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README.md

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+---
+tags:
+- sentence-transformers
+- feature-extraction
+- sentence-similarity
+- mteb
+- llama-cpp
+- gguf-my-repo
+language:
+- es
+- en
+inference: false
+license: apache-2.0
+base_model: jinaai/jina-embeddings-v2-base-es
+model-index:
+- name: jina-embeddings-v2-base-es
+  results:
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB AmazonCounterfactualClassification (en)
+      type: mteb/amazon_counterfactual
+      config: en
+      split: test
+      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
+    metrics:
+    - type: accuracy
+      value: 74.25373134328358
+    - type: ap
+      value: 37.05201236793268
+    - type: f1
+      value: 68.16770391201077
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB AmazonPolarityClassification
+      type: mteb/amazon_polarity
+      config: default
+      split: test
+      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
+    metrics:
+    - type: accuracy
+      value: 78.30885
+    - type: ap
+      value: 73.01622441156408
+    - type: f1
+      value: 78.20769284466313
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB AmazonReviewsClassification (en)
+      type: mteb/amazon_reviews_multi
+      config: en
+      split: test
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+    metrics:
+    - type: accuracy
+      value: 38.324
+    - type: f1
+      value: 37.89543008761673
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB AmazonReviewsClassification (es)
+      type: mteb/amazon_reviews_multi
+      config: es
+      split: test
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+    metrics:
+    - type: accuracy
+      value: 38.678000000000004
+    - type: f1
+      value: 38.122639506976
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB ArguAna
+      type: arguana
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 23.968999999999998
+    - type: map_at_10
+      value: 40.691
+    - type: map_at_100
+      value: 41.713
+    - type: map_at_1000
+      value: 41.719
+    - type: map_at_3
+      value: 35.42
+    - type: map_at_5
+      value: 38.442
+    - type: mrr_at_1
+      value: 24.395
+    - type: mrr_at_10
+      value: 40.853
+    - type: mrr_at_100
+      value: 41.869
+    - type: mrr_at_1000
+      value: 41.874
+    - type: mrr_at_3
+      value: 35.68
+    - type: mrr_at_5
+      value: 38.572
+    - type: ndcg_at_1
+      value: 23.968999999999998
+    - type: ndcg_at_10
+      value: 50.129999999999995
+    - type: ndcg_at_100
+      value: 54.364000000000004
+    - type: ndcg_at_1000
+      value: 54.494
+    - type: ndcg_at_3
+      value: 39.231
+    - type: ndcg_at_5
+      value: 44.694
+    - type: precision_at_1
+      value: 23.968999999999998
+    - type: precision_at_10
+      value: 8.036999999999999
+    - type: precision_at_100
+      value: 0.9860000000000001
+    - type: precision_at_1000
+      value: 0.1
+    - type: precision_at_3
+      value: 16.761
+    - type: precision_at_5
+      value: 12.717
+    - type: recall_at_1
+      value: 23.968999999999998
+    - type: recall_at_10
+      value: 80.36999999999999
+    - type: recall_at_100
+      value: 98.578
+    - type: recall_at_1000
+      value: 99.57300000000001
+    - type: recall_at_3
+      value: 50.28399999999999
+    - type: recall_at_5
+      value: 63.585
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB ArxivClusteringP2P
+      type: mteb/arxiv-clustering-p2p
+      config: default
+      split: test
+      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
+    metrics:
+    - type: v_measure
+      value: 41.54886683150053
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB ArxivClusteringS2S
+      type: mteb/arxiv-clustering-s2s
+      config: default
+      split: test
+      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
+    metrics:
+    - type: v_measure
+      value: 32.186028697637234
+  - task:
+      type: Reranking
+    dataset:
+      name: MTEB AskUbuntuDupQuestions
+      type: mteb/askubuntudupquestions-reranking
+      config: default
+      split: test
+      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
+    metrics:
+    - type: map
+      value: 61.19432643698725
+    - type: mrr
+      value: 75.28646176845622
+  - task:
+      type: STS
+    dataset:
+      name: MTEB BIOSSES
+      type: mteb/biosses-sts
+      config: default
+      split: test
+      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
+    metrics:
+    - type: cos_sim_pearson
+      value: 86.3828259381228
+    - type: cos_sim_spearman
+      value: 83.04647058342209
+    - type: euclidean_pearson
+      value: 84.02895346096244
+    - type: euclidean_spearman
+      value: 82.34524978635342
+    - type: manhattan_pearson
+      value: 84.35030723233426
+    - type: manhattan_spearman
+      value: 83.17177464337936
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB Banking77Classification
+      type: mteb/banking77
+      config: default
+      split: test
+      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
+    metrics:
+    - type: accuracy
+      value: 85.25649350649351
+    - type: f1
+      value: 85.22320474023192
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB BigPatentClustering
+      type: jinaai/big-patent-clustering
+      config: default
+      split: test
+      revision: 62d5330920bca426ce9d3c76ea914f15fc83e891
+    metrics:
+    - type: v_measure
+      value: 20.42929408254094
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB BiorxivClusteringP2P
+      type: mteb/biorxiv-clustering-p2p
+      config: default
+      split: test
+      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
+    metrics:
+    - type: v_measure
+      value: 35.165318177498136
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB BiorxivClusteringS2S
+      type: mteb/biorxiv-clustering-s2s
+      config: default
+      split: test
+      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
+    metrics:
+    - type: v_measure
+      value: 28.89030154229562
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CQADupstackAndroidRetrieval
+      type: BeIR/cqadupstack
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 30.119
+    - type: map_at_10
+      value: 42.092
+    - type: map_at_100
+      value: 43.506
+    - type: map_at_1000
+      value: 43.631
+    - type: map_at_3
+      value: 38.373000000000005
+    - type: map_at_5
+      value: 40.501
+    - type: mrr_at_1
+      value: 38.196999999999996
+    - type: mrr_at_10
+      value: 48.237
+    - type: mrr_at_100
+      value: 48.914
+    - type: mrr_at_1000
+      value: 48.959
+    - type: mrr_at_3
+      value: 45.279
+    - type: mrr_at_5
+      value: 47.11
+    - type: ndcg_at_1
+      value: 38.196999999999996
+    - type: ndcg_at_10
+      value: 48.849
+    - type: ndcg_at_100
+      value: 53.713
+    - type: ndcg_at_1000
+      value: 55.678000000000004
+    - type: ndcg_at_3
+      value: 43.546
+    - type: ndcg_at_5
+      value: 46.009
+    - type: precision_at_1
+      value: 38.196999999999996
+    - type: precision_at_10
+      value: 9.642000000000001
+    - type: precision_at_100
+      value: 1.5190000000000001
+    - type: precision_at_1000
+      value: 0.199
+    - type: precision_at_3
+      value: 21.65
+    - type: precision_at_5
+      value: 15.708
+    - type: recall_at_1
+      value: 30.119
+    - type: recall_at_10
+      value: 61.788
+    - type: recall_at_100
+      value: 82.14399999999999
+    - type: recall_at_1000
+      value: 95.003
+    - type: recall_at_3
+      value: 45.772
+    - type: recall_at_5
+      value: 53.04600000000001
+    - type: map_at_1
+      value: 28.979
+    - type: map_at_10
+      value: 37.785000000000004
+    - type: map_at_100
+      value: 38.945
+    - type: map_at_1000
+      value: 39.071
+    - type: map_at_3
+      value: 35.083999999999996
+    - type: map_at_5
+      value: 36.571999999999996
+    - type: mrr_at_1
+      value: 36.242000000000004
+    - type: mrr_at_10
+      value: 43.552
+    - type: mrr_at_100
+      value: 44.228
+    - type: mrr_at_1000
+      value: 44.275999999999996
+    - type: mrr_at_3
+      value: 41.359
+    - type: mrr_at_5
+      value: 42.598
+    - type: ndcg_at_1
+      value: 36.242000000000004
+    - type: ndcg_at_10
+      value: 42.94
+    - type: ndcg_at_100
+      value: 47.343
+    - type: ndcg_at_1000
+      value: 49.538
+    - type: ndcg_at_3
+      value: 39.086999999999996
+    - type: ndcg_at_5
+      value: 40.781
+    - type: precision_at_1
+      value: 36.242000000000004
+    - type: precision_at_10
+      value: 7.954999999999999
+    - type: precision_at_100
+      value: 1.303
+    - type: precision_at_1000
+      value: 0.178
+    - type: precision_at_3
+      value: 18.556
+    - type: precision_at_5
+      value: 13.145999999999999
+    - type: recall_at_1
+      value: 28.979
+    - type: recall_at_10
+      value: 51.835
+    - type: recall_at_100
+      value: 70.47
+    - type: recall_at_1000
+      value: 84.68299999999999
+    - type: recall_at_3
+      value: 40.410000000000004
+    - type: recall_at_5
+      value: 45.189
+    - type: map_at_1
+      value: 37.878
+    - type: map_at_10
+      value: 49.903
+    - type: map_at_100
+      value: 50.797000000000004
+    - type: map_at_1000
+      value: 50.858000000000004
+    - type: map_at_3
+      value: 46.526
+    - type: map_at_5
+      value: 48.615
+    - type: mrr_at_1
+      value: 43.135
+    - type: mrr_at_10
+      value: 53.067
+    - type: mrr_at_100
