diff --git "a/README.md" "b/README.md"
new file mode 100644--- /dev/null
+++ "b/README.md"
@@ -0,0 +1,2968 @@
+---
+base_model: Mihaiii/Bulbasaur
+license: mit
+library_name: sentence-transformers
+pipeline_tag: sentence-similarity
+tags:
+- sentence-transformers
+- feature-extraction
+- sentence-similarity
+- gte
+- mteb
+datasets:
+- Mihaiii/qa-assistant
+model-index:
+- name: Venusaur
+  results:
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_counterfactual
+      name: MTEB AmazonCounterfactualClassification (en)
+      config: en
+      split: test
+      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
+    metrics:
+    - type: accuracy
+      value: 73.17910447761194
+    - type: ap
+      value: 35.29994612283548
+    - type: f1
+      value: 66.87845205993153
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_polarity
+      name: MTEB AmazonPolarityClassification
+      config: default
+      split: test
+      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
+    metrics:
+    - type: accuracy
+      value: 79.993525
+    - type: ap
+      value: 74.7042261687233
+    - type: f1
+      value: 79.9004149386498
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_reviews_multi
+      name: MTEB AmazonReviewsClassification (en)
+      config: en
+      split: test
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+    metrics:
+    - type: accuracy
+      value: 39.656000000000006
+    - type: f1
+      value: 39.287139345446256
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/arguana
+      name: MTEB ArguAna
+      config: default
+      split: test
+      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
+    metrics:
+    - type: map_at_1
+      value: 16.643
+    - type: map_at_10
+      value: 28.276
+    - type: map_at_100
+      value: 29.543999999999997
+    - type: map_at_1000
+      value: 29.595
+    - type: map_at_20
+      value: 29.043000000000003
+    - type: map_at_3
+      value: 24.739
+    - type: map_at_5
+      value: 26.592
+    - type: mrr_at_1
+      value: 17.639
+    - type: mrr_at_10
+      value: 28.631
+    - type: mrr_at_100
+      value: 29.891000000000002
+    - type: mrr_at_1000
+      value: 29.942999999999998
+    - type: mrr_at_20
+      value: 29.391000000000002
+    - type: mrr_at_3
+      value: 25.107000000000003
+    - type: mrr_at_5
+      value: 26.942
+    - type: ndcg_at_1
+      value: 16.643
+    - type: ndcg_at_10
+      value: 34.8
+    - type: ndcg_at_100
+      value: 41.179
+    - type: ndcg_at_1000
+      value: 42.564
+    - type: ndcg_at_20
+      value: 37.601
+    - type: ndcg_at_3
+      value: 27.356
+    - type: ndcg_at_5
+      value: 30.725
+    - type: precision_at_1
+      value: 16.643
+    - type: precision_at_10
+      value: 5.576
+    - type: precision_at_100
+      value: 0.861
+    - type: precision_at_1000
+      value: 0.097
+    - type: precision_at_20
+      value: 3.343
+    - type: precision_at_3
+      value: 11.641
+    - type: precision_at_5
+      value: 8.634
+    - type: recall_at_1
+      value: 16.643
+    - type: recall_at_10
+      value: 55.761
+    - type: recall_at_100
+      value: 86.06
+    - type: recall_at_1000
+      value: 97.013
+    - type: recall_at_20
+      value: 66.85600000000001
+    - type: recall_at_3
+      value: 34.922
+    - type: recall_at_5
+      value: 43.172
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/arxiv-clustering-p2p
+      name: MTEB ArxivClusteringP2P
+      config: default
+      split: test
+      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
+    metrics:
+    - type: v_measure
+      value: 31.76467048453136
+    - type: v_measures
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+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/arxiv-clustering-s2s
+      name: MTEB ArxivClusteringS2S
+      config: default
+      split: test
+      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
+    metrics:
+    - type: v_measure
+      value: 21.06388933035354
+    - type: v_measures
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+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/askubuntudupquestions-reranking
+      name: MTEB AskUbuntuDupQuestions
+      config: default
+      split: test
+      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
+    metrics:
+    - type: map
+      value: 53.770982215325056
+    - type: mrr
+      value: 68.00400123114805
+  - task:
+      type: STS
+    dataset:
+      type: mteb/biosses-sts
+      name: MTEB BIOSSES
+      config: default
+      split: test
+      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
+    metrics:
+    - type: cos_sim_pearson
+      value: 77.20301104745533
+    - type: cos_sim_spearman
+      value: 77.59453912854975
+    - type: euclidean_pearson
+      value: 74.21678798189272
+    - type: euclidean_spearman
+      value: 74.9956847311664
+    - type: manhattan_pearson
+      value: 74.55059214013183
+    - type: manhattan_spearman
+      value: 75.51557609531613
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/banking77
+      name: MTEB Banking77Classification
+      config: default
+      split: test
+      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
+    metrics:
+    - type: accuracy
+      value: 77.9512987012987
+    - type: f1
+      value: 77.89256430400536
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/biorxiv-clustering-p2p
+      name: MTEB BiorxivClusteringP2P
+      config: default
+      split: test
+      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
+    metrics:
+    - type: v_measure
+      value: 29.83922611010262
+    - type: v_measures
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+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/biorxiv-clustering-s2s
+      name: MTEB BiorxivClusteringS2S
+      config: default
+      split: test
+      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
+    metrics:
+    - type: v_measure
+      value: 18.34253917925029
+    - type: v_measures
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+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/cqadupstack-android
+      name: MTEB CQADupstackAndroidRetrieval
+      config: default
+      split: test
+      revision: f46a197baaae43b4f621051089b82a364682dfeb
+    metrics:
+    - type: map_at_1
+      value: 19.709
+    - type: map_at_10
+      value: 26.522000000000002
+    - type: map_at_100
+      value: 27.613
+    - type: map_at_1000
+      value: 27.750999999999998
+    - type: map_at_20
+      value: 27.033
+    - type: map_at_3
+      value: 24.127000000000002
+    - type: map_at_5
+      value: 25.319000000000003
+    - type: mrr_at_1
+      value: 24.607
+    - type: mrr_at_10
+      value: 31.776
+    - type: mrr_at_100
+      value: 32.629999999999995
+    - type: mrr_at_1000
+      value: 32.699
+    - type: mrr_at_20
+      value: 32.23
+    - type: mrr_at_3
+      value: 29.423
+    - type: mrr_at_5
+      value: 30.703000000000003
+    - type: ndcg_at_1
+      value: 24.607
+    - type: ndcg_at_10
+      value: 31.311
+    - type: ndcg_at_100
+      value: 36.412
+    - type: ndcg_at_1000
+      value: 39.428999999999995
+    - type: ndcg_at_20
+      value: 32.793
+    - type: ndcg_at_3
+      value: 27.388
+    - type: ndcg_at_5
+      value: 28.899
+    - type: precision_at_1
+      value: 24.607
+    - type: precision_at_10
+      value: 5.951
+    - type: precision_at_100
+      value: 1.083
+    - type: precision_at_1000
+      value: 0.165
+    - type: precision_at_20
+      value: 3.5479999999999996
+    - type: precision_at_3
+      value: 12.971
+    - type: precision_at_5
+      value: 9.356
+    - type: recall_at_1
+      value: 19.709
+    - type: recall_at_10
+      value: 40.274
+    - type: recall_at_100
+      value: 62.926
+    - type: recall_at_1000
+      value: 83.54599999999999
+    - type: recall_at_20
+      value: 45.585
+    - type: recall_at_3
+      value: 28.587
+    - type: recall_at_5
+      value: 32.967999999999996
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/cqadupstack-english
+      name: MTEB CQADupstackEnglishRetrieval
+      config: default
+      split: test
+      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
+    metrics:
+    - type: map_at_1
+      value: 11.749
+    - type: map_at_10
+      value: 15.958
+    - type: map_at_100
+      value: 16.694
+    - type: map_at_1000
+      value: 16.805
+    - type: map_at_20
+      value: 16.325
+    - type: map_at_3
+      value: 14.469000000000001
+    - type: map_at_5
+      value: 15.286
+    - type: mrr_at_1
+      value: 14.521999999999998
+    - type: mrr_at_10
+      value: 19.076999999999998
+    - type: mrr_at_100
+      value: 19.785
+    - type: mrr_at_1000
+      value: 19.863
+    - type: mrr_at_20
+      value: 19.451999999999998
+    - type: mrr_at_3
+      value: 17.419999999999998
+    - type: mrr_at_5
+      value: 18.379
+    - type: ndcg_at_1
+      value: 14.521999999999998
+    - type: ndcg_at_10
+      value: 18.944
+    - type: ndcg_at_100
+      value: 22.685
+    - type: ndcg_at_1000
+      value: 25.562
+    - type: ndcg_at_20
+      value: 20.169999999999998
+    - type: ndcg_at_3
+      value: 16.18
+    - type: ndcg_at_5
+      value: 17.476
+    - type: precision_at_1
+      value: 14.521999999999998
+    - type: precision_at_10
+      value: 3.5409999999999995
