diff --git "a/README.md" "b/README.md"
--- "a/README.md"
+++ "b/README.md"
@@ -1,3 +1,8650 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+tags:
+- text-embedding
+- feature-extraction
+- sentence-similarity
+- transformers
+- mteb
+model-index:
+- name: Gouzi3618/LENS-8000
+  results:
+  - dataset:
+      config: en
+      name: MTEB AmazonCounterfactualClassification (en)
+      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
+      split: test
+      type: mteb/amazon_counterfactual
+    metrics:
+    - type: accuracy
+      value: 93.6865671641791
+    - type: ap
+      value: 74.44778735403261
+    - type: ap_weighted
+      value: 74.44778735403261
+    - type: f1
+      value: 90.57338628851295
+    - type: f1_weighted
+      value: 93.87207694461506
+    - type: main_score
+      value: 93.6865671641791
+    task:
+      type: Classification
+  - dataset:
+      config: default
+      name: MTEB AmazonPolarityClassification (default)
+      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
+      split: test
+      type: mteb/amazon_polarity
+    metrics:
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+      value: 97.06832499999999
+    - type: ap
+      value: 95.71019538629211
+    - type: ap_weighted
+      value: 95.71019538629211
+    - type: f1
+      value: 97.06781792337515
+    - type: f1_weighted
+      value: 97.06781792337515
+    - type: main_score
+      value: 97.06832499999999
+    task:
+      type: Classification
+  - dataset:
+      config: en
+      name: MTEB AmazonReviewsClassification (en)
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+      split: test
+      type: mteb/amazon_reviews_multi
+    metrics:
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+      value: 63.608
+    - type: f1
+      value: 62.41274991021244
+    - type: f1_weighted
+      value: 62.41274991021244
+    - type: main_score
+      value: 63.608
+    task:
+      type: Classification
+  - dataset:
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+      name: MTEB ArguAna (default)
+      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
+      split: test
+      type: mteb/arguana
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+      value: 69.887
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+    - type: map_at_1000
+      value: 70.159
+    - type: map_at_20
+      value: 70.101
+    - type: map_at_3
+      value: 67.378
+    - type: map_at_5
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+      value: 97.795
+    - type: recall_at_3
+      value: 81.57900000000001
+    - type: recall_at_5
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+    task:
+      type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB ArxivClusteringP2P (default)
+      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
+      split: test
+      type: mteb/arxiv-clustering-p2p
+    metrics:
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+    - type: v_measure
+      value: 54.809064728970625
+    - type: v_measure_std
+      value: 14.497861425102215
+    task:
+      type: Clustering
+  - dataset:
+      config: default
+      name: MTEB ArxivClusteringS2S (default)
+      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
+      split: test
+      type: mteb/arxiv-clustering-s2s
+    metrics:
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+    - type: v_measure
+      value: 50.144159631474416
+    - type: v_measure_std
+      value: 14.596959041091187
+    task:
+      type: Clustering
+  - dataset:
+      config: default
+      name: MTEB AskUbuntuDupQuestions (default)
+      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
+      split: test
+      type: mteb/askubuntudupquestions-reranking
+    metrics:
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+    - type: map
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+    - type: nAUC_mrr_std
+      value: 28.863440464092747
+    task:
+      type: Reranking
+  - dataset:
+      config: default
+      name: MTEB BIOSSES (default)
+      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
+      split: test
+      type: mteb/biosses-sts
+    metrics:
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+    - type: cosine_spearman
+      value: 85.83087137728063
+    - type: euclidean_pearson
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+    - type: euclidean_spearman
+      value: 85.83087137728063
+    - type: main_score
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+      value: 85.96460936435044
+    - type: pearson
+      value: 86.59612727828603
+    - type: spearman
+      value: 85.83087137728063
+    task:
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+  - dataset:
+      config: default
+      name: MTEB Banking77Classification (default)
+      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
+      split: test
+      type: mteb/banking77