+      value: 53.668000000000006
+    - type: mrr_at_1000
+      value: 53.698
+    - type: mrr_at_3
+      value: 50.449
+    - type: mrr_at_5
+      value: 52.117000000000004
+    - type: ndcg_at_1
+      value: 43.135
+    - type: ndcg_at_10
+      value: 55.641
+    - type: ndcg_at_100
+      value: 59.427
+    - type: ndcg_at_1000
+      value: 60.655
+    - type: ndcg_at_3
+      value: 49.969
+    - type: ndcg_at_5
+      value: 53.075
+    - type: precision_at_1
+      value: 43.135
+    - type: precision_at_10
+      value: 8.997
+    - type: precision_at_100
+      value: 1.1809999999999998
+    - type: precision_at_1000
+      value: 0.133
+    - type: precision_at_3
+      value: 22.215
+    - type: precision_at_5
+      value: 15.586
+    - type: recall_at_1
+      value: 37.878
+    - type: recall_at_10
+      value: 69.405
+    - type: recall_at_100
+      value: 86.262
+    - type: recall_at_1000
+      value: 95.012
+    - type: recall_at_3
+      value: 54.458
+    - type: recall_at_5
+      value: 61.965
+    - type: map_at_1
+      value: 24.853
+    - type: map_at_10
+      value: 32.402
+    - type: map_at_100
+      value: 33.417
+    - type: map_at_1000
+      value: 33.498
+    - type: map_at_3
+      value: 30.024
+    - type: map_at_5
+      value: 31.407
+    - type: mrr_at_1
+      value: 26.667
+    - type: mrr_at_10
+      value: 34.399
+    - type: mrr_at_100
+      value: 35.284
+    - type: mrr_at_1000
+      value: 35.345
+    - type: mrr_at_3
+      value: 32.109
+    - type: mrr_at_5
+      value: 33.375
+    - type: ndcg_at_1
+      value: 26.667
+    - type: ndcg_at_10
+      value: 36.854
+    - type: ndcg_at_100
+      value: 42.196
+    - type: ndcg_at_1000
+      value: 44.303
+    - type: ndcg_at_3
+      value: 32.186
+    - type: ndcg_at_5
+      value: 34.512
+    - type: precision_at_1
+      value: 26.667
+    - type: precision_at_10
+      value: 5.559
+    - type: precision_at_100
+      value: 0.88
+    - type: precision_at_1000
+      value: 0.109
+    - type: precision_at_3
+      value: 13.333
+    - type: precision_at_5
+      value: 9.379
+    - type: recall_at_1
+      value: 24.853
+    - type: recall_at_10
+      value: 48.636
+    - type: recall_at_100
+      value: 73.926
+    - type: recall_at_1000
+      value: 89.94
+    - type: recall_at_3
+      value: 36.266
+    - type: recall_at_5
+      value: 41.723
+    - type: map_at_1
+      value: 14.963999999999999
+    - type: map_at_10
+      value: 22.591
+    - type: map_at_100
+      value: 23.735999999999997
+    - type: map_at_1000
+      value: 23.868000000000002
+    - type: map_at_3
+      value: 20.093
+    - type: map_at_5
+      value: 21.499
+    - type: mrr_at_1
+      value: 18.407999999999998
+    - type: mrr_at_10
+      value: 26.863
+    - type: mrr_at_100
+      value: 27.87
+    - type: mrr_at_1000
+      value: 27.947
+    - type: mrr_at_3
+      value: 24.254
+    - type: mrr_at_5
+      value: 25.784000000000002
+    - type: ndcg_at_1
+      value: 18.407999999999998
+    - type: ndcg_at_10
+      value: 27.549
+    - type: ndcg_at_100
+      value: 33.188
+    - type: ndcg_at_1000
+      value: 36.312
+    - type: ndcg_at_3
+      value: 22.862
+    - type: ndcg_at_5
+      value: 25.130999999999997
+    - type: precision_at_1
+      value: 18.407999999999998
+    - type: precision_at_10
+      value: 5.087
+    - type: precision_at_100
+      value: 0.923
+    - type: precision_at_1000
+      value: 0.133
+    - type: precision_at_3
+      value: 10.987
+    - type: precision_at_5
+      value: 8.209
+    - type: recall_at_1
+      value: 14.963999999999999
+    - type: recall_at_10
+      value: 38.673
+    - type: recall_at_100
+      value: 63.224999999999994
+    - type: recall_at_1000
+      value: 85.443
+    - type: recall_at_3
+      value: 25.840000000000003
+    - type: recall_at_5
+      value: 31.503999999999998
+    - type: map_at_1
+      value: 27.861000000000004
+    - type: map_at_10
+      value: 37.562
+    - type: map_at_100
+      value: 38.906
+    - type: map_at_1000
+      value: 39.021
+    - type: map_at_3
+      value: 34.743
+    - type: map_at_5
+      value: 36.168
+    - type: mrr_at_1
+      value: 34.455999999999996
+    - type: mrr_at_10
+      value: 43.428
+    - type: mrr_at_100
+      value: 44.228
+    - type: mrr_at_1000
+      value: 44.278
+    - type: mrr_at_3
+      value: 41.001
+    - type: mrr_at_5
+      value: 42.315000000000005
+    - type: ndcg_at_1
+      value: 34.455999999999996
+    - type: ndcg_at_10
+      value: 43.477
+    - type: ndcg_at_100
+      value: 48.953
+    - type: ndcg_at_1000
+      value: 51.19200000000001
+    - type: ndcg_at_3
+      value: 38.799
+    - type: ndcg_at_5
+      value: 40.743
+    - type: precision_at_1
+      value: 34.455999999999996
+    - type: precision_at_10
+      value: 7.902000000000001
+    - type: precision_at_100
+      value: 1.244
+    - type: precision_at_1000
+      value: 0.161
+    - type: precision_at_3
+      value: 18.511
+    - type: precision_at_5
+      value: 12.859000000000002
+    - type: recall_at_1
+      value: 27.861000000000004
+    - type: recall_at_10
+      value: 55.36
+    - type: recall_at_100
+      value: 78.384
+    - type: recall_at_1000
+      value: 93.447
+    - type: recall_at_3
+      value: 41.926
+    - type: recall_at_5
+      value: 47.257
+    - type: map_at_1
+      value: 26.375
+    - type: map_at_10
+      value: 35.571000000000005
+    - type: map_at_100
+      value: 36.785000000000004
+    - type: map_at_1000
+      value: 36.905
+    - type: map_at_3
+      value: 32.49
+    - type: map_at_5
+      value: 34.123999999999995
+    - type: mrr_at_1
+      value: 32.647999999999996
+    - type: mrr_at_10
+      value: 40.598
+    - type: mrr_at_100
+      value: 41.484
+    - type: mrr_at_1000
+      value: 41.546
+    - type: mrr_at_3
+      value: 37.9
+    - type: mrr_at_5
+      value: 39.401
+    - type: ndcg_at_1
+      value: 32.647999999999996
+    - type: ndcg_at_10
+      value: 41.026
+    - type: ndcg_at_100
+      value: 46.365
+    - type: ndcg_at_1000
+      value: 48.876
+    - type: ndcg_at_3
+      value: 35.843
+    - type: ndcg_at_5
+      value: 38.118
+    - type: precision_at_1
+      value: 32.647999999999996
+    - type: precision_at_10
+      value: 7.443
+    - type: precision_at_100
+      value: 1.18
+    - type: precision_at_1000
+      value: 0.158
+    - type: precision_at_3
+      value: 16.819
+    - type: precision_at_5
+      value: 11.985999999999999
+    - type: recall_at_1
+      value: 26.375
+    - type: recall_at_10
+      value: 52.471000000000004
+    - type: recall_at_100
+      value: 75.354
+    - type: recall_at_1000
+      value: 92.35
+    - type: recall_at_3
+      value: 37.893
+    - type: recall_at_5
+      value: 43.935
+    - type: map_at_1
+      value: 25.012666666666668
+    - type: map_at_10
+      value: 33.685833333333335
+    - type: map_at_100
+      value: 34.849250000000005
+    - type: map_at_1000
+      value: 34.970083333333335
+    - type: map_at_3
+      value: 31.065083333333334
+    - type: map_at_5
+      value: 32.494416666666666
+    - type: mrr_at_1
+      value: 29.772666666666662
+    - type: mrr_at_10
+      value: 37.824666666666666
+    - type: mrr_at_100
+      value: 38.66741666666666
+    - type: mrr_at_1000
+      value: 38.72916666666666
+    - type: mrr_at_3
+      value: 35.54575
+    - type: mrr_at_5
+      value: 36.81524999999999
+    - type: ndcg_at_1
+      value: 29.772666666666662
+    - type: ndcg_at_10
+      value: 38.78241666666666
+    - type: ndcg_at_100
+      value: 43.84591666666667
+    - type: ndcg_at_1000
+      value: 46.275416666666665
+    - type: ndcg_at_3
+      value: 34.33416666666667
+    - type: ndcg_at_5
+      value: 36.345166666666664
+    - type: precision_at_1
+      value: 29.772666666666662
+    - type: precision_at_10
+      value: 6.794916666666667
+    - type: precision_at_100
+      value: 1.106416666666667
+    - type: precision_at_1000
+      value: 0.15033333333333335
+    - type: precision_at_3
+      value: 15.815083333333336
+    - type: precision_at_5
+      value: 11.184166666666664
+    - type: recall_at_1
+      value: 25.012666666666668
+    - type: recall_at_10
+      value: 49.748500000000014
+    - type: recall_at_100
+      value: 72.11341666666667
+    - type: recall_at_1000
+      value: 89.141
+    - type: recall_at_3
+      value: 37.242999999999995
+    - type: recall_at_5
+      value: 42.49033333333333
+    - type: map_at_1
+      value: 23.177
+    - type: map_at_10
+      value: 29.310000000000002
+    - type: map_at_100
+      value: 30.188
+    - type: map_at_1000
+      value: 30.29
+    - type: map_at_3
+      value: 27.356
+    - type: map_at_5
+      value: 28.410999999999998
+    - type: mrr_at_1
+      value: 26.074
+    - type: mrr_at_10
+      value: 32.002
+    - type: mrr_at_100
+      value: 32.838
+    - type: mrr_at_1000
+      value: 32.909
+    - type: mrr_at_3
+      value: 30.317
+    - type: mrr_at_5
+      value: 31.222
+    - type: ndcg_at_1
+      value: 26.074
+    - type: ndcg_at_10
+      value: 32.975
+    - type: ndcg_at_100
+      value: 37.621
+    - type: ndcg_at_1000
+      value: 40.253
+    - type: ndcg_at_3
+      value: 29.452
+    - type: ndcg_at_5
+      value: 31.020999999999997
+    - type: precision_at_1
+      value: 26.074
+    - type: precision_at_10
+      value: 5.077
+    - type: precision_at_100
+      value: 0.8049999999999999
+    - type: precision_at_1000
+      value: 0.11100000000000002