+    - type: precision_at_100
+      value: 0.679
+    - type: precision_at_1000
+      value: 0.11399999999999999
+    - type: precision_at_20
+      value: 2.185
+    - type: precision_at_3
+      value: 7.495
+    - type: precision_at_5
+      value: 5.541
+    - type: recall_at_1
+      value: 11.749
+    - type: recall_at_10
+      value: 24.759999999999998
+    - type: recall_at_100
+      value: 41.54
+    - type: recall_at_1000
+      value: 61.836
+    - type: recall_at_20
+      value: 29.252
+    - type: recall_at_3
+      value: 17.278
+    - type: recall_at_5
+      value: 20.57
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/cqadupstack-gaming
+      name: MTEB CQADupstackGamingRetrieval
+      config: default
+      split: test
+      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
+    metrics:
+    - type: map_at_1
+      value: 19.827
+    - type: map_at_10
+      value: 27.417
+    - type: map_at_100
+      value: 28.383000000000003
+    - type: map_at_1000
+      value: 28.483000000000004
+    - type: map_at_20
+      value: 27.901999999999997
+    - type: map_at_3
+      value: 25.3
+    - type: map_at_5
+      value: 26.432
+    - type: mrr_at_1
+      value: 22.947
+    - type: mrr_at_10
+      value: 30.279
+    - type: mrr_at_100
+      value: 31.1
+    - type: mrr_at_1000
+      value: 31.171
+    - type: mrr_at_20
+      value: 30.714000000000002
+    - type: mrr_at_3
+      value: 28.37
+    - type: mrr_at_5
+      value: 29.37
+    - type: ndcg_at_1
+      value: 22.947
+    - type: ndcg_at_10
+      value: 31.793
+    - type: ndcg_at_100
+      value: 36.571999999999996
+    - type: ndcg_at_1000
+      value: 39.106
+    - type: ndcg_at_20
+      value: 33.376
+    - type: ndcg_at_3
+      value: 27.872000000000003
+    - type: ndcg_at_5
+      value: 29.601
+    - type: precision_at_1
+      value: 22.947
+    - type: precision_at_10
+      value: 5.3420000000000005
+    - type: precision_at_100
+      value: 0.856
+    - type: precision_at_1000
+      value: 0.116
+    - type: precision_at_20
+      value: 3.107
+    - type: precision_at_3
+      value: 12.684999999999999
+    - type: precision_at_5
+      value: 8.790000000000001
+    - type: recall_at_1
+      value: 19.827
+    - type: recall_at_10
+      value: 42.191
+    - type: recall_at_100
+      value: 64.307
+    - type: recall_at_1000
+      value: 83.161
+    - type: recall_at_20
+      value: 48.046
+    - type: recall_at_3
+      value: 31.352999999999998
+    - type: recall_at_5
+      value: 35.783
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/cqadupstack-gis
+      name: MTEB CQADupstackGisRetrieval
+      config: default
+      split: test
+      revision: 5003b3064772da1887988e05400cf3806fe491f2
+    metrics:
+    - type: map_at_1
+      value: 11.802
+    - type: map_at_10
+      value: 15.799
+    - type: map_at_100
+      value: 16.53
+    - type: map_at_1000
+      value: 16.638
+    - type: map_at_20
+      value: 16.161
+    - type: map_at_3
+      value: 14.495
+    - type: map_at_5
+      value: 15.128
+    - type: mrr_at_1
+      value: 12.655
+    - type: mrr_at_10
+      value: 17.03
+    - type: mrr_at_100
+      value: 17.785999999999998
+    - type: mrr_at_1000
+      value: 17.88
+    - type: mrr_at_20
+      value: 17.416
+    - type: mrr_at_3
+      value: 15.65
+    - type: mrr_at_5
+      value: 16.305
+    - type: ndcg_at_1
+      value: 12.655
+    - type: ndcg_at_10
+      value: 18.411
+    - type: ndcg_at_100
+      value: 22.547
+    - type: ndcg_at_1000
+      value: 25.685999999999996
+    - type: ndcg_at_20
+      value: 19.732
+    - type: ndcg_at_3
+      value: 15.713
+    - type: ndcg_at_5
+      value: 16.821
+    - type: precision_at_1
+      value: 12.655
+    - type: precision_at_10
+      value: 2.904
+    - type: precision_at_100
+      value: 0.525
+    - type: precision_at_1000
+      value: 0.083
+    - type: precision_at_20
+      value: 1.7399999999999998
+    - type: precision_at_3
+      value: 6.6290000000000004
+    - type: precision_at_5
+      value: 4.655
+    - type: recall_at_1
+      value: 11.802
+    - type: recall_at_10
+      value: 25.373
+    - type: recall_at_100
+      value: 45.462
+    - type: recall_at_1000
+      value: 69.98299999999999
+    - type: recall_at_20
+      value: 30.455
+    - type: recall_at_3
+      value: 17.941
+    - type: recall_at_5
+      value: 20.61
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/cqadupstack-mathematica
+      name: MTEB CQADupstackMathematicaRetrieval
+      config: default
+      split: test
+      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
+    metrics:
+    - type: map_at_1
+      value: 6.6739999999999995
+    - type: map_at_10
+      value: 10.181
+    - type: map_at_100
+      value: 11.138
+    - type: map_at_1000
+      value: 11.258
+    - type: map_at_20
+      value: 10.673
+    - type: map_at_3
+      value: 8.997
+    - type: map_at_5
+      value: 9.587
+    - type: mrr_at_1
+      value: 8.209
+    - type: mrr_at_10
+      value: 12.356
+    - type: mrr_at_100
+      value: 13.370000000000001
+    - type: mrr_at_1000
+      value: 13.466000000000001
+    - type: mrr_at_20
+      value: 12.889000000000001
+    - type: mrr_at_3
+      value: 10.821
+    - type: mrr_at_5
+      value: 11.604000000000001
+    - type: ndcg_at_1
+      value: 8.209
+    - type: ndcg_at_10
+      value: 12.849
+    - type: ndcg_at_100
+      value: 17.916
+    - type: ndcg_at_1000
+      value: 21.192
+    - type: ndcg_at_20
+      value: 14.643
+    - type: ndcg_at_3
+      value: 10.299
+    - type: ndcg_at_5
+      value: 11.350999999999999
+    - type: precision_at_1
+      value: 8.209
+    - type: precision_at_10
+      value: 2.5
+    - type: precision_at_100
+      value: 0.577
+    - type: precision_at_1000
+      value: 0.099
+    - type: precision_at_20
+      value: 1.667
+    - type: precision_at_3
+      value: 5.017
+    - type: precision_at_5
+      value: 3.7560000000000002
+    - type: recall_at_1
+      value: 6.6739999999999995
+    - type: recall_at_10
+      value: 19.016
+    - type: recall_at_100
+      value: 41.806
+    - type: recall_at_1000
+      value: 65.605
+    - type: recall_at_20
+      value: 25.764
+    - type: recall_at_3
+      value: 12.030000000000001
+    - type: recall_at_5
+      value: 14.568
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/cqadupstack-physics
+      name: MTEB CQADupstackPhysicsRetrieval
+      config: default
+      split: test
+      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
+    metrics:
+    - type: map_at_1
+      value: 12.133
+    - type: map_at_10
+      value: 17.32
+    - type: map_at_100
+      value: 18.294
+    - type: map_at_1000
+      value: 18.404
+    - type: map_at_20
+      value: 17.804000000000002
+    - type: map_at_3
+      value: 15.626000000000001
+    - type: map_at_5
+      value: 16.572
+    - type: mrr_at_1
+      value: 15.399
+    - type: mrr_at_10
+      value: 21.054000000000002
+    - type: mrr_at_100
+      value: 21.951999999999998
+    - type: mrr_at_1000
+      value: 22.03
+    - type: mrr_at_20
+      value: 21.522
+    - type: mrr_at_3
+      value: 19.297
+    - type: mrr_at_5
+      value: 20.294
+    - type: ndcg_at_1
+      value: 15.399
+    - type: ndcg_at_10
+      value: 21.02
+    - type: ndcg_at_100
+      value: 25.978
+    - type: ndcg_at_1000
+      value: 28.803
+    - type: ndcg_at_20
+      value: 22.642
+    - type: ndcg_at_3
+      value: 17.864
+    - type: ndcg_at_5
+      value: 19.335
+    - type: precision_at_1
+      value: 15.399
+    - type: precision_at_10
+      value: 3.9079999999999995
+    - type: precision_at_100
+      value: 0.781
+    - type: precision_at_1000
+      value: 0.12
+    - type: precision_at_20
+      value: 2.493
+    - type: precision_at_3
+      value: 8.502
+    - type: precision_at_5
+      value: 6.16
+    - type: recall_at_1
+      value: 12.133
+    - type: recall_at_10
+      value: 28.753
+    - type: recall_at_100
+      value: 50.806
+    - type: recall_at_1000
+      value: 70.75399999999999
+    - type: recall_at_20
+      value: 34.485
+    - type: recall_at_3
+      value: 19.664
+    - type: recall_at_5
+      value: 23.566000000000003
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/cqadupstack-programmers
+      name: MTEB CQADupstackProgrammersRetrieval
+      config: default
+      split: test
+      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
+    metrics:
+    - type: map_at_1
+      value: 9.555
+    - type: map_at_10
+      value: 13.553
+    - type: map_at_100
+      value: 14.438
+    - type: map_at_1000
+      value: 14.562
+    - type: map_at_20
+      value: 13.977999999999998
+    - type: map_at_3
+      value: 12.118
+    - type: map_at_5
+      value: 12.811
+    - type: mrr_at_1
+      value: 11.872
+    - type: mrr_at_10
+      value: 16.613
+    - type: mrr_at_100
+      value: 17.512
+    - type: mrr_at_1000
+      value: 17.607
+    - type: mrr_at_20
+      value: 17.108
+    - type: mrr_at_3
+      value: 15.068000000000001
+    - type: mrr_at_5
+      value: 15.839
+    - type: ndcg_at_1
+      value: 11.872
+    - type: ndcg_at_10
+      value: 16.556
+    - type: ndcg_at_100
+      value: 21.34
+    - type: ndcg_at_1000
+      value: 24.903
+    - type: ndcg_at_20
+      value: 18.102
