonReviewsClassification (zh)
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+      split: test
+      type: mteb/amazon_reviews_multi
+    metrics:
+    - type: accuracy
+      value: 44.944
+    - type: f1
+      value: 44.223824487744395
+    - type: f1_weighted
+      value: 44.22382448774439
+    - type: main_score
+      value: 44.944
+    task:
+      type: Classification
+  - dataset:
+      config: default
+      name: MTEB ArguAna (default)
+      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
+      split: test
+      type: mteb/arguana
+    metrics:
+    - type: map_at_1
+      value: 29.232000000000003
+    - type: map_at_10
+      value: 45.117000000000004
+    - type: map_at_100
+      value: 45.977000000000004
+    - type: map_at_1000
+      value: 45.98
+    - type: map_at_20
+      value: 45.815
+    - type: map_at_3
+      value: 39.912
+    - type: map_at_5
+      value: 42.693
+    - type: mrr_at_1
+      value: 29.659000000000002
+    - type: mrr_at_10
+      value: 45.253
+    - type: mrr_at_100
+      value: 46.125
+    - type: mrr_at_1000
+      value: 46.129
+    - type: mrr_at_20
+      value: 45.964
+    - type: mrr_at_3
+      value: 40.043
+    - type: mrr_at_5
+      value: 42.870000000000005
+    - type: ndcg_at_1
+      value: 29.232000000000003
+    - type: ndcg_at_10
+      value: 54.327999999999996
+    - type: ndcg_at_100
+      value: 57.86
+    - type: ndcg_at_1000
+      value: 57.935
+    - type: ndcg_at_20
+      value: 56.794
+    - type: ndcg_at_3
+      value: 43.516
+    - type: ndcg_at_5
+      value: 48.512
+    - type: precision_at_1
+      value: 29.232000000000003
+    - type: precision_at_10
+      value: 8.393
+    - type: precision_at_100
+      value: 0.991
+    - type: precision_at_1000
+      value: 0.1
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+    - type: recall_at_3
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+    - type: recall_at_5
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+      name: MTEB Banking77Classification (default)
+      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
+      split: test
+      type: mteb/banking77
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+    - type: main_score
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+      name: MTEB BiorxivClusteringP2P (default)
+      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
+      split: test
+      type: mteb/biorxiv-clustering-p2p
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+    - type: v_measure
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+    - type: v_measure_std
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+      name: MTEB BiorxivClusteringS2S (default)
+      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
+      split: test
+      type: mteb/biorxiv-clustering-s2s
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+    - type: v_measure
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+    - type: v_measure_std
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+      revision: a2dd5b02a77de3466a3eaa98ae586b5610314496
+      split: test
+      type: slvnwhrl/blurbs-clustering-p2p
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+    - type: v_measure_std
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+      revision: 22793b6a6465bf00120ad525e38c51210858132c
+      split: test
+      type: slvnwhrl/blurbs-clustering-s2s
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+      name: MTEB CBD (default)
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+      type: PL-MTEB/cbd
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+    - type: ap
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+    - type: main_score
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+      name: MTEB CDSC-E (default)
+      revision: 0a3d4aa409b22f80eb22cbf59b492637637b536d
+      split: test
+      type: PL-MTEB/cdsce-pairclassification
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+    - type: dot_accuracy
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+      name: MTEB CDSC-R (default)
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+      split: test
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+    - type: cosine_pearson
+      value: 92.97492495289738
+    - type: cosine_spearman
+      value: 92.63248098608472
+    - type: euclidean_pearson
+      value: 92.04712487782031
+    - type: euclidean_spearman
+      value: 92.19679486755008
+    - type: main_score
+      value: 92.63248098608472
+    - type: manhattan_pearson
+      value: 92.0101187740438
+    - type: manhattan_spearman
+      value: 92.20926859332754
+    - type: pearson
+      value: 92.97492495289738
+    - type: spearman
+      value: 92.63248098608472
+    task:
+      type: STS
+  - dataset:
+      config: default
+      name: MTEB CLSClusteringP2P (default)
+      revision: 4b6227591c6c1a73bc76b1055f3b7f3588e72476
+      split: test
+      type: C-MTEB/CLSClusteringP2P
+    metrics:
+    - type: main_score
+      value: 39.96377851800628
+    - type: v_measure
+      value: 39.96377851800628
+    - type: v_measure_std
+      value: 0.9793033243093288
+    task:
+      type: Clustering
+  - dataset:
+      config: default
+      name: MTEB CLSClusteringS2S (default)
+      revision: e458b3f5414b62b7f9f83499ac1f5497ae2e869f
+      split: test
+      type: C-MTEB/CLSClusteringS2S
+    metrics:
+    - type: main_score
+      value: 38.788850224595784
+    - type: v_measure
+      value: 38.788850224595784
+    - type: v_measure_std
+      value: 1.0712604145916924
+    task:
+      type: Clustering
+  - dataset:
+      config: default
+      name: MTEB CMedQAv1-reranking (default)
+      revision: 8d7f1e942507dac42dc58017c1a001c3717da7df
+      split: test
+      type: C-MTEB/CMedQAv1-reranking
+    metrics:
+    - type: map
+      value: 77.95952507806115
+    - type: mrr
+      value: 80.8643253968254
+    - type: main_score
+      value: 77.95952507806115
+    task:
+      type: Reranking
+  - dataset:
+      config: default
+      name: MTEB CMedQAv2-reranking (default)
+      revision: 23d186750531a14a0357ca22cd92d712fd512ea0
+      split: test
+      type: C-MTEB/CMedQAv2-reranking
+    metrics:
+    - type: map
+      value: 78.21522500165045
+    - type: mrr
+      value: 81.28194444444443
+    - type: main_score
+      value: 78.21522500165045
+    task:
+      type: Reranking
+  - dataset:
+      config: default
+      name: MTEB CQADupstackAndroidRetrieval (default)
+      revision: f46a197baaae43b4f621051089b82a364682dfeb
+      split: test
+      type: mteb/cqadupstack-android
+    metrics:
+    - type: map_at_1
+      value: 33.377
+    - type: map_at_10
+      value: 46.371
+    - type: map_at_100
+      value: 47.829
+    - type: map_at_1000
+      value: 47.94
+    - type: map_at_20
+      value: 47.205000000000005
+    - type: map_at_3
+      value: 42.782
+    - type: map_at_5
+      value: 44.86
+    - type: mrr_at_1
+      value: 41.345
+    - type: mrr_at_10
+      value: 52.187
+    - type: mrr_at_100
+      value: 52.893
+    - type: mrr_at_1000
+      value: 52.929
+    - type: mrr_at_20
+      value: 52.637
+    - type: mrr_at_3
+      value: 49.714000000000006
+    - type: mrr_at_5
+      value: 51.373000000000005
+    - type: ndcg_at_1
+      value: 41.345
+    - type: ndcg_at_10
+      value: 52.946000000000005
+    - type: ndcg_at_100
+      value: 57.92699999999999
+    - type: ndcg_at_1000
+      value: 59.609
+    - type: ndcg_at_20
+      value: 54.900999999999996
+    - type: ndcg_at_3
+      value: 48.357
+    - type: ndcg_at_5
+      value: 50.739000000000004
+    - type: precision_at_1
+      value: 41.345
+    - type: precision_at_10
+      value: 10.186
+    - type: precision_at_100
+      value: 1.554
+    - type: precision_at_1000
+      value: 0.2
+    - type: precision_at_20
+      value: 5.959
+    - type: precision_at_3
+      value: 23.796
+    - type: precision_at_5
+      value: 17.024
+    - type: recall_at_1
+      value: 33.377
+    - type: recall_at_10
+      value: 65.067
+    - type: recall_at_100
+      value: 86.04899999999999
+    - type: recall_at_1000
+      value: 96.54899999999999
+    - type: recall_at_20
+      value: 72.071
+    - type: recall_at_3
+      value: 51.349999999999994
+    - type: recall_at_5
+      value: 58.41
+    - type: main_score
+      value: 52.946000000000005
+    task:
+      type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB CQADupstackEnglishRetrieval (default)
+      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
+      split: test
+      type: mteb/cqadupstack-english
+    metrics:
+    - type: map_at_1
+      value: 31.097
+    - type: map_at_10
+      value: 42.183
+    - type: map_at_100
+      value: 43.580999999999996
+    - type: map_at_1000
+      value: 43.718
+    - type: map_at_20
+      value: 42.921
+    - type: map_at_3
+      value: 38.963
+    - type: map_at_5
+      value: 40.815
+    - type: mrr_at_1
+      value: 39.745000000000005
+    - type: mrr_at_10
+      value: 48.736000000000004
+    - type: mrr_at_100
+      value: 49.405
+    - type: mrr_at_1000
+      value: 49.452
+    - type: mrr_at_20
+      value: 49.118
+    - type: mrr_at_3
+      value: 46.497
+    - type: mrr_at_5
+      value: 47.827999999999996
+    - type: ndcg_at_1
+      value: 39.745000000000005
+    - type: ndcg_at_10
+      value: 48.248000000000005
+    - type: ndcg_at_100
+      value: 52.956
+    - type: ndcg_at_1000
+      value: 54.99699999999999
+    - type: ndcg_at_20
+      value: 50.01
+    - type: ndcg_at_3
+      value: 43.946000000000005
+    - type: ndcg_at_5
+      value: 46.038000000000004
+    - type: precision_at_1
+      value: 39.745000000000005
+    - type: precision_at_10
+      value: 9.229
+    - type: precision_at_100
+      value: 1.5070000000000001
+    - type: precision_at_1000
+      value: 0.199
+    - type: precision_at_20
+      value: 5.489999999999999
+    - type: precision_at_3
+      value: 21.38
+    - type: precision_at_5
+      value: 15.274
+    - type: recall_at_1
+      value: 31.097
+    - type: recall_at_10
+      value: 58.617
+    - type: recall_at_100
+      value: 78.55199999999999
+    - type: recall_at_1000
+      value: 91.13900000000001
+    - type: recall_at_20
+      value: 64.92
+    - type: recall_at_3
+      value: 45.672000000000004
+    - type: recall_at_5
+      value: 51.669
+    - type: main_score
+      value: 48.248000000000005
+    task:
+      type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB CQADupstackGamingRetrieval (default)
+      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
+      split: test
+      type: mteb/cqadupstack-gaming
+    metrics:
+    - type: map_at_1
+      value: 39.745000000000005
+    - type: map_at_10
+      value: 52.063
+    - type: map_at_100
+      value: 53.077
+    - type: map_at_1000
+      value: 53.13
+    - type: map_at_20
+      value: 52.66
+    - type: map_at_3
+      value: 48.662
+    - type: map_at_5
+      value: 50.507000000000005
+    - type: mrr_at_1
+      value: 45.391999999999996
+    - type: mrr_at_10
+      value: 55.528
+    - type: mrr_at_100
+      value: 56.16100000000001
+    - type: mrr_at_1000
+      value: 56.192
+    - type: mrr_at_20
+      value: 55.923
+    - type: mrr_at_3
+      value: 52.93600000000001
+    - type: mrr_at_5
+      value: 54.435
+    - type: ndcg_at_1
+      value: 45.391999999999996
+    - type: ndcg_at_10
+      value: 58.019
+    - type: ndcg_at_100
+      value: 61.936
+    - type: ndcg_at_1000
+      value: 63.015
+    - type: ndcg_at_20
+      value: 59.691
+    - type: ndcg_at_3
+      value: 52.294
+    - type: ndcg_at_5
+      value: 55.017
+    - type: precision_at_1
+      value: 45.391999999999996
+    - type: precision_at_10
+      value: 9.386
+    - type: precision_at_100
+      value: 1.232
+    - type: precision_at_1000
+      value: 0.136
+    - type: precision_at_20
+      value: 5.223
+    - type: precision_at_3
+      value: 23.177
+    - type: precision_at_5
+      value: 15.9
+    - type: recall_at_1
+      value: 39.745000000000005
+    - type: recall_at_10
+      value: 72.08099999999999
+    - type: recall_at_100
+      value: 88.85300000000001
+    - type: recall_at_1000
+      value: 96.569
+    - type: recall_at_20
+      value: 78.203
+    - type: recall_at_3
+      value: 56.957
+    - type: recall_at_5
+      value: 63.63100000000001
+    - type: main_score
+      value: 58.019
+    task:
+      type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB CQADupstackGisRetrieval (default)
+      revision: 5003b3064772da1887988e05400cf3806fe491f2
+      split: test
+      type: mteb/cqadupstack-gis
+    metrics:
+    - type: map_at_1
+      value: 26.651999999999997
+    - type: map_at_10
+      value: 35.799
+    - type: map_at_100
+      value: 36.846000000000004
+    - type: map_at_1000
+      value: 36.931000000000004
+    - type: map_at_20
+      value: 36.341
+    - type: map_at_3
+      value: 32.999
+    - type: map_at_5
+      value: 34.597
+    - type: mrr_at_1
+      value: 28.814
+    - type: mrr_at_10
+      value: 37.869
+    - type: mrr_at_100
+      value: 38.728
+    - type: mrr_at_1000
+      value: 38.795
+    - type: mrr_at_20
+      value: 38.317
+    - type: mrr_at_3
+      value: 35.235
+    - type: mrr_at_5
+      value: 36.738
+    - type: ndcg_at_1
+      value: 28.814
+    - type: ndcg_at_10
+      value: 41.028
+    - type: ndcg_at_100
+      value: 46.162
+    - type: ndcg_at_1000
+      value: 48.15
+    - type: ndcg_at_20
+      value: 42.824
+    - type: ndcg_at_3
+      value: 35.621
+    - type: ndcg_at_5
+      value: 38.277
+    - type: precision_at_1
+      value: 28.814
+    - type: precision_at_10
+      value: 6.361999999999999
+    - type: precision_at_100
+      value: 0.9450000000000001
+    - type: precision_at_1000
+      value: 0.11399999999999999
+    - type: precision_at_20
+      value: 3.6159999999999997
+    - type: precision_at_3
+      value: 15.140999999999998
+    - type: precision_at_5
+      value: 10.712000000000002
+    - type: recall_at_1
+      value: 26.651999999999997
+    - type: recall_at_10
+      value: 55.038
+    - type: recall_at_100
+      value: 78.806
+    - type: recall_at_1000
+      value: 93.485
+    - type: recall_at_20
+      value: 61.742
+    - type: recall_at_3
+      value: 40.682
+    - type: recall_at_5
+      value: 46.855000000000004
+    - type: main_score
+      value: 41.028
+    task:
+      type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB CQADupstackMathematicaRetrieval (default)
+      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
+      split: test
+      type: mteb/cqadupstack-mathematica
+    metrics:
+    - type: map_at_1
+      value: 17.627000000000002
+    - type: map_at_10
+      value: 26.436999999999998
+    - type: map_at_100
+      value: 27.85
+    - type: map_at_1000
+      value: 27.955999999999996
+    - type: map_at_20
+      value: 27.233
+    - type: map_at_3
+      value: 23.777
+    - type: map_at_5
+      value: 25.122
+    - type: mrr_at_1
+      value: 22.387999999999998
+    - type: mrr_at_10
+      value: 31.589
+    - type: mrr_at_100
+      value: 32.641999999999996
+    - type: mrr_at_1000
+      value: 32.696999999999996
+    - type: mrr_at_20
+      value: 32.201
+    - type: mrr_at_3
+      value: 28.98
+    - type: mrr_at_5
+      value: 30.342000000000002
+    - type: ndcg_at_1
+      value: 22.387999999999998
+    - type: ndcg_at_10
+      value: 32.129999999999995
+    - type: ndcg_at_100
+      value: 38.562999999999995
+    - type: ndcg_at_1000
+      value: 40.903
+    - type: ndcg_at_20
+      value: 34.652
+    - type: ndcg_at_3
+      value: 27.26
+    - type: ndcg_at_5
+      value: 29.235
+    - type: precision_at_1
+      value: 22.387999999999998
+    - type: precision_at_10
+      value: 5.970000000000001
+    - type: precision_at_100
+      value: 1.068
+    - type: precision_at_1000
+      value: 0.13899999999999998
+    - type: precision_at_20
+      value: 3.6999999999999997
+    - type: precision_at_3
+      value: 13.267000000000001
+    - type: precision_at_5
+      value: 9.403
+    - type: recall_at_1
+      value: 17.627000000000002
+    - type: recall_at_10
+      value: 44.71
+    - type: recall_at_100
+      value: 72.426
+    - type: recall_at_1000
+      value: 88.64699999999999
+    - type: recall_at_20
+      value: 53.65
+    - type: recall_at_3
+      value: 30.989
+    - type: recall_at_5
+      value: 36.237
+    - type: main_score
+      value: 32.129999999999995
+    task:
+      type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB CQADupstackPhysicsRetrieval (default)
+      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
+      split: test
+      type: mteb/cqadupstack-physics
+    metrics:
+    - type: map_at_1
+      value: 30.891000000000002
+    - type: map_at_10
+      value: 41.519