+    metrics:
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+    - type: f1_weighted
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+    - type: main_score
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+    task:
+      type: Classification
+  - dataset:
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+      name: MTEB BiorxivClusteringP2P (default)
+      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
+      split: test
+      type: mteb/biorxiv-clustering-p2p
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+      name: MTEB BiorxivClusteringS2S (default)
+      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
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+      type: mteb/biorxiv-clustering-s2s
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+    task:
+      type: Clustering
+  - dataset:
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+      name: MTEB CQADupstackAndroidRetrieval (default)
+      revision: f46a197baaae43b4f621051089b82a364682dfeb
+      split: test
+      type: mteb/cqadupstack-android
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+      name: MTEB STS15 (default)
+      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
+      split: test
+      type: mteb/sts15-sts
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+    - type: cosine_spearman
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+    - type: euclidean_pearson
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+    - type: euclidean_spearman
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+    - type: main_score
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+    - type: manhattan_pearson
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+    - type: manhattan_spearman
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+    - type: pearson
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+    - type: spearman
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+      config: default
+      name: MTEB STS16 (default)
+      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
+      split: test
+      type: mteb/sts16-sts
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+    - type: cosine_spearman
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+    - type: euclidean_pearson
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+    - type: euclidean_spearman
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+    - type: main_score
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+    - type: manhattan_pearson
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+    - type: spearman
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+      name: MTEB STS17 (en-en)
+      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
+      split: test
+      type: mteb/sts17-crosslingual-sts
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+    - type: euclidean_pearson
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+    - type: euclidean_spearman
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+    - type: main_score
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+    - type: manhattan_pearson
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+    - type: pearson
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+    - type: spearman
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+      name: MTEB STS22 (en)
+      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
+      split: test
+      type: mteb/sts22-crosslingual-sts
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+    - type: euclidean_spearman
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+    - type: main_score
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+    - type: manhattan_pearson
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+    - type: spearman
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+      name: MTEB STSBenchmark (default)
+      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
+      split: test
+      type: mteb/stsbenchmark-sts
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+    - type: main_score
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+    - type: manhattan_pearson
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+    - type: spearman
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+      name: MTEB SciDocsRR (default)
+      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
+      split: test
+      type: mteb/scidocs-reranking
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+    - type: nAUC_mrr_max
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+    - type: nAUC_mrr_std
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+      name: MTEB SciFact (default)
+      revision: 0228b52cf27578f30900b9e5271d331663a030d7
+      split: test
+      type: mteb/scifact
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+    - type: ndcg_at_1