+    - type: ndcg_at_3
+      value: 13.844000000000001
+    - type: ndcg_at_5
+      value: 14.893999999999998
+    - type: precision_at_1
+      value: 11.872
+    - type: precision_at_10
+      value: 3.082
+    - type: precision_at_100
+      value: 0.658
+    - type: precision_at_1000
+      value: 0.11299999999999999
+    - type: precision_at_20
+      value: 1.992
+    - type: precision_at_3
+      value: 6.544999999999999
+    - type: precision_at_5
+      value: 4.68
+    - type: recall_at_1
+      value: 9.555
+    - type: recall_at_10
+      value: 22.931
+    - type: recall_at_100
+      value: 44.535000000000004
+    - type: recall_at_1000
+      value: 70.77799999999999
+    - type: recall_at_20
+      value: 28.403
+    - type: recall_at_3
+      value: 15.201
+    - type: recall_at_5
+      value: 18.145
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/cqadupstack
+      name: MTEB CQADupstackRetrieval
+      config: default
+      split: test
+      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
+    metrics:
+    - type: map_at_1
+      value: 11.476083333333333
+    - type: map_at_10
+      value: 16.002499999999998
+    - type: map_at_100
+      value: 16.875083333333333
+    - type: map_at_1000
+      value: 16.991916666666665
+    - type: map_at_20
+      value: 16.445416666666667
+    - type: map_at_3
+      value: 14.473666666666668
+    - type: map_at_5
+      value: 15.269583333333333
+    - type: mrr_at_1
+      value: 13.799083333333334
+    - type: mrr_at_10
+      value: 18.69941666666667
+    - type: mrr_at_100
+      value: 19.54075
+    - type: mrr_at_1000
+      value: 19.62791666666667
+    - type: mrr_at_20
+      value: 19.15166666666667
+    - type: mrr_at_3
+      value: 17.079666666666665
+    - type: mrr_at_5
+      value: 17.93583333333333
+    - type: ndcg_at_1
+      value: 13.799083333333334
+    - type: ndcg_at_10
+      value: 19.157583333333335
+    - type: ndcg_at_100
+      value: 23.675666666666668
+    - type: ndcg_at_1000
+      value: 26.761499999999998
+    - type: ndcg_at_20
+      value: 20.688416666666665
+    - type: ndcg_at_3
+      value: 16.23775
+    - type: ndcg_at_5
+      value: 17.494500000000002
+    - type: precision_at_1
+      value: 13.799083333333334
+    - type: precision_at_10
+      value: 3.449666666666667
+    - type: precision_at_100
+      value: 0.6782499999999999
+    - type: precision_at_1000
+      value: 0.11108333333333333
+    - type: precision_at_20
+      value: 2.1610833333333335
+    - type: precision_at_3
+      value: 7.496333333333332
+    - type: precision_at_5
+      value: 5.4156666666666675
+    - type: recall_at_1
+      value: 11.476083333333333
+    - type: recall_at_10
+      value: 26.132916666666667
+    - type: recall_at_100
+      value: 46.88099999999999
+    - type: recall_at_1000
+      value: 69.47425
+    - type: recall_at_20
+      value: 31.838583333333336
+    - type: recall_at_3
+      value: 17.943749999999998
+    - type: recall_at_5
+      value: 21.176833333333335
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/cqadupstack-stats
+      name: MTEB CQADupstackStatsRetrieval
+      config: default
+      split: test
+      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
+    metrics:
+    - type: map_at_1
+      value: 10.166
+    - type: map_at_10
+      value: 13.980999999999998
+    - type: map_at_100
+      value: 14.728
+    - type: map_at_1000
+      value: 14.812
+    - type: map_at_20
+      value: 14.338000000000001
+    - type: map_at_3
+      value: 12.5
+    - type: map_at_5
+      value: 13.408000000000001
+    - type: mrr_at_1
+      value: 11.503
+    - type: mrr_at_10
+      value: 15.799
+    - type: mrr_at_100
+      value: 16.539
+    - type: mrr_at_1000
+      value: 16.614
+    - type: mrr_at_20
+      value: 16.155
+    - type: mrr_at_3
+      value: 14.213000000000001
+    - type: mrr_at_5
+      value: 15.201999999999998
+    - type: ndcg_at_1
+      value: 11.503
+    - type: ndcg_at_10
+      value: 16.647000000000002
+    - type: ndcg_at_100
+      value: 20.84
+    - type: ndcg_at_1000
+      value: 23.385
+    - type: ndcg_at_20
+      value: 17.93
+    - type: ndcg_at_3
+      value: 13.761999999999999
+    - type: ndcg_at_5
+      value: 15.311
+    - type: precision_at_1
+      value: 11.503
+    - type: precision_at_10
+      value: 2.7449999999999997
+    - type: precision_at_100
+      value: 0.541
+    - type: precision_at_1000
+      value: 0.082
+    - type: precision_at_20
+      value: 1.6789999999999998
+    - type: precision_at_3
+      value: 6.033
+    - type: precision_at_5
+      value: 4.5089999999999995
+    - type: recall_at_1
+      value: 10.166
+    - type: recall_at_10
+      value: 23.284
+    - type: recall_at_100
+      value: 43.224000000000004
+    - type: recall_at_1000
+      value: 62.856
+    - type: recall_at_20
+      value: 28.166000000000004
+    - type: recall_at_3
+      value: 15.396
+    - type: recall_at_5
+      value: 19.248
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/cqadupstack-tex
+      name: MTEB CQADupstackTexRetrieval
+      config: default
+      split: test
+      revision: 46989137a86843e03a6195de44b09deda022eec7
+    metrics:
+    - type: map_at_1
+      value: 6.516
+    - type: map_at_10
+      value: 9.185
+    - type: map_at_100
+      value: 9.795
+    - type: map_at_1000
+      value: 9.902
+    - type: map_at_20
+      value: 9.508999999999999
+    - type: map_at_3
+      value: 8.245
+    - type: map_at_5
+      value: 8.724
+    - type: mrr_at_1
+      value: 8.121
+    - type: mrr_at_10
+      value: 11.228
+    - type: mrr_at_100
+      value: 11.885
+    - type: mrr_at_1000
+      value: 11.978
+    - type: mrr_at_20
+      value: 11.583
+    - type: mrr_at_3
+      value: 10.145999999999999
+    - type: mrr_at_5
+      value: 10.688
+    - type: ndcg_at_1
+      value: 8.121
+    - type: ndcg_at_10
+      value: 11.245
+    - type: ndcg_at_100
+      value: 14.524999999999999
+    - type: ndcg_at_1000
+      value: 17.62
+    - type: ndcg_at_20
+      value: 12.385
+    - type: ndcg_at_3
+      value: 9.429
+    - type: ndcg_at_5
+      value: 10.181999999999999
+    - type: precision_at_1
+      value: 8.121
+    - type: precision_at_10
+      value: 2.137
+    - type: precision_at_100
+      value: 0.451
+    - type: precision_at_1000
+      value: 0.08499999999999999
+    - type: precision_at_20
+      value: 1.387
+    - type: precision_at_3
+      value: 4.4510000000000005
+    - type: precision_at_5
+      value: 3.2620000000000005
+    - type: recall_at_1
+      value: 6.516
+    - type: recall_at_10
+      value: 15.456
+    - type: recall_at_100
+      value: 30.709999999999997
+    - type: recall_at_1000
+      value: 53.854
+    - type: recall_at_20
+      value: 19.756
+    - type: recall_at_3
+      value: 10.41
+    - type: recall_at_5
+      value: 12.317
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/cqadupstack-unix
+      name: MTEB CQADupstackUnixRetrieval
+      config: default
+      split: test
+      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
+    metrics:
+    - type: map_at_1
+      value: 10.955
+    - type: map_at_10
+      value: 14.689
+    - type: map_at_100
+      value: 15.482000000000001
+    - type: map_at_1000
+      value: 15.614
+    - type: map_at_20
+      value: 15.085
+    - type: map_at_3
+      value: 13.318
+    - type: map_at_5
+      value: 13.950999999999999
+    - type: mrr_at_1
+      value: 13.34
+    - type: mrr_at_10
+      value: 17.514
+    - type: mrr_at_100
+      value: 18.3
+    - type: mrr_at_1000
+      value: 18.406
+    - type: mrr_at_20
+      value: 17.924
+    - type: mrr_at_3
+      value: 15.920000000000002
+    - type: mrr_at_5
+      value: 16.625
+    - type: ndcg_at_1
+      value: 13.34
+    - type: ndcg_at_10
+      value: 17.574
+    - type: ndcg_at_100
+      value: 21.909
+    - type: ndcg_at_1000
+      value: 25.402
+    - type: ndcg_at_20
+      value: 19.017
+    - type: ndcg_at_3
+      value: 14.75
+    - type: ndcg_at_5
+      value: 15.787999999999998
+    - type: precision_at_1
+      value: 13.34
+    - type: precision_at_10
+      value: 3.041
+    - type: precision_at_100
+      value: 0.599
+    - type: precision_at_1000
+      value: 0.1
+    - type: precision_at_20
+      value: 1.908
+    - type: precision_at_3
+      value: 6.529999999999999
+    - type: precision_at_5
+      value: 4.646
+    - type: recall_at_1
+      value: 10.955
+    - type: recall_at_10
+      value: 23.831
+    - type: recall_at_100
+      value: 43.747
+    - type: recall_at_1000
+      value: 69.327
+    - type: recall_at_20
+      value: 29.17
+    - type: recall_at_3
+      value: 16.165
+    - type: recall_at_5
+      value: 18.701
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/cqadupstack-webmasters
+      name: MTEB CQADupstackWebmastersRetrieval
+      config: default
+      split: test
+      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
+    metrics:
+    - type: map_at_1
+      value: 11.936
+    - type: map_at_10
+      value: 16.878
+    - type: map_at_100
+      value: 17.921
+    - type: map_at_1000
+      value: 18.093
+    - type: map_at_20
+      value: 17.468
+    - type: map_at_3
+      value: 15.21
+    - type: map_at_5
+      value: 16.056
+    - type: mrr_at_1
+      value: 15.02