+    - type: map_at_100
+      value: 42.896
+    - type: map_at_1000
+      value: 42.992999999999995
+    - type: map_at_20
+      value: 42.287
+    - type: map_at_3
+      value: 37.822
+    - type: map_at_5
+      value: 39.976
+    - type: mrr_at_1
+      value: 37.921
+    - type: mrr_at_10
+      value: 47.260999999999996
+    - type: mrr_at_100
+      value: 48.044
+    - type: mrr_at_1000
+      value: 48.08
+    - type: mrr_at_20
+      value: 47.699999999999996
+    - type: mrr_at_3
+      value: 44.513999999999996
+    - type: mrr_at_5
+      value: 46.064
+    - type: ndcg_at_1
+      value: 37.921
+    - type: ndcg_at_10
+      value: 47.806
+    - type: ndcg_at_100
+      value: 53.274
+    - type: ndcg_at_1000
+      value: 55.021
+    - type: ndcg_at_20
+      value: 49.973
+    - type: ndcg_at_3
+      value: 42.046
+    - type: ndcg_at_5
+      value: 44.835
+    - type: precision_at_1
+      value: 37.921
+    - type: precision_at_10
+      value: 8.767999999999999
+    - type: precision_at_100
+      value: 1.353
+    - type: precision_at_1000
+      value: 0.168
+    - type: precision_at_20
+      value: 5.135
+    - type: precision_at_3
+      value: 20.051
+    - type: precision_at_5
+      value: 14.398
+    - type: recall_at_1
+      value: 30.891000000000002
+    - type: recall_at_10
+      value: 60.897999999999996
+    - type: recall_at_100
+      value: 83.541
+    - type: recall_at_1000
+      value: 94.825
+    - type: recall_at_20
+      value: 68.356
+    - type: recall_at_3
+      value: 44.65
+    - type: recall_at_5
+      value: 51.919000000000004
+    - type: main_score
+      value: 47.806
+    task:
+      type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB CQADupstackProgrammersRetrieval (default)
+      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
+      split: test
+      type: mteb/cqadupstack-programmers
+    metrics:
+    - type: map_at_1
+      value: 27.654
+    - type: map_at_10
+      value: 38.025999999999996
+    - type: map_at_100
+      value: 39.425
+    - type: map_at_1000
+      value: 39.528
+    - type: map_at_20
+      value: 38.838
+    - type: map_at_3
+      value: 34.745
+    - type: map_at_5
+      value: 36.537
+    - type: mrr_at_1
+      value: 34.018
+    - type: mrr_at_10
+      value: 43.314
+    - type: mrr_at_100
+      value: 44.283
+    - type: mrr_at_1000
+      value: 44.327
+    - type: mrr_at_20
+      value: 43.929
+    - type: mrr_at_3
+      value: 40.868
+    - type: mrr_at_5
+      value: 42.317
+    - type: ndcg_at_1
+      value: 34.018
+    - type: ndcg_at_10
+      value: 43.887
+    - type: ndcg_at_100
+      value: 49.791000000000004
+    - type: ndcg_at_1000
+      value: 51.834
+    - type: ndcg_at_20
+      value: 46.376
+    - type: ndcg_at_3
+      value: 38.769999999999996
+    - type: ndcg_at_5
+      value: 41.144
+    - type: precision_at_1
+      value: 34.018
+    - type: precision_at_10
+      value: 8.001999999999999
+    - type: precision_at_100
+      value: 1.2630000000000001
+    - type: precision_at_1000
+      value: 0.16
+    - type: precision_at_20
+      value: 4.737
+    - type: precision_at_3
+      value: 18.417
+    - type: precision_at_5
+      value: 13.150999999999998
+    - type: recall_at_1
+      value: 27.654
+    - type: recall_at_10
+      value: 56.111
+    - type: recall_at_100
+      value: 81.136
+    - type: recall_at_1000
+      value: 94.788
+    - type: recall_at_20
+      value: 65.068
+    - type: recall_at_3
+      value: 41.713
+    - type: recall_at_5
+      value: 48.106
+    - type: main_score
+      value: 43.887
+    task:
+      type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB CQADupstackRetrieval (default)
+      revision: CQADupstackRetrieval_is_a_combined_dataset
+      split: test
+      type: CQADupstackRetrieval_is_a_combined_dataset
+    metrics:
+    - type: main_score
+      value: 42.58858333333333
+    - type: ndcg_at_10
+      value: 42.58858333333333
+    task:
+      type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB CQADupstackStatsRetrieval (default)
+      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
+      split: test
+      type: mteb/cqadupstack-stats
+    metrics:
+    - type: map_at_1
+      value: 24.501
+    - type: map_at_10
+      value: 32.814
+    - type: map_at_100
+      value: 33.754
+    - type: map_at_1000
+      value: 33.859
+    - type: map_at_20
+      value: 33.324
+    - type: map_at_3
+      value: 30.758000000000003
+    - type: map_at_5
+      value: 31.936999999999998
+    - type: mrr_at_1
+      value: 27.761000000000003
+    - type: mrr_at_10
+      value: 35.662
+    - type: mrr_at_100
+      value: 36.443999999999996
+    - type: mrr_at_1000
+      value: 36.516999999999996
+    - type: mrr_at_20
+      value: 36.085
+    - type: mrr_at_3
+      value: 33.742
+    - type: mrr_at_5
+      value: 34.931
+    - type: ndcg_at_1
+      value: 27.761000000000003
+    - type: ndcg_at_10
+      value: 37.208000000000006
+    - type: ndcg_at_100
+      value: 41.839
+    - type: ndcg_at_1000
+      value: 44.421
+    - type: ndcg_at_20
+      value: 38.917
+    - type: ndcg_at_3
+      value: 33.544000000000004
+    - type: ndcg_at_5
+      value: 35.374
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+      value: 38.143
+    - type: recall_at_10
+      value: 65.982
+    - type: recall_at_100
+      value: 77.225
+    - type: recall_at_1000
+      value: 86.077
+    - type: recall_at_20
+      value: 69.68299999999999
+    - type: recall_at_3
+      value: 56.989000000000004
+    - type: recall_at_5
+      value: 61.35
+    - type: main_score
+      value: 64.673
+    task:
+      type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB IFlyTek (default)
+      revision: 421605374b29664c5fc098418fe20ada9bd55f8a
+      split: validation
+      type: C-MTEB/IFlyTek-classification
+    metrics:
+    - type: accuracy
+      value: 41.67756829549827
+    - type: f1
+      value: 33.929325579581636
+    - type: f1_weighted
+      value: 43.03952025643197
+    - type: main_score
+      value: 41.67756829549827
+    task:
+      type: Classification
+  - dataset:
+      config: default
+      name: MTEB ImdbClassification (default)
+      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
+      split: test
+      type: mteb/imdb
+    metrics:
+    - type: accuracy
+      value: 91.90440000000001
+    - type: ap
+      value: 88.78663714603425
+    - type: ap_weighted
+      value: 88.78663714603425
+    - type: f1
+      value: 91.89564361975891
+    - type: f1_weighted
+      value: 91.89564361975891
+    - type: main_score
+      value: 91.90440000000001
+    task:
+      type: Classification
+  - dataset:
+      config: default
+      name: MTEB InappropriatenessClassification (default)
+      revision: 601651fdc45ef243751676e62dd7a19f491c0285
+      split: test
+      type: ai-forever/inappropriateness-classification
+    metrics:
+    - type: accuracy
+      value: 61.0498046875
+    - type: ap
+      value: 57.04240566648215
+    - type: ap_weighted
+      value: 57.04240566648215
+    - type: f1
+      value: 60.867630038606954
+    - type: f1_weighted
+      value: 60.867630038606954
+    - type: main_score
+      value: 61.0498046875
+    task:
+      type: Classification
+  - dataset:
+      config: default
+      name: MTEB JDReview (default)
+      revision: b7c64bd89eb87f8ded463478346f76731f07bf8b
+      split: test
+      type: C-MTEB/JDReview-classification
+    metrics:
+    - type: accuracy
+      value: 83.50844277673546
+    - type: ap
+      value: 48.46732380712268
+    - type: ap_weighted
+      value: 48.46732380712268
+    - type: f1
+      value: 77.43967451387445
+    - type: f1_weighted
+      value: 84.78462929014114
+    - type: main_score
+      value: 83.50844277673546
+    task:
+      type: Classification
+  - dataset:
+      config: default
+      name: MTEB KinopoiskClassification (default)
+      revision: 5911f26666ac11af46cb9c6849d0dc80a378af24
+      split: test
+      type: ai-forever/kinopoisk-sentiment-classification
+    metrics:
+    - type: accuracy
+      value: 62.393333333333324
+    - type: f1
+      value: 61.35940129568015
+    - type: f1_weighted
+      value: 61.35940129568015
+    - type: main_score
+      value: 62.393333333333324
+    task:
+      type: Classification
+  - dataset:
+      config: default
+      name: MTEB LCQMC (default)
+      revision: 17f9b096f80380fce5ed12a9be8be7784b337daf
+      split: test
+      type: C-MTEB/LCQMC
+    metrics:
+    - type: cosine_pearson
+      value: 67.74375505907872
+    - type: cosine_spearman
+      value: 75.94582231399434
+    - type: euclidean_pearson
+      value: 74.52501692443582
+    - type: euclidean_spearman
+      value: 75.88428434746646
+    - type: main_score
+      value: 75.94582231399434
+    - type: manhattan_pearson
+      value: 74.55015441749529
+    - type: manhattan_spearman
+      value: 75.83288262176175
+    - type: pearson
+      value: 67.74375505907872
+    - type: spearman
+      value: 75.94582231399434
+    task:
+      type: STS
+  - dataset:
+      config: default
+      name: MTEB LEMBNarrativeQARetrieval (default)
+      revision: 6e346642246bfb4928c560ee08640dc84d074e8c
+      split: test
+      type: dwzhu/LongEmbed
+    metrics:
+    - type: map_at_1
+      value: 23.093
+    - type: map_at_10
+      value: 30.227999999999998
+    - type: map_at_100
+      value: 31.423000000000002
+    - type: map_at_1000
+      value: 31.533
+    - type: map_at_20
+      value: 30.835
+    - type: map_at_3
+      value: 27.983999999999998
+    - type: map_at_5
+      value: 29.253
+    - type: mrr_at_1
+      value: 23.093
+    - type: mrr_at_10
+      value: 30.227999999999998
+    - type: mrr_at_100
+      value: 31.423000000000002
+    - type: mrr_at_1000
+      value: 31.533
+    - type: mrr_at_20
+      value: 30.835
+    - type: mrr_at_3
+      value: 27.983999999999998
+    - type: mrr_at_5
+      value: 29.253
+    - type: ndcg_at_1
+      value: 23.093
+    - type: ndcg_at_10
+      value: 34.297
+    - type: ndcg_at_100
+      value: 41.049
+    - type: ndcg_at_1000
+      value: 43.566
+    - type: ndcg_at_20
+      value: 36.52
+    - type: ndcg_at_3
+      value: 29.629
+    - type: ndcg_at_5
+      value: 31.926
+    - type: precision_at_1
+      value: 23.093
+    - type: precision_at_10
+      value: 4.735
+    - type: precision_at_100
+      value: 0.8109999999999999
+    - type: precision_at_1000
+      value: 0.1
+    - type: precision_at_20
+      value: 2.8080000000000003
+    - type: precision_at_3
+      value: 11.468
+    - type: precision_at_5
+      value: 8.001
+    - type: recall_at_1
+      value: 23.093
+    - type: recall_at_10
+      value: 47.354
+    - type: recall_at_100
+      value: 81.147
+    - type: recall_at_1000
+      value: 100.0
+    - type: recall_at_20
+      value: 56.16799999999999
+    - type: recall_at_3
+      value: 34.405
+    - type: recall_at_5
+      value: 40.004
+    - type: main_score
+      value: 34.297
+    task:
+      type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB LEMBNeedleRetrieval (default)
+      revision: 6e346642246bfb4928c560ee08640dc84d074e8c
+      split: test_256
+      type: dwzhu/LongEmbed
+    metrics:
+    - type: map_at_1
+      value: 64.0
+    - type: map_at_10
+      value: 77.083
+    - type: map_at_100
+      value: 77.265
+    - type: map_at_1000
+      value: 77.265
+    - type: map_at_20
+      value: 77.265
+    - type: map_at_3
+      value: 76.333
+    - type: map_at_5
+      value: 76.833
+    - type: mrr_at_1
+      value: 64.0
+    - type: mrr_at_10
+      value: 77.083
+    - type: mrr_at_100
+      value: 77.265
+    - type: mrr_at_1000
+      value: 77.265
+    - type: mrr_at_20
+      value: 77.265
+    - type: mrr_at_3
+      value: 76.333
+    - type: mrr_at_5
+      value: 76.833
+    - type: ndcg_at_1
+      value: 64.0
+    - type: ndcg_at_10
+      value: 82.325
+    - type: ndcg_at_100
+      value: 82.883
+    - type: ndcg_at_1000
+      value: 82.883
+    - type: ndcg_at_20
+      value: 82.883
+    - type: ndcg_at_3
+      value: 80.833
+    - type: ndcg_at_5
+      value: 81.694
+    - type: precision_at_1
+      value: 64.0
+    - type: precision_at_10
+      value: 9.8
+    - type: precision_at_100
+      value: 1.0
+    - type: precision_at_1000
+      value: 0.1
+    - type: precision_at_20
+      value: 5.0
+    - type: precision_at_3
+      value: 31.333
+    - type: precision_at_5
+      value: 19.2
+    - type: recall_at_1
+      value: 64.0
+    - type: recall_at_10
+      value: 98.0
+    - type: recall_at_100
+      value: 100.0
+    - type: recall_at_1000
+      value: 100.0
+    - type: recall_at_20
+      value: 100.0
+    - type: recall_at_3
+      value: 94.0
+    - type: recall_at_5
+      value: 96.0
+    - type: main_score
+      value: 64.0
+    task:
+      type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB LEMBPasskeyRetrieval (default)
+      revision: 6e346642246bfb4928c560ee08640dc84d074e8c
+      split: test_256
+      type: dwzhu/LongEmbed
+    metrics:
+    - type: map_at_1
+      value: 100.0
+    - type: map_at_10
+      value: 100.0
+    - type: map_at_100
+      value: 100.0
+    - type: map_at_1000
+      value: 100.0
+    - type: map_at_20
+      value: 100.0
+    - type: map_at_3
+      value: 100.0
+    - type: map_at_5
+      value: 100.0
+    - type: mrr_at_1
+      value: 100.0
+    - type: mrr_at_10
+      value: 100.0
+    - type: mrr_at_100
+      value: 100.0
+    - type: mrr_at_1000
+      value: 100.0
+    - type: mrr_at_20
+      value: 100.0
+    - type: mrr_at_3
+      value: 100.0
+    - type: mrr_at_5
+      value: 100.0
+    - type: ndcg_at_1
+      value: 100.0
+    - type: ndcg_at_10
+      value: 100.0
+    - type: ndcg_at_100
+      value: 100.0
+    - type: ndcg_at_1000
+      value: 100.0
+    - type: ndcg_at_20
+      value: 100.0
+    - type: ndcg_at_3
+      value: 100.0
+    - type: ndcg_at_5
+      value: 100.0
+    - type: precision_at_1
+      value: 100.0
+    - type: precision_at_10
+      value: 10.0
+    - type: precision_at_100
+      value: 1.0
+    - type: precision_at_1000
+      value: 0.1
+    - type: precision_at_20
+      value: 5.0
+    - type: precision_at_3
+      value: 33.333
+    - type: precision_at_5
+      value: 20.0
+    - type: recall_at_1
+      value: 100.0
+    - type: recall_at_10
+      value: 100.0
+    - type: recall_at_100
+      value: 100.0
+    - type: recall_at_1000
+      value: 100.0
+    - type: recall_at_20
+      value: 100.0
+    - type: recall_at_3
+      value: 100.0
+    - type: recall_at_5
+      value: 100.0
+    - type: main_score
+      value: 100.0
+    task:
+      type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB LEMBQMSumRetrieval (default)
+      revision: 6e346642246bfb4928c560ee08640dc84d074e8c
+      split: test
+      type: dwzhu/LongEmbed
+    metrics:
+    - type: map_at_1
+      value: 24.361
+    - type: map_at_10
+      value: 33.641
+    - type: map_at_100
+      value: 35.104
+    - type: map_at_1000
+      value: 35.127
+    - type: map_at_20
+      value: 34.388999999999996
+    - type: map_at_3
+      value: 30.255
+    - type: map_at_5
+      value: 32.079
+    - type: mrr_at_1
+      value: 24.361
+    - type: mrr_at_10
+      value: 33.641
+    - type: mrr_at_100
+      value: 35.104
+    - type: mrr_at_1000
+      value: 35.127
+    - type: mrr_at_20
+      value: 34.388999999999996
+    - type: mrr_at_3
+      value: 30.255
+    - type: mrr_at_5
+      value: 32.079
+    - type: ndcg_at_1
+      value: 24.361
+    - type: ndcg_at_10
+      value: 39.337
+    - type: ndcg_at_100
+      value: 47.384
+    - type: ndcg_at_1000
+      value: 47.75
+    - type: ndcg_at_20
+      value: 42.077999999999996
+    - type: ndcg_at_3
+      value: 32.235
+    - type: ndcg_at_5
+      value: 35.524
+    - type: precision_at_1
+      value: 24.361
+    - type: precision_at_10
+      value: 5.783
+    - type: precision_at_100
+      value: 0.975
+    - type: precision_at_1000
+      value: 0.1
+    - type: precision_at_20
+      value: 3.435
+    - type: precision_at_3
+      value: 12.661
+    - type: precision_at_5
+      value: 9.193999999999999
+    - type: recall_at_1
+      value: 24.361
+    - type: recall_at_10
+      value: 57.826
+    - type: recall_at_100
+      value: 97.51100000000001
+    - type: recall_at_1000
+      value: 100.0
+    - type: recall_at_20
+      value: 68.697
+    - type: recall_at_3
+      value: 37.983
+    - type: recall_at_5
+      value: 45.972
+    - type: main_score
+      value: 39.337
+    task:
+      type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB LEMBSummScreenFDRetrieval (default)
+      revision: 6e346642246bfb4928c560ee08640dc84d074e8c
+      split: validation
+      type: dwzhu/LongEmbed
+    metrics:
+    - type: map_at_1