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+    - type: ndcg_at_100
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+    - type: ndcg_at_3
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+    - type: ndcg_at_5
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+    - type: precision_at_1
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+    - type: precision_at_10
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+    - type: precision_at_100
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+    - type: precision_at_20
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+    - type: precision_at_3
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+    - type: precision_at_5
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+    - type: recall_at_1
+      value: 64.328
+    - type: recall_at_10
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+    - type: recall_at_100
+      value: 97.667
+    - type: recall_at_1000
+      value: 100.0
+    - type: recall_at_20
+      value: 94.5
+    - type: recall_at_3
+      value: 81.072
+    - type: recall_at_5
+      value: 87.339
+    task:
+      type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB SprintDuplicateQuestions (default)
+      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
+      split: test
+      type: mteb/sprintduplicatequestions-pairclassification
+    metrics:
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+      value: 99.86039603960396
+    - type: cosine_accuracy_threshold
+      value: 72.46292233467102
+    - type: cosine_ap
+      value: 96.9963756118777
+    - type: cosine_f1
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+    - type: cosine_f1_threshold
+      value: 72.46292233467102
+    - type: cosine_precision
+      value: 93.69277721261444
+    - type: cosine_recall
+      value: 92.10000000000001
+    - type: dot_accuracy
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+    - type: dot_accuracy_threshold
+      value: 72.46291637420654
+    - type: dot_ap
+      value: 96.99637561187771
+    - type: dot_f1
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+    - type: dot_f1_threshold
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+    - type: dot_precision
+      value: 93.69277721261444
+    - type: dot_recall
+      value: 92.10000000000001
+    - type: euclidean_accuracy
+      value: 99.86039603960396
+    - type: euclidean_accuracy_threshold
+      value: 74.21196699142456
+    - type: euclidean_ap
+      value: 96.99637561187768
+    - type: euclidean_f1
+      value: 92.8895612708018
+    - type: euclidean_f1_threshold
+      value: 74.21196699142456
+    - type: euclidean_precision
+      value: 93.69277721261444
+    - type: euclidean_recall
+      value: 92.10000000000001
+    - type: main_score
+      value: 96.99637561187771
+    - type: manhattan_accuracy
+      value: 99.81980198019802
+    - type: manhattan_accuracy_threshold
+      value: 2608.760452270508
+    - type: manhattan_ap
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+    - type: manhattan_f1
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+    - type: manhattan_f1_threshold
+      value: 2608.760452270508
+    - type: manhattan_precision
+      value: 92.33954451345755
+    - type: manhattan_recall
+      value: 89.2
+    - type: max_accuracy
+      value: 99.86039603960396
+    - type: max_ap
+      value: 96.99637561187771
+    - type: max_f1
+      value: 92.8895612708018
+    - type: max_precision
+      value: 93.69277721261444
+    - type: max_recall
+      value: 92.10000000000001
+    - type: similarity_accuracy
+      value: 99.86039603960396
+    - type: similarity_accuracy_threshold
+      value: 72.46292233467102
+    - type: similarity_ap
+      value: 96.9963756118777
+    - type: similarity_f1
+      value: 92.8895612708018
+    - type: similarity_f1_threshold
+      value: 72.46292233467102
+    - type: similarity_precision
+      value: 93.69277721261444
+    - type: similarity_recall
+      value: 92.10000000000001
+    task:
+      type: PairClassification
+  - dataset:
+      config: default
+      name: MTEB StackExchangeClustering (default)
+      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
+      split: test
+      type: mteb/stackexchange-clustering
+    metrics:
+    - type: main_score
+      value: 81.5950420419382
+    - type: v_measure
+      value: 81.5950420419382
+    - type: v_measure_std
+      value: 2.3518861207789126
+    task:
+      type: Clustering
+  - dataset:
+      config: default
+      name: MTEB StackExchangeClusteringP2P (default)
+      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
+      split: test
+      type: mteb/stackexchange-clustering-p2p
+    metrics:
+    - type: main_score
+      value: 44.40836435329055
+    - type: v_measure
+      value: 44.40836435329055