+    - type: precision_at_3
+      value: 12.526000000000002
+    - type: precision_at_5
+      value: 8.588999999999999
+    - type: recall_at_1
+      value: 23.177
+    - type: recall_at_10
+      value: 41.613
+    - type: recall_at_100
+      value: 63.287000000000006
+    - type: recall_at_1000
+      value: 83.013
+    - type: recall_at_3
+      value: 31.783
+    - type: recall_at_5
+      value: 35.769
+    - type: map_at_1
+      value: 15.856
+    - type: map_at_10
+      value: 22.651
+    - type: map_at_100
+      value: 23.649
+    - type: map_at_1000
+      value: 23.783
+    - type: map_at_3
+      value: 20.591
+    - type: map_at_5
+      value: 21.684
+    - type: mrr_at_1
+      value: 19.408
+    - type: mrr_at_10
+      value: 26.51
+    - type: mrr_at_100
+      value: 27.356
+    - type: mrr_at_1000
+      value: 27.439999999999998
+    - type: mrr_at_3
+      value: 24.547
+    - type: mrr_at_5
+      value: 25.562
+    - type: ndcg_at_1
+      value: 19.408
+    - type: ndcg_at_10
+      value: 27.072000000000003
+    - type: ndcg_at_100
+      value: 31.980999999999998
+    - type: ndcg_at_1000
+      value: 35.167
+    - type: ndcg_at_3
+      value: 23.338
+    - type: ndcg_at_5
+      value: 24.94
+    - type: precision_at_1
+      value: 19.408
+    - type: precision_at_10
+      value: 4.9590000000000005
+    - type: precision_at_100
+      value: 0.8710000000000001
+    - type: precision_at_1000
+      value: 0.132
+    - type: precision_at_3
+      value: 11.138
+    - type: precision_at_5
+      value: 7.949000000000001
+    - type: recall_at_1
+      value: 15.856
+    - type: recall_at_10
+      value: 36.578
+    - type: recall_at_100
+      value: 58.89
+    - type: recall_at_1000
+      value: 81.743
+    - type: recall_at_3
+      value: 25.94
+    - type: recall_at_5
+      value: 30.153999999999996
+    - type: map_at_1
+      value: 25.892
+    - type: map_at_10
+      value: 33.899
+    - type: map_at_100
+      value: 34.955000000000005
+    - type: map_at_1000
+      value: 35.066
+    - type: map_at_3
+      value: 31.41
+    - type: map_at_5
+      value: 32.669
+    - type: mrr_at_1
+      value: 30.224
+    - type: mrr_at_10
+      value: 37.936
+    - type: mrr_at_100
+      value: 38.777
+    - type: mrr_at_1000
+      value: 38.85
+    - type: mrr_at_3
+      value: 35.821
+    - type: mrr_at_5
+      value: 36.894
+    - type: ndcg_at_1
+      value: 30.224
+    - type: ndcg_at_10
+      value: 38.766
+    - type: ndcg_at_100
+      value: 43.806
+    - type: ndcg_at_1000
+      value: 46.373999999999995
+    - type: ndcg_at_3
+      value: 34.325
+    - type: ndcg_at_5
+      value: 36.096000000000004
+    - type: precision_at_1
+      value: 30.224
+    - type: precision_at_10
+      value: 6.446000000000001
+    - type: precision_at_100
+      value: 1.0
+    - type: precision_at_1000
+      value: 0.133
+    - type: precision_at_3
+      value: 15.392
+    - type: precision_at_5
+      value: 10.671999999999999
+    - type: recall_at_1
+      value: 25.892
+    - type: recall_at_10
+      value: 49.573
+    - type: recall_at_100
+      value: 71.885
+    - type: recall_at_1000
+      value: 89.912
+    - type: recall_at_3
+      value: 37.226
+    - type: recall_at_5
+      value: 41.74
+    - type: map_at_1
+      value: 23.915
+    - type: map_at_10
+      value: 33.613
+    - type: map_at_100
+      value: 35.333999999999996
+    - type: map_at_1000
+      value: 35.563
+    - type: map_at_3
+      value: 31.203999999999997
+    - type: map_at_5
+      value: 32.479
+    - type: mrr_at_1
+      value: 29.447000000000003
+    - type: mrr_at_10
+      value: 38.440000000000005
+    - type: mrr_at_100
+      value: 39.459
+    - type: mrr_at_1000
+      value: 39.513999999999996
+    - type: mrr_at_3
+      value: 36.495
+    - type: mrr_at_5
+      value: 37.592
+    - type: ndcg_at_1
+      value: 29.447000000000003
+    - type: ndcg_at_10
+      value: 39.341
+    - type: ndcg_at_100
+      value: 45.382
+    - type: ndcg_at_1000
+      value: 47.921
+    - type: ndcg_at_3
+      value: 35.671
+    - type: ndcg_at_5
+      value: 37.299
+    - type: precision_at_1
+      value: 29.447000000000003
+    - type: precision_at_10
+      value: 7.648000000000001
+    - type: precision_at_100
+      value: 1.567
+    - type: precision_at_1000
+      value: 0.241
+    - type: precision_at_3
+      value: 17.194000000000003
+    - type: precision_at_5
+      value: 12.253
+    - type: recall_at_1
+      value: 23.915
+    - type: recall_at_10
+      value: 49.491
+    - type: recall_at_100
+      value: 76.483
+    - type: recall_at_1000
+      value: 92.674
+    - type: recall_at_3
+      value: 38.878
+    - type: recall_at_5
+      value: 43.492
+    - type: map_at_1
+      value: 20.283
+    - type: map_at_10
+      value: 26.851000000000003
+    - type: map_at_100
+      value: 27.973
+    - type: map_at_1000
+      value: 28.087
+    - type: map_at_3
+      value: 24.887
+    - type: map_at_5
+      value: 25.804
+    - type: mrr_at_1
+      value: 22.366
+    - type: mrr_at_10
+      value: 28.864
+    - type: mrr_at_100
+      value: 29.903000000000002
+    - type: mrr_at_1000
+      value: 29.988
+    - type: mrr_at_3
+      value: 27.017999999999997
+    - type: mrr_at_5
+      value: 27.813
+    - type: ndcg_at_1
+      value: 22.366
+    - type: ndcg_at_10
+      value: 30.898999999999997
+    - type: ndcg_at_100
+      value: 36.176
+    - type: ndcg_at_1000
+      value: 39.036
+    - type: ndcg_at_3
+      value: 26.932000000000002
+    - type: ndcg_at_5
+      value: 28.416999999999998
+    - type: precision_at_1
+      value: 22.366
+    - type: precision_at_10
+      value: 4.824
+    - type: precision_at_100
+      value: 0.804
+    - type: precision_at_1000
+      value: 0.116
+    - type: precision_at_3
+      value: 11.459999999999999
+    - type: precision_at_5
+      value: 7.8740000000000006
+    - type: recall_at_1
+      value: 20.283
+    - type: recall_at_10
+      value: 41.559000000000005
+    - type: recall_at_100
+      value: 65.051
+    - type: recall_at_1000
+      value: 86.47200000000001
+    - type: recall_at_3
+      value: 30.524
+    - type: recall_at_5
+      value: 34.11
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB ClimateFEVER
+      type: climate-fever
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 11.326
+    - type: map_at_10
+      value: 19.357
+    - type: map_at_100
+      value: 21.014
+    - type: map_at_1000
+      value: 21.188000000000002
+    - type: map_at_3
+      value: 16.305
+    - type: map_at_5
+      value: 17.886
+    - type: mrr_at_1
+      value: 24.820999999999998
+    - type: mrr_at_10
+      value: 36.150999999999996
+    - type: mrr_at_100
+      value: 37.080999999999996
+    - type: mrr_at_1000
+      value: 37.123
+    - type: mrr_at_3
+      value: 32.952999999999996
+    - type: mrr_at_5
+      value: 34.917
+    - type: ndcg_at_1
+      value: 24.820999999999998
+    - type: ndcg_at_10
+      value: 27.131
+    - type: ndcg_at_100
+      value: 33.841
+    - type: ndcg_at_1000
+      value: 37.159
+    - type: ndcg_at_3
+      value: 22.311
+    - type: ndcg_at_5
+      value: 24.026
+    - type: precision_at_1
+      value: 24.820999999999998
+    - type: precision_at_10
+      value: 8.450000000000001
+    - type: precision_at_100
+      value: 1.557
+    - type: precision_at_1000
+      value: 0.218
+    - type: precision_at_3
+      value: 16.612
+    - type: precision_at_5
+      value: 12.808
+    - type: recall_at_1
+      value: 11.326
+    - type: recall_at_10
+      value: 32.548
+    - type: recall_at_100
+      value: 55.803000000000004
+    - type: recall_at_1000
+      value: 74.636
+    - type: recall_at_3
+      value: 20.549
+    - type: recall_at_5
+      value: 25.514
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB DBPedia
+      type: dbpedia-entity
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 7.481
+    - type: map_at_10
+      value: 15.043999999999999
+    - type: map_at_100
+      value: 20.194000000000003
+    - type: map_at_1000
+      value: 21.423000000000002
+    - type: map_at_3
+      value: 11.238
+    - type: map_at_5
+      value: 12.828999999999999
+    - type: mrr_at_1
+      value: 54.50000000000001
+    - type: mrr_at_10
+      value: 64.713
+    - type: mrr_at_100
+      value: 65.216
+    - type: mrr_at_1000
+      value: 65.23
+    - type: mrr_at_3
+      value: 62.74999999999999
+    - type: mrr_at_5
+      value: 63.87500000000001
+    - type: ndcg_at_1
+      value: 43.375
+    - type: ndcg_at_10
+      value: 32.631
+    - type: ndcg_at_100
+      value: 36.338
+    - type: ndcg_at_1000
+      value: 43.541000000000004
+    - type: ndcg_at_3
+      value: 36.746
+    - type: ndcg_at_5
+      value: 34.419
+    - type: precision_at_1
+      value: 54.50000000000001
+    - type: precision_at_10
+      value: 24.825
+    - type: precision_at_100
+      value: 7.698
+    - type: precision_at_1000
+      value: 1.657
+    - type: precision_at_3
+      value: 38.917
+    - type: precision_at_5
+      value: 32.35
+    - type: recall_at_1
+      value: 7.481
+    - type: recall_at_10
+      value: 20.341
+    - type: recall_at_100
+      value: 41.778
+    - type: recall_at_1000
+      value: 64.82
+    - type: recall_at_3
+      value: 12.748000000000001
+    - type: recall_at_5
+      value: 15.507000000000001
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB EmotionClassification
+      type: mteb/emotion
+      config: default
+      split: test
+      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
