README.md

---
license: mit
library_name: sentence-transformers
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- bge
- mteb
- mergekit
- merge
base_model:
- Mihaiii/Wartortle
- TaylorAI/bge-micro-v2
model-index:
- name: Giratina
  results:
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_counterfactual
      name: MTEB AmazonCounterfactualClassification (en)
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 69.56716417910448
    - type: ap
      value: 31.399435128856624
    - type: f1
      value: 63.139089415537256
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_polarity
      name: MTEB AmazonPolarityClassification
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 74.73525000000001
    - type: ap
      value: 69.2327764533514
    - type: f1
      value: 74.61617659775962
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_reviews_multi
      name: MTEB AmazonReviewsClassification (en)
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 35.356
    - type: f1
      value: 35.165109893437204
  - task:
      type: Retrieval
    dataset:
      type: mteb/arguana
      name: MTEB ArguAna
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 17.141000000000002
    - type: map_at_10
      value: 28.292
    - type: map_at_100
      value: 29.532000000000004
    - type: map_at_1000
      value: 29.580000000000002
    - type: map_at_20
      value: 29.048000000000002
    - type: map_at_3
      value: 24.277
    - type: map_at_5
      value: 26.339000000000002
    - type: mrr_at_1
      value: 17.781
    - type: mrr_at_10
      value: 28.534
    - type: mrr_at_100
      value: 29.779
    - type: mrr_at_1000
      value: 29.826999999999998
    - type: mrr_at_20
      value: 29.293000000000003
    - type: mrr_at_3
      value: 24.490000000000002
    - type: mrr_at_5
      value: 26.564
    - type: ndcg_at_1
      value: 17.141000000000002
    - type: ndcg_at_10
      value: 35.004000000000005
    - type: ndcg_at_100
      value: 41.056
    - type: ndcg_at_1000
      value: 42.388
    - type: ndcg_at_20
      value: 37.721
    - type: ndcg_at_3
      value: 26.592
    - type: ndcg_at_5
      value: 30.294999999999998
    - type: precision_at_1
      value: 17.141000000000002
    - type: precision_at_10
      value: 5.676
    - type: precision_at_100
      value: 0.851
    - type: precision_at_1000
      value: 0.096
    - type: precision_at_20
      value: 3.3709999999999996
    - type: precision_at_3
      value: 11.094999999999999
    - type: precision_at_5
      value: 8.450000000000001
    - type: recall_at_1
      value: 17.141000000000002
    - type: recall_at_10
      value: 56.757000000000005
    - type: recall_at_100
      value: 85.064
    - type: recall_at_1000
      value: 95.661
    - type: recall_at_20
      value: 67.425
    - type: recall_at_3
      value: 33.286
    - type: recall_at_5
      value: 42.248000000000005
  - task:
      type: Clustering
    dataset:
      type: mteb/arxiv-clustering-p2p
      name: MTEB ArxivClusteringP2P
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 37.86211319797047
    - 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: 28.836354293877637
    - 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: 55.77162231859219
    - type: mrr
      value: 69.60614254935584
  - task:
      type: STS
    dataset:
      type: mteb/biosses-sts
      name: MTEB BIOSSES
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 75.005851173518
    - type: cos_sim_spearman
      value: 76.4866825599851
    - type: euclidean_pearson
      value: 74.6002011099264
    - type: euclidean_spearman
      value: 74.99267261434052
    - type: manhattan_pearson
      value: 74.69084330891174
    - type: manhattan_spearman
      value: 74.06253093850374
  - task:
      type: Classification
    dataset:
      type: mteb/banking77
      name: MTEB Banking77Classification
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 77.51298701298701
    - type: f1
      value: 77.42714563211781
  - task:
      type: Clustering
    dataset:
      type: mteb/biorxiv-clustering-p2p
      name: MTEB BiorxivClusteringP2P
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 32.087909450126375
    - 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: 23.549481691079134
    - 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: 20.156
    - type: map_at_10
      value: 26.989
    - type: map_at_100
      value: 28.165000000000003
    - type: map_at_1000
      value: 28.302
    - type: map_at_20
      value: 27.505000000000003
    - type: map_at_3
      value: 24.631
    - type: map_at_5
      value: 25.886
    - type: mrr_at_1
      value: 25.607999999999997
    - type: mrr_at_10
      value: 31.972
    - type: mrr_at_100
      value: 32.993
    - type: mrr_at_1000
      value: 33.061
    - type: mrr_at_20
      value: 32.471
    - type: mrr_at_3
      value: 30.019000000000002
    - type: mrr_at_5
      value: 31.041999999999998
    - type: ndcg_at_1
      value: 25.607999999999997
    - type: ndcg_at_10
      value: 31.438
    - type: ndcg_at_100
      value: 37.347
    - type: ndcg_at_1000
      value: 40.075
    - type: ndcg_at_20
      value: 33.068
    - type: ndcg_at_3
      value: 27.846
    - type: ndcg_at_5
      value: 29.304999999999996
    - type: precision_at_1
      value: 25.607999999999997
    - type: precision_at_10
      value: 5.923
    - type: precision_at_100
      value: 1.102
    - type: precision_at_1000
      value: 0.161
    - type: precision_at_20
      value: 3.5340000000000003
    - type: precision_at_3
      value: 13.305
    - type: precision_at_5
      value: 9.585
    - type: recall_at_1
      value: 20.156
    - type: recall_at_10
      value: 39.741
    - type: recall_at_100
      value: 66.428
    - type: recall_at_1000
      value: 84.694
    - type: recall_at_20
      value: 45.688
    - type: recall_at_3
      value: 28.876
    - type: recall_at_5
      value: 33.284000000000006
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack-english
      name: MTEB CQADupstackEnglishRetrieval
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 14.568
    - type: map_at_10
      value: 19.356
    - type: map_at_100
      value: 20.044
    - type: map_at_1000
      value: 20.146
    - type: map_at_20
      value: 19.717000000000002
    - type: map_at_3
      value: 17.82
    - type: map_at_5
      value: 18.724
    - type: mrr_at_1
      value: 18.025
    - type: mrr_at_10
      value: 22.933
    - type: mrr_at_100
      value: 23.599
    - type: mrr_at_1000
      value: 23.669999999999998
    - type: mrr_at_20
      value: 23.283
    - type: mrr_