+      value: 84.821
+    - type: map_at_10
+      value: 90.11200000000001
+    - type: map_at_100
+      value: 90.158
+    - type: map_at_1000
+      value: 90.158
+    - type: map_at_20
+      value: 90.137
+    - type: map_at_3
+      value: 89.385
+    - type: map_at_5
+      value: 89.876
+    - type: mrr_at_1
+      value: 84.821
+    - type: mrr_at_10
+      value: 90.11200000000001
+    - type: mrr_at_100
+      value: 90.158
+    - type: mrr_at_1000
+      value: 90.158
+    - type: mrr_at_20
+      value: 90.137
+    - type: mrr_at_3
+      value: 89.385
+    - type: mrr_at_5
+      value: 89.876
+    - type: ndcg_at_1
+      value: 84.821
+    - type: ndcg_at_10
+      value: 92.334
+    - type: ndcg_at_100
+      value: 92.535
+    - type: ndcg_at_1000
+      value: 92.535
+    - type: ndcg_at_20
+      value: 92.414
+    - type: ndcg_at_3
+      value: 90.887
+    - type: ndcg_at_5
+      value: 91.758
+    - type: precision_at_1
+      value: 84.821
+    - type: precision_at_10
+      value: 9.911
+    - type: precision_at_100
+      value: 1.0
+    - type: precision_at_1000
+      value: 0.1
+    - type: precision_at_20
+      value: 4.97
+    - type: precision_at_3
+      value: 31.746000000000002
+    - type: precision_at_5
+      value: 19.464000000000002
+    - type: recall_at_1
+      value: 84.821
+    - type: recall_at_10
+      value: 99.107
+    - type: recall_at_100
+      value: 100.0
+    - type: recall_at_1000
+      value: 100.0
+    - type: recall_at_20
+      value: 99.405
+    - type: recall_at_3
+      value: 95.238
+    - type: recall_at_5
+      value: 97.321
+    - type: main_score
+      value: 92.334
+    task:
+      type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB LEMBWikimQARetrieval (default)
+      revision: 6e346642246bfb4928c560ee08640dc84d074e8c
+      split: test
+      type: dwzhu/LongEmbed
+    metrics:
+    - type: map_at_1
+      value: 53.667
+    - type: map_at_10
+      value: 61.719
+    - type: map_at_100
+      value: 62.471
+    - type: map_at_1000
+      value: 62.492000000000004
+    - type: map_at_20
+      value: 62.153000000000006
+    - type: map_at_3
+      value: 59.167
+    - type: map_at_5
+      value: 60.95
+    - type: mrr_at_1
+      value: 53.667
+    - type: mrr_at_10
+      value: 61.719
+    - type: mrr_at_100
+      value: 62.471
+    - type: mrr_at_1000
+      value: 62.492000000000004
+    - type: mrr_at_20
+      value: 62.153000000000006
+    - type: mrr_at_3
+      value: 59.167
+    - type: mrr_at_5
+      value: 60.95
+    - type: ndcg_at_1
+      value: 53.667
+    - type: ndcg_at_10
+      value: 66.018
+    - type: ndcg_at_100
+      value: 69.726
+    - type: ndcg_at_1000
+      value: 70.143
+    - type: ndcg_at_20
+      value: 67.61399999999999
+    - type: ndcg_at_3
+      value: 60.924
+    - type: ndcg_at_5
+      value: 64.10900000000001
+    - type: precision_at_1
+      value: 53.667
+    - type: precision_at_10
+      value: 7.9670000000000005
+    - type: precision_at_100
+      value: 0.97
+    - type: precision_at_1000
+      value: 0.1
+    - type: precision_at_20
+      value: 4.3
+    - type: precision_at_3
+      value: 22.0
+    - type: precision_at_5
+      value: 14.732999999999999
+    - type: recall_at_1
+      value: 53.667
+    - type: recall_at_10
+      value: 79.667
+    - type: recall_at_100
+      value: 97.0
+    - type: recall_at_1000
+      value: 100.0
+    - type: recall_at_20
+      value: 86.0
+    - type: recall_at_3
+      value: 66.0
+    - type: recall_at_5
+      value: 73.667
+    - type: main_score
+      value: 66.018
+    task:
+      type: Retrieval
+  - dataset:
+      config: deu-deu
+      name: MTEB MLQARetrieval (deu-deu)
+      revision: 397ed406c1a7902140303e7faf60fff35b58d285
+      split: test
+      type: facebook/mlqa
+    metrics:
+    - type: main_score
+      value: 67.548
+    - type: map_at_1
+      value: 56.559000000000005
+    - type: map_at_10
+      value: 63.867
+    - type: map_at_100
+      value: 64.429
+    - type: map_at_1000
+      value: 64.457
+    - type: map_at_20
+      value: 64.215
+    - type: map_at_3
+      value: 62.109
+    - type: map_at_5
+      value: 63.101
+    - type: mrr_at_1
+      value: 56.56990915134057
+    - type: mrr_at_10
+      value: 63.86820789324668
+    - type: mrr_at_100
+      value: 64.42973602152581
+    - type: mrr_at_1000
+      value: 64.45818598090155
+    - type: mrr_at_20
+      value: 64.2163052263868
+    - type: mrr_at_3
+      value: 62.10946155550634
+    - type: mrr_at_5
+      value: 63.10104143585199
+    - type: nauc_map_at_1000_diff1
+      value: 73.78440163370111
+    - type: nauc_map_at_1000_max
+      value: 66.37875518052162
+    - type: nauc_map_at_1000_std
+      value: -17.063915098135396
+    - type: nauc_map_at_100_diff1
+      value: 73.77180802985815
+    - type: nauc_map_at_100_max
+      value: 66.38365998362033
+    - type: nauc_map_at_100_std
+      value: -17.053345109661972
+    - type: nauc_map_at_10_diff1
+      value: 73.70041876696037
+    - type: nauc_map_at_10_max
+      value: 66.33213342705997
+    - type: nauc_map_at_10_std
+      value: -17.40657791273925
+    - type: nauc_map_at_1_diff1
+      value: 76.8784374396948
+    - type: nauc_map_at_1_max
+      value: 64.07170606935357
+    - type: nauc_map_at_1_std
+      value: -18.464213686790654
+    - type: nauc_map_at_20_diff1
+      value: 73.72371377231813
+    - type: nauc_map_at_20_max
+      value: 66.42108121059451
+    - type: nauc_map_at_20_std
+      value: -17.05384923889036
+    - type: nauc_map_at_3_diff1
+      value: 74.08287018839246
+    - type: nauc_map_at_3_max
+      value: 66.42422337760333
+    - type: nauc_map_at_3_std
+      value: -17.79503404131652
+    - type: nauc_map_at_5_diff1
+      value: 73.9294779027339
+    - type: nauc_map_at_5_max
+      value: 66.51752041065726
+    - type: nauc_map_at_5_std
+      value: -17.67309805113804
+    - type: nauc_mrr_at_1000_diff1
+      value: 73.78389736923545
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+      revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
+      split: test
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+      value: 34.429711214740564
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+      revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
+      split: test
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+      revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
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+      value: 34.87547994284835
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+      revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
+      split: test
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+      value: 37.330148394033365
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+      name: MTEB MasakhaNEWSClusteringS2S (eng)
+      revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
+      split: test
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+      split: test
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+      split: test
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+      split: test
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+      revision: 4672e20407010da34463acc759c162ca9734bca6
+      split: test
+      type: mteb/amazon_massive_intent
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+      name: MTEB MassiveIntentClassification (de)
+      revision: 4672e20407010da34463acc759c162ca9734bca6
+      split: test
+      type: mteb/amazon_massive_intent
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+      revision: 4672e20407010da34463acc759c162ca9734bca6
+      split: test
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+    task:
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+      name: MTEB MassiveIntentClassification (ru)
+      revision: 4672e20407010da34463acc759c162ca9734bca6
+      split: test
+      type: mteb/amazon_massive_intent
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+    task:
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+      name: MTEB MassiveIntentClassification (en)
+      revision: 4672e20407010da34463acc759c162ca9734bca6
+      split: test
+      type: mteb/amazon_massive_intent
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+    task:
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+      config: fr
+      name: MTEB MassiveIntentClassification (fr)
+      revision: 4672e20407010da34463acc759c162ca9734bca6
+      split: test
+      type: mteb/amazon_massive_intent
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+    task:
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+      name: MTEB MassiveIntentClassification (zh-CN)
+      revision: 4672e20407010da34463acc759c162ca9734bca6
+      split: test
+      type: mteb/amazon_massive_intent
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+      name: MTEB MassiveScenarioClassification (zh-CN)
+      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
+      split: test
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+      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
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+      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
+      split: test
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+      name: MTEB MassiveScenarioClassification (de)
+      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
+      split: test
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+      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
+      split: test
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+      name: MTEB MassiveScenarioClassification (fr)
+      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
+      split: test
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+      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
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+    - type: mrr_at_20
+      value: 56.00000000000001
+    - type: mrr_at_3
+      value: 54.17999999999999
+    - type: mrr_at_5
+      value: 55.155
+    - type: ndcg_at_1
+      value: 44.427
+    - type: ndcg_at_10
+      value: 36.623
+    - type: ndcg_at_100
+      value: 33.664
+    - type: ndcg_at_1000
+      value: 42.538
+    - type: ndcg_at_20
+      value: 34.066
+    - type: ndcg_at_3
+      value: 41.118
+    - type: ndcg_at_5
+      value: 39.455
+    - type: precision_at_1
+      value: 46.44
+    - type: precision_at_10
+      value: 28.607
+    - type: precision_at_100
+      value: 9.189
+    - type: precision_at_1000
+      value: 2.261
+    - type: precision_at_20
+      value: 21.238
+    - type: precision_at_3
+      value: 39.628
+    - type: precision_at_5
+      value: 35.604
+    - type: recall_at_1
+      value: 4.822
+    - type: recall_at_10
+      value: 17.488999999999997
+    - type: recall_at_100
+      value: 35.052
+    - type: recall_at_1000
+      value: 66.67999999999999
+    - type: recall_at_20
+      value: 21.343999999999998
+    - type: recall_at_3
+      value: 10.259
+    - type: recall_at_5
+      value: 13.406
+    - type: main_score
+      value: 36.623
+    task:
+      type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB NQ (default)
+      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
+      split: test
+      type: mteb/nq
+    metrics:
+    - type: map_at_1
+      value: 41.411
+    - type: map_at_10
+      value: 57.179
+    - type: map_at_100
+      value: 57.945
+    - type: map_at_1000
+      value: 57.967999999999996
+    - type: map_at_20
+      value: 57.687
+    - type: map_at_3
+      value: 53.46300000000001
+    - type: map_at_5
+      value: 55.696999999999996
+    - type: mrr_at_1
+      value: 46.233999999999995
+    - type: mrr_at_10
+      value: 59.831999999999994
+    - type: mrr_at_100
+      value: 60.33500000000001
+    - type: mrr_at_1000
+      value: 60.348
+    - type: mrr_at_20
+      value: 60.167
+    - type: mrr_at_3
+      value: 56.972
+    - type: mrr_at_5
+      value: 58.74
+    - type: ndcg_at_1
+      value: 46.205
+    - type: ndcg_at_10
+      value: 64.23100000000001
+    - type: ndcg_at_100
+      value: 67.242
+    - type: ndcg_at_1000
+      value: 67.72500000000001
+    - type: ndcg_at_20
+      value: 65.77300000000001
+    - type: ndcg_at_3
+      value: 57.516
+    - type: ndcg_at_5
+      value: 61.11600000000001
+    - type: precision_at_1
+      value: 46.205
+    - type: precision_at_10
+      value: 9.873
+    - type: precision_at_100
+      value: 1.158
+    - type: precision_at_1000
+      value: 0.12
+    - type: precision_at_20
+      value: 5.319
+    - type: precision_at_3
+      value: 25.424999999999997
+    - type: precision_at_5
+      value: 17.375
+    - type: recall_at_1
+      value: 41.411
+    - type: recall_at_10
+      value: 82.761
+    - type: recall_at_100
+      value: 95.52199999999999
+    - type: recall_at_1000
+      value: 99.02499999999999
+    - type: recall_at_20
+      value: 88.34
+    - type: recall_at_3
+      value: 65.73
+    - type: recall_at_5
+      value: 73.894
+    - type: main_score
+      value: 64.23100000000001
+    task:
+      type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB Ocnli (default)
+      revision: 66e76a618a34d6d565d5538088562851e6daa7ec
+      split: validation
+      type: C-MTEB/OCNLI
+    metrics:
+    - type: cosine_accuracy
+      value: 62.3714131023281
+    - type: cosine_accuracy_threshold
+      value: 79.70921993255615
+    - type: cosine_ap
+      value: 66.41380155495659
+    - type: cosine_f1
+      value: 68.89547185780786
+    - type: cosine_f1_threshold
+      value: 72.91591167449951
+    - type: cosine_precision
+      value: 57.485875706214685
+    - type: cosine_recall
+      value: 85.95564941921859
+    - type: dot_accuracy
+      value: 60.47644829453167
+    - type: dot_accuracy_threshold
+      value: 36627.362060546875
+    - type: dot_ap
+      value: 63.696303449293204
+    - type: dot_f1
+      value: 68.3986041101202
+    - type: dot_f1_threshold
+      value: 30452.72216796875
+    - type: dot_precision
+      value: 54.04411764705882
+    - type: dot_recall
+      value: 93.13621964097149
+    - type: euclidean_accuracy
+      value: 63.02111532214402
+    - type: euclidean_accuracy_threshold
+      value: 1392.76762008667
+    - type: euclidean_ap
+      value: 66.65907089443218
+    - type: euclidean_f1
+      value: 69.05036524413688
+    - type: euclidean_f1_threshold
+      value: 1711.5310668945312
+    - type: euclidean_precision
+      value: 54.29262394195889
+    - type: euclidean_recall
+      value: 94.82576557550159
+    - type: main_score
+      value: 63.02111532214402
+    - type: manhattan_accuracy
+      value: 62.75040606388739
+    - type: manhattan_accuracy_threshold
+      value: 32475.347900390625
+    - type: manhattan_ap
+      value: 66.50943585125434
+    - type: manhattan_f1
+      value: 69.08382066276802
+    - type: manhattan_f1_threshold
+      value: 41238.470458984375
+    - type: manhattan_precision
+      value: 54.75896168108776
+    - type: manhattan_recall
+      value: 93.55860612460401
+    - type: max_accuracy
+      value: 63.02111532214402
+    - type: max_ap
+      value: 66.65907089443218
+    - type: max_f1
+      value: 69.08382066276802
+    - type: max_precision
+      value: 57.485875706214685
+    - type: max_recall
+      value: 94.82576557550159
+    - type: similarity_accuracy
+      value: 62.3714131023281
+    - type: similarity_accuracy_threshold
+      value: 79.70921993255615
+    - type: similarity_ap
+      value: 66.41380155495659
+    - type: similarity_f1
+      value: 68.89547185780786
+    - type: similarity_f1_threshold
+      value: 72.91591167449951
+    - type: similarity_precision
+      value: 57.485875706214685
+    - type: similarity_recall
+      value: 85.95564941921859
+    task:
+      type: PairClassification
+  - dataset:
+      config: default
+      name: MTEB OnlineShopping (default)
+      revision: e610f2ebd179a8fda30ae534c3878750a96db120
+      split: test
+      type: C-MTEB/OnlineShopping-classification
+    metrics:
+    - type: accuracy
+      value: 91.88000000000001
+    - type: ap
+      value: 89.52463684448476
+    - type: ap_weighted
+      value: 89.52463684448476
+    - type: f1
+      value: 91.86313022306673
+    - type: f1_weighted
+      value: 91.87806318146912
+    - type: main_score
+      value: 91.88000000000001
+    task:
+      type: Classification
+  - dataset:
+      config: en
+      name: MTEB OpusparcusPC (en)
+      revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
+      split: test.full
+      type: GEM/opusparcus
+    metrics:
+    - type: cosine_accuracy
+      value: 92.65578635014838
+    - type: cosine_accuracy_threshold
+      value: 74.02530312538147
+    - type: cosine_ap
+      value: 98.3834226153613
+    - type: cosine_f1