+    metrics:
+    - type: accuracy
+      value: 46.580000000000005
+    - type: f1
+      value: 41.5149462395095
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB FEVER
+      type: fever
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 61.683
+    - type: map_at_10
+      value: 73.071
+    - type: map_at_100
+      value: 73.327
+    - type: map_at_1000
+      value: 73.341
+    - type: map_at_3
+      value: 71.446
+    - type: map_at_5
+      value: 72.557
+    - type: mrr_at_1
+      value: 66.44200000000001
+    - type: mrr_at_10
+      value: 77.725
+    - type: mrr_at_100
+      value: 77.89399999999999
+    - type: mrr_at_1000
+      value: 77.898
+    - type: mrr_at_3
+      value: 76.283
+    - type: mrr_at_5
+      value: 77.29700000000001
+    - type: ndcg_at_1
+      value: 66.44200000000001
+    - type: ndcg_at_10
+      value: 78.43
+    - type: ndcg_at_100
+      value: 79.462
+    - type: ndcg_at_1000
+      value: 79.754
+    - type: ndcg_at_3
+      value: 75.53800000000001
+    - type: ndcg_at_5
+      value: 77.332
+    - type: precision_at_1
+      value: 66.44200000000001
+    - type: precision_at_10
+      value: 9.878
+    - type: precision_at_100
+      value: 1.051
+    - type: precision_at_1000
+      value: 0.109
+    - type: precision_at_3
+      value: 29.878
+    - type: precision_at_5
+      value: 18.953
+    - type: recall_at_1
+      value: 61.683
+    - type: recall_at_10
+      value: 90.259
+    - type: recall_at_100
+      value: 94.633
+    - type: recall_at_1000
+      value: 96.60499999999999
+    - type: recall_at_3
+      value: 82.502
+    - type: recall_at_5
+      value: 86.978
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB FiQA2018
+      type: fiqa
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 17.724
+    - type: map_at_10
+      value: 29.487999999999996
+    - type: map_at_100
+      value: 31.243
+    - type: map_at_1000
+      value: 31.419999999999998
+    - type: map_at_3
+      value: 25.612000000000002
+    - type: map_at_5
+      value: 27.859
+    - type: mrr_at_1
+      value: 35.802
+    - type: mrr_at_10
+      value: 44.684000000000005
+    - type: mrr_at_100
+      value: 45.578
+    - type: mrr_at_1000
+      value: 45.621
+    - type: mrr_at_3
+      value: 42.361
+    - type: mrr_at_5
+      value: 43.85
+    - type: ndcg_at_1
+      value: 35.802
+    - type: ndcg_at_10
+      value: 37.009
+    - type: ndcg_at_100
+      value: 43.903
+    - type: ndcg_at_1000
+      value: 47.019
+    - type: ndcg_at_3
+      value: 33.634
+    - type: ndcg_at_5
+      value: 34.965
+    - type: precision_at_1
+      value: 35.802
+    - type: precision_at_10
+      value: 10.386
+    - type: precision_at_100
+      value: 1.7309999999999999
+    - type: precision_at_1000
+      value: 0.231
+    - type: precision_at_3
+      value: 22.84
+    - type: precision_at_5
+      value: 17.037
+    - type: recall_at_1
+      value: 17.724
+    - type: recall_at_10
+      value: 43.708000000000006
+    - type: recall_at_100
+      value: 69.902
+    - type: recall_at_1000
+      value: 88.51
+    - type: recall_at_3
+      value: 30.740000000000002
+    - type: recall_at_5
+      value: 36.742000000000004
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB FloresClusteringS2S
+      type: jinaai/flores_clustering
+      config: default
+      split: test
+      revision: 480b580487f53a46f881354a8348335d4edbb2de
+    metrics:
+    - type: v_measure
+      value: 39.79120149869612
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB HotpotQA
+      type: hotpotqa
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 34.801
+    - type: map_at_10
+      value: 50.42100000000001
+    - type: map_at_100
+      value: 51.254
+    - type: map_at_1000
+      value: 51.327999999999996
+    - type: map_at_3
+      value: 47.56
+    - type: map_at_5
+      value: 49.379
+    - type: mrr_at_1
+      value: 69.602
+    - type: mrr_at_10
+      value: 76.385
+    - type: mrr_at_100
+      value: 76.668
+    - type: mrr_at_1000
+      value: 76.683
+    - type: mrr_at_3
+      value: 75.102
+    - type: mrr_at_5
+      value: 75.949
+    - type: ndcg_at_1
+      value: 69.602
+    - type: ndcg_at_10
+      value: 59.476
+    - type: ndcg_at_100
+      value: 62.527
+    - type: ndcg_at_1000
+      value: 64.043
+    - type: ndcg_at_3
+      value: 55.155
+    - type: ndcg_at_5
+      value: 57.623000000000005
+    - type: precision_at_1
+      value: 69.602
+    - type: precision_at_10
+      value: 12.292
+    - type: precision_at_100
+      value: 1.467
+    - type: precision_at_1000
+      value: 0.167
+    - type: precision_at_3
+      value: 34.634
+    - type: precision_at_5
+      value: 22.728
+    - type: recall_at_1
+      value: 34.801
+    - type: recall_at_10
+      value: 61.458
+    - type: recall_at_100
+      value: 73.363
+    - type: recall_at_1000
+      value: 83.43
+    - type: recall_at_3
+      value: 51.951
+    - type: recall_at_5
+      value: 56.82000000000001
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB ImdbClassification
+      type: mteb/imdb
+      config: default
+      split: test
+      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
+    metrics:
+    - type: accuracy
+      value: 67.46079999999999
+    - type: ap
+      value: 61.81278199159353
+    - type: f1
+      value: 67.26505019954826
+  - task:
+      type: Reranking
+    dataset:
+      name: MTEB MIRACL
+      type: jinaai/miracl
+      config: default
+      split: test
+      revision: d28a029f35c4ff7f616df47b0edf54e6882395e6
+    metrics:
+    - type: map
+      value: 73.90464144118539
+    - type: mrr
+      value: 82.44674693216022
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB MIRACLRetrieval
+      type: jinaai/miracl
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 21.299
+    - type: map_at_10
+      value: 70.547
+    - type: map_at_100
+      value: 72.394
+    - type: map_at_1000
+      value: 72.39999999999999
+    - type: map_at_3
+      value: 41.317
+    - type: map_at_5
+      value: 53.756
+    - type: mrr_at_1
+      value: 72.84
+    - type: mrr_at_10
+      value: 82.466
+    - type: mrr_at_100
+      value: 82.52199999999999
+    - type: mrr_at_1000
+      value: 82.52199999999999
+    - type: mrr_at_3
+      value: 80.607
+    - type: mrr_at_5
+      value: 82.065
+    - type: ndcg_at_1
+      value: 72.994
+    - type: ndcg_at_10
+      value: 80.89
+    - type: ndcg_at_100
+      value: 83.30199999999999
+    - type: ndcg_at_1000
+      value: 83.337
+    - type: ndcg_at_3
+      value: 70.357
+    - type: ndcg_at_5
+      value: 72.529
+    - type: precision_at_1
+      value: 72.994
+    - type: precision_at_10
+      value: 43.056
+    - type: precision_at_100
+      value: 4.603
+    - type: precision_at_1000
+      value: 0.461
+    - type: precision_at_3
+      value: 61.626000000000005
+    - type: precision_at_5
+      value: 55.525000000000006
+    - type: recall_at_1
+      value: 21.299
+    - type: recall_at_10
+      value: 93.903
+    - type: recall_at_100
+      value: 99.86699999999999
+    - type: recall_at_1000
+      value: 100.0
+    - type: recall_at_3
+      value: 46.653
+    - type: recall_at_5
+      value: 65.72200000000001
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB MTOPDomainClassification (en)
+      type: mteb/mtop_domain
+      config: en
+      split: test
+      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
+    metrics:
+    - type: accuracy
+      value: 90.37163702690378
+    - type: f1
+      value: 90.18615216514222
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB MTOPDomainClassification (es)
+      type: mteb/mtop_domain
+      config: es
+      split: test
+      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
+    metrics:
+    - type: accuracy
+      value: 89.88992661774515
+    - type: f1
+      value: 89.3738963046966
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB MTOPIntentClassification (en)
+      type: mteb/mtop_intent
+      config: en
+      split: test
+      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
+    metrics:
+    - type: accuracy
+      value: 71.97218422252622
+    - type: f1
+      value: 54.03096570916335
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB MTOPIntentClassification (es)
+      type: mteb/mtop_intent
+      config: es
+      split: test
+      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
+    metrics:
+    - type: accuracy
+      value: 68.75917278185457
+    - type: f1
+      value: 49.144083814705844
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB MassiveIntentClassification (en)
+      type: mteb/amazon_massive_intent
+      config: en
+      split: test
+      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
+    metrics:
+    - type: accuracy
+      value: 70.75991930060525
+    - type: f1
+      value: 69.37993796176502
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB MassiveIntentClassification (es)
+      type: mteb/amazon_massive_intent
+      config: es
+      split: test
+      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
+    metrics:
+    - type: accuracy
+      value: 66.93006052454606
+    - type: f1
+      value: 66.04029135274683
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB MassiveScenarioClassification (en)
+      type: mteb/amazon_massive_scenario
+      config: en
+      split: test
+      revision: 7d571f92784cd94a019292a1f45445077d0ef634
+    metrics:
+    - type: accuracy
+      value: 73.81977135171486
+    - type: f1
+      value: 74.10477122507747