+    - type: mrr_at_10
+      value: 20.023
+    - type: mrr_at_100
+      value: 20.965
+    - type: mrr_at_1000
+      value: 21.060000000000002
+    - type: mrr_at_20
+      value: 20.576
+    - type: mrr_at_3
+      value: 18.215
+    - type: mrr_at_5
+      value: 19.134
+    - type: ndcg_at_1
+      value: 15.02
+    - type: ndcg_at_10
+      value: 20.459
+    - type: ndcg_at_100
+      value: 25.163999999999998
+    - type: ndcg_at_1000
+      value: 28.811999999999998
+    - type: ndcg_at_20
+      value: 22.387
+    - type: ndcg_at_3
+      value: 17.265
+    - type: ndcg_at_5
+      value: 18.605
+    - type: precision_at_1
+      value: 15.02
+    - type: precision_at_10
+      value: 3.9530000000000003
+    - type: precision_at_100
+      value: 0.8659999999999999
+    - type: precision_at_1000
+      value: 0.173
+    - type: precision_at_20
+      value: 2.619
+    - type: precision_at_3
+      value: 8.169
+    - type: precision_at_5
+      value: 6.047000000000001
+    - type: recall_at_1
+      value: 11.936
+    - type: recall_at_10
+      value: 27.694999999999997
+    - type: recall_at_100
+      value: 49.159000000000006
+    - type: recall_at_1000
+      value: 74.134
+    - type: recall_at_20
+      value: 35.258
+    - type: recall_at_3
+      value: 18.54
+    - type: recall_at_5
+      value: 21.959
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/cqadupstack-wordpress
+      name: MTEB CQADupstackWordpressRetrieval
+      config: default
+      split: test
+      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
+    metrics:
+    - type: map_at_1
+      value: 6.691
+    - type: map_at_10
+      value: 10.546999999999999
+    - type: map_at_100
+      value: 11.485
+    - type: map_at_1000
+      value: 11.581
+    - type: map_at_20
+      value: 11.068999999999999
+    - type: map_at_3
+      value: 9.279
+    - type: map_at_5
+      value: 9.961
+    - type: mrr_at_1
+      value: 7.394
+    - type: mrr_at_10
+      value: 11.644
+    - type: mrr_at_100
+      value: 12.665000000000001
+    - type: mrr_at_1000
+      value: 12.761
+    - type: mrr_at_20
+      value: 12.251
+    - type: mrr_at_3
+      value: 10.413
+    - type: mrr_at_5
+      value: 11.087
+    - type: ndcg_at_1
+      value: 7.394
+    - type: ndcg_at_10
+      value: 13.081999999999999
+    - type: ndcg_at_100
+      value: 18.22
+    - type: ndcg_at_1000
+      value: 21.238
+    - type: ndcg_at_20
+      value: 15.084
+    - type: ndcg_at_3
+      value: 10.487
+    - type: ndcg_at_5
+      value: 11.671
+    - type: precision_at_1
+      value: 7.394
+    - type: precision_at_10
+      value: 2.292
+    - type: precision_at_100
+      value: 0.523
+    - type: precision_at_1000
+      value: 0.083
+    - type: precision_at_20
+      value: 1.608
+    - type: precision_at_3
+      value: 4.929
+    - type: precision_at_5
+      value: 3.5860000000000003
+    - type: recall_at_1
+      value: 6.691
+    - type: recall_at_10
+      value: 20.031
+    - type: recall_at_100
+      value: 44.35
+    - type: recall_at_1000
+      value: 67.857
+    - type: recall_at_20
+      value: 27.723
+    - type: recall_at_3
+      value: 12.76
+    - type: recall_at_5
+      value: 15.687000000000001
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/climate-fever
+      name: MTEB ClimateFEVER
+      config: default
+      split: test
+      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
+    metrics:
+    - type: map_at_1
+      value: 3.218
+    - type: map_at_10
+      value: 5.554
+    - type: map_at_100
+      value: 6.216
+    - type: map_at_1000
+      value: 6.338000000000001
+    - type: map_at_20
+      value: 5.907
+    - type: map_at_3
+      value: 4.707
+    - type: map_at_5
+      value: 5.094
+    - type: mrr_at_1
+      value: 6.84
+    - type: mrr_at_10
+      value: 11.296000000000001
+    - type: mrr_at_100
+      value: 12.224
+    - type: mrr_at_1000
+      value: 12.31
+    - type: mrr_at_20
+      value: 11.791
+    - type: mrr_at_3
+      value: 9.609
+    - type: mrr_at_5
+      value: 10.404
+    - type: ndcg_at_1
+      value: 6.84
+    - type: ndcg_at_10
+      value: 8.346
+    - type: ndcg_at_100
+      value: 12.06
+    - type: ndcg_at_1000
+      value: 15.132000000000001
+    - type: ndcg_at_20
+      value: 9.652
+    - type: ndcg_at_3
+      value: 6.489000000000001
+    - type: ndcg_at_5
+      value: 7.045999999999999
+    - type: precision_at_1
+      value: 6.84
+    - type: precision_at_10
+      value: 2.658
+    - type: precision_at_100
+      value: 0.655
+    - type: precision_at_1000
+      value: 0.121
+    - type: precision_at_20
+      value: 1.863
+    - type: precision_at_3
+      value: 4.691
+    - type: precision_at_5
+      value: 3.6479999999999997
+    - type: recall_at_1
+      value: 3.218
+    - type: recall_at_10
+      value: 10.725
+    - type: recall_at_100
+      value: 24.131
+    - type: recall_at_1000
+      value: 42.106
+    - type: recall_at_20
+      value: 14.539
+    - type: recall_at_3
+      value: 6.3020000000000005
+    - type: recall_at_5
+      value: 7.763000000000001
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/dbpedia
+      name: MTEB DBPedia
+      config: default
+      split: test
+      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
+    metrics:
+    - type: map_at_1
+      value: 4.506
+    - type: map_at_10
+      value: 8.535
+    - type: map_at_100
+      value: 11.072
+    - type: map_at_1000
+      value: 11.764
+    - type: map_at_20
+      value: 9.492
+    - type: map_at_3
+      value: 6.697
+    - type: map_at_5
+      value: 7.452
+    - type: mrr_at_1
+      value: 36.75
+    - type: mrr_at_10
+      value: 46.35
+    - type: mrr_at_100
+      value: 47.034
+    - type: mrr_at_1000
+      value: 47.08
+    - type: mrr_at_20
+      value: 46.784
+    - type: mrr_at_3
+      value: 44.0
+    - type: mrr_at_5
+      value: 45.262
+    - type: ndcg_at_1
+      value: 29.25
+    - type: ndcg_at_10
+      value: 21.318
+    - type: ndcg_at_100
+      value: 23.449
+    - type: ndcg_at_1000
+      value: 29.267
+    - type: ndcg_at_20
+      value: 20.735
+    - type: ndcg_at_3
+      value: 24.45
+    - type: ndcg_at_5
+      value: 22.637999999999998
+    - type: precision_at_1
+      value: 36.75
+    - type: precision_at_10
+      value: 16.775000000000002
+    - type: precision_at_100
+      value: 5.212
+    - type: precision_at_1000
+      value: 1.167
+    - type: precision_at_20
+      value: 12.225
+    - type: precision_at_3
+      value: 26.917
+    - type: precision_at_5
+      value: 22.0
+    - type: recall_at_1
+      value: 4.506
+    - type: recall_at_10
+      value: 12.341000000000001
+    - type: recall_at_100
+      value: 26.723000000000003
+    - type: recall_at_1000
+      value: 46.293
+    - type: recall_at_20
+      value: 15.903
+    - type: recall_at_3
+      value: 7.994999999999999
+    - type: recall_at_5
+      value: 9.407
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/emotion
+      name: MTEB EmotionClassification
+      config: default
+      split: test
+      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
+    metrics:
+    - type: accuracy
+      value: 44.375
+    - type: f1
+      value: 39.487258967288
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/fever
+      name: MTEB FEVER
+      config: default
+      split: test
+      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
+    metrics:
+    - type: map_at_1
+      value: 16.572
+    - type: map_at_10
+      value: 22.349
+    - type: map_at_100
+      value: 23.145
+    - type: map_at_1000
+      value: 23.22
+    - type: map_at_20
+      value: 22.771
+    - type: map_at_3
+      value: 20.326
+    - type: map_at_5
+      value: 21.404
+    - type: mrr_at_1
+      value: 17.657
+    - type: mrr_at_10
+      value: 23.679
+    - type: mrr_at_100
+      value: 24.504
+    - type: mrr_at_1000
+      value: 24.576999999999998
+    - type: mrr_at_20
+      value: 24.122
+    - type: mrr_at_3
+      value: 21.557000000000002
+    - type: mrr_at_5
+      value: 22.695
+    - type: ndcg_at_1
+      value: 17.657
+    - type: ndcg_at_10
+      value: 26.081
+    - type: ndcg_at_100
+      value: 30.366
+    - type: ndcg_at_1000
+      value: 32.607
+    - type: ndcg_at_20
+      value: 27.608
+    - type: ndcg_at_3
+      value: 21.85
+    - type: ndcg_at_5
+      value: 23.796999999999997
+    - type: precision_at_1
+      value: 17.657
+    - type: precision_at_10
+      value: 3.968
+    - type: precision_at_100
+      value: 0.626
+    - type: precision_at_1000
+      value: 0.083
+    - type: precision_at_20
+      value: 2.3120000000000003
+    - type: precision_at_3
+      value: 8.951
+    - type: precision_at_5
+      value: 6.4
+    - type: recall_at_1
+      value: 16.572
+    - type: recall_at_10
+      value: 36.634
+    - type: recall_at_100
+      value: 57.135000000000005
+    - type: recall_at_1000
+      value: 74.832
+    - type: recall_at_20
+      value: 42.491
+    - type: recall_at_3
+      value: 25.087
+    - type: recall_at_5
+      value: 29.744999999999997
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/fiqa
+      name: MTEB FiQA2018
+      config: default
+      split: test
+      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
+    metrics:
+    - type: map_at_1