+      value: 94.92567913890312
+    - type: cosine_f1_threshold
+      value: 74.02530312538147
+    - type: cosine_precision
+      value: 95.562435500516
+    - type: cosine_recall
+      value: 94.29735234215886
+    - type: dot_accuracy
+      value: 91.54302670623146
+    - type: dot_accuracy_threshold
+      value: 34452.29187011719
+    - type: dot_ap
+      value: 98.1237257754439
+    - type: dot_f1
+      value: 94.22400803616273
+    - type: dot_f1_threshold
+      value: 33670.41931152344
+    - type: dot_precision
+      value: 92.9633300297324
+    - type: dot_recall
+      value: 95.5193482688391
+    - type: euclidean_accuracy
+      value: 92.28486646884274
+    - type: euclidean_accuracy_threshold
+      value: 1602.8022766113281
+    - type: euclidean_ap
+      value: 98.3099021504706
+    - type: euclidean_f1
+      value: 94.75277497477296
+    - type: euclidean_f1_threshold
+      value: 1604.7462463378906
+    - type: euclidean_precision
+      value: 93.89999999999999
+    - type: euclidean_recall
+      value: 95.62118126272912
+    - type: main_score
+      value: 98.3834226153613
+    - type: manhattan_accuracy
+      value: 92.2106824925816
+    - type: manhattan_accuracy_threshold
+      value: 38872.90954589844
+    - type: manhattan_ap
+      value: 98.28694101230218
+    - type: manhattan_f1
+      value: 94.67815509376584
+    - type: manhattan_f1_threshold
+      value: 38872.90954589844
+    - type: manhattan_precision
+      value: 94.24823410696267
+    - type: manhattan_recall
+      value: 95.11201629327903
+    - type: max_accuracy
+      value: 92.65578635014838
+    - type: max_ap
+      value: 98.3834226153613
+    - type: max_f1
+      value: 94.92567913890312
+    - type: max_precision
+      value: 95.562435500516
+    - type: max_recall
+      value: 95.62118126272912
+    - type: similarity_accuracy
+      value: 92.65578635014838
+    - type: similarity_accuracy_threshold
+      value: 74.02530312538147
+    - type: similarity_ap
+      value: 98.3834226153613
+    - type: similarity_f1
+      value: 94.92567913890312
+    - type: similarity_f1_threshold
+      value: 74.02530312538147
+    - type: similarity_precision
+      value: 95.562435500516
+    - type: similarity_recall
+      value: 94.29735234215886
+    task:
+      type: PairClassification
+  - dataset:
+      config: de
+      name: MTEB OpusparcusPC (de)
+      revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
+      split: test.full
+      type: GEM/opusparcus
+    metrics:
+    - type: cosine_accuracy
+      value: 87.72178850248403
+    - type: cosine_accuracy_threshold
+      value: 73.33863377571106
+    - type: cosine_ap
+      value: 96.98901408834976
+    - type: cosine_f1
+      value: 91.89944134078212
+    - type: cosine_f1_threshold
+      value: 71.45810127258301
+    - type: cosine_precision
+      value: 89.64577656675749
+    - type: cosine_recall
+      value: 94.26934097421203
+    - type: dot_accuracy
+      value: 86.30234208658624
+    - type: dot_accuracy_threshold
+      value: 32027.130126953125
+    - type: dot_ap
+      value: 96.12260574893256
+    - type: dot_f1
+      value: 91.31602506714414
+    - type: dot_f1_threshold
+      value: 30804.376220703125
+    - type: dot_precision
+      value: 85.93091828138164
+    - type: dot_recall
+      value: 97.42120343839542
+    - type: euclidean_accuracy
+      value: 87.9347054648687
+    - type: euclidean_accuracy_threshold
+      value: 1609.6670150756836
+    - type: euclidean_ap
+      value: 97.00238860358252
+    - type: euclidean_f1
+      value: 92.1089063221043
+    - type: euclidean_f1_threshold
+      value: 1641.8487548828125
+    - type: euclidean_precision
+      value: 89.10714285714286
+    - type: euclidean_recall
+      value: 95.31996179560649
+    - type: main_score
+      value: 97.00238860358252
+    - type: manhattan_accuracy
+      value: 87.72178850248403
+    - type: manhattan_accuracy_threshold
+      value: 40137.060546875
+    - type: manhattan_ap
+      value: 96.98653728159941
+    - type: manhattan_f1
+      value: 92.03865623561896
+    - type: manhattan_f1_threshold
+      value: 40137.060546875
+    - type: manhattan_precision
+      value: 88.80994671403198
+    - type: manhattan_recall
+      value: 95.51098376313276
+    - type: max_accuracy
+      value: 87.9347054648687
+    - type: max_ap
+      value: 97.00238860358252
+    - type: max_f1
+      value: 92.1089063221043
+    - type: max_precision
+      value: 89.64577656675749
+    - type: max_recall
+      value: 97.42120343839542
+    - type: similarity_accuracy
+      value: 87.72178850248403
+    - type: similarity_accuracy_threshold
+      value: 73.33863377571106
+    - type: similarity_ap
+      value: 96.98901408834976
+    - type: similarity_f1
+      value: 91.89944134078212
+    - type: similarity_f1_threshold
+      value: 71.45810127258301
+    - type: similarity_precision
+      value: 89.64577656675749
+    - type: similarity_recall
+      value: 94.26934097421203
+    task:
+      type: PairClassification
+  - dataset:
+      config: fr
+      name: MTEB OpusparcusPC (fr)
+      revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
+      split: test.full
+      type: GEM/opusparcus
+    metrics:
+    - type: cosine_accuracy
+      value: 80.92643051771117
+    - type: cosine_accuracy_threshold
+      value: 76.68856382369995
+    - type: cosine_ap
+      value: 93.74622381534307
+    - type: cosine_f1
+      value: 87.12328767123287
+    - type: cosine_f1_threshold
+      value: 71.64022922515869
+    - type: cosine_precision
+      value: 80.64243448858834
+    - type: cosine_recall
+      value: 94.73684210526315
+    - type: dot_accuracy
+      value: 80.858310626703
+    - type: dot_accuracy_threshold
+      value: 34028.3935546875
+    - type: dot_ap
+      value: 91.18448457633308
+    - type: dot_f1
+      value: 86.82606657290202
+    - type: dot_f1_threshold
+      value: 34028.3935546875
+    - type: dot_precision
+      value: 82.2380106571936
+    - type: dot_recall
+      value: 91.9563058589871
+    - type: euclidean_accuracy
+      value: 80.858310626703
+    - type: euclidean_accuracy_threshold
+      value: 1595.7651138305664
+    - type: euclidean_ap
+      value: 93.8182717829648
+    - type: euclidean_f1
+      value: 87.04044117647058
+    - type: euclidean_f1_threshold
+      value: 1609.2475891113281
+    - type: euclidean_precision
+      value: 81.00940975192472
+    - type: euclidean_recall
+      value: 94.04170804369414
+    - type: main_score
+      value: 93.8182717829648
+    - type: manhattan_accuracy
+      value: 80.99455040871935
+    - type: manhattan_accuracy_threshold
+      value: 38092.132568359375
+    - type: manhattan_ap
+      value: 93.77563401151711
+    - type: manhattan_f1
+      value: 86.91983122362869
+    - type: manhattan_f1_threshold
+      value: 38092.132568359375
+    - type: manhattan_precision
+      value: 82.32682060390763
+    - type: manhattan_recall
+      value: 92.05561072492551
+    - type: max_accuracy
+      value: 80.99455040871935
+    - type: max_ap
+      value: 93.8182717829648
+    - type: max_f1
+      value: 87.12328767123287
+    - type: max_precision
+      value: 82.32682060390763
+    - type: max_recall
+      value: 94.73684210526315
+    - type: similarity_accuracy
+      value: 80.92643051771117
+    - type: similarity_accuracy_threshold
+      value: 76.68856382369995
+    - type: similarity_ap
+      value: 93.74622381534307
+    - type: similarity_f1
+      value: 87.12328767123287
+    - type: similarity_f1_threshold
+      value: 71.64022922515869
+    - type: similarity_precision
+      value: 80.64243448858834
+    - type: similarity_recall
+      value: 94.73684210526315
+    task:
+      type: PairClassification
+  - dataset:
+      config: ru
+      name: MTEB OpusparcusPC (ru)
+      revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
+      split: test.full
+      type: GEM/opusparcus
+    metrics:
+    - type: cosine_accuracy
+      value: 76.83823529411765
+    - type: cosine_accuracy_threshold
+      value: 72.70769476890564
+    - type: cosine_ap
+      value: 89.56692049908222
+    - type: cosine_f1
+      value: 83.99832003359934
+    - type: cosine_f1_threshold
+      value: 70.9052324295044
+    - type: cosine_precision
+      value: 76.16146230007617
+    - type: cosine_recall
+      value: 93.63295880149812
+    - type: dot_accuracy
+      value: 76.28676470588235
+    - type: dot_accuracy_threshold
+      value: 33740.68908691406
+    - type: dot_ap
+      value: 87.77185177141567
+    - type: dot_f1
+      value: 83.62251375370292
+    - type: dot_f1_threshold
+      value: 32726.611328125
+    - type: dot_precision
+      value: 76.29343629343629
+    - type: dot_recall
+      value: 92.50936329588015
+    - type: euclidean_accuracy
+      value: 77.32843137254902
+    - type: euclidean_accuracy_threshold
+      value: 1566.510009765625
+    - type: euclidean_ap
+      value: 89.60605626791111
+    - type: euclidean_f1
+      value: 84.06546080964686
+    - type: euclidean_f1_threshold
+      value: 1576.4202117919922
+    - type: euclidean_precision
+      value: 77.83094098883574
+    - type: euclidean_recall
+      value: 91.38576779026218
+    - type: main_score
+      value: 89.60605626791111
+    - type: manhattan_accuracy
+      value: 76.89950980392157
+    - type: manhattan_accuracy_threshold
+      value: 38202.215576171875
+    - type: manhattan_ap
+      value: 89.55766894104868
+    - type: manhattan_f1
+      value: 83.80462724935732
+    - type: manhattan_f1_threshold
+      value: 38934.375
+    - type: manhattan_precision
+      value: 77.25118483412322
+    - type: manhattan_recall
+      value: 91.57303370786516
+    - type: max_accuracy
+      value: 77.32843137254902
+    - type: max_ap
+      value: 89.60605626791111
+    - type: max_f1
+      value: 84.06546080964686
+    - type: max_precision
+      value: 77.83094098883574
+    - type: max_recall
+      value: 93.63295880149812
+    - type: similarity_accuracy
+      value: 76.83823529411765
+    - type: similarity_accuracy_threshold
+      value: 72.70769476890564
+    - type: similarity_ap
+      value: 89.56692049908222
+    - type: similarity_f1
+      value: 83.99832003359934
+    - type: similarity_f1_threshold
+      value: 70.9052324295044
+    - type: similarity_precision
+      value: 76.16146230007617
+    - type: similarity_recall
+      value: 93.63295880149812
+    task:
+      type: PairClassification
+  - dataset:
+      config: default
+      name: MTEB PAC (default)
+      revision: fc69d1c153a8ccdcf1eef52f4e2a27f88782f543
+      split: test
+      type: laugustyniak/abusive-clauses-pl
+    metrics:
+    - type: accuracy
+      value: 68.39559803069794
+    - type: ap
+      value: 77.68074206719457
+    - type: ap_weighted
+      value: 77.68074206719457
+    - type: f1
+      value: 66.23485605467732
+    - type: f1_weighted
+      value: 69.03201442129347
+    - type: main_score
+      value: 68.39559803069794
+    task:
+      type: Classification
+  - dataset:
+      config: default
+      name: MTEB PAWSX (default)
+      revision: 9c6a90e430ac22b5779fb019a23e820b11a8b5e1
+      split: test
+      type: C-MTEB/PAWSX
+    metrics:
+    - type: cosine_pearson
+      value: 13.161523266433587
+    - type: cosine_spearman
+      value: 15.557333873773386
+    - type: euclidean_pearson
+      value: 17.147508431907525
+    - type: euclidean_spearman
+      value: 15.664112857732146
+    - type: main_score
+      value: 15.557333873773386
+    - type: manhattan_pearson
+      value: 17.130875906264386
+    - type: manhattan_spearman
+      value: 15.624397342229637
+    - type: pearson
+      value: 13.161523266433587
+    - type: spearman
+      value: 15.557333873773386
+    task:
+      type: STS
+  - dataset:
+      config: default
+      name: MTEB PSC (default)
+      revision: d05a294af9e1d3ff2bfb6b714e08a24a6cabc669
+      split: test
+      type: PL-MTEB/psc-pairclassification
+    metrics:
+    - type: cosine_accuracy
+      value: 97.86641929499072
+    - type: cosine_accuracy_threshold
+      value: 79.0391206741333
+    - type: cosine_ap
+      value: 99.19403807771533
+    - type: cosine_f1
+      value: 96.45608628659475
+    - type: cosine_f1_threshold
+      value: 79.0391206741333
+    - type: cosine_precision
+      value: 97.50778816199377
+    - type: cosine_recall
+      value: 95.42682926829268
+    - type: dot_accuracy
+      value: 98.14471243042672
+    - type: dot_accuracy_threshold
+      value: 29808.1787109375
+    - type: dot_ap
+      value: 99.331999859971
+    - type: dot_f1
+      value: 97.01492537313433
+    - type: dot_f1_threshold
+      value: 29808.1787109375
+    - type: dot_precision
+      value: 95.02923976608187
+    - type: dot_recall
+      value: 99.08536585365853
+    - type: euclidean_accuracy
+      value: 97.49536178107606
+    - type: euclidean_accuracy_threshold
+      value: 1276.227855682373
+    - type: euclidean_ap
+      value: 98.91056467717377
+    - type: euclidean_f1
+      value: 95.83975346687212
+    - type: euclidean_f1_threshold
+      value: 1276.227855682373
+    - type: euclidean_precision
+      value: 96.88473520249221
+    - type: euclidean_recall
+      value: 94.8170731707317
+    - type: main_score
+      value: 99.331999859971
+    - type: manhattan_accuracy
+      value: 97.49536178107606
+    - type: manhattan_accuracy_threshold
+      value: 31097.674560546875
+    - type: manhattan_ap
+      value: 98.95694691792707
+    - type: manhattan_f1
+      value: 95.83975346687212
+    - type: manhattan_f1_threshold
+      value: 31097.674560546875
+    - type: manhattan_precision
+      value: 96.88473520249221
+    - type: manhattan_recall
+      value: 94.8170731707317
+    - type: max_accuracy
+      value: 98.14471243042672
+    - type: max_ap
+      value: 99.331999859971
+    - type: max_f1
+      value: 97.01492537313433
+    - type: max_precision
+      value: 97.50778816199377
+    - type: max_recall
+      value: 99.08536585365853
+    - type: similarity_accuracy
+      value: 97.86641929499072
+    - type: similarity_accuracy_threshold
+      value: 79.0391206741333
+    - type: similarity_ap
+      value: 99.19403807771533
+    - type: similarity_f1
+      value: 96.45608628659475
+    - type: similarity_f1_threshold
+      value: 79.0391206741333
+    - type: similarity_precision
+      value: 97.50778816199377
+    - type: similarity_recall
+      value: 95.42682926829268
+    task:
+      type: PairClassification
+  - dataset:
+      config: en
+      name: MTEB PawsXPairClassification (en)
+      revision: 8a04d940a42cd40658986fdd8e3da561533a3646
+      split: test
+      type: google-research-datasets/paws-x
+    metrics:
+    - type: cosine_accuracy
+      value: 61.8
+    - type: cosine_accuracy_threshold
+      value: 99.5664119720459
+    - type: cosine_ap
+      value: 60.679317786040585
+    - type: cosine_f1
+      value: 63.17354143441101
+    - type: cosine_f1_threshold
+      value: 97.22164869308472
+    - type: cosine_precision
+      value: 47.6457399103139
+    - type: cosine_recall
+      value: 93.71554575523705
+    - type: dot_accuracy
+      value: 55.7
+    - type: dot_accuracy_threshold
+      value: 48353.62548828125
+    - type: dot_ap
+      value: 48.53805970536875
+    - type: dot_f1
+      value: 62.42214532871972
+    - type: dot_f1_threshold
+      value: 38215.53955078125
+    - type: dot_precision
+      value: 45.48663640948058
+    - type: dot_recall
+      value: 99.44873208379272
+    - type: euclidean_accuracy
+      value: 61.75000000000001
+    - type: euclidean_accuracy_threshold
+      value: 189.0761137008667
+    - type: euclidean_ap
+      value: 60.55517418691518
+    - type: euclidean_f1
+      value: 63.07977736549165
+    - type: euclidean_f1_threshold
+      value: 504.3168067932129
+    - type: euclidean_precision
+      value: 47.53914988814318
+    - type: euclidean_recall
+      value: 93.71554575523705
+    - type: main_score
+      value: 60.679317786040585
+    - type: manhattan_accuracy
+      value: 61.9
+    - type: manhattan_accuracy_threshold
+      value: 4695.778274536133
+    - type: manhattan_ap
+      value: 60.48686620413608
+    - type: manhattan_f1
+      value: 62.92880855772778
+    - type: manhattan_f1_threshold
+      value: 12542.36831665039
+    - type: manhattan_precision
+      value: 47.28381374722838
+    - type: manhattan_recall
+      value: 94.04630650496141
+    - type: max_accuracy
+      value: 61.9
+    - type: max_ap
+      value: 60.679317786040585
+    - type: max_f1
+      value: 63.17354143441101
+    - type: max_precision
+      value: 47.6457399103139
+    - type: max_recall
+      value: 99.44873208379272
+    - type: similarity_accuracy
+      value: 61.8
+    - type: similarity_accuracy_threshold
+      value: 99.5664119720459