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB MassiveScenarioClassification (es)
+      type: mteb/amazon_massive_scenario
+      config: es
+      split: test
+      revision: 7d571f92784cd94a019292a1f45445077d0ef634
+    metrics:
+    - type: accuracy
+      value: 71.23402824478816
+    - type: f1
+      value: 71.75572665880296
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB MedrxivClusteringP2P
+      type: mteb/medrxiv-clustering-p2p
+      config: default
+      split: test
+      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
+    metrics:
+    - type: v_measure
+      value: 32.189750849969215
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB MedrxivClusteringS2S
+      type: mteb/medrxiv-clustering-s2s
+      config: default
+      split: test
+      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
+    metrics:
+    - type: v_measure
+      value: 28.78357393555938
+  - task:
+      type: Reranking
+    dataset:
+      name: MTEB MindSmallReranking
+      type: mteb/mind_small
+      config: default
+      split: test
+      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
+    metrics:
+    - type: map
+      value: 30.605612998328358
+    - type: mrr
+      value: 31.595529205695833
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB MintakaESRetrieval
+      type: jinaai/mintakaqa
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 16.213
+    - type: map_at_10
+      value: 24.079
+    - type: map_at_100
+      value: 25.039
+    - type: map_at_1000
+      value: 25.142999999999997
+    - type: map_at_3
+      value: 21.823
+    - type: map_at_5
+      value: 23.069
+    - type: mrr_at_1
+      value: 16.213
+    - type: mrr_at_10
+      value: 24.079
+    - type: mrr_at_100
+      value: 25.039
+    - type: mrr_at_1000
+      value: 25.142999999999997
+    - type: mrr_at_3
+      value: 21.823
+    - type: mrr_at_5
+      value: 23.069
+    - type: ndcg_at_1
+      value: 16.213
+    - type: ndcg_at_10
+      value: 28.315
+    - type: ndcg_at_100
+      value: 33.475
+    - type: ndcg_at_1000
+      value: 36.838
+    - type: ndcg_at_3
+      value: 23.627000000000002
+    - type: ndcg_at_5
+      value: 25.879
+    - type: precision_at_1
+      value: 16.213
+    - type: precision_at_10
+      value: 4.183
+    - type: precision_at_100
+      value: 0.6709999999999999
+    - type: precision_at_1000
+      value: 0.095
+    - type: precision_at_3
+      value: 9.612
+    - type: precision_at_5
+      value: 6.865
+    - type: recall_at_1
+      value: 16.213
+    - type: recall_at_10
+      value: 41.832
+    - type: recall_at_100
+      value: 67.12
+    - type: recall_at_1000
+      value: 94.843
+    - type: recall_at_3
+      value: 28.837000000000003
+    - type: recall_at_5
+      value: 34.323
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB NFCorpus
+      type: nfcorpus
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 4.692
+    - type: map_at_10
+      value: 10.783
+    - type: map_at_100
+      value: 13.447999999999999
+    - type: map_at_1000
+      value: 14.756
+    - type: map_at_3
+      value: 7.646
+    - type: map_at_5
+      value: 9.311
+    - type: mrr_at_1
+      value: 42.415000000000006
+    - type: mrr_at_10
+      value: 50.471
+    - type: mrr_at_100
+      value: 51.251999999999995
+    - type: mrr_at_1000
+      value: 51.292
+    - type: mrr_at_3
+      value: 48.4
+    - type: mrr_at_5
+      value: 49.809
+    - type: ndcg_at_1
+      value: 40.867
+    - type: ndcg_at_10
+      value: 30.303
+    - type: ndcg_at_100
+      value: 27.915
+    - type: ndcg_at_1000
+      value: 36.734
+    - type: ndcg_at_3
+      value: 35.74
+    - type: ndcg_at_5
+      value: 33.938
+    - type: precision_at_1
+      value: 42.415000000000006
+    - type: precision_at_10
+      value: 22.105
+    - type: precision_at_100
+      value: 7.173
+    - type: precision_at_1000
+      value: 2.007
+    - type: precision_at_3
+      value: 33.437
+    - type: precision_at_5
+      value: 29.349999999999998
+    - type: recall_at_1
+      value: 4.692
+    - type: recall_at_10
+      value: 14.798
+    - type: recall_at_100
+      value: 28.948
+    - type: recall_at_1000
+      value: 59.939
+    - type: recall_at_3
+      value: 8.562
+    - type: recall_at_5
+      value: 11.818
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB NQ
+      type: nq
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 27.572999999999997
+    - type: map_at_10
+      value: 42.754
+    - type: map_at_100
+      value: 43.8
+    - type: map_at_1000
+      value: 43.838
+    - type: map_at_3
+      value: 38.157000000000004
+    - type: map_at_5
+      value: 40.9
+    - type: mrr_at_1
+      value: 31.373
+    - type: mrr_at_10
+      value: 45.321
+    - type: mrr_at_100
+      value: 46.109
+    - type: mrr_at_1000
+      value: 46.135
+    - type: mrr_at_3
+      value: 41.483
+    - type: mrr_at_5
+      value: 43.76
+    - type: ndcg_at_1
+      value: 31.373
+    - type: ndcg_at_10
+      value: 50.7
+    - type: ndcg_at_100
+      value: 55.103
+    - type: ndcg_at_1000
+      value: 55.955999999999996
+    - type: ndcg_at_3
+      value: 42.069
+    - type: ndcg_at_5
+      value: 46.595
+    - type: precision_at_1
+      value: 31.373
+    - type: precision_at_10
+      value: 8.601
+    - type: precision_at_100
+      value: 1.11
+    - type: precision_at_1000
+      value: 0.11900000000000001
+    - type: precision_at_3
+      value: 19.399
+    - type: precision_at_5
+      value: 14.224
+    - type: recall_at_1
+      value: 27.572999999999997
+    - type: recall_at_10
+      value: 72.465
+    - type: recall_at_100
+      value: 91.474
+    - type: recall_at_1000
+      value: 97.78099999999999
+    - type: recall_at_3
+      value: 50.087
+    - type: recall_at_5
+      value: 60.516000000000005
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB QuoraRetrieval
+      type: quora
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 70.525
+    - type: map_at_10
+      value: 84.417
+    - type: map_at_100
+      value: 85.07000000000001
+    - type: map_at_1000
+      value: 85.085
+    - type: map_at_3
+      value: 81.45
+    - type: map_at_5
+      value: 83.317
+    - type: mrr_at_1
+      value: 81.17999999999999
+    - type: mrr_at_10
+      value: 87.34100000000001
+    - type: mrr_at_100
+      value: 87.461
+    - type: mrr_at_1000
+      value: 87.46199999999999
+    - type: mrr_at_3
+      value: 86.372
+    - type: mrr_at_5
+      value: 87.046
+    - type: ndcg_at_1
+      value: 81.17999999999999
+    - type: ndcg_at_10
+      value: 88.144
+    - type: ndcg_at_100
+      value: 89.424
+    - type: ndcg_at_1000
+      value: 89.517
+    - type: ndcg_at_3
+      value: 85.282
+    - type: ndcg_at_5
+      value: 86.874
+    - type: precision_at_1
+      value: 81.17999999999999
+    - type: precision_at_10
+      value: 13.385
+    - type: precision_at_100
+      value: 1.533
+    - type: precision_at_1000
+      value: 0.157
+    - type: precision_at_3
+      value: 37.29
+    - type: precision_at_5
+      value: 24.546
+    - type: recall_at_1
+      value: 70.525
+    - type: recall_at_10
+      value: 95.22500000000001
+    - type: recall_at_100
+      value: 99.572
+    - type: recall_at_1000
+      value: 99.98899999999999
+    - type: recall_at_3
+      value: 87.035
+    - type: recall_at_5
+      value: 91.526
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB RedditClustering
+      type: mteb/reddit-clustering
+      config: default
+      split: test
+      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
+    metrics:
+    - type: v_measure
+      value: 48.284384328108736
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB RedditClusteringP2P
+      type: mteb/reddit-clustering-p2p
+      config: default
+      split: test
+      revision: 282350215ef01743dc01b456c7f5241fa8937f16
+    metrics:
+    - type: v_measure
+      value: 56.02508021518392
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB SCIDOCS
+      type: scidocs
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 4.023000000000001
+    - type: map_at_10
+      value: 10.046
+    - type: map_at_100
+      value: 11.802999999999999
+    - type: map_at_1000
+      value: 12.074
+    - type: map_at_3
+      value: 7.071
+    - type: map_at_5
+      value: 8.556
+    - type: mrr_at_1
+      value: 19.8
+    - type: mrr_at_10
+      value: 30.105999999999998
+    - type: mrr_at_100
+      value: 31.16
+    - type: mrr_at_1000
+      value: 31.224
+    - type: mrr_at_3
+      value: 26.633000000000003
+    - type: mrr_at_5
+      value: 28.768
+    - type: ndcg_at_1
+      value: 19.8
+    - type: ndcg_at_10
+      value: 17.358
+    - type: ndcg_at_100
+      value: 24.566
+    - type: ndcg_at_1000
+      value: 29.653000000000002
+    - type: ndcg_at_3
+      value: 16.052
+    - type: ndcg_at_5
+      value: 14.325
+    - type: precision_at_1
+      value: 19.8
+    - type: precision_at_10
+      value: 9.07
+    - type: precision_at_100
+      value: 1.955
+    - type: precision_at_1000
+      value: 0.318
+    - type: precision_at_3
+      value: 14.933
+    - type: precision_at_5
+      value: 12.68
+    - type: recall_at_1
+      value: 4.023000000000001
+    - type: recall_at_10
+      value: 18.398
+    - type: recall_at_100
+      value: 39.683
+    - type: recall_at_1000
+      value: 64.625
+    - type: recall_at_3
+      value: 9.113
+    - type: recall_at_5
+      value: 12.873000000000001
+  - task:
+      type: STS
+    dataset:
+      name: MTEB SICK-R
+      type: mteb/sickr-sts