+      value: 4.891
+    - type: map_at_10
+      value: 8.346
+    - type: map_at_100
+      value: 9.286
+    - type: map_at_1000
+      value: 9.465
+    - type: map_at_20
+      value: 8.826
+    - type: map_at_3
+      value: 7.13
+    - type: map_at_5
+      value: 7.643999999999999
+    - type: mrr_at_1
+      value: 10.030999999999999
+    - type: mrr_at_10
+      value: 14.899000000000001
+    - type: mrr_at_100
+      value: 15.82
+    - type: mrr_at_1000
+      value: 15.931000000000001
+    - type: mrr_at_20
+      value: 15.408
+    - type: mrr_at_3
+      value: 13.169
+    - type: mrr_at_5
+      value: 13.971
+    - type: ndcg_at_1
+      value: 10.030999999999999
+    - type: ndcg_at_10
+      value: 11.713
+    - type: ndcg_at_100
+      value: 16.436999999999998
+    - type: ndcg_at_1000
+      value: 20.971999999999998
+    - type: ndcg_at_20
+      value: 13.341
+    - type: ndcg_at_3
+      value: 9.879999999999999
+    - type: ndcg_at_5
+      value: 10.249
+    - type: precision_at_1
+      value: 10.030999999999999
+    - type: precision_at_10
+      value: 3.519
+    - type: precision_at_100
+      value: 0.8330000000000001
+    - type: precision_at_1000
+      value: 0.16
+    - type: precision_at_20
+      value: 2.377
+    - type: precision_at_3
+      value: 6.687
+    - type: precision_at_5
+      value: 5.0
+    - type: recall_at_1
+      value: 4.891
+    - type: recall_at_10
+      value: 15.221000000000002
+    - type: recall_at_100
+      value: 33.432
+    - type: recall_at_1000
+      value: 62.475
+    - type: recall_at_20
+      value: 20.467
+    - type: recall_at_3
+      value: 9.393
+    - type: recall_at_5
+      value: 11.214
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/hotpotqa
+      name: MTEB HotpotQA
+      config: default
+      split: test
+      revision: ab518f4d6fcca38d87c25209f94beba119d02014
+    metrics:
+    - type: map_at_1
+      value: 22.856
+    - type: map_at_10
+      value: 30.656
+    - type: map_at_100
+      value: 31.447000000000003
+    - type: map_at_1000
+      value: 31.545
+    - type: map_at_20
+      value: 31.066
+    - type: map_at_3
+      value: 28.692
+    - type: map_at_5
+      value: 29.817
+    - type: mrr_at_1
+      value: 45.712
+    - type: mrr_at_10
+      value: 52.481
+    - type: mrr_at_100
+      value: 53.049
+    - type: mrr_at_1000
+      value: 53.09
+    - type: mrr_at_20
+      value: 52.803999999999995
+    - type: mrr_at_3
+      value: 50.709
+    - type: mrr_at_5
+      value: 51.795
+    - type: ndcg_at_1
+      value: 45.712
+    - type: ndcg_at_10
+      value: 38.381
+    - type: ndcg_at_100
+      value: 41.965
+    - type: ndcg_at_1000
+      value: 44.234
+    - type: ndcg_at_20
+      value: 39.657
+    - type: ndcg_at_3
+      value: 34.776
+    - type: ndcg_at_5
+      value: 36.622
+    - type: precision_at_1
+      value: 45.712
+    - type: precision_at_10
+      value: 8.062999999999999
+    - type: precision_at_100
+      value: 1.094
+    - type: precision_at_1000
+      value: 0.13999999999999999
+    - type: precision_at_20
+      value: 4.443
+    - type: precision_at_3
+      value: 21.476
+    - type: precision_at_5
+      value: 14.35
+    - type: recall_at_1
+      value: 22.856
+    - type: recall_at_10
+      value: 40.317
+    - type: recall_at_100
+      value: 54.705999999999996
+    - type: recall_at_1000
+      value: 69.892
+    - type: recall_at_20
+      value: 44.429
+    - type: recall_at_3
+      value: 32.214999999999996
+    - type: recall_at_5
+      value: 35.874
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/imdb
+      name: MTEB ImdbClassification
+      config: default
+      split: test
+      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
+    metrics:
+    - type: accuracy
+      value: 73.02000000000001
+    - type: ap
+      value: 67.25944041954726
+    - type: f1
+      value: 72.8697134997555
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/msmarco
+      name: MTEB MSMARCO
+      config: default
+      split: dev
+      revision: c5a29a104738b98a9e76336939199e264163d4a0
+    metrics:
+    - type: map_at_1
+      value: 8.751000000000001
+    - type: map_at_10
+      value: 13.916999999999998
+    - type: map_at_100
+      value: 14.684
+    - type: map_at_1000
+      value: 14.766000000000002
+    - type: map_at_20
+      value: 14.338999999999999
+    - type: map_at_3
+      value: 12.197
+    - type: map_at_5
+      value: 13.163
+    - type: mrr_at_1
+      value: 8.911
+    - type: mrr_at_10
+      value: 14.198
+    - type: mrr_at_100
+      value: 14.960999999999999
+    - type: mrr_at_1000
+      value: 15.040000000000001
+    - type: mrr_at_20
+      value: 14.616999999999999
+    - type: mrr_at_3
+      value: 12.452
+    - type: mrr_at_5
+      value: 13.427
+    - type: ndcg_at_1
+      value: 8.911
+    - type: ndcg_at_10
+      value: 16.963
+    - type: ndcg_at_100
+      value: 21.062
+    - type: ndcg_at_1000
+      value: 23.543
+    - type: ndcg_at_20
+      value: 18.482000000000003
+    - type: ndcg_at_3
+      value: 13.391
+    - type: ndcg_at_5
+      value: 15.139
+    - type: precision_at_1
+      value: 8.911
+    - type: precision_at_10
+      value: 2.741
+    - type: precision_at_100
+      value: 0.485
+    - type: precision_at_1000
+      value: 0.06999999999999999
+    - type: precision_at_20
+      value: 1.683
+    - type: precision_at_3
+      value: 5.688
+    - type: precision_at_5
+      value: 4.3069999999999995
+    - type: recall_at_1
+      value: 8.751000000000001
+    - type: recall_at_10
+      value: 26.368000000000002
+    - type: recall_at_100
+      value: 46.22
+    - type: recall_at_1000
+      value: 66.22
+    - type: recall_at_20
+      value: 32.291
+    - type: recall_at_3
+      value: 16.595
+    - type: recall_at_5
+      value: 20.802
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_domain
+      name: MTEB MTOPDomainClassification (en)
+      config: en
+      split: test
+      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
+    metrics:
+    - type: accuracy
+      value: 89.87232102143183
+    - type: f1
+      value: 89.25570902684863
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_intent
+      name: MTEB MTOPIntentClassification (en)
+      config: en
+      split: test
+      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
+    metrics:
+    - type: accuracy
+      value: 71.02599179206568
+    - type: f1
+      value: 52.14883678941826
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (en)
+      config: en
+      split: test
+      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
+    metrics:
+    - type: accuracy
+      value: 67.74714189643576
+    - type: f1
+      value: 65.4738868705899
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (en)
+      config: en
+      split: test
+      revision: 7d571f92784cd94a019292a1f45445077d0ef634
+    metrics:
+    - type: accuracy
+      value: 72.36381977135171
+    - type: f1
+      value: 71.5956356866047
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/medrxiv-clustering-p2p
+      name: MTEB MedrxivClusteringP2P
+      config: default
+      split: test
+      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
+    metrics:
+    - type: v_measure
+      value: 27.418721421866266
+    - type: v_measures
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+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/medrxiv-clustering-s2s
+      name: MTEB MedrxivClusteringS2S
+      config: default
+      split: test
+      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
+    metrics:
+    - type: v_measure
+      value: 22.40590099674712
+    - type: v_measures
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+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/mind_small
+      name: MTEB MindSmallReranking
+      config: default
+      split: test
+      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
+    metrics:
+    - type: map
+      value: 29.924796610724826
+    - type: mrr
+      value: 30.962158101843464
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/nfcorpus
+      name: MTEB NFCorpus
+      config: default
+      split: test
+      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
+    metrics:
+    - type: map_at_1
+      value: 1.3379999999999999
+    - type: map_at_10
+      value: 3.62
+    - type: map_at_100
+      value: 4.891
+    - type: map_at_1000
+      value: 5.87
+    - type: map_at_20
+      value: 4.164000000000001
+    - type: map_at_3
+      value: 2.608
+    - type: map_at_5
+      value: 3.1910000000000003
+    - type: mrr_at_1
+      value: 18.576
+    - type: mrr_at_10
+      value: 26.487
+    - type: mrr_at_100
+      value: 27.736
+    - type: mrr_at_1000
+      value: 27.828000000000003
+    - type: mrr_at_20
+      value: 27.319
+    - type: mrr_at_3
+      value: 23.891000000000002
+    - type: mrr_at_5
+      value: 25.501
+    - type: ndcg_at_1
+      value: 17.957
+    - type: ndcg_at_10
+      value: 14.021
+    - type: ndcg_at_100
+      value: 14.41
+    - type: ndcg_at_1000
+      value: 24.197
+    - type: ndcg_at_20
+      value: 13.883000000000001
+    - type: ndcg_at_3
+      value: 15.913
+    - type: ndcg_at_5
+      value: 15.120000000000001
+    - type: precision_at_1
+      value: 18.576
+    - type: precision_at_10