+    - type: similarity_ap
+      value: 60.679317786040585
+    - type: similarity_f1
+      value: 63.17354143441101
+    - type: similarity_f1_threshold
+      value: 97.22164869308472
+    - type: similarity_precision
+      value: 47.6457399103139
+    - type: similarity_recall
+      value: 93.71554575523705
+    task:
+      type: PairClassification
+  - dataset:
+      config: de
+      name: MTEB PawsXPairClassification (de)
+      revision: 8a04d940a42cd40658986fdd8e3da561533a3646
+      split: test
+      type: google-research-datasets/paws-x
+    metrics:
+    - type: cosine_accuracy
+      value: 60.25
+    - type: cosine_accuracy_threshold
+      value: 99.54338073730469
+    - type: cosine_ap
+      value: 56.7863613689054
+    - type: cosine_f1
+      value: 62.23499820337766
+    - type: cosine_f1_threshold
+      value: 89.95014429092407
+    - type: cosine_precision
+      value: 45.86864406779661
+    - type: cosine_recall
+      value: 96.75977653631284
+    - type: dot_accuracy
+      value: 56.8
+    - type: dot_accuracy_threshold
+      value: 47349.78332519531
+    - type: dot_ap
+      value: 49.7857806061729
+    - type: dot_f1
+      value: 62.31225986727209
+    - type: dot_f1_threshold
+      value: 30143.206787109375
+    - type: dot_precision
+      value: 45.32520325203252
+    - type: dot_recall
+      value: 99.66480446927373
+    - type: euclidean_accuracy
+      value: 60.3
+    - type: euclidean_accuracy_threshold
+      value: 219.78106498718262
+    - type: euclidean_ap
+      value: 56.731544327179606
+    - type: euclidean_f1
+      value: 62.19895287958115
+    - type: euclidean_f1_threshold
+      value: 1792.1623229980469
+    - type: euclidean_precision
+      value: 45.22842639593909
+    - type: euclidean_recall
+      value: 99.55307262569832
+    - type: main_score
+      value: 56.7863613689054
+    - type: manhattan_accuracy
+      value: 60.150000000000006
+    - type: manhattan_accuracy_threshold
+      value: 5104.503631591797
+    - type: manhattan_ap
+      value: 56.70304479768734
+    - type: manhattan_f1
+      value: 62.22067039106145
+    - type: manhattan_f1_threshold
+      value: 42839.471435546875
+    - type: manhattan_precision
+      value: 45.2513966480447
+    - type: manhattan_recall
+      value: 99.55307262569832
+    - type: max_accuracy
+      value: 60.3
+    - type: max_ap
+      value: 56.7863613689054
+    - type: max_f1
+      value: 62.31225986727209
+    - type: max_precision
+      value: 45.86864406779661
+    - type: max_recall
+      value: 99.66480446927373
+    - type: similarity_accuracy
+      value: 60.25
+    - type: similarity_accuracy_threshold
+      value: 99.54338073730469
+    - type: similarity_ap
+      value: 56.7863613689054
+    - type: similarity_f1
+      value: 62.23499820337766
+    - type: similarity_f1_threshold
+      value: 89.95014429092407
+    - type: similarity_precision
+      value: 45.86864406779661
+    - type: similarity_recall
+      value: 96.75977653631284
+    task:
+      type: PairClassification
+  - dataset:
+      config: es
+      name: MTEB PawsXPairClassification (es)
+      revision: 8a04d940a42cd40658986fdd8e3da561533a3646
+      split: test
+      type: google-research-datasets/paws-x
+    metrics:
+    - type: cosine_accuracy
+      value: 59.699999999999996
+    - type: cosine_accuracy_threshold
+      value: 99.55930709838867
+    - type: cosine_ap
+      value: 57.31662248806265
+    - type: cosine_f1
+      value: 62.444061962134256
+    - type: cosine_f1_threshold
+      value: 74.75898265838623
+    - type: cosine_precision
+      value: 45.3953953953954
+    - type: cosine_recall
+      value: 100.0
+    - type: dot_accuracy
+      value: 55.900000000000006
+    - type: dot_accuracy_threshold
+      value: 47512.90283203125
+    - type: dot_ap
+      value: 49.39339147787568
+    - type: dot_f1
+      value: 62.487082328625554
+    - type: dot_f1_threshold
+      value: 34989.03503417969
+    - type: dot_precision
+      value: 45.44088176352705
+    - type: dot_recall
+      value: 100.0
+    - type: euclidean_accuracy
+      value: 59.599999999999994
+    - type: euclidean_accuracy_threshold
+      value: 200.82547664642334
+    - type: euclidean_ap
+      value: 57.19737488445163
+    - type: euclidean_f1
+      value: 62.444061962134256
+    - type: euclidean_f1_threshold
+      value: 1538.8837814331055
+    - type: euclidean_precision
+      value: 45.3953953953954
+    - type: euclidean_recall
+      value: 100.0
+    - type: main_score
+      value: 57.31662248806265
+    - type: manhattan_accuracy
+      value: 59.550000000000004
+    - type: manhattan_accuracy_threshold
+      value: 5016.501617431641
+    - type: manhattan_ap
+      value: 57.089959907945065
+    - type: manhattan_f1
+      value: 62.444061962134256
+    - type: manhattan_f1_threshold
+      value: 37523.53515625
+    - type: manhattan_precision
+      value: 45.3953953953954
+    - type: manhattan_recall
+      value: 100.0
+    - type: max_accuracy
+      value: 59.699999999999996
+    - type: max_ap
+      value: 57.31662248806265
+    - type: max_f1
+      value: 62.487082328625554
+    - type: max_precision
+      value: 45.44088176352705
+    - type: max_recall
+      value: 100.0
+    - type: similarity_accuracy
+      value: 59.699999999999996
+    - type: similarity_accuracy_threshold
+      value: 99.55930709838867
+    - type: similarity_ap
+      value: 57.31662248806265
+    - type: similarity_f1
+      value: 62.444061962134256
+    - type: similarity_f1_threshold
+      value: 74.75898265838623
+    - type: similarity_precision
+      value: 45.3953953953954
+    - type: similarity_recall
+      value: 100.0
+    task:
+      type: PairClassification
+  - dataset:
+      config: fr
+      name: MTEB PawsXPairClassification (fr)
+      revision: 8a04d940a42cd40658986fdd8e3da561533a3646
+      split: test
+      type: google-research-datasets/paws-x
+    metrics:
+    - type: cosine_accuracy
+      value: 61.150000000000006
+    - type: cosine_accuracy_threshold
+      value: 99.36153888702393
+    - type: cosine_ap
+      value: 59.43845317938599
+    - type: cosine_f1
+      value: 62.51298026998961
+    - type: cosine_f1_threshold
+      value: 76.77866220474243
+    - type: cosine_precision
+      value: 45.468277945619334
+    - type: cosine_recall
+      value: 100.0
+    - type: dot_accuracy
+      value: 55.75
+    - type: dot_accuracy_threshold
+      value: 48931.55212402344
+    - type: dot_ap
+      value: 50.15949290538757
+    - type: dot_f1
+      value: 62.53462603878117
+    - type: dot_f1_threshold
+      value: 34415.7958984375
+    - type: dot_precision
+      value: 45.4911838790932
+    - type: dot_recall
+      value: 100.0
+    - type: euclidean_accuracy
+      value: 61.050000000000004
+    - type: euclidean_accuracy_threshold
+      value: 240.8097267150879
+    - type: euclidean_ap
+      value: 59.367971294226216
+    - type: euclidean_f1
+      value: 62.51298026998961
+    - type: euclidean_f1_threshold
+      value: 1444.132423400879
+    - type: euclidean_precision
+      value: 45.468277945619334
+    - type: euclidean_recall
+      value: 100.0
+    - type: main_score
+      value: 59.43845317938599
+    - type: manhattan_accuracy
+      value: 60.95
+    - type: manhattan_accuracy_threshold
+      value: 5701.206207275391
+    - type: manhattan_ap
+      value: 59.30094096378774
+    - type: manhattan_f1
+      value: 62.53462603878117
+    - type: manhattan_f1_threshold
+      value: 33445.672607421875
+    - type: manhattan_precision
+      value: 45.4911838790932
+    - type: manhattan_recall
+      value: 100.0
+    - type: max_accuracy
+      value: 61.150000000000006
+    - type: max_ap
+      value: 59.43845317938599
+    - type: max_f1
+      value: 62.53462603878117
+    - type: max_precision
+      value: 45.4911838790932
+    - type: max_recall
+      value: 100.0
+    - type: similarity_accuracy
+      value: 61.150000000000006
+    - type: similarity_accuracy_threshold
+      value: 99.36153888702393
+    - type: similarity_ap
+      value: 59.43845317938599
+    - type: similarity_f1
+      value: 62.51298026998961
+    - type: similarity_f1_threshold
+      value: 76.77866220474243
+    - type: similarity_precision
+      value: 45.468277945619334
+    - type: similarity_recall
+      value: 100.0
+    task:
+      type: PairClassification
+  - dataset:
+      config: zh
+      name: MTEB PawsXPairClassification (zh)
+      revision: 8a04d940a42cd40658986fdd8e3da561533a3646
+      split: test
+      type: google-research-datasets/paws-x
+    metrics:
+    - type: cosine_accuracy
+      value: 58.85
+    - type: cosine_accuracy_threshold
+      value: 99.73838329315186
+    - type: cosine_ap
+      value: 54.66913160570546
+    - type: cosine_f1
+      value: 62.32136632973162
+    - type: cosine_f1_threshold
+      value: 76.4499306678772
+    - type: cosine_precision
+      value: 45.265822784810126
+    - type: cosine_recall
+      value: 100.0
+    - type: dot_accuracy
+      value: 56.25
+    - type: dot_accuracy_threshold
+      value: 47351.9287109375
+    - type: dot_ap
+      value: 48.5266232989438
+    - type: dot_f1
+      value: 62.277951933124356
+    - type: dot_f1_threshold
+      value: 31325.28076171875
+    - type: dot_precision
+      value: 45.220030349013655
+    - type: dot_recall
+      value: 100.0
+    - type: euclidean_accuracy
+      value: 58.9
+    - type: euclidean_accuracy_threshold
+      value: 144.24468278884888
+    - type: euclidean_ap
+      value: 54.66981490353506
+    - type: euclidean_f1
+      value: 62.32136632973162
+    - type: euclidean_f1_threshold
+      value: 1484.908676147461
+    - type: euclidean_precision
+      value: 45.265822784810126
+    - type: euclidean_recall
+      value: 100.0
+    - type: main_score
+      value: 54.66981490353506
+    - type: manhattan_accuracy
+      value: 58.9
+    - type: manhattan_accuracy_threshold
+      value: 3586.785125732422
+    - type: manhattan_ap
+      value: 54.668355260247736
+    - type: manhattan_f1
+      value: 62.32136632973162
+    - type: manhattan_f1_threshold
+      value: 36031.22863769531
+    - type: manhattan_precision
+      value: 45.265822784810126
+    - type: manhattan_recall
+      value: 100.0
+    - type: max_accuracy
+      value: 58.9
+    - type: max_ap
+      value: 54.66981490353506
+    - type: max_f1
+      value: 62.32136632973162
+    - type: max_precision
+      value: 45.265822784810126
+    - type: max_recall
+      value: 100.0
+    - type: similarity_accuracy
+      value: 58.85
+    - type: similarity_accuracy_threshold
+      value: 99.73838329315186
+    - type: similarity_ap
+      value: 54.66913160570546
+    - type: similarity_f1
+      value: 62.32136632973162
+    - type: similarity_f1_threshold
+      value: 76.4499306678772
+    - type: similarity_precision
+      value: 45.265822784810126
+    - type: similarity_recall
+      value: 100.0
+    task:
+      type: PairClassification
+  - dataset:
+      config: default
+      name: MTEB PolEmo2.0-IN (default)
+      revision: d90724373c70959f17d2331ad51fb60c71176b03
+      split: test
+      type: PL-MTEB/polemo2_in
+    metrics:
+    - type: accuracy
+      value: 83.75346260387812
+    - type: f1
+      value: 81.98304891214909
+    - type: f1_weighted
+      value: 84.29623200830078
+    - type: main_score
+      value: 83.75346260387812
+    task:
+      type: Classification
+  - dataset:
+      config: default
+      name: MTEB PolEmo2.0-OUT (default)
+      revision: 6a21ab8716e255ab1867265f8b396105e8aa63d4
+      split: test
+      type: PL-MTEB/polemo2_out
+    metrics:
+    - type: accuracy
+      value: 66.53846153846153
+    - type: f1
+      value: 52.71826064368638
+    - type: f1_weighted
+      value: 69.10010124630334
+    - type: main_score
+      value: 66.53846153846153
+    task:
+      type: Classification
+  - dataset:
+      config: default
+      name: MTEB PpcPC (default)
+      revision: 2c7d2df57801a591f6b1e3aaf042e7a04ec7d9f2
+      split: test
+      type: PL-MTEB/ppc-pairclassification
+    metrics:
+    - type: cosine_accuracy
+      value: 81.8
+    - type: cosine_accuracy_threshold
+      value: 90.47793745994568
+    - type: cosine_ap
+      value: 91.42490266080884
+    - type: cosine_f1
+      value: 85.4632587859425
+    - type: cosine_f1_threshold
+      value: 90.47793745994568
+    - type: cosine_precision
+      value: 82.56172839506173
+    - type: cosine_recall
+      value: 88.57615894039735
+    - type: dot_accuracy
+      value: 74.6
+    - type: dot_accuracy_threshold
+      value: 42102.23693847656
+    - type: dot_ap
+      value: 86.20060009096979
+    - type: dot_f1
+      value: 80.02842928216063
+    - type: dot_f1_threshold
+      value: 38970.16906738281
+    - type: dot_precision
+      value: 70.1120797011208
+    - type: dot_recall
+      value: 93.21192052980133
+    - type: euclidean_accuracy
+      value: 81.5
+    - type: euclidean_accuracy_threshold
+      value: 880.433464050293
+    - type: euclidean_ap
+      value: 91.33143477982087
+    - type: euclidean_f1
+      value: 85.44600938967135
+    - type: euclidean_f1_threshold
+      value: 964.0384674072266
+    - type: euclidean_precision
+      value: 81.00890207715133
+    - type: euclidean_recall
+      value: 90.39735099337747
+    - type: main_score
+      value: 91.42490266080884
+    - type: manhattan_accuracy
+      value: 81.3
+    - type: manhattan_accuracy_threshold
+      value: 22100.830078125
+    - type: manhattan_ap
+      value: 91.25996158651282
+    - type: manhattan_f1
+      value: 85.38102643856921
+    - type: manhattan_f1_threshold
+      value: 24043.515014648438
+    - type: manhattan_precision
+      value: 80.49853372434018
+    - type: manhattan_recall
+      value: 90.89403973509934
+    - type: max_accuracy
+      value: 81.8
+    - type: max_ap
+      value: 91.42490266080884
+    - type: max_f1
+      value: 85.4632587859425
+    - type: max_precision
+      value: 82.56172839506173
+    - type: max_recall
+      value: 93.21192052980133
+    - type: similarity_accuracy
+      value: 81.8
+    - type: similarity_accuracy_threshold
+      value: 90.47793745994568
+    - type: similarity_ap
+      value: 91.42490266080884
+    - type: similarity_f1
+      value: 85.4632587859425
+    - type: similarity_f1_threshold
+      value: 90.47793745994568
+    - type: similarity_precision
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+    - type: similarity_recall
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+    - type: ndcg_at_10
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+    - type: ndcg_at_100
+      value: 75.074
+    - type: ndcg_at_1000
+      value: 75.581
+    - type: ndcg_at_20
+      value: 73.875
+    - type: ndcg_at_3
+      value: 65.641
+    - type: ndcg_at_5
+      value: 69.48299999999999
+    - type: precision_at_1
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+    - type: precision_at_10
+      value: 13.907
+    - type: precision_at_100
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+    - type: precision_at_1000
+      value: 0.166
+    - type: precision_at_20
+      value: 7.446999999999999
+    - type: precision_at_3
+      value: 35.619
+    - type: precision_at_5
+      value: 24.917
+    - type: recall_at_1
+      value: 44.187
+    - type: recall_at_10
+      value: 85.10600000000001
+    - type: recall_at_100
+      value: 95.488
+    - type: recall_at_1000
+      value: 98.831
+    - type: recall_at_20
+      value: 90.22200000000001
+    - type: recall_at_3
+      value: 68.789
+    - type: recall_at_5
+      value: 77.85499999999999
+    task:
+      type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB RuReviewsClassification (default)
+      revision: f6d2c31f4dc6b88f468552750bfec05b4b41b05a
+      split: test
+      type: ai-forever/ru-reviews-classification
+    metrics:
+    - type: accuracy
+      value: 67.5830078125
+    - type: f1
+      value: 67.56931936632446
+    - type: f1_weighted
+      value: 67.57137733752779
+    - type: main_score
+      value: 67.5830078125
+    task:
+      type: Classification
+  - dataset:
+      config: default
+      name: MTEB RuSTSBenchmarkSTS (default)
+      revision: 7cf24f325c6da6195df55bef3d86b5e0616f3018
+      split: test
+      type: ai-forever/ru-stsbenchmark-sts
+    metrics:
+    - type: cosine_pearson
+      value: 85.90493484626788
+    - type: cosine_spearman
+      value: 86.21965691667411
+    - type: euclidean_pearson
+      value: 86.07499842984909
+    - type: euclidean_spearman
+      value: 86.55506818735688
+    - type: main_score
+      value: 86.21965691667411
+    - type: manhattan_pearson
+      value: 85.95976420231729
+    - type: manhattan_spearman
+      value: 86.48604243661234
+    - type: pearson
+      value: 85.90493484626788