+      config: default
+      split: test
+      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
+    metrics:
+    - type: cos_sim_pearson
+      value: 87.90508618312852
+    - type: cos_sim_spearman
+      value: 83.01323463129205
+    - type: euclidean_pearson
+      value: 84.35845059002891
+    - type: euclidean_spearman
+      value: 82.85508559018527
+    - type: manhattan_pearson
+      value: 84.3682368950498
+    - type: manhattan_spearman
+      value: 82.8619728517302
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STS12
+      type: mteb/sts12-sts
+      config: default
+      split: test
+      revision: a0d554a64d88156834ff5ae9920b964011b16384
+    metrics:
+    - type: cos_sim_pearson
+      value: 89.28294535873366
+    - type: cos_sim_spearman
+      value: 81.61879268131732
+    - type: euclidean_pearson
+      value: 85.99053604863724
+    - type: euclidean_spearman
+      value: 80.95176684739084
+    - type: manhattan_pearson
+      value: 85.98054086663903
+    - type: manhattan_spearman
+      value: 80.9911070430335
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STS13
+      type: mteb/sts13-sts
+      config: default
+      split: test
+      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
+    metrics:
+    - type: cos_sim_pearson
+      value: 86.15898098455258
+    - type: cos_sim_spearman
+      value: 86.8247985072307
+    - type: euclidean_pearson
+      value: 86.25342429918649
+    - type: euclidean_spearman
+      value: 87.13468603023252
+    - type: manhattan_pearson
+      value: 86.2006134067688
+    - type: manhattan_spearman
+      value: 87.06135811996896
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STS14
+      type: mteb/sts14-sts
+      config: default
+      split: test
+      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
+    metrics:
+    - type: cos_sim_pearson
+      value: 85.57403998481877
+    - type: cos_sim_spearman
+      value: 83.55947075172618
+    - type: euclidean_pearson
+      value: 84.97097562965358
+    - type: euclidean_spearman
+      value: 83.6287075601467
+    - type: manhattan_pearson
+      value: 84.87092197104133
+    - type: manhattan_spearman
+      value: 83.53783891641335
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STS15
+      type: mteb/sts15-sts
+      config: default
+      split: test
+      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
+    metrics:
+    - type: cos_sim_pearson
+      value: 88.14632780204231
+    - type: cos_sim_spearman
+      value: 88.74903634923868
+    - type: euclidean_pearson
+      value: 88.03922995855112
+    - type: euclidean_spearman
+      value: 88.72852190525855
+    - type: manhattan_pearson
+      value: 87.9694791024271
+    - type: manhattan_spearman
+      value: 88.66461452107418
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STS16
+      type: mteb/sts16-sts
+      config: default
+      split: test
+      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
+    metrics:
+    - type: cos_sim_pearson
+      value: 84.75989818558652
+    - type: cos_sim_spearman
+      value: 86.03107893122942
+    - type: euclidean_pearson
+      value: 85.21908960133018
+    - type: euclidean_spearman
+      value: 85.93012720153482
+    - type: manhattan_pearson
+      value: 85.1969170195502
+    - type: manhattan_spearman
+      value: 85.8975254197784
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STS17 (en-en)
+      type: mteb/sts17-crosslingual-sts
+      config: en-en
+      split: test
+      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
+    metrics:
+    - type: cos_sim_pearson
+      value: 89.16803898789955
+    - type: cos_sim_spearman
+      value: 88.56139047950525
+    - type: euclidean_pearson
+      value: 88.09685325747859
+    - type: euclidean_spearman
+      value: 88.0457609458947
+    - type: manhattan_pearson
+      value: 88.07054413001431
+    - type: manhattan_spearman
+      value: 88.10784098889314
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STS17 (es-en)
+      type: mteb/sts17-crosslingual-sts
+      config: es-en
+      split: test
+      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
+    metrics:
+    - type: cos_sim_pearson
+      value: 86.7160384474547
+    - type: cos_sim_spearman
+      value: 86.4899235500562
+    - type: euclidean_pearson
+      value: 85.90854477703468
+    - type: euclidean_spearman
+      value: 86.16085009124498
+    - type: manhattan_pearson
+      value: 85.9249735317884
+    - type: manhattan_spearman
+      value: 86.25038421339116
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STS17 (es-es)
+      type: mteb/sts17-crosslingual-sts
+      config: es-es
+      split: test
+      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
+    metrics:
+    - type: cos_sim_pearson
+      value: 89.37914622360788
+    - type: cos_sim_spearman
+      value: 88.24619159322809
+    - type: euclidean_pearson
+      value: 89.00538382632769
+    - type: euclidean_spearman
+      value: 88.44675863524736
+    - type: manhattan_pearson
+      value: 88.97372120683606
+    - type: manhattan_spearman
+      value: 88.33509324222129
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STS22 (en)
+      type: mteb/sts22-crosslingual-sts
+      config: en
+      split: test
+      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
+    metrics:
+    - type: cos_sim_pearson
+      value: 66.22181360203069
+    - type: cos_sim_spearman
+      value: 65.6218291833768
+    - type: euclidean_pearson
+      value: 67.14543788822508
+    - type: euclidean_spearman
+      value: 65.21269939987857
+    - type: manhattan_pearson
+      value: 67.03304607195636
+    - type: manhattan_spearman
+      value: 65.18885316423805
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STS22 (es)
+      type: mteb/sts22-crosslingual-sts
+      config: es
+      split: test
+      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
+    metrics:
+    - type: cos_sim_pearson
+      value: 65.71694059677084
+    - type: cos_sim_spearman
+      value: 67.96591844540954
+    - type: euclidean_pearson
+      value: 65.6964079162296
+    - type: euclidean_spearman
+      value: 67.53027948900173
+    - type: manhattan_pearson
+      value: 65.93545097673741
+    - type: manhattan_spearman
+      value: 67.7261811805062
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STS22 (es-en)
+      type: mteb/sts22-crosslingual-sts
+      config: es-en
+      split: test
+      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
+    metrics:
+    - type: cos_sim_pearson
+      value: 75.43544796375058
+    - type: cos_sim_spearman
+      value: 78.80462701160789
+    - type: euclidean_pearson
+      value: 76.19135575163138
+    - type: euclidean_spearman
+      value: 78.4974732597096
+    - type: manhattan_pearson
+      value: 76.3254742699264
+    - type: manhattan_spearman
+      value: 78.51884307690416
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STSBenchmark
+      type: mteb/stsbenchmark-sts
+      config: default
+      split: test
+      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
+    metrics:
+    - type: cos_sim_pearson
+      value: 87.46805293607684
+    - type: cos_sim_spearman
+      value: 87.83792784689113
+    - type: euclidean_pearson
+      value: 87.3872143683234
+    - type: euclidean_spearman
+      value: 87.61611384542778
+    - type: manhattan_pearson
+      value: 87.38542672601992
+    - type: manhattan_spearman
+      value: 87.61423971087297
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STSES
+      type: PlanTL-GOB-ES/sts-es
+      config: default
+      split: test
+      revision: 0912bb6c9393c76d62a7c5ee81c4c817ff47c9f4
+    metrics:
+    - type: cos_sim_pearson
+      value: 82.55286866116202
+    - type: cos_sim_spearman
+      value: 80.22150503320272
+    - type: euclidean_pearson
+      value: 83.27223445187087
+    - type: euclidean_spearman
+      value: 80.59078590992925
+    - type: manhattan_pearson
+      value: 83.23095887013197
+    - type: manhattan_spearman
+      value: 80.87994285189795
+  - task:
+      type: Reranking
+    dataset:
+      name: MTEB SciDocsRR
+      type: mteb/scidocs-reranking
+      config: default
+      split: test
+      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
+    metrics:
+    - type: map
+      value: 79.29717302265792
+    - type: mrr
+      value: 94.02156304117088
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB SciFact
+      type: scifact
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 49.9
+    - type: map_at_10
+      value: 58.626
+    - type: map_at_100
+      value: 59.519999999999996
+    - type: map_at_1000
+      value: 59.55200000000001
+    - type: map_at_3
+      value: 56.232000000000006
+    - type: map_at_5
+      value: 57.833
+    - type: mrr_at_1
+      value: 52.333
+    - type: mrr_at_10
+      value: 60.039
+    - type: mrr_at_100
+      value: 60.732
+    - type: mrr_at_1000
+      value: 60.75899999999999
+    - type: mrr_at_3
+      value: 58.278
+    - type: mrr_at_5
+      value: 59.428000000000004
+    - type: ndcg_at_1
+      value: 52.333
+    - type: ndcg_at_10
+      value: 62.67
+    - type: ndcg_at_100
+      value: 66.465
+    - type: ndcg_at_1000
+      value: 67.425
+    - type: ndcg_at_3
+      value: 58.711999999999996
+    - type: ndcg_at_5
+      value: 60.958999999999996
+    - type: precision_at_1
+      value: 52.333
+    - type: precision_at_10
+      value: 8.333
+    - type: precision_at_100
+      value: 1.027
+    - type: precision_at_1000
+      value: 0.11100000000000002