+    - type: v_measure_std
+      value: 1.3850659888959282
+    task:
+      type: Clustering
+  - dataset:
+      config: default
+      name: MTEB StackOverflowDupQuestions (default)
+      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
+      split: test
+      type: mteb/stackoverflowdupquestions-reranking
+    metrics:
+    - type: main_score
+      value: 58.792345747482436
+    - type: map
+      value: 58.792345747482436
+    - type: mrr
+      value: 59.87494429590018
+    - type: nAUC_map_diff1
+      value: 43.36254267831821
+    - type: nAUC_map_max
+      value: 13.241350111456592
+    - type: nAUC_map_std
+      value: 6.075720164270261
+    - type: nAUC_mrr_diff1
+      value: 43.6953851299995
+    - type: nAUC_mrr_max
+      value: 14.587424770057197
+    - type: nAUC_mrr_std
+      value: 6.683981115477786
+    task:
+      type: Reranking
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+      value: -26.226217172137154
+    - type: nauc_recall_at_20_diff1
+      value: 5.794232787977484
+    - type: nauc_recall_at_20_max
+      value: -27.084183224457064
+    - type: nauc_recall_at_20_std
+      value: -13.003930840567254
+    - type: nauc_recall_at_3_diff1
+      value: 12.630860577189745
+    - type: nauc_recall_at_3_max
+      value: -17.119921468454315
+    - type: nauc_recall_at_3_std
+      value: -17.473340753437792
+    - type: nauc_recall_at_5_diff1
+      value: 7.301486684241046
+    - type: nauc_recall_at_5_max
+      value: -15.68243996895239
+    - type: nauc_recall_at_5_std
+      value: -20.13598669484435
+    - type: ndcg_at_1
+      value: 35.714
+    - type: ndcg_at_10
+      value: 29.343000000000004
+    - type: ndcg_at_100
+      value: 41.568
+    - type: ndcg_at_1000
+      value: 51.93
+    - type: ndcg_at_20
+      value: 30.173
+    - type: ndcg_at_3
+      value: 33.622
+    - type: ndcg_at_5
+      value: 31.807999999999996
+    - type: precision_at_1
+      value: 36.735
+    - type: precision_at_10
+      value: 25.509999999999998
+    - type: precision_at_100
+      value: 8.571
+    - type: precision_at_1000
+      value: 1.559
+    - type: precision_at_20
+      value: 19.694
+    - type: precision_at_3
+      value: 34.694
+    - type: precision_at_5
+      value: 31.429000000000002
+    - type: recall_at_1
+      value: 3.0220000000000002
+    - type: recall_at_10
+      value: 18.838
+    - type: recall_at_100
+      value: 51.471999999999994
+    - type: recall_at_1000
+      value: 83.012
+    - type: recall_at_20
+      value: 27.165
+    - type: recall_at_3
+      value: 7.868
+    - type: recall_at_5
+      value: 11.413
+    task:
+      type: Retrieval
+  - dataset:
+      config: default
+      name: MTEB ToxicConversationsClassification (default)
+      revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
+      split: test
+      type: mteb/toxic_conversations_50k
+    metrics:
+    - type: accuracy
+      value: 92.3681640625
+    - type: ap
+      value: 43.441682015979104
+    - type: ap_weighted
+      value: 43.441682015979104
+    - type: f1
+      value: 79.35383898838042
+    - type: f1_weighted
+      value: 93.14474638528736
+    - type: main_score
+      value: 92.3681640625
+    task:
+      type: Classification
+  - dataset:
+      config: default
+      name: MTEB TweetSentimentExtractionClassification (default)
+      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
+      split: test
+      type: mteb/tweet_sentiment_extraction
+    metrics:
+    - type: accuracy
+      value: 80.42161856253539
+    - type: f1
+      value: 80.69309707938646
+    - type: f1_weighted
+      value: 80.3228654725881
+    - type: main_score
+      value: 80.42161856253539
+    task:
+      type: Classification
+  - dataset:
+      config: default
+      name: MTEB TwentyNewsgroupsClustering (default)
+      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
+      split: test
+      type: mteb/twentynewsgroups-clustering
+    metrics:
+    - type: main_score
+      value: 68.78385330772423
+    - type: v_measure
+      value: 68.78385330772423
+    - type: v_measure_std
+      value: 1.4814035017480702
+    task:
+      type: Clustering
+  - dataset:
+      config: default
+      name: MTEB TwitterSemEval2015 (default)
+      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
+      split: test
+      type: mteb/twittersemeval2015-pairclassification
+    metrics:
+    - type: cosine_accuracy
+      value: 87.96566728258925
+    - type: cosine_accuracy_threshold
+      value: 74.39426183700562
+    - type: cosine_ap
+      value: 79.55550776766384
+    - type: cosine_f1
+      value: 72.25950782997764
+    - type: cosine_f1_threshold
+      value: 71.66670560836792
+    - type: cosine_precision
+      value: 68.30357142857143
+    - type: cosine_recall
+      value: 76.7018469656992
+    - type: dot_accuracy