+      value: 10.402000000000001
+    - type: precision_at_100
+      value: 4.334
+    - type: precision_at_1000
+      value: 1.661
+    - type: precision_at_20
+      value: 8.731
+    - type: precision_at_3
+      value: 15.067
+    - type: precision_at_5
+      value: 12.940999999999999
+    - type: recall_at_1
+      value: 1.3379999999999999
+    - type: recall_at_10
+      value: 6.711
+    - type: recall_at_100
+      value: 16.862
+    - type: recall_at_1000
+      value: 52.537
+    - type: recall_at_20
+      value: 9.89
+    - type: recall_at_3
+      value: 3.614
+    - type: recall_at_5
+      value: 5.428999999999999
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/nq
+      name: MTEB NQ
+      config: default
+      split: test
+      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
+    metrics:
+    - type: map_at_1
+      value: 10.187
+    - type: map_at_10
+      value: 16.61
+    - type: map_at_100
+      value: 17.599
+    - type: map_at_1000
+      value: 17.689
+    - type: map_at_20
+      value: 17.141000000000002
+    - type: map_at_3
+      value: 14.405000000000001
+    - type: map_at_5
+      value: 15.543000000000001
+    - type: mrr_at_1
+      value: 11.327
+    - type: mrr_at_10
+      value: 18.184
+    - type: mrr_at_100
+      value: 19.137
+    - type: mrr_at_1000
+      value: 19.215
+    - type: mrr_at_20
+      value: 18.717
+    - type: mrr_at_3
+      value: 15.918
+    - type: mrr_at_5
+      value: 17.052
+    - type: ndcg_at_1
+      value: 11.327
+    - type: ndcg_at_10
+      value: 20.744
+    - type: ndcg_at_100
+      value: 25.865
+    - type: ndcg_at_1000
+      value: 28.419
+    - type: ndcg_at_20
+      value: 22.648
+    - type: ndcg_at_3
+      value: 16.147
+    - type: ndcg_at_5
+      value: 18.168
+    - type: precision_at_1
+      value: 11.327
+    - type: precision_at_10
+      value: 3.7220000000000004
+    - type: precision_at_100
+      value: 0.658
+    - type: precision_at_1000
+      value: 0.091
+    - type: precision_at_20
+      value: 2.294
+    - type: precision_at_3
+      value: 7.503
+    - type: precision_at_5
+      value: 5.608
+    - type: recall_at_1
+      value: 10.187
+    - type: recall_at_10
+      value: 32.051
+    - type: recall_at_100
+      value: 56.016
+    - type: recall_at_1000
+      value: 75.649
+    - type: recall_at_20
+      value: 39.267
+    - type: recall_at_3
+      value: 19.689
+    - type: recall_at_5
+      value: 24.445
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/quora
+      name: MTEB QuoraRetrieval
+      config: default
+      split: test
+      revision: e4e08e0b7dbe3c8700f0daef558ff32256715259
+    metrics:
+    - type: map_at_1
+      value: 58.404
+    - type: map_at_10
+      value: 70.125
+    - type: map_at_100
+      value: 70.923
+    - type: map_at_1000
+      value: 70.968
+    - type: map_at_20
+      value: 70.60300000000001
+    - type: map_at_3
+      value: 67.342
+    - type: map_at_5
+      value: 68.97999999999999
+    - type: mrr_at_1
+      value: 67.29
+    - type: mrr_at_10
+      value: 74.773
+    - type: mrr_at_100
+      value: 75.093
+    - type: mrr_at_1000
+      value: 75.106
+    - type: mrr_at_20
+      value: 74.973
+    - type: mrr_at_3
+      value: 73.188
+    - type: mrr_at_5
+      value: 74.165
+    - type: ndcg_at_1
+      value: 67.33
+    - type: ndcg_at_10
+      value: 74.936
+    - type: ndcg_at_100
+      value: 77.479
+    - type: ndcg_at_1000
+      value: 78.147
+    - type: ndcg_at_20
+      value: 76.048
+    - type: ndcg_at_3
+      value: 71.30499999999999
+    - type: ndcg_at_5
+      value: 73.09400000000001
+    - type: precision_at_1
+      value: 67.33
+    - type: precision_at_10
+      value: 11.335
+    - type: precision_at_100
+      value: 1.385
+    - type: precision_at_1000
+      value: 0.151
+    - type: precision_at_20
+      value: 6.116
+    - type: precision_at_3
+      value: 30.833
+    - type: precision_at_5
+      value: 20.384
+    - type: recall_at_1
+      value: 58.404
+    - type: recall_at_10
+      value: 84.138
+    - type: recall_at_100
+      value: 94.32000000000001
+    - type: recall_at_1000
+      value: 98.51299999999999
+    - type: recall_at_20
+      value: 87.996
+    - type: recall_at_3
+      value: 73.68400000000001
+    - type: recall_at_5
+      value: 78.681
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/reddit-clustering
+      name: MTEB RedditClustering
+      config: default
+      split: test
+      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
+    metrics:
+    - type: v_measure
+      value: 26.713463922652704
+    - type: v_measures
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+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/reddit-clustering-p2p
+      name: MTEB RedditClusteringP2P
+      config: default
+      split: test
+      revision: 385e3cb46b4cfa89021f56c4380204149d0efe33
+    metrics:
+    - type: v_measure
+      value: 44.135854520709856
+    - type: v_measures
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+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/scidocs
+      name: MTEB SCIDOCS
+      config: default
+      split: test
+      revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88
+    metrics:
+    - type: map_at_1
+      value: 2.1350000000000002
+    - type: map_at_10
+      value: 5.118
+    - type: map_at_100
+      value: 6.08
+    - type: map_at_1000
+      value: 6.308
+    - type: map_at_20
+      value: 5.562
+    - type: map_at_3
+      value: 3.804
+    - type: map_at_5
+      value: 4.468
+    - type: mrr_at_1
+      value: 10.5
+    - type: mrr_at_10
+      value: 17.278
+    - type: mrr_at_100
+      value: 18.418
+    - type: mrr_at_1000
+      value: 18.526
+    - type: mrr_at_20
+      value: 17.876
+    - type: mrr_at_3
+      value: 14.832999999999998
+    - type: mrr_at_5
+      value: 16.317999999999998
+    - type: ndcg_at_1
+      value: 10.5
+    - type: ndcg_at_10
+      value: 9.39
+    - type: ndcg_at_100
+      value: 14.362
+    - type: ndcg_at_1000
+      value: 19.524
+    - type: ndcg_at_20
+      value: 10.949
+    - type: ndcg_at_3
+      value: 8.794
+    - type: ndcg_at_5
+      value: 7.789
+    - type: precision_at_1
+      value: 10.5
+    - type: precision_at_10
+      value: 4.91
+    - type: precision_at_100
+      value: 1.221
+    - type: precision_at_1000
+      value: 0.247
+    - type: precision_at_20
+      value: 3.36
+    - type: precision_at_3
+      value: 8.233
+    - type: precision_at_5
+      value: 6.9
+    - type: recall_at_1
+      value: 2.1350000000000002
+    - type: recall_at_10
+      value: 9.955
+    - type: recall_at_100
+      value: 24.778
+    - type: recall_at_1000
+      value: 50.222
+    - type: recall_at_20
+      value: 13.63
+    - type: recall_at_3
+      value: 5.01
+    - type: recall_at_5
+      value: 6.995
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sickr-sts
+      name: MTEB SICK-R
+      config: default
+      split: test
+      revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
+    metrics:
+    - type: cos_sim_pearson
+      value: 78.43659263950201
+    - type: cos_sim_spearman
+      value: 74.68461406509039
+    - type: euclidean_pearson
+      value: 76.31168073146695
+    - type: euclidean_spearman
+      value: 75.13681406263804
+    - type: manhattan_pearson
+      value: 76.2960985430519
+    - type: manhattan_spearman
+      value: 75.03513932091352
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts12-sts
+      name: MTEB STS12
+      config: default
+      split: test
+      revision: a0d554a64d88156834ff5ae9920b964011b16384
+    metrics:
+    - type: cos_sim_pearson
+      value: 55.096195345864295
+    - type: cos_sim_spearman
+      value: 54.34570729554049
+    - type: euclidean_pearson
+      value: 64.79488422312815
+    - type: euclidean_spearman
+      value: 61.19116930098903
+    - type: manhattan_pearson
+      value: 65.04388378143294
+    - type: manhattan_spearman
+      value: 61.33457037020176
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts13-sts
+      name: MTEB STS13
+      config: default
+      split: test
+      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
+    metrics:
+    - type: cos_sim_pearson
+      value: 71.40902040706975
+    - type: cos_sim_spearman
+      value: 74.24315395719762
+    - type: euclidean_pearson
+      value: 75.94675003130055
+    - type: euclidean_spearman
+      value: 76.18445285168187
+    - type: manhattan_pearson
+      value: 75.88786726620313
+    - type: manhattan_spearman
+      value: 76.1188105671321
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts14-sts
+      name: MTEB STS14
+      config: default
+      split: test
+      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
+    metrics:
+    - type: cos_sim_pearson
+      value: 71.9514442512574
+    - type: cos_sim_spearman
+      value: 69.99484176761607
+    - type: euclidean_pearson
+      value: 75.02706002860513
+    - type: euclidean_spearman
+      value: 72.9036480559019
+    - type: manhattan_pearson
+      value: 75.03815961673163
+    - type: manhattan_spearman
+      value: 72.92353672671821
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts15-sts
+      name: MTEB STS15
+      config: default
+      split: test
+      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