+    - type: precision_at_3
+      value: 22.778000000000002
+    - type: precision_at_5
+      value: 15.267
+    - type: recall_at_1
+      value: 49.9
+    - type: recall_at_10
+      value: 73.394
+    - type: recall_at_100
+      value: 90.43299999999999
+    - type: recall_at_1000
+      value: 98.167
+    - type: recall_at_3
+      value: 63.032999999999994
+    - type: recall_at_5
+      value: 68.444
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB SpanishNewsClusteringP2P
+      type: jinaai/spanish_news_clustering
+      config: default
+      split: test
+      revision: b5edc3d3d7c12c7b9f883e9da50f6732f3624142
+    metrics:
+    - type: v_measure
+      value: 48.30543557796266
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB SpanishPassageRetrievalS2P
+      type: jinaai/spanish_passage_retrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 14.443
+    - type: map_at_10
+      value: 28.736
+    - type: map_at_100
+      value: 34.514
+    - type: map_at_1000
+      value: 35.004000000000005
+    - type: map_at_3
+      value: 20.308
+    - type: map_at_5
+      value: 25.404
+    - type: mrr_at_1
+      value: 50.29900000000001
+    - type: mrr_at_10
+      value: 63.757
+    - type: mrr_at_100
+      value: 64.238
+    - type: mrr_at_1000
+      value: 64.24600000000001
+    - type: mrr_at_3
+      value: 59.480999999999995
+    - type: mrr_at_5
+      value: 62.924
+    - type: ndcg_at_1
+      value: 50.29900000000001
+    - type: ndcg_at_10
+      value: 42.126999999999995
+    - type: ndcg_at_100
+      value: 57.208000000000006
+    - type: ndcg_at_1000
+      value: 60.646
+    - type: ndcg_at_3
+      value: 38.722
+    - type: ndcg_at_5
+      value: 40.007999999999996
+    - type: precision_at_1
+      value: 50.29900000000001
+    - type: precision_at_10
+      value: 19.82
+    - type: precision_at_100
+      value: 4.82
+    - type: precision_at_1000
+      value: 0.5910000000000001
+    - type: precision_at_3
+      value: 31.537
+    - type: precision_at_5
+      value: 28.262999999999998
+    - type: recall_at_1
+      value: 14.443
+    - type: recall_at_10
+      value: 43.885999999999996
+    - type: recall_at_100
+      value: 85.231
+    - type: recall_at_1000
+      value: 99.07000000000001
+    - type: recall_at_3
+      value: 22.486
+    - type: recall_at_5
+      value: 33.035
+    - type: map_at_1
+      value: 15.578
+    - type: map_at_10
+      value: 52.214000000000006
+    - type: map_at_100
+      value: 64.791
+    - type: map_at_1000
+      value: 64.791
+    - type: map_at_3
+      value: 33.396
+    - type: map_at_5
+      value: 41.728
+    - type: mrr_at_1
+      value: 73.653
+    - type: mrr_at_10
+      value: 85.116
+    - type: mrr_at_100
+      value: 85.205
+    - type: mrr_at_1000
+      value: 85.205
+    - type: mrr_at_3
+      value: 84.631
+    - type: mrr_at_5
+      value: 85.05
+    - type: ndcg_at_1
+      value: 76.64699999999999
+    - type: ndcg_at_10
+      value: 70.38600000000001
+    - type: ndcg_at_100
+      value: 82.27600000000001
+    - type: ndcg_at_1000
+      value: 82.27600000000001
+    - type: ndcg_at_3
+      value: 70.422
+    - type: ndcg_at_5
+      value: 69.545
+    - type: precision_at_1
+      value: 76.64699999999999
+    - type: precision_at_10
+      value: 43.653
+    - type: precision_at_100
+      value: 7.718999999999999
+    - type: precision_at_1000
+      value: 0.772
+    - type: precision_at_3
+      value: 64.671
+    - type: precision_at_5
+      value: 56.766000000000005
+    - type: recall_at_1
+      value: 15.578
+    - type: recall_at_10
+      value: 67.459
+    - type: recall_at_100
+      value: 100.0
+    - type: recall_at_1000
+      value: 100.0
+    - type: recall_at_3
+      value: 36.922
+    - type: recall_at_5
+      value: 49.424
+  - task:
+      type: PairClassification
+    dataset:
+      name: MTEB SprintDuplicateQuestions
+      type: mteb/sprintduplicatequestions-pairclassification
+      config: default
+      split: test
+      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
+    metrics:
+    - type: cos_sim_accuracy
+      value: 99.81683168316832
+    - type: cos_sim_ap
+      value: 95.61502659412484
+    - type: cos_sim_f1
+      value: 90.6813627254509
+    - type: cos_sim_precision
+      value: 90.86345381526104
+    - type: cos_sim_recall
+      value: 90.5
+    - type: dot_accuracy
+      value: 99.8039603960396
+    - type: dot_ap
+      value: 95.36783483182609
+    - type: dot_f1
+      value: 89.90825688073394
+    - type: dot_precision
+      value: 91.68399168399168
+    - type: dot_recall
+      value: 88.2
+    - type: euclidean_accuracy
+      value: 99.81188118811882
+    - type: euclidean_ap
+      value: 95.51583052324564
+    - type: euclidean_f1
+      value: 90.46214355948868
+    - type: euclidean_precision
+      value: 88.97485493230174
+    - type: euclidean_recall
+      value: 92.0
+    - type: manhattan_accuracy
+      value: 99.8079207920792
+    - type: manhattan_ap
+      value: 95.44030644653718
+    - type: manhattan_f1
+      value: 90.37698412698413
+    - type: manhattan_precision
+      value: 89.66535433070865
+    - type: manhattan_recall
+      value: 91.10000000000001
+    - type: max_accuracy
+      value: 99.81683168316832
+    - type: max_ap
+      value: 95.61502659412484
+    - type: max_f1
+      value: 90.6813627254509
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB StackExchangeClustering
+      type: mteb/stackexchange-clustering
+      config: default
+      split: test
+      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
+    metrics:
+    - type: v_measure
+      value: 55.39046705023096
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB StackExchangeClusteringP2P
+      type: mteb/stackexchange-clustering-p2p
+      config: default
+      split: test
+      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
+    metrics:
+    - type: v_measure
+      value: 33.57429225651293
+  - task:
+      type: Reranking
+    dataset:
+      name: MTEB StackOverflowDupQuestions
+      type: mteb/stackoverflowdupquestions-reranking
+      config: default
+      split: test
+      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
+    metrics:
+    - type: map
+      value: 50.17622570658746
+    - type: mrr
+      value: 50.99844293778118
+  - task:
+      type: Summarization
+    dataset:
+      name: MTEB SummEval
+      type: mteb/summeval
+      config: default
+      split: test
+      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
+    metrics:
+    - type: cos_sim_pearson
+      value: 29.97416289382191
+    - type: cos_sim_spearman
+      value: 29.871890597161432
+    - type: dot_pearson
+      value: 28.768845892613644
+    - type: dot_spearman
+      value: 28.872458999448686
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB TRECCOVID
+      type: trec-covid
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 0.22599999999999998
+    - type: map_at_10
+      value: 1.646
+    - type: map_at_100
+      value: 9.491
+    - type: map_at_1000
+      value: 23.75
+    - type: map_at_3
+      value: 0.588
+    - type: map_at_5
+      value: 0.9129999999999999
+    - type: mrr_at_1
+      value: 84.0
+    - type: mrr_at_10
+      value: 89.889
+    - type: mrr_at_100
+      value: 89.889
+    - type: mrr_at_1000
+      value: 89.889
+    - type: mrr_at_3
+      value: 89.667
+    - type: mrr_at_5
+      value: 89.667
+    - type: ndcg_at_1
+      value: 75.0
+    - type: ndcg_at_10
+      value: 67.368
+    - type: ndcg_at_100
+      value: 52.834
+    - type: ndcg_at_1000
+      value: 49.144
+    - type: ndcg_at_3
+      value: 72.866
+    - type: ndcg_at_5
+      value: 70.16
+    - type: precision_at_1
+      value: 84.0
+    - type: precision_at_10
+      value: 71.8
+    - type: precision_at_100
+      value: 54.04
+    - type: precision_at_1000
+      value: 21.709999999999997
+    - type: precision_at_3
+      value: 77.333
+    - type: precision_at_5
+      value: 74.0
+    - type: recall_at_1
+      value: 0.22599999999999998
+    - type: recall_at_10
+      value: 1.9029999999999998
+    - type: recall_at_100
+      value: 13.012
+    - type: recall_at_1000
+      value: 46.105000000000004
+    - type: recall_at_3
+      value: 0.63
+    - type: recall_at_5
+      value: 1.0030000000000001
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB Touche2020
+      type: webis-touche2020
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 1.5
+    - type: map_at_10
+      value: 8.193999999999999
+    - type: map_at_100
+      value: 14.01
+    - type: map_at_1000
+      value: 15.570999999999998
+    - type: map_at_3
+      value: 4.361000000000001
+    - type: map_at_5
+      value: 5.9270000000000005
+    - type: mrr_at_1
+      value: 16.326999999999998
+    - type: mrr_at_10
+      value: 33.326
+    - type: mrr_at_100
+      value: 34.592
+    - type: mrr_at_1000
+      value: 34.592
+    - type: mrr_at_3
+      value: 29.252
+    - type: mrr_at_5
+      value: 30.680000000000003
+    - type: ndcg_at_1
+      value: 15.306000000000001
+    - type: ndcg_at_10
+      value: 19.819
+    - type: ndcg_at_100
+      value: 33.428000000000004
+    - type: ndcg_at_1000
+      value: 45.024
+    - type: ndcg_at_3
+      value: 19.667
+    - type: ndcg_at_5
+      value: 19.625
+    - type: precision_at_1
+      value: 16.326999999999998
+    - type: precision_at_10
+      value: 18.367
+    - type: precision_at_100
+      value: 7.367
+    - type: precision_at_1000
+      value: 1.496
+    - type: precision_at_3
+      value: 23.128999999999998