+      value: 87.96566728258925
+    - type: dot_accuracy_threshold
+      value: 74.39426183700562
+    - type: dot_ap
+      value: 79.55551194873313
+    - type: dot_f1
+      value: 72.25950782997764
+    - type: dot_f1_threshold
+      value: 71.66670560836792
+    - type: dot_precision
+      value: 68.30357142857143
+    - type: dot_recall
+      value: 76.7018469656992
+    - type: euclidean_accuracy
+      value: 87.96566728258925
+    - type: euclidean_accuracy_threshold
+      value: 71.56219482421875
+    - type: euclidean_ap
+      value: 79.55550945424486
+    - type: euclidean_f1
+      value: 72.25950782997764
+    - type: euclidean_f1_threshold
+      value: 75.27719736099243
+    - type: euclidean_precision
+      value: 68.30357142857143
+    - type: euclidean_recall
+      value: 76.7018469656992
+    - type: main_score
+      value: 79.55707708553916
+    - type: manhattan_accuracy
+      value: 87.88221970554928
+    - type: manhattan_accuracy_threshold
+      value: 3136.1982345581055
+    - type: manhattan_ap
+      value: 79.55707708553916
+    - type: manhattan_f1
+      value: 72.5288998571243
+    - type: manhattan_f1_threshold
+      value: 3327.1324157714844
+    - type: manhattan_precision
+      value: 71.42491685853159
+    - type: manhattan_recall
+      value: 73.66754617414249
+    - type: max_accuracy
+      value: 87.96566728258925
+    - type: max_ap
+      value: 79.55707708553916
+    - type: max_f1
+      value: 72.5288998571243
+    - type: max_precision
+      value: 71.42491685853159
+    - type: max_recall
+      value: 76.7018469656992
+    - type: similarity_accuracy
+      value: 87.96566728258925
+    - type: similarity_accuracy_threshold
+      value: 74.39426183700562
+    - type: similarity_ap
+      value: 79.55550776766384
+    - type: similarity_f1
+      value: 72.25950782997764
+    - type: similarity_f1_threshold
+      value: 71.66670560836792
+    - type: similarity_precision
+      value: 68.30357142857143
+    - type: similarity_recall
+      value: 76.7018469656992
+    task:
+      type: PairClassification
+  - dataset:
+      config: default
+      name: MTEB TwitterURLCorpus (default)
+      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
+      split: test
+      type: mteb/twitterurlcorpus-pairclassification
+    metrics:
+    - type: cosine_accuracy
+      value: 89.48073116777273
+    - type: cosine_accuracy_threshold
+      value: 73.83834719657898
+    - type: cosine_ap
+      value: 87.04248262089361
+    - type: cosine_f1
+      value: 79.40769846467293
+    - type: cosine_f1_threshold
+      value: 70.96807956695557
+    - type: cosine_precision
+      value: 75.27245137260311
+    - type: cosine_recall
+      value: 84.02371419772098
+    - type: dot_accuracy
+      value: 89.48073116777273
+    - type: dot_accuracy_threshold
+      value: 73.83835315704346
+    - type: dot_ap
+      value: 87.04248357792484
+    - type: dot_f1
+      value: 79.40769846467293
+    - type: dot_f1_threshold
+      value: 70.96806764602661
+    - type: dot_precision
+      value: 75.27245137260311
+    - type: dot_recall
+      value: 84.02371419772098
+    - type: euclidean_accuracy
+      value: 89.48073116777273
+    - type: euclidean_accuracy_threshold
+      value: 72.33483791351318
+    - type: euclidean_ap
+      value: 87.04247988177627
+    - type: euclidean_f1
+      value: 79.40769846467293
+    - type: euclidean_f1_threshold
+      value: 76.19963884353638
+    - type: euclidean_precision
+      value: 75.27245137260311
+    - type: euclidean_recall
+      value: 84.02371419772098
+    - type: main_score
+      value: 87.37453072241573
+    - type: manhattan_accuracy
+      value: 89.67283735009897
+    - type: manhattan_accuracy_threshold
+      value: 3345.201873779297
+    - type: manhattan_ap
+      value: 87.37453072241573
+    - type: manhattan_f1
+      value: 79.9237656873674
+    - type: manhattan_f1_threshold
+      value: 3592.564010620117
+    - type: manhattan_precision
+      value: 74.98144524660955
+    - type: manhattan_recall
+      value: 85.56359716661534
+    - type: max_accuracy
+      value: 89.67283735009897
+    - type: max_ap
+      value: 87.37453072241573
+    - type: max_f1
+      value: 79.9237656873674
+    - type: max_precision
+      value: 75.27245137260311
+    - type: max_recall
+      value: 85.56359716661534
+    - type: similarity_accuracy
+      value: 89.48073116777273
+    - type: similarity_accuracy_threshold
+      value: 73.83834719657898
+    - type: similarity_ap
+      value: 87.04248262089361
+    - type: similarity_f1
+      value: 79.40769846467293
+    - type: similarity_f1_threshold
+      value: 70.96807956695557
+    - type: similarity_precision
+      value: 75.27245137260311
+    - type: similarity_recall
+      value: 84.02371419772098
+    task:
+      type: PairClassification
+---