+    metrics:
+    - type: cos_sim_pearson
+      value: 72.80522195974591
+    - type: cos_sim_spearman
+      value: 75.73762657362906
+    - type: euclidean_pearson
+      value: 80.1521753666007
+    - type: euclidean_spearman
+      value: 80.25738481137047
+    - type: manhattan_pearson
+      value: 80.19317991797196
+    - type: manhattan_spearman
+      value: 80.31866668763018
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts16-sts
+      name: MTEB STS16
+      config: default
+      split: test
+      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
+    metrics:
+    - type: cos_sim_pearson
+      value: 69.45092072084951
+    - type: cos_sim_spearman
+      value: 73.6472761328024
+    - type: euclidean_pearson
+      value: 74.95031941602217
+    - type: euclidean_spearman
+      value: 75.37029502504294
+    - type: manhattan_pearson
+      value: 74.7846441654404
+    - type: manhattan_spearman
+      value: 75.19664481480419
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts17-crosslingual-sts
+      name: MTEB STS17 (en-en)
+      config: en-en
+      split: test
+      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
+    metrics:
+    - type: cos_sim_pearson
+      value: 82.66021611621103
+    - type: cos_sim_spearman
+      value: 84.81452353756737
+    - type: euclidean_pearson
+      value: 85.32338150846037
+    - type: euclidean_spearman
+      value: 85.46672916577448
+    - type: manhattan_pearson
+      value: 84.86427674633184
+    - type: manhattan_spearman
+      value: 85.098246631915
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (en)
+      config: en
+      split: test
+      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
+    metrics:
+    - type: cos_sim_pearson
+      value: 56.880105002604566
+    - type: cos_sim_spearman
+      value: 62.56487199261157
+    - type: euclidean_pearson
+      value: 57.49369653074593
+    - type: euclidean_spearman
+      value: 61.038143206328854
+    - type: manhattan_pearson
+      value: 57.85496348413732
+    - type: manhattan_spearman
+      value: 61.22736674852764
+  - task:
+      type: STS
+    dataset:
+      type: mteb/stsbenchmark-sts
+      name: MTEB STSBenchmark
+      config: default
+      split: test
+      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
+    metrics:
+    - type: cos_sim_pearson
+      value: 75.41209102908195
+    - type: cos_sim_spearman
+      value: 76.72196352753278
+    - type: euclidean_pearson
+      value: 79.97933288080695
+    - type: euclidean_spearman
+      value: 79.36350387100728
+    - type: manhattan_pearson
+      value: 79.89865614781017
+    - type: manhattan_spearman
+      value: 79.36099141428603
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/scidocs-reranking
+      name: MTEB SciDocsRR
+      config: default
+      split: test
+      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
+    metrics:
+    - type: map
+      value: 70.81824436527221
+    - type: mrr
+      value: 90.04096937920467
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/scifact
+      name: MTEB SciFact
+      config: default
+      split: test
+      revision: 0228b52cf27578f30900b9e5271d331663a030d7
+    metrics:
+    - type: map_at_1
+      value: 33.567
+    - type: map_at_10
+      value: 41.409
+    - type: map_at_100
+      value: 42.281
+    - type: map_at_1000
+      value: 42.358000000000004
+    - type: map_at_20
+      value: 41.916
+    - type: map_at_3
+      value: 38.784
+    - type: map_at_5
+      value: 40.355999999999995
+    - type: mrr_at_1
+      value: 35.667
+    - type: mrr_at_10
+      value: 43.189
+    - type: mrr_at_100
+      value: 43.885000000000005
+    - type: mrr_at_1000
+      value: 43.95
+    - type: mrr_at_20
+      value: 43.584
+    - type: mrr_at_3
+      value: 41.0
+    - type: mrr_at_5
+      value: 42.266999999999996
+    - type: ndcg_at_1
+      value: 35.667
+    - type: ndcg_at_10
+      value: 45.999
+    - type: ndcg_at_100
+      value: 50.153000000000006
+    - type: ndcg_at_1000
+      value: 52.161
+    - type: ndcg_at_20
+      value: 47.662
+    - type: ndcg_at_3
+      value: 41.178
+    - type: ndcg_at_5
+      value: 43.59
+    - type: precision_at_1
+      value: 35.667
+    - type: precision_at_10
+      value: 6.6000000000000005
+    - type: precision_at_100
+      value: 0.89
+    - type: precision_at_1000
+      value: 0.106
+    - type: precision_at_20
+      value: 3.6830000000000003
+    - type: precision_at_3
+      value: 16.556
+    - type: precision_at_5
+      value: 11.466999999999999
+    - type: recall_at_1
+      value: 33.567
+    - type: recall_at_10
+      value: 58.599999999999994
+    - type: recall_at_100
+      value: 77.9
+    - type: recall_at_1000
+      value: 93.667
+    - type: recall_at_20
+      value: 64.878
+    - type: recall_at_3
+      value: 45.483000000000004
+    - type: recall_at_5
+      value: 51.4
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/sprintduplicatequestions-pairclassification
+      name: MTEB SprintDuplicateQuestions
+      config: default
+      split: test
+      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
+    metrics:
+    - type: cos_sim_accuracy
+      value: 99.6930693069307
+    - type: cos_sim_ap
+      value: 89.25594498972691
+    - type: cos_sim_f1
+      value: 83.84499245093104
+    - type: cos_sim_precision
+      value: 84.39716312056737
+    - type: cos_sim_recall
+      value: 83.3
+    - type: dot_accuracy
+      value: 99.48514851485149
+    - type: dot_ap
+      value: 75.92127370670867
+    - type: dot_f1
+      value: 71.16104868913857
+    - type: dot_precision
+      value: 76.52474108170311
+    - type: dot_recall
+      value: 66.5
+    - type: euclidean_accuracy
+      value: 99.6891089108911
+    - type: euclidean_ap
+      value: 89.2180446358921
+    - type: euclidean_f1
+      value: 83.57142857142857
+    - type: euclidean_precision
+      value: 85.3125
+    - type: euclidean_recall
+      value: 81.89999999999999
+    - type: manhattan_accuracy
+      value: 99.6980198019802
+    - type: manhattan_ap
+      value: 89.43047814044381
+    - type: manhattan_f1
+      value: 84.07445708376422
+    - type: manhattan_precision
+      value: 87.04496788008565
+    - type: manhattan_recall
+      value: 81.3
+    - type: max_accuracy
+      value: 99.6980198019802
+    - type: max_ap
+      value: 89.43047814044381
+    - type: max_f1
+      value: 84.07445708376422
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/stackexchange-clustering
+      name: MTEB StackExchangeClustering
+      config: default
+      split: test
+      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
+    metrics:
+    - type: v_measure
+      value: 32.83904946173562
+    - type: v_measures
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+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/stackexchange-clustering-p2p
+      name: MTEB StackExchangeClusteringP2P
+      config: default
+      split: test
+      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
+    metrics:
+    - type: v_measure
+      value: 27.476810145753827
+    - type: v_measures
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+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/stackoverflowdupquestions-reranking
+      name: MTEB StackOverflowDupQuestions
+      config: default
+      split: test
+      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
+    metrics:
+    - type: map
+      value: 43.14055223869571
+    - type: mrr
+      value: 43.506533295136244
+  - task:
+      type: Summarization
+    dataset:
+      type: mteb/summeval
+      name: MTEB SummEval
+      config: default
+      split: test
+      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
+    metrics:
+    - type: cos_sim_pearson
+      value: 30.24218821701958
+    - type: cos_sim_spearman
+      value: 29.907749825179124
+    - type: dot_pearson
+      value: 27.348198725124227
+    - type: dot_spearman
+      value: 25.950835375041038
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/trec-covid
+      name: MTEB TRECCOVID
+      config: default
+      split: test
+      revision: bb9466bac8153a0349341eb1b22e06409e78ef4e
+    metrics:
+    - type: map_at_1
+      value: 0.1
+    - type: map_at_10
+      value: 0.505
+    - type: map_at_100
+      value: 2.207
+    - type: map_at_1000
+      value: 6.0600000000000005
+    - type: map_at_20
+      value: 0.814
+    - type: map_at_3
+      value: 0.218
+    - type: map_at_5
+      value: 0.329
+    - type: mrr_at_1
+      value: 44.0
+    - type: mrr_at_10
+      value: 54.763
+    - type: mrr_at_100
+      value: 55.345
+    - type: mrr_at_1000
+      value: 55.349000000000004
+    - type: mrr_at_20
+      value: 55.035000000000004
+    - type: mrr_at_3
+      value: 51.333
+    - type: mrr_at_5
+      value: 52.632999999999996
+    - type: ndcg_at_1
+      value: 39.0
+    - type: ndcg_at_10
+      value: 30.272
+    - type: ndcg_at_100
+      value: 21.906
+    - type: ndcg_at_1000
+      value: 22.439
+    - type: ndcg_at_20
+      value: 28.316000000000003
+    - type: ndcg_at_3
+      value: 35.235
+    - type: ndcg_at_5
+      value: 33.843
+    - type: precision_at_1
+      value: 44.0
+    - type: precision_at_10
+      value: 32.0
+    - type: precision_at_100
+      value: 22.5