+    - type: precision_at_5
+      value: 21.633
+    - type: recall_at_1
+      value: 1.5
+    - type: recall_at_10
+      value: 14.362
+    - type: recall_at_100
+      value: 45.842
+    - type: recall_at_1000
+      value: 80.42
+    - type: recall_at_3
+      value: 5.99
+    - type: recall_at_5
+      value: 8.701
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB ToxicConversationsClassification
+      type: mteb/toxic_conversations_50k
+      config: default
+      split: test
+      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
+    metrics:
+    - type: accuracy
+      value: 70.04740000000001
+    - type: ap
+      value: 13.58661943759992
+    - type: f1
+      value: 53.727487131754195
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB TweetSentimentExtractionClassification
+      type: mteb/tweet_sentiment_extraction
+      config: default
+      split: test
+      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
+    metrics:
+    - type: accuracy
+      value: 61.06395019807584
+    - type: f1
+      value: 61.36753664680866
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB TwentyNewsgroupsClustering
+      type: mteb/twentynewsgroups-clustering
+      config: default
+      split: test
+      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
+    metrics:
+    - type: v_measure
+      value: 40.19881263066229
+  - task:
+      type: PairClassification
+    dataset:
+      name: MTEB TwitterSemEval2015
+      type: mteb/twittersemeval2015-pairclassification
+      config: default
+      split: test
+      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
+    metrics:
+    - type: cos_sim_accuracy
+      value: 85.19401561661799
+    - type: cos_sim_ap
+      value: 71.62462506173092
+    - type: cos_sim_f1
+      value: 66.0641327225455
+    - type: cos_sim_precision
+      value: 62.234662934453
+    - type: cos_sim_recall
+      value: 70.3957783641161
+    - type: dot_accuracy
+      value: 84.69333015437802
+    - type: dot_ap
+      value: 69.83805526490895
+    - type: dot_f1
+      value: 64.85446235265817
+    - type: dot_precision
+      value: 59.59328028293546
+    - type: dot_recall
+      value: 71.13456464379946
+    - type: euclidean_accuracy
+      value: 85.38475293556655
+    - type: euclidean_ap
+      value: 72.05594596250286
+    - type: euclidean_f1
+      value: 66.53543307086615
+    - type: euclidean_precision
+      value: 62.332872291378514
+    - type: euclidean_recall
+      value: 71.34564643799473
+    - type: manhattan_accuracy
+      value: 85.3907134767837
+    - type: manhattan_ap
+      value: 72.04585410650152
+    - type: manhattan_f1
+      value: 66.57132642116554
+    - type: manhattan_precision
+      value: 60.704194740273856
+    - type: manhattan_recall
+      value: 73.6939313984169
+    - type: max_accuracy
+      value: 85.3907134767837
+    - type: max_ap
+      value: 72.05594596250286
+    - type: max_f1
+      value: 66.57132642116554
+  - task:
+      type: PairClassification
+    dataset:
+      name: MTEB TwitterURLCorpus
+      type: mteb/twitterurlcorpus-pairclassification
+      config: default
+      split: test
+      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
+    metrics:
+    - type: cos_sim_accuracy
+      value: 89.30414871735165
+    - type: cos_sim_ap
+      value: 86.4398673359918
+    - type: cos_sim_f1
+      value: 78.9243598692186
+    - type: cos_sim_precision
+      value: 75.47249350101876
+    - type: cos_sim_recall
+      value: 82.7071142593163
+    - type: dot_accuracy
+      value: 89.26145845461248
+    - type: dot_ap
+      value: 86.32172118414802
+    - type: dot_f1
+      value: 78.8277467755645
+    - type: dot_precision
+      value: 75.79418662497335
+    - type: dot_recall
+      value: 82.11425931629196
+    - type: euclidean_accuracy
+      value: 89.24205378973105
+    - type: euclidean_ap
+      value: 86.23988673522649
+    - type: euclidean_f1
+      value: 78.67984857951413
+    - type: euclidean_precision
+      value: 75.2689684269742
+    - type: euclidean_recall
+      value: 82.41453649522637
+    - type: manhattan_accuracy
+      value: 89.18189932859859
+    - type: manhattan_ap
+      value: 86.21003833972824
+    - type: manhattan_f1
+      value: 78.70972564850115
+    - type: manhattan_precision
+      value: 76.485544094145
+    - type: manhattan_recall
+      value: 81.0671388974438
+    - type: max_accuracy
+      value: 89.30414871735165
+    - type: max_ap
+      value: 86.4398673359918
+    - type: max_f1
+      value: 78.9243598692186
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB WikiCitiesClustering
+      type: jinaai/cities_wiki_clustering
+      config: default
+      split: test
+      revision: ddc9ee9242fa65332597f70e967ecc38b9d734fa
+    metrics:
+    - type: v_measure
+      value: 73.254610626148
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB XMarketES
+      type: jinaai/xmarket_ml
+      config: default
+      split: test
+      revision: 705db869e8107dfe6e34b832af90446e77d813e3
+    metrics:
+    - type: map_at_1
+      value: 5.506
+    - type: map_at_10
+      value: 11.546
+    - type: map_at_100
+      value: 14.299999999999999
+    - type: map_at_1000
+      value: 15.146999999999998
+    - type: map_at_3
+      value: 8.748000000000001
+    - type: map_at_5
+      value: 10.036000000000001
+    - type: mrr_at_1
+      value: 17.902
+    - type: mrr_at_10
+      value: 25.698999999999998
+    - type: mrr_at_100
+      value: 26.634
+    - type: mrr_at_1000
+      value: 26.704
+    - type: mrr_at_3
+      value: 23.244999999999997
+    - type: mrr_at_5
+      value: 24.555
+    - type: ndcg_at_1
+      value: 17.902
+    - type: ndcg_at_10
+      value: 19.714000000000002
+    - type: ndcg_at_100
+      value: 25.363000000000003
+    - type: ndcg_at_1000
+      value: 30.903999999999996
+    - type: ndcg_at_3
+      value: 17.884
+    - type: ndcg_at_5
+      value: 18.462
+    - type: precision_at_1
+      value: 17.902
+    - type: precision_at_10
+      value: 10.467
+    - type: precision_at_100
+      value: 3.9699999999999998
+    - type: precision_at_1000
+      value: 1.1320000000000001
+    - type: precision_at_3
+      value: 14.387
+    - type: precision_at_5
+      value: 12.727
+    - type: recall_at_1
+      value: 5.506
+    - type: recall_at_10
+      value: 19.997999999999998
+    - type: recall_at_100
+      value: 42.947
+    - type: recall_at_1000
+      value: 67.333
+    - type: recall_at_3
+      value: 11.158
+    - type: recall_at_5
+      value: 14.577000000000002
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB XPQAESRetrieval
+      type: jinaai/xpqa
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 32.53
+    - type: map_at_10
+      value: 58.68600000000001
+    - type: map_at_100
+      value: 60.45399999999999
+    - type: map_at_1000
+      value: 60.51499999999999
+    - type: map_at_3
+      value: 50.356
+    - type: map_at_5
+      value: 55.98
+    - type: mrr_at_1
+      value: 61.791
+    - type: mrr_at_10
+      value: 68.952
+    - type: mrr_at_100
+      value: 69.524
+    - type: mrr_at_1000
+      value: 69.538
+    - type: mrr_at_3
+      value: 67.087
+    - type: mrr_at_5
+      value: 68.052
+    - type: ndcg_at_1
+      value: 61.791
+    - type: ndcg_at_10
+      value: 65.359
+    - type: ndcg_at_100
+      value: 70.95700000000001
+    - type: ndcg_at_1000
+      value: 71.881
+    - type: ndcg_at_3
+      value: 59.999
+    - type: ndcg_at_5
+      value: 61.316
+    - type: precision_at_1
+      value: 61.791
+    - type: precision_at_10
+      value: 18.184
+    - type: precision_at_100
+      value: 2.317
+    - type: precision_at_1000
+      value: 0.245
+    - type: precision_at_3
+      value: 42.203
+    - type: precision_at_5
+      value: 31.374999999999996
+    - type: recall_at_1
+      value: 32.53
+    - type: recall_at_10
+      value: 73.098
+    - type: recall_at_100
+      value: 94.029
+    - type: recall_at_1000
+      value: 99.842
+    - type: recall_at_3
+      value: 54.525
+    - type: recall_at_5
+      value: 63.796
+---
+
+# AndreasX/jina-embeddings-v2-base-es-Q2_K-GGUF
+This model was converted to GGUF format from [`jinaai/jina-embeddings-v2-base-es`](https://huggingface.co/jinaai/jina-embeddings-v2-base-es) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
+Refer to the [original model card](https://huggingface.co/jinaai/jina-embeddings-v2-base-es) for more details on the model.
+
+## Use with llama.cpp
+Install llama.cpp through brew (works on Mac and Linux)
+
+```bash
+brew install llama.cpp
+
+```
+Invoke the llama.cpp server or the CLI.
+
+### CLI:
+```bash
+llama-cli --hf-repo AndreasX/jina-embeddings-v2-base-es-Q2_K-GGUF --hf-file jina-embeddings-v2-base-es-q2_k.gguf -p "The meaning to life and the universe is"
+```
+
+### Server:
+```bash
+llama-server --hf-repo AndreasX/jina-embeddings-v2-base-es-Q2_K-GGUF --hf-file jina-embeddings-v2-base-es-q2_k.gguf -c 2048
+```
+
+Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.
+
+Step 1: Clone llama.cpp from GitHub.
+```
+git clone https://github.com/ggerganov/llama.cpp
+```
+
+Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
+```
+cd llama.cpp && LLAMA_CURL=1 make
+```
+
+Step 3: Run inference through the main binary.
+```
+./llama-cli --hf-repo AndreasX/jina-embeddings-v2-base-es-Q2_K-GGUF --hf-file jina-embeddings-v2-base-es-q2_k.gguf -p "The meaning to life and the universe is"
+```
+or 
+```
+./llama-server --hf-repo AndreasX/jina-embeddings-v2-base-es-Q2_K-GGUF --hf-file jina-embeddings-v2-base-es-q2_k.gguf -c 2048
+```