+    - type: spearman
+      value: 86.21965691667411
+    task:
+      type: STS
+  - dataset:
+      config: default
+      name: MTEB RuSciBenchGRNTIClassification (default)
+      revision: 673a610d6d3dd91a547a0d57ae1b56f37ebbf6a1
+      split: test
+      type: ai-forever/ru-scibench-grnti-classification
+    metrics:
+    - type: accuracy
+      value: 59.1943359375
+    - type: f1
+      value: 58.894480861440414
+    - type: f1_weighted
+      value: 58.903615560240866
+    - type: main_score
+      value: 59.1943359375
+    task:
+      type: Classification
+  - dataset:
+      config: default
+      name: MTEB RuSciBenchGRNTIClusteringP2P (default)
+      revision: 673a610d6d3dd91a547a0d57ae1b56f37ebbf6a1
+      split: test
+      type: ai-forever/ru-scibench-grnti-classification
+    metrics:
+    - type: main_score
+      value: 57.99209448663228
+    - type: v_measure
+      value: 57.99209448663228
+    - type: v_measure_std
+      value: 1.0381163861993816
+    task:
+      type: Clustering
+  - dataset:
+      config: default
+      name: MTEB RuSciBenchOECDClassification (default)
+      revision: 26c88e99dcaba32bb45d0e1bfc21902337f6d471
+      split: test
+      type: ai-forever/ru-scibench-oecd-classification
+    metrics:
+    - type: accuracy
+      value: 45.556640625
+    - type: f1
+      value: 45.159163104085906
+    - type: f1_weighted
+      value: 45.16098316398626
+    - type: main_score
+      value: 45.556640625
+    task:
+      type: Classification
+  - dataset:
+      config: default
+      name: MTEB RuSciBenchOECDClusteringP2P (default)
+      revision: 26c88e99dcaba32bb45d0e1bfc21902337f6d471
+      split: test
+      type: ai-forever/ru-scibench-oecd-classification
+    metrics:
+    - type: main_score
+      value: 50.787548070488974
+    - type: v_measure
+      value: 50.787548070488974
+    - type: v_measure_std
+      value: 0.8569958168946827
+    task:
+      type: Clustering
+  - dataset:
+      config: default
+      name: MTEB SCIDOCS (default)
+      revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88
+      split: test
+      type: mteb/scidocs
+    metrics:
+    - type: map_at_1
+      value: 4.843
+    - type: map_at_10
+      value: 11.752
+    - type: map_at_100
+      value: 13.919
+    - type: map_at_1000
+      value: 14.198
+    - type: map_at_20
+      value: 12.898000000000001
+    - type: map_at_3
+      value: 8.603
+    - type: map_at_5
+      value: 10.069
+    - type: mrr_at_1
+      value: 23.799999999999997
+    - type: mrr_at_10
+      value: 34.449999999999996
+    - type: mrr_at_100
+      value: 35.64
+    - type: mrr_at_1000
+      value: 35.691
+    - type: mrr_at_20
+      value: 35.213
+    - type: mrr_at_3
+      value: 31.383
+    - type: mrr_at_5
+      value: 33.062999999999995
+    - type: ndcg_at_1
+      value: 23.799999999999997
+    - type: ndcg_at_10
+      value: 19.811
+    - type: ndcg_at_100
+      value: 28.108
+    - type: ndcg_at_1000
+      value: 33.1
+    - type: ndcg_at_20
+      value: 22.980999999999998
+    - type: ndcg_at_3
+      value: 19.153000000000002
+    - type: ndcg_at_5
+      value: 16.408
+    - type: precision_at_1
+      value: 23.799999999999997
+    - type: precision_at_10
+      value: 10.16
+    - type: precision_at_100
+      value: 2.1999999999999997
+    - type: precision_at_1000
+      value: 0.34099999999999997
+    - type: precision_at_20
+      value: 6.915
+    - type: precision_at_3
+      value: 17.8
+    - type: precision_at_5
+      value: 14.14
+    - type: recall_at_1
+      value: 4.843
+    - type: recall_at_10
+      value: 20.595
+    - type: recall_at_100
+      value: 44.66
+    - type: recall_at_1000
+      value: 69.152
+    - type: recall_at_20
+      value: 28.04
+    - type: recall_at_3
+      value: 10.833
+    - type: recall_at_5
+      value: 14.346999999999998
+    - type: main_score
+      value: 19.811
+    task:
+      type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB SICK-E-PL (default)
+      revision: 71bba34b0ece6c56dfcf46d9758a27f7a90f17e9
+      split: test
+      type: PL-MTEB/sicke-pl-pairclassification
+    metrics:
+    - type: cosine_accuracy
+      value: 80.90093762739502
+    - type: cosine_accuracy_threshold
+      value: 94.40930485725403
+    - type: cosine_ap
+      value: 71.15400909912427
+    - type: cosine_f1
+      value: 66.8213457076566
+    - type: cosine_f1_threshold
+      value: 91.53673648834229
+    - type: cosine_precision
+      value: 62.4922504649721
+    - type: cosine_recall
+      value: 71.7948717948718
+    - type: dot_accuracy
+      value: 78.41418671015083
+    - type: dot_accuracy_threshold
+      value: 42924.45068359375
+    - type: dot_ap
+      value: 63.34003025365763
+    - type: dot_f1
+      value: 62.518258837277244
+    - type: dot_f1_threshold
+      value: 40900.738525390625
+    - type: dot_precision
+      value: 52.99653293709758
+    - type: dot_recall
+      value: 76.21082621082621
+    - type: euclidean_accuracy
+      value: 80.67672238075826
+    - type: euclidean_accuracy_threshold
+      value: 696.0524559020996
+    - type: euclidean_ap
+      value: 70.88762835990224
+    - type: euclidean_f1
+      value: 66.711051930759
+    - type: euclidean_f1_threshold
+      value: 878.5581588745117
+    - type: euclidean_precision
+      value: 62.625
+    - type: euclidean_recall
+      value: 71.36752136752136
+    - type: main_score
+      value: 71.15400909912427
+    - type: manhattan_accuracy
+      value: 80.65633917651854
+    - type: manhattan_accuracy_threshold
+      value: 17277.72674560547
+    - type: manhattan_ap
+      value: 70.67105336611716
+    - type: manhattan_f1
+      value: 66.51346027577151
+    - type: manhattan_f1_threshold
+      value: 21687.957763671875
+    - type: manhattan_precision
+      value: 61.69305724725944
+    - type: manhattan_recall
+      value: 72.15099715099716
+    - type: max_accuracy
+      value: 80.90093762739502
+    - type: max_ap
+      value: 71.15400909912427
+    - type: max_f1
+      value: 66.8213457076566
+    - type: max_precision
+      value: 62.625
+    - type: max_recall
+      value: 76.21082621082621
+    - type: similarity_accuracy
+      value: 80.90093762739502
+    - type: similarity_accuracy_threshold
+      value: 94.40930485725403
+    - type: similarity_ap
+      value: 71.15400909912427
+    - type: similarity_f1
+      value: 66.8213457076566
+    - type: similarity_f1_threshold
+      value: 91.53673648834229
+    - type: similarity_precision
+      value: 62.4922504649721
+    - type: similarity_recall
+      value: 71.7948717948718
+    task:
+      type: PairClassification
+  - dataset:
+      config: default
+      name: MTEB SICK-R (default)
+      revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
+      split: test
+      type: mteb/sickr-sts
+    metrics:
+    - type: cosine_pearson
+      value: 92.3339946866199
+    - type: cosine_spearman
+      value: 89.61697355115497
+    - type: euclidean_pearson
+      value: 90.3264916449669
+    - type: euclidean_spearman
+      value: 89.36270451308866
+    - type: main_score
+      value: 89.61697355115497
+    - type: manhattan_pearson
+      value: 90.18909339052534
+    - type: manhattan_spearman
+      value: 89.28337093097377
+    - type: pearson
+      value: 92.3339946866199
+    - type: spearman
+      value: 89.61697355115497
+    task:
+      type: STS
+  - dataset:
+      config: default
+      name: MTEB SICK-R-PL (default)
+      revision: fd5c2441b7eeff8676768036142af4cfa42c1339
+      split: test
+      type: PL-MTEB/sickr-pl-sts
+    metrics:
+    - type: cosine_pearson
+      value: 85.27883048457821
+    - type: cosine_spearman
+      value: 80.53204892678619
+    - type: euclidean_pearson
+      value: 82.78520705216168
+    - type: euclidean_spearman
+      value: 80.27848359873212
+    - type: main_score
+      value: 80.53204892678619
+    - type: manhattan_pearson
+      value: 82.63270640583454
+    - type: manhattan_spearman
+      value: 80.21507977473146
+    - type: pearson
+      value: 85.27883048457821
+    - type: spearman
+      value: 80.53204892678619
+    task:
+      type: STS
+  - dataset:
+      config: default
+      name: MTEB SICKFr (default)
+      revision: e077ab4cf4774a1e36d86d593b150422fafd8e8a
+      split: test
+      type: Lajavaness/SICK-fr
+    metrics:
+    - type: cosine_pearson
+      value: 88.77029361817212
+    - type: cosine_spearman
+      value: 83.9453600346894
+    - type: euclidean_pearson
+      value: 85.85331086208573
+    - type: euclidean_spearman
+      value: 83.70852031985308
+    - type: main_score
+      value: 83.9453600346894
+    - type: manhattan_pearson
+      value: 85.66222265885914
+    - type: manhattan_spearman
+      value: 83.60833111525962
+    - type: pearson
+      value: 88.77029361817212
+    - type: spearman
+      value: 83.9453600346894
+    task:
+      type: STS
+  - dataset:
+      config: default
+      name: MTEB STS12 (default)
+      revision: a0d554a64d88156834ff5ae9920b964011b16384
+      split: test
+      type: mteb/sts12-sts
+    metrics:
+    - type: cosine_pearson
+      value: 88.76435859522375
+    - type: cosine_spearman
+      value: 82.43768167804375
+    - type: euclidean_pearson
+      value: 87.43566183874832
+    - type: euclidean_spearman
+      value: 82.82166873757507
+    - type: main_score
+      value: 82.43768167804375
+    - type: manhattan_pearson
+      value: 87.39450871380951
+    - type: manhattan_spearman
+      value: 82.89253043430163
+    - type: pearson
+      value: 88.76435859522375
+    - type: spearman
+      value: 82.43768167804375
+    task:
+      type: STS
+  - dataset:
+      config: default
+      name: MTEB STS13 (default)
+      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
+      split: test
+      type: mteb/sts13-sts
+    metrics:
+    - type: cosine_pearson
+      value: 88.86627241652141
+    - type: cosine_spearman
+      value: 89.49011599120688
+    - type: euclidean_pearson
+      value: 89.3314120073772
+    - type: euclidean_spearman
+      value: 89.8226502776963
+    - type: main_score
+      value: 89.49011599120688
+    - type: manhattan_pearson
+      value: 89.2252179076963
+    - type: manhattan_spearman
+      value: 89.74573844021225
+    - type: pearson
+      value: 88.86627241652141
+    - type: spearman
+      value: 89.49011599120688
+    task:
+      type: STS
+  - dataset:
+      config: default
+      name: MTEB STS14 (default)
+      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
+      split: test
+      type: mteb/sts14-sts
+    metrics:
+    - type: cosine_pearson
+      value: 87.22891405215968
+    - type: cosine_spearman
+      value: 84.9467188157614
+    - type: euclidean_pearson
+      value: 87.20330004726237
+    - type: euclidean_spearman
+      value: 85.34806059461808
+    - type: main_score
+      value: 84.9467188157614
+    - type: manhattan_pearson
+      value: 87.15224666107623
+    - type: manhattan_spearman
+      value: 85.34596898699708
+    - type: pearson
+      value: 87.22891405215968
+    - type: spearman
+      value: 84.9467188157614
+    task:
+      type: STS
+  - dataset:
+      config: default
+      name: MTEB STS15 (default)
+      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
+      split: test
+      type: mteb/sts15-sts
+    metrics:
+    - type: cosine_pearson
+      value: 88.14066430111033
+    - type: cosine_spearman
+      value: 89.31337445552545
+    - type: euclidean_pearson
+      value: 89.08039335366983
+    - type: euclidean_spearman
+      value: 89.6658762856415
+    - type: main_score
+      value: 89.31337445552545
+    - type: manhattan_pearson
+      value: 89.08057438154486
+    - type: manhattan_spearman
+      value: 89.68673984203022
+    - type: pearson
+      value: 88.14066430111033
+    - type: spearman
+      value: 89.31337445552545
+    task:
+      type: STS
+  - dataset:
+      config: default
+      name: MTEB STS16 (default)
+      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
+      split: test
+      type: mteb/sts16-sts
+    metrics:
+    - type: cosine_pearson
+      value: 85.14908856657084
+    - type: cosine_spearman
+      value: 86.84648320786727
+    - type: euclidean_pearson
+      value: 86.11454713131947
+    - type: euclidean_spearman
+      value: 86.77738862047961
+    - type: main_score
+      value: 86.84648320786727
+    - type: manhattan_pearson
+      value: 86.07804821916372
+    - type: manhattan_spearman
+      value: 86.78676064310474
+    - type: pearson
+      value: 85.14908856657084
+    - type: spearman
+      value: 86.84648320786727
+    task:
+      type: STS
+  - dataset:
+      config: en-en
+      name: MTEB STS17 (en-en)
+      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
+      split: test
+      type: mteb/sts17-crosslingual-sts
+    metrics:
+    - type: cosine_pearson
+      value: 89.61633502468356
+    - type: cosine_spearman
+      value: 89.99772663224805
+    - type: euclidean_pearson
+      value: 90.14056501501044
+    - type: euclidean_spearman
+      value: 90.04496896837503
+    - type: main_score
+      value: 89.99772663224805
+    - type: manhattan_pearson
+      value: 90.08964860311801
+    - type: manhattan_spearman
+      value: 90.00091712362196
+    - type: pearson
+      value: 89.61633502468356
+    - type: spearman
+      value: 89.99772663224805
+    task:
+      type: STS
+  - dataset:
+      config: es-en
+      name: MTEB STS17 (es-en)
+      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
+      split: test
+      type: mteb/sts17-crosslingual-sts
+    metrics:
+    - type: cosine_pearson
+      value: 86.44548026840202
+    - type: cosine_spearman
+      value: 87.26263108768539
+    - type: euclidean_pearson
+      value: 86.42844593583838
+    - type: euclidean_spearman
+      value: 86.89388428664364
+    - type: main_score
+      value: 87.26263108768539
+    - type: manhattan_pearson
+      value: 86.47186940800881
+    - type: manhattan_spearman
+      value: 87.02163091089946
+    - type: pearson
+      value: 86.44548026840202
+    - type: spearman
+      value: 87.26263108768539
+    task:
+      type: STS
+  - dataset:
+      config: en-de
+      name: MTEB STS17 (en-de)
+      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
+      split: test
+      type: mteb/sts17-crosslingual-sts
+    metrics:
+    - type: cosine_pearson
+      value: 87.89345132532758
+    - type: cosine_spearman
+      value: 87.96246221327699
+    - type: euclidean_pearson
+      value: 88.49013032701419
+    - type: euclidean_spearman
+      value: 87.81981265317344
+    - type: main_score
+      value: 87.96246221327699
+    - type: manhattan_pearson
+      value: 88.31360914178538
+    - type: manhattan_spearman
+      value: 87.62734530005075
+    - type: pearson
+      value: 87.89345132532758
+    - type: spearman
+      value: 87.96246221327699
+    task:
+      type: STS
+  - dataset:
+      config: es-es
+      name: MTEB STS17 (es-es)
+      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
+      split: test
+      type: mteb/sts17-crosslingual-sts
+    metrics:
+    - type: cosine_pearson
+      value: 88.4084678497171
+    - type: cosine_spearman
+      value: 88.77640638748285
+    - type: euclidean_pearson
+      value: 89.60124312475843
+    - type: euclidean_spearman
+      value: 88.4321442688528
+    - type: main_score
+      value: 88.77640638748285
+    - type: manhattan_pearson
+      value: 89.62375118021299
+    - type: manhattan_spearman
+      value: 88.46998118661577
+    - type: pearson
+      value: 88.4084678497171
+    - type: spearman
+      value: 88.77640638748285
+    task:
+      type: STS
+  - dataset:
+      config: fr-en
+      name: MTEB STS17 (fr-en)
+      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
+      split: test
+      type: mteb/sts17-crosslingual-sts
+    metrics:
+    - type: cosine_pearson
+      value: 87.30688801326498
+    - type: cosine_spearman
+      value: 87.55684697258378
+    - type: euclidean_pearson
+      value: 87.89672951056794
+    - type: euclidean_spearman
+      value: 87.28050429201674
+    - type: main_score
+      value: 87.55684697258378
+    - type: manhattan_pearson
+      value: 87.74292745320572
+    - type: manhattan_spearman
+      value: 87.16383993876582
+    - type: pearson
+      value: 87.30688801326498
+    - type: spearman
+      value: 87.55684697258378
+    task:
+      type: STS
+  - dataset:
+      config: zh-en
+      name: MTEB STS22 (zh-en)
+      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
+      split: test
+      type: mteb/sts22-crosslingual-sts
+    metrics:
+    - type: cosine_pearson
+      value: 73.46180375170147
+    - type: cosine_spearman
+      value: 73.39559590127081
+    - type: euclidean_pearson
+      value: 73.72613901293681
+    - type: euclidean_spearman