+    - type: precision_at_1000
+      value: 10.9
+    - type: precision_at_20
+      value: 29.7
+    - type: precision_at_3
+      value: 38.0
+    - type: precision_at_5
+      value: 36.0
+    - type: recall_at_1
+      value: 0.1
+    - type: recall_at_10
+      value: 0.719
+    - type: recall_at_100
+      value: 4.7620000000000005
+    - type: recall_at_1000
+      value: 22.285
+    - type: recall_at_20
+      value: 1.277
+    - type: recall_at_3
+      value: 0.244
+    - type: recall_at_5
+      value: 0.40299999999999997
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/touche2020
+      name: MTEB Touche2020
+      config: default
+      split: test
+      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
+    metrics:
+    - type: map_at_1
+      value: 0.865
+    - type: map_at_10
+      value: 2.962
+    - type: map_at_100
+      value: 5.713
+    - type: map_at_1000
+      value: 6.719
+    - type: map_at_20
+      value: 3.939
+    - type: map_at_3
+      value: 1.582
+    - type: map_at_5
+      value: 2.215
+    - type: mrr_at_1
+      value: 14.285999999999998
+    - type: mrr_at_10
+      value: 24.844
+    - type: mrr_at_100
+      value: 26.861
+    - type: mrr_at_1000
+      value: 26.904
+    - type: mrr_at_20
+      value: 26.375999999999998
+    - type: mrr_at_3
+      value: 20.068
+    - type: mrr_at_5
+      value: 22.619
+    - type: ndcg_at_1
+      value: 12.245000000000001
+    - type: ndcg_at_10
+      value: 10.508000000000001
+    - type: ndcg_at_100
+      value: 18.935
+    - type: ndcg_at_1000
+      value: 29.747
+    - type: ndcg_at_20
+      value: 11.701
+    - type: ndcg_at_3
+      value: 10.381
+    - type: ndcg_at_5
+      value: 11.339
+    - type: precision_at_1
+      value: 14.285999999999998
+    - type: precision_at_10
+      value: 10.612
+    - type: precision_at_100
+      value: 4.531000000000001
+    - type: precision_at_1000
+      value: 1.133
+    - type: precision_at_20
+      value: 8.98
+    - type: precision_at_3
+      value: 11.565
+    - type: precision_at_5
+      value: 12.653
+    - type: recall_at_1
+      value: 0.865
+    - type: recall_at_10
+      value: 6.493
+    - type: recall_at_100
+      value: 28.16
+    - type: recall_at_1000
+      value: 61.026
+    - type: recall_at_20
+      value: 11.726
+    - type: recall_at_3
+      value: 2.221
+    - type: recall_at_5
+      value: 3.849
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/toxic_conversations_50k
+      name: MTEB ToxicConversationsClassification
+      config: default
+      split: test
+      revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
+    metrics:
+    - type: accuracy
+      value: 64.4091796875
+    - type: ap
+      value: 11.076947197887051
+    - type: f1
+      value: 49.07978901357373
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/tweet_sentiment_extraction
+      name: MTEB TweetSentimentExtractionClassification
+      config: default
+      split: test
+      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
+    metrics:
+    - type: accuracy
+      value: 59.663271080928126
+    - type: f1
+      value: 59.99492026885337
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/twentynewsgroups-clustering
+      name: MTEB TwentyNewsgroupsClustering
+      config: default
+      split: test
+      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
+    metrics:
+    - type: v_measure
+      value: 26.09282097093625
+    - type: v_measures
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+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/twittersemeval2015-pairclassification
+      name: MTEB TwitterSemEval2015
+      config: default
+      split: test
+      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
+    metrics:
+    - type: cos_sim_accuracy
+      value: 84.88406747332658
+    - type: cos_sim_ap
+      value: 69.26105491403395
+    - type: cos_sim_f1
+      value: 65.52488910793494
+    - type: cos_sim_precision
+      value: 61.465557096625055
+    - type: cos_sim_recall
+      value: 70.15831134564644
+    - type: dot_accuracy
+      value: 82.16606067830959
+    - type: dot_ap
+      value: 61.09102948421686
+    - type: dot_f1
+      value: 57.59054713588492
+    - type: dot_precision
+      value: 56.106106106106104
+    - type: dot_recall
+      value: 59.155672823219
+    - type: euclidean_accuracy
+      value: 84.85426476724086
+    - type: euclidean_ap
+      value: 69.32917418684202
+    - type: euclidean_f1
+      value: 65.59770252482949
+    - type: euclidean_precision
+      value: 60.01751696956427
+    - type: euclidean_recall
+      value: 72.32189973614776
+    - type: manhattan_accuracy
+      value: 84.83638314358943
+    - type: manhattan_ap
+      value: 69.13012845791405
+    - type: manhattan_f1
+      value: 65.35336124107363
+    - type: manhattan_precision
+      value: 61.26500461680517
+    - type: manhattan_recall
+      value: 70.0263852242744
+    - type: max_accuracy
+      value: 84.88406747332658
+    - type: max_ap
+      value: 69.32917418684202
+    - type: max_f1
+      value: 65.59770252482949
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/twitterurlcorpus-pairclassification
+      name: MTEB TwitterURLCorpus
+      config: default
+      split: test
+      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
+    metrics:
+    - type: cos_sim_accuracy
+      value: 87.81387045445726
+    - type: cos_sim_ap
+      value: 83.19376576098023
+    - type: cos_sim_f1
+      value: 75.85641331494391
+    - type: cos_sim_precision
+      value: 73.52409856203484
+    - type: cos_sim_recall
+      value: 78.34154604250077
+    - type: dot_accuracy
+      value: 85.33007334963325
+    - type: dot_ap
+      value: 75.69925817222503
+    - type: dot_f1
+      value: 70.44983722994968
+    - type: dot_precision
+      value: 67.80119624038736
+    - type: dot_recall
+      value: 73.31382814906067
+    - type: euclidean_accuracy
+      value: 87.78864439011139
+    - type: euclidean_ap
+      value: 83.33289584854239
+    - type: euclidean_f1
+      value: 75.70217471433837
+    - type: euclidean_precision
+      value: 72.61349172677131
+    - type: euclidean_recall
+      value: 79.06529103788112
+    - type: manhattan_accuracy
+      value: 87.73819226141964
+    - type: manhattan_ap
+      value: 83.29254385989515
+    - type: manhattan_f1
+      value: 75.70975618644992
+    - type: manhattan_precision
+      value: 71.8773787281157
+    - type: manhattan_recall
+      value: 79.97382198952879
+    - type: max_accuracy
+      value: 87.81387045445726
+    - type: max_ap
+      value: 83.33289584854239
+    - type: max_f1
+      value: 75.85641331494391
+---
+# Venusaur
+
+This is a distill of [Bulbasaur](https://huggingface.co/Mihaiii/Bulbasaur) using [qa-assistant](https://huggingface.co/datasets/Mihaiii/qa-assistant).
+
+## Intended purpose
+
+<span style="color:blue">This model is designed for use in semantic-autocomplete ([click here for demo](https://mihaiii.github.io/semantic-autocomplete/)).</span>
+
+## Usage (Sentence-Transformers) (same as [gte-tiny](https://huggingface.co/TaylorAI/gte-tiny))
+
+Using this model becomes easy when you have [sentence-transformers](https://www.SBERT.net) installed:
+
+```
+pip install -U sentence-transformers
+```
+
+Then you can use the model like this:
+
+```python
+from sentence_transformers import SentenceTransformer
+sentences = ["This is an example sentence", "Each sentence is converted"]
+
+model = SentenceTransformer('Mihaiii/Venusaur')
+embeddings = model.encode(sentences)
+print(embeddings)
+```
+
+
+
+## Usage (HuggingFace Transformers) (same as [gte-tiny](https://huggingface.co/TaylorAI/gte-tiny))
+Without [sentence-transformers](https://www.SBERT.net), you can use the model like this: First, you pass your input through the transformer model, then you have to apply the right pooling-operation on-top of the contextualized word embeddings.
+
+```python
+from transformers import AutoTokenizer, AutoModel
+import torch
+
+
+#Mean Pooling - Take attention mask into account for correct averaging
+def mean_pooling(model_output, attention_mask):
+    token_embeddings = model_output[0] #First element of model_output contains all token embeddings
+    input_mask_expanded = attention_mask.unsqueeze(-1).expand(token_embeddings.size()).float()
+    return torch.sum(token_embeddings * input_mask_expanded, 1) / torch.clamp(input_mask_expanded.sum(1), min=1e-9)
+
+
+# Sentences we want sentence embeddings for
+sentences = ['This is an example sentence', 'Each sentence is converted']
+
+# Load model from HuggingFace Hub
+tokenizer = AutoTokenizer.from_pretrained('Mihaiii/Venusaur')
+model = AutoModel.from_pretrained('Mihaiii/Venusaur')
+
+# Tokenize sentences
+encoded_input = tokenizer(sentences, padding=True, truncation=True, return_tensors='pt')
+
+# Compute token embeddings
+with torch.no_grad():
+    model_output = model(**encoded_input)
+
+# Perform pooling. In this case, mean pooling.
+sentence_embeddings = mean_pooling(model_output, encoded_input['attention_mask'])
+
+print("Sentence embeddings:")
+print(sentence_embeddings)
+```
+
+### Limitation (same as [gte-small](https://huggingface.co/thenlper/gte-small))
+This model exclusively caters to English texts, and any lengthy texts will be truncated to a maximum of 512 tokens.
\ No newline at end of file