+      value: 71.85465165176795
+    - type: main_score
+      value: 73.39559590127081
+    - type: manhattan_pearson
+      value: 73.07859140869076
+    - type: manhattan_spearman
+      value: 71.22047343718893
+    - type: pearson
+      value: 73.46180375170147
+    - type: spearman
+      value: 73.39559590127081
+    task:
+      type: STS
+  - dataset:
+      config: zh
+      name: MTEB STS22 (zh)
+      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
+      split: test
+      type: mteb/sts22-crosslingual-sts
+    metrics:
+    - type: cosine_pearson
+      value: 62.47531620842637
+    - type: cosine_spearman
+      value: 66.22504667157702
+    - type: euclidean_pearson
+      value: 66.76201254783692
+    - type: euclidean_spearman
+      value: 66.86115760269463
+    - type: main_score
+      value: 66.22504667157702
+    - type: manhattan_pearson
+      value: 66.73847836793489
+    - type: manhattan_spearman
+      value: 66.7677116377695
+    - type: pearson
+      value: 62.47531620842637
+    - type: spearman
+      value: 66.22504667157702
+    task:
+      type: STS
+  - dataset:
+      config: es
+      name: MTEB STS22 (es)
+      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
+      split: test
+      type: mteb/sts22-crosslingual-sts
+    metrics:
+    - type: cosine_pearson
+      value: 69.89707002436481
+    - type: cosine_spearman
+      value: 72.2054865735116
+    - type: euclidean_pearson
+      value: 71.81856615570756
+    - type: euclidean_spearman
+      value: 72.72593304629407
+    - type: main_score
+      value: 72.2054865735116
+    - type: manhattan_pearson
+      value: 72.00362684700072
+    - type: manhattan_spearman
+      value: 72.62783534769964
+    - type: pearson
+      value: 69.89707002436481
+    - type: spearman
+      value: 72.2054865735116
+    task:
+      type: STS
+  - dataset:
+      config: fr
+      name: MTEB STS22 (fr)
+      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
+      split: test
+      type: mteb/sts22-crosslingual-sts
+    metrics:
+    - type: cosine_pearson
+      value: 81.59623734395916
+    - type: cosine_spearman
+      value: 83.28946105111358
+    - type: euclidean_pearson
+      value: 79.377330171466
+    - type: euclidean_spearman
+      value: 81.81029781662205
+    - type: main_score
+      value: 83.28946105111358
+    - type: manhattan_pearson
+      value: 78.96970881689698
+    - type: manhattan_spearman
+      value: 81.91773236079703
+    - type: pearson
+      value: 81.59623734395916
+    - type: spearman
+      value: 83.28946105111358
+    task:
+      type: STS
+  - dataset:
+      config: de-fr
+      name: MTEB STS22 (de-fr)
+      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
+      split: test
+      type: mteb/sts22-crosslingual-sts
+    metrics:
+    - type: cosine_pearson
+      value: 55.03825643126142
+    - type: cosine_spearman
+      value: 58.25792501780429
+    - type: euclidean_pearson
+      value: 50.38007603973409
+    - type: euclidean_spearman
+      value: 59.39961789383097
+    - type: main_score
+      value: 58.25792501780429
+    - type: manhattan_pearson
+      value: 50.518568927999155
+    - type: manhattan_spearman
+      value: 59.84185466003894
+    - type: pearson
+      value: 55.03825643126142
+    - type: spearman
+      value: 58.25792501780429
+    task:
+      type: STS
+  - dataset:
+      config: pl-en
+      name: MTEB STS22 (pl-en)
+      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
+      split: test
+      type: mteb/sts22-crosslingual-sts
+    metrics:
+    - type: cosine_pearson
+      value: 77.77233721490776
+    - type: cosine_spearman
+      value: 76.17596588017625
+    - type: euclidean_pearson
+      value: 74.47600468156611
+    - type: euclidean_spearman
+      value: 72.61278728057012
+    - type: main_score
+      value: 76.17596588017625
+    - type: manhattan_pearson
+      value: 74.48118910099699
+    - type: manhattan_spearman
+      value: 73.33167419101696
+    - type: pearson
+      value: 77.77233721490776
+    - type: spearman
+      value: 76.17596588017625
+    task:
+      type: STS
+  - dataset:
+      config: pl
+      name: MTEB STS22 (pl)
+      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
+      split: test
+      type: mteb/sts22-crosslingual-sts
+    metrics:
+    - type: cosine_pearson
+      value: 42.87453608131507
+    - type: cosine_spearman
+      value: 45.137849894401185
+    - type: euclidean_pearson
+      value: 31.66964197694796
+    - type: euclidean_spearman
+      value: 44.1014900837869
+    - type: main_score
+      value: 45.137849894401185
+    - type: manhattan_pearson
+      value: 31.007199259384745
+    - type: manhattan_spearman
+      value: 43.48181523288926
+    - type: pearson
+      value: 42.87453608131507
+    - type: spearman
+      value: 45.137849894401185
+    task:
+      type: STS
+  - dataset:
+      config: en
+      name: MTEB STS22 (en)
+      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
+      split: test
+      type: mteb/sts22-crosslingual-sts
+    metrics:
+    - type: cosine_pearson
+      value: 66.87400150638176
+    - type: cosine_spearman
+      value: 67.27861354834066
+    - type: euclidean_pearson
+      value: 66.81789582140216
+    - type: euclidean_spearman
+      value: 66.44220479858708
+    - type: main_score
+      value: 67.27861354834066
+    - type: manhattan_pearson
+      value: 66.92509859033235
+    - type: manhattan_spearman
+      value: 66.46841124185076
+    - type: pearson
+      value: 66.87400150638176
+    - type: spearman
+      value: 67.27861354834066
+    task:
+      type: STS
+  - dataset:
+      config: ru
+      name: MTEB STS22 (ru)
+      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
+      split: test
+      type: mteb/sts22-crosslingual-sts
+    metrics:
+    - type: cosine_pearson
+      value: 61.819804551576084
+    - type: cosine_spearman
+      value: 65.0864146772135
+    - type: euclidean_pearson
+      value: 62.518151090361876
+    - type: euclidean_spearman
+      value: 65.13608138548017
+    - type: main_score
+      value: 65.0864146772135
+    - type: manhattan_pearson
+      value: 62.51413246915267
+    - type: manhattan_spearman
+      value: 65.19077543064323
+    - type: pearson
+      value: 61.819804551576084
+    - type: spearman
+      value: 65.0864146772135
+    task:
+      type: STS
+  - dataset:
+      config: de
+      name: MTEB STS22 (de)
+      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
+      split: test
+      type: mteb/sts22-crosslingual-sts
+    metrics:
+    - type: cosine_pearson
+      value: 54.85728696035389
+    - type: cosine_spearman
+      value: 61.60906359227576
+    - type: euclidean_pearson
+      value: 52.57582587901851
+    - type: euclidean_spearman
+      value: 61.41823097598308
+    - type: main_score
+      value: 61.60906359227576
+    - type: manhattan_pearson
+      value: 52.500978361080506
+    - type: manhattan_spearman
+      value: 61.30365596659758
+    - type: pearson
+      value: 54.85728696035389
+    - type: spearman
+      value: 61.60906359227576
+    task:
+      type: STS
+  - dataset:
+      config: fr-pl
+      name: MTEB STS22 (fr-pl)
+      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
+      split: test
+      type: mteb/sts22-crosslingual-sts
+    metrics:
+    - type: cosine_pearson
+      value: 67.68016005631422
+    - type: cosine_spearman
+      value: 84.51542547285167
+    - type: euclidean_pearson
+      value: 66.19871164667245
+    - type: euclidean_spearman
+      value: 73.24670207647144
+    - type: main_score
+      value: 84.51542547285167
+    - type: manhattan_pearson
+      value: 67.0443525268974
+    - type: manhattan_spearman
+      value: 73.24670207647144
+    - type: pearson
+      value: 67.68016005631422
+    - type: spearman
+      value: 84.51542547285167
+    task:
+      type: STS
+  - dataset:
+      config: de-pl
+      name: MTEB STS22 (de-pl)
+      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
+      split: test
+      type: mteb/sts22-crosslingual-sts
+    metrics:
+    - type: cosine_pearson
+      value: 47.49467414030747
+    - type: cosine_spearman
+      value: 56.81512095681289
+    - type: euclidean_pearson
+      value: 48.42860221765214
+    - type: euclidean_spearman
+      value: 58.63197306329092
+    - type: main_score
+      value: 56.81512095681289
+    - type: manhattan_pearson
+      value: 48.39594959260441
+    - type: manhattan_spearman
+      value: 58.63197306329092
+    - type: pearson
+      value: 47.49467414030747
+    - type: spearman
+      value: 56.81512095681289
+    task:
+      type: STS
+  - dataset:
+      config: es-en
+      name: MTEB STS22 (es-en)
+      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
+      split: test
+      type: mteb/sts22-crosslingual-sts
+    metrics:
+    - type: cosine_pearson
+      value: 76.8364678896155
+    - type: cosine_spearman
+      value: 78.45516413087114
+    - type: euclidean_pearson
+      value: 78.62779318576634
+    - type: euclidean_spearman
+      value: 78.88760695649488
+    - type: main_score
+      value: 78.45516413087114
+    - type: manhattan_pearson
+      value: 78.62131335760031
+    - type: manhattan_spearman
+      value: 78.81861844200388
+    - type: pearson
+      value: 76.8364678896155
+    - type: spearman
+      value: 78.45516413087114
+    task:
+      type: STS
+  - dataset:
+      config: de-en
+      name: MTEB STS22 (de-en)
+      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
+      split: test
+      type: mteb/sts22-crosslingual-sts
+    metrics:
+    - type: cosine_pearson
+      value: 65.16640313911604
+    - type: cosine_spearman
+      value: 60.887608967403914
+    - type: euclidean_pearson
+      value: 67.49902244990913
+    - type: euclidean_spearman
+      value: 59.2458787136538
+    - type: main_score
+      value: 60.887608967403914
+    - type: manhattan_pearson
+      value: 67.34313506388378
+    - type: manhattan_spearman
+      value: 59.05283429200166
+    - type: pearson
+      value: 65.16640313911604
+    - type: spearman
+      value: 60.887608967403914
+    task:
+      type: STS
+  - dataset:
+      config: default
+      name: MTEB STSB (default)
+      revision: 0cde68302b3541bb8b3c340dc0644b0b745b3dc0
+      split: test
+      type: C-MTEB/STSB
+    metrics:
+    - type: cosine_pearson
+      value: 81.5092853013241
+    - type: cosine_spearman
+      value: 83.54005474244292
+    - type: euclidean_pearson
+      value: 83.7246578378554
+    - type: euclidean_spearman
+      value: 84.46767551087716
+    - type: main_score
+      value: 83.54005474244292
+    - type: manhattan_pearson
+      value: 83.65922665594636
+    - type: manhattan_spearman
+      value: 84.42431449101848
+    - type: pearson
+      value: 81.5092853013241
+    - type: spearman
+      value: 83.54005474244292
+    task:
+      type: STS
+  - dataset:
+      config: default
+      name: MTEB STSBenchmark (default)
+      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
+      split: test
+      type: mteb/stsbenchmark-sts
+    metrics:
+    - type: cosine_pearson
+      value: 87.70246866744966
+    - type: cosine_spearman
+      value: 89.44070045346106
+    - type: euclidean_pearson
+      value: 89.56956519641007
+    - type: euclidean_spearman
+      value: 89.95830112784283
+    - type: main_score
+      value: 89.44070045346106
+    - type: manhattan_pearson
+      value: 89.48264471425145
+    - type: manhattan_spearman
+      value: 89.87900732483114
+    - type: pearson
+      value: 87.70246866744966
+    - type: spearman
+      value: 89.44070045346106
+    task:
+      type: STS
+  - dataset:
+      config: de
+      name: MTEB STSBenchmarkMultilingualSTS (de)
+      revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
+      split: test
+      type: mteb/stsb_multi_mt
+    metrics:
+    - type: cosine_pearson
+      value: 86.83701990805217
+    - type: cosine_spearman
+      value: 87.80280785492258
+    - type: euclidean_pearson
+      value: 87.77325330043514
+    - type: euclidean_spearman
+      value: 88.3564607283144
+    - type: main_score
+      value: 87.80280785492258
+    - type: manhattan_pearson
+      value: 87.6745449945946
+    - type: manhattan_spearman
+      value: 88.30660465978795
+    - type: pearson
+      value: 86.83701990805217
+    - type: spearman
+      value: 87.80280785492258
+    task:
+      type: STS
+  - dataset:
+      config: zh
+      name: MTEB STSBenchmarkMultilingualSTS (zh)
+      revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
+      split: test
+      type: mteb/stsb_multi_mt
+    metrics:
+    - type: cosine_pearson
+      value: 84.27751020600267
+    - type: cosine_spearman
+      value: 85.63500407412486
+    - type: euclidean_pearson
+      value: 85.21829891649696
+    - type: euclidean_spearman
+      value: 85.9384575715382
+    - type: main_score
+      value: 85.63500407412486
+    - type: manhattan_pearson
+      value: 85.10797194089801
+    - type: manhattan_spearman
+      value: 85.8770162042784
+    - type: pearson
+      value: 84.27751020600267
+    - type: spearman
+      value: 85.63500407412486
+    task:
+      type: STS
+  - dataset:
+      config: fr
+      name: MTEB STSBenchmarkMultilingualSTS (fr)
+      revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
+      split: test
+      type: mteb/stsb_multi_mt
+    metrics:
+    - type: cosine_pearson
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+      name: MTEB STSBenchmarkMultilingualSTS (pl)
+      revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
+      split: test
+      type: mteb/stsb_multi_mt
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+      name: MTEB STSBenchmarkMultilingualSTS (es)
+      revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
+      split: test
+      type: mteb/stsb_multi_mt
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+      name: MTEB STSBenchmarkMultilingualSTS (ru)
+      revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
+      split: test
+      type: mteb/stsb_multi_mt
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+      name: MTEB STSBenchmarkMultilingualSTS (en)
+      revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
+      split: test
+      type: mteb/stsb_multi_mt
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+      name: MTEB SciDocsRR (default)
+      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
+      split: test
+      type: mteb/scidocs-reranking
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+      name: MTEB SciFact (default)
+      revision: 0228b52cf27578f30900b9e5271d331663a030d7
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+      type: mteb/scifact
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+      revision: 9cddf2ce5209ade52c2115ccfa00eb22c6d3a837
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+      type: jinaai/spanish_passage_retrieval
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+      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
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+    - type: nauc_ndcg_at_5_max
+      value: 62.33360746285387
+    - type: nauc_ndcg_at_5_std
+      value: 24.898000803570227
+    - type: nauc_precision_at_1000_diff1
+      value: -35.14745130154524
+    - type: nauc_precision_at_1000_max
+      value: 48.811507982849065
+    - type: nauc_precision_at_1000_std
+      value: 62.43036496029399
+    - type: nauc_precision_at_100_diff1
+      value: -35.15276411320076
+    - type: nauc_precision_at_100_max
+      value: 50.87010333741109
+    - type: nauc_precision_at_100_std
+      value: 63.418221030407175
+    - type: nauc_precision_at_10_diff1
+      value: -34.84255710936113
+    - type: nauc_precision_at_10_max
+      value: 56.588401051428825
+    - type: nauc_precision_at_10_std
+      value: 57.4763370653757
+    - type: nauc_precision_at_1_diff1
+      value: 47.98740362820094
+    - type: nauc_precision_at_1_max
+      value: 80.32340034580369
+    - type: nauc_precision_at_1_std
+      value: 34.57857131423388
+    - type: nauc_precision_at_20_diff1
+      value: -35.165762365233505
+    - type: nauc_precision_at_20_max
+      value: 54.148762449660424
+    - type: nauc_precision_at_20_std
+      value: 61.569719669368716
+    - type: nauc_precision_at_3_diff1
+      value: -28.63023175340299
+    - type: nauc_precision_at_3_max
+      value: 68.69825987618499
+    - type: nauc_precision_at_3_std
+      value: 48.15479495755423
+    - type: nauc_precision_at_5_diff1
+      value: -34.13811355456687
+    - type: nauc_precision_at_5_max
+      value: 62.369363941490604
+    - type: nauc_precision_at_5_std
+      value: 52.282904411187914
+    - type: nauc_recall_at_1000_diff1
+      value: 8.686444579162663
+    - type: nauc_recall_at_1000_max
+      value: 59.58864478011338
+    - type: nauc_recall_at_1000_std
+      value: 56.692774954297455
+    - type: nauc_recall_at_100_diff1
+      value: 8.820596225758342
+    - type: nauc_recall_at_100_max
+      value: 53.15048885657892
+    - type: nauc_recall_at_100_std
+      value: 39.78931159236714
+    - type: nauc_recall_at_10_diff1
+      value: 16.022301106315027
+    - type: nauc_recall_at_10_max
+      value: 29.83242342459543
+    - type: nauc_recall_at_10_std
+      value: -4.805965555875844
+    - type: nauc_recall_at_1_diff1
+      value: 52.87356542654683
+    - type: nauc_recall_at_1_max
+      value: -22.210039746171255
+    - type: nauc_recall_at_1_std
+      value: -38.11345358035342
+    - type: nauc_recall_at_20_diff1
+      value: 10.35772828627265
+    - type: nauc_recall_at_20_max
+      value: 43.06420839754062
+    - type: nauc_recall_at_20_std
+      value: 15.040522218235692
+    - type: nauc_recall_at_3_diff1
+      value: 36.23953684770224
+    - type: nauc_recall_at_3_max
+      value: -11.709269151700374
+    - type: nauc_recall_at_3_std
+      value: -38.13943178150384
+    - type: nauc_recall_at_5_diff1
+      value: 28.644872415763384
+    - type: nauc_recall_at_5_max
+      value: 2.062151266111129
+    - type: nauc_recall_at_5_std
+      value: -30.81114034774277
+    - type: ndcg_at_1
+      value: 88.901
+    - type: ndcg_at_10
+      value: 83.163
+    - type: ndcg_at_100
+      value: 86.854
+    - type: ndcg_at_1000
+      value: 87.602
+    - type: ndcg_at_20
+      value: 84.908
+    - type: ndcg_at_3
+      value: 84.848
+    - type: ndcg_at_5
+      value: 83.372
+    - type: precision_at_1
+      value: 88.901
+    - type: precision_at_10
+      value: 41.343
+    - type: precision_at_100
+      value: 4.957000000000001
+    - type: precision_at_1000
+      value: 0.513
+    - type: precision_at_20
+      value: 22.955000000000002
+    - type: precision_at_3
+      value: 74.29599999999999
+    - type: precision_at_5
+      value: 62.251999999999995
+    - type: recall_at_1
+      value: 26.875
+    - type: recall_at_10
+      value: 81.902
+    - type: recall_at_100
+      value: 93.988
+    - type: recall_at_1000
+      value: 97.801
+    - type: recall_at_20
+      value: 87.809
+    - type: recall_at_3
+      value: 54.869
+    - type: recall_at_5
+      value: 68.728
+    task:
+      type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB TERRa (default)
+      revision: 7b58f24536063837d644aab9a023c62199b2a612
+      split: dev
+      type: ai-forever/terra-pairclassification
+    metrics:
+    - type: cosine_accuracy
+      value: 60.586319218241044
+    - type: cosine_accuracy_threshold
+      value: 82.49806761741638
+    - type: cosine_ap
+      value: 58.73198048427448
+    - type: cosine_f1
+      value: 67.37967914438502
+    - type: cosine_f1_threshold
+      value: 77.46461033821106
+    - type: cosine_precision
+      value: 57.01357466063348
+    - type: cosine_recall
+      value: 82.35294117647058
+    - type: dot_accuracy
+      value: 60.26058631921825
+    - type: dot_accuracy_threshold
+      value: 35627.020263671875
+    - type: dot_ap
+      value: 57.418783612898224
+    - type: dot_f1
+      value: 66.51982378854623
+    - type: dot_f1_threshold
+      value: 27620.843505859375
+    - type: dot_precision
+      value: 50.16611295681063
+    - type: dot_recall
+      value: 98.69281045751634
+    - type: euclidean_accuracy
+      value: 60.26058631921825
+    - type: euclidean_accuracy_threshold
+      value: 1255.4466247558594
+    - type: euclidean_ap
+      value: 58.748656145387955
+    - type: euclidean_f1
+      value: 66.99029126213591
+    - type: euclidean_f1_threshold
+      value: 1565.1330947875977
+    - type: euclidean_precision
+      value: 53.28185328185329
+    - type: euclidean_recall
+      value: 90.19607843137256
+    - type: main_score
+      value: 58.8479126365766
+    - type: manhattan_accuracy
+      value: 59.934853420195445
+    - type: manhattan_accuracy_threshold
+      value: 29897.271728515625
+    - type: manhattan_ap
+      value: 58.8479126365766
+    - type: manhattan_f1
+      value: 66.81318681318683
+    - type: manhattan_f1_threshold
+      value: 46291.802978515625
+    - type: manhattan_precision
+      value: 50.331125827814574
+    - type: manhattan_recall
+      value: 99.34640522875817
+    - type: max_accuracy
+      value: 60.586319218241044
+    - type: max_ap
+      value: 58.8479126365766
+    - type: max_f1
+      value: 67.37967914438502
+    - type: max_precision
+      value: 57.01357466063348
+    - type: max_recall
+      value: 99.34640522875817
+    - type: similarity_accuracy
+      value: 60.586319218241044
+    - type: similarity_accuracy_threshold
+      value: 82.49806761741638
+    - type: similarity_ap
+      value: 58.73198048427448
+    - type: similarity_f1
+      value: 67.37967914438502
+    - type: similarity_f1_threshold
+      value: 77.46461033821106
+    - type: similarity_precision
+      value: 57.01357466063348
+    - type: similarity_recall
+      value: 82.35294117647058
+    task:
+      type: PairClassification
+  - dataset:
+      config: default
+      name: MTEB TNews (default)
+      revision: 317f262bf1e6126357bbe89e875451e4b0938fe4
+      split: validation
+      type: C-MTEB/TNews-classification
+    metrics:
+    - type: accuracy
+      value: 45.967999999999996
+    - type: f1
+      value: 44.699306100915706
+    - type: f1_weighted
+      value: 46.03730319014832
+    - type: main_score
+      value: 45.967999999999996
+    task:
+      type: Classification
+  - dataset:
+      config: default
+      name: MTEB TRECCOVID (default)
+      revision: bb9466bac8153a0349341eb1b22e06409e78ef4e
+      split: test
+      type: mteb/trec-covid
+    metrics:
+    - type: map_at_1
+      value: 0.251
+    - type: map_at_10
+      value: 1.9480000000000002
+    - type: map_at_100
+      value: 11.082
+    - type: map_at_1000
+      value: 26.700000000000003
+    - type: map_at_20
+      value: 3.3529999999999998
+    - type: map_at_3
+      value: 0.679
+    - type: map_at_5
+      value: 1.079
+    - type: mrr_at_1
+      value: 94.0
+    - type: mrr_at_10
+      value: 95.786
+    - type: mrr_at_100
+      value: 95.786
+    - type: mrr_at_1000
+      value: 95.786
+    - type: mrr_at_20
+      value: 95.786
+    - type: mrr_at_3
+      value: 95.0
+    - type: mrr_at_5
+      value: 95.5
+    - type: ndcg_at_1
+      value: 91.0
+    - type: ndcg_at_10
+      value: 77.71900000000001
+    - type: ndcg_at_100
+      value: 57.726
+    - type: ndcg_at_1000
+      value: 52.737
+    - type: ndcg_at_20
+      value: 72.54
+    - type: ndcg_at_3
+      value: 83.397
+    - type: ndcg_at_5
+      value: 80.806
+    - type: precision_at_1
+      value: 94.0
+    - type: precision_at_10
+      value: 81.0
+    - type: precision_at_100
+      value: 59.199999999999996
+    - type: precision_at_1000
+      value: 23.244
+    - type: precision_at_20
+      value: 75.2
+    - type: precision_at_3
+      value: 88.0
+    - type: precision_at_5
+      value: 84.8
+    - type: recall_at_1
+      value: 0.251
+    - type: recall_at_10
+      value: 2.1229999999999998
+    - type: recall_at_100
+      value: 14.496999999999998
+    - type: recall_at_1000
+      value: 50.09
+    - type: recall_at_20
+      value: 3.8309999999999995
+    - type: recall_at_3
+      value: 0.696
+    - type: recall_at_5
+      value: 1.1400000000000001
+    - type: main_score
+      value: 77.71900000000001
+    task:
+      type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB TenKGnadClusteringP2P (default)
+      revision: 5c59e41555244b7e45c9a6be2d720ab4bafae558
+      split: test
+      type: slvnwhrl/tenkgnad-clustering-p2p
+    metrics:
+    - type: main_score
+      value: 43.763609722295215
+    - type: v_measure
+      value: 43.763609722295215
+    - type: v_measure_std
+      value: 2.8751199473862457
+    task:
+      type: Clustering
+  - dataset:
+      config: default
+      name: MTEB TenKGnadClusteringS2S (default)
+      revision: 6cddbe003f12b9b140aec477b583ac4191f01786
+      split: test
+      type: slvnwhrl/tenkgnad-clustering-s2s
+    metrics:
+    - type: main_score
+      value: 39.762424448504355
+    - type: v_measure
+      value: 39.762424448504355
+    - type: v_measure_std
+      value: 3.30146124979502
+    task:
+      type: Clustering
+  - dataset:
+      config: default
+      name: MTEB ThuNewsClusteringP2P (default)
+      revision: 5798586b105c0434e4f0fe5e767abe619442cf93
+      split: test
+      type: C-MTEB/ThuNewsClusteringP2P
+    metrics:
+    - type: main_score
+      value: 63.133819258289456
+    - type: v_measure
+      value: 63.133819258289456
+    - type: v_measure_std
+      value: 1.8854253356479695
+    task:
+      type: Clustering
+  - dataset:
+      config: default
+      name: MTEB ThuNewsClusteringS2S (default)
+      revision: 8a8b2caeda43f39e13c4bc5bea0f8a667896e10d
+      split: test
+      type: C-MTEB/ThuNewsClusteringS2S
+    metrics:
+    - type: main_score
+      value: 58.98195851785808
+    - type: v_measure
+      value: 58.98195851785808
+    - type: v_measure_std
+      value: 1.6237600076393737
+    task:
+      type: Clustering
+  - dataset:
+      config: default
+      name: MTEB Touche2020 (default)
+      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
+      split: test
+      type: mteb/touche2020
+    metrics:
+    - type: map_at_1
+      value: 3.3550000000000004
+    - type: map_at_10
+      value: 10.08
+    - type: map_at_100
+      value: 16.136
+    - type: map_at_1000
+      value: 17.605
+    - type: map_at_20
+      value: 12.561
+    - type: map_at_3
+      value: 5.641
+    - type: map_at_5
+      value: 7.3260000000000005
+    - type: mrr_at_1
+      value: 46.939
+    - type: mrr_at_10
+      value: 58.152
+    - type: mrr_at_100
+      value: 58.594
+    - type: mrr_at_1000
+      value: 58.601000000000006
+    - type: mrr_at_20
+      value: 58.279
+    - type: mrr_at_3
+      value: 55.102
+    - type: mrr_at_5
+      value: 56.531
+    - type: ndcg_at_1
+      value: 44.897999999999996
+    - type: ndcg_at_10
+      value: 26.298
+    - type: ndcg_at_100
+      value: 37.596000000000004
+    - type: ndcg_at_1000
+      value: 49.424
+    - type: ndcg_at_20
+      value: 27.066000000000003
+    - type: ndcg_at_3
+      value: 31.528
+    - type: ndcg_at_5
+      value: 28.219
+    - type: precision_at_1
+      value: 46.939
+    - type: precision_at_10
+      value: 22.245
+    - type: precision_at_100
+      value: 7.531000000000001
+    - type: precision_at_1000
+      value: 1.5350000000000001
+    - type: precision_at_20
+      value: 17.041
+    - type: precision_at_3
+      value: 30.612000000000002
+    - type: precision_at_5
+      value: 26.122
+    - type: recall_at_1
+      value: 3.3550000000000004
+    - type: recall_at_10
+      value: 16.41
+    - type: recall_at_100
+      value: 47.272
+    - type: recall_at_1000
+      value: 83.584
+    - type: recall_at_20
+      value: 24.091
+    - type: recall_at_3
+      value: 6.8180000000000005
+    - type: recall_at_5
+      value: 9.677
+    - type: main_score
+      value: 26.298
+    task:
+      type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB ToxicConversationsClassification (default)
+      revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
+      split: test
+      type: mteb/toxic_conversations_50k
+    metrics:
+    - type: accuracy
+      value: 91.2890625
+    - type: ap
+      value: 33.95547153875715
+    - type: ap_weighted
+      value: 33.95547153875715
+    - type: f1
+      value: 75.10768597556462
+    - type: f1_weighted
+      value: 92.00161208992606
+    - type: main_score
+      value: 91.2890625
+    task:
+      type: Classification
+  - dataset:
+      config: default
+      name: MTEB TweetSentimentExtractionClassification (default)
+      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
+      split: test
+      type: mteb/tweet_sentiment_extraction
+    metrics:
+    - type: accuracy
+      value: 71.3978494623656
+    - type: f1
+      value: 71.7194818511814
+    - type: f1_weighted
+      value: 71.13860187349744
+    - type: main_score
+      value: 71.3978494623656
+    task:
+      type: Classification
+  - dataset:
+      config: default
+      name: MTEB TwentyNewsgroupsClustering (default)
+      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
+      split: test
+      type: mteb/twentynewsgroups-clustering
+    metrics:
+    - type: main_score
+      value: 52.4921688720602
+    - type: v_measure
+      value: 52.4921688720602
+    - type: v_measure_std
+      value: 0.992768152658908
+    task:
+      type: Clustering
+  - dataset:
+      config: default
+      name: MTEB TwitterSemEval2015 (default)
+      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
+      split: test
+      type: mteb/twittersemeval2015-pairclassification
+    metrics:
+    - type: cosine_accuracy
+      value: 85.11652858079513
+    - type: cosine_accuracy_threshold
+      value: 87.90839910507202
+    - type: cosine_ap
+      value: 70.90459908851724
+    - type: cosine_f1
+      value: 65.66581227877457
+    - type: cosine_f1_threshold
+      value: 85.13308763504028
+    - type: cosine_precision
+      value: 61.094708153531684
+    - type: cosine_recall
+      value: 70.97625329815304
+    - type: dot_accuracy
+      value: 83.41181379269239
+    - type: dot_accuracy_threshold
+      value: 43110.113525390625
+    - type: dot_ap
+      value: 65.64869491143095
+    - type: dot_f1
+      value: 62.05308447460914
+    - type: dot_f1_threshold
+      value: 41412.542724609375
+    - type: dot_precision
+      value: 57.38623626989464
+    - type: dot_recall
+      value: 67.54617414248021
+    - type: euclidean_accuracy
+      value: 85.15229182809799
+    - type: euclidean_accuracy_threshold
+      value: 1043.08500289917
+    - type: euclidean_ap
+      value: 70.71204383269375
+    - type: euclidean_f1
+      value: 65.20304568527919
+    - type: euclidean_f1_threshold
+      value: 1179.2595863342285
+    - type: euclidean_precision
+      value: 62.81173594132029
+    - type: euclidean_recall
+      value: 67.78364116094987
+    - type: main_score
+      value: 70.90459908851724
+    - type: manhattan_accuracy
+      value: 85.1820945341837
+    - type: manhattan_accuracy_threshold
+      value: 26115.0390625
+    - type: manhattan_ap
+      value: 70.66113937117431
+    - type: manhattan_f1
+      value: 65.33383628819313
+    - type: manhattan_f1_threshold
+      value: 29105.181884765625
+    - type: manhattan_precision
+      value: 62.40691808791736
+    - type: manhattan_recall
+      value: 68.54881266490766
+    - type: max_accuracy
+      value: 85.1820945341837
+    - type: max_ap
+      value: 70.90459908851724
+    - type: max_f1
+      value: 65.66581227877457
+    - type: max_precision
+      value: 62.81173594132029
+    - type: max_recall
+      value: 70.97625329815304
+    - type: similarity_accuracy
+      value: 85.11652858079513
+    - type: similarity_accuracy_threshold
+      value: 87.90839910507202
+    - type: similarity_ap
+      value: 70.90459908851724
+    - type: similarity_f1
+      value: 65.66581227877457
+    - type: similarity_f1_threshold
+      value: 85.13308763504028
+    - type: similarity_precision
+      value: 61.094708153531684
+    - type: similarity_recall
+      value: 70.97625329815304
+    task:
+      type: PairClassification
+  - dataset:
+      config: default
+      name: MTEB TwitterURLCorpus (default)
+      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
+      split: test
+      type: mteb/twitterurlcorpus-pairclassification
+    metrics:
+    - type: cosine_accuracy
+      value: 88.10299996119068
+    - type: cosine_accuracy_threshold
+      value: 84.34982895851135
+    - type: cosine_ap
+      value: 84.13755787769226
+    - type: cosine_f1
+      value: 76.0967548076923
+    - type: cosine_f1_threshold
+      value: 82.8936219215393
+    - type: cosine_precision
+      value: 74.28864769727193
+    - type: cosine_recall
+      value: 77.99507237449954
+    - type: dot_accuracy
+      value: 86.64182869561843
+    - type: dot_accuracy_threshold
+      value: 38794.677734375
+    - type: dot_ap
+      value: 80.20301567411457
+    - type: dot_f1
+      value: 73.50650291634967
+    - type: dot_f1_threshold
+      value: 37447.23205566406
+    - type: dot_precision
+      value: 69.41498460485802
+    - type: dot_recall
+      value: 78.11056359716662
+    - type: euclidean_accuracy
+      value: 87.9361198432103
+    - type: euclidean_accuracy_threshold
+      value: 1184.421157836914
+    - type: euclidean_ap
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+    - type: recall_at_5
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+    task:
+      type: Retrieval
 ---
 
 <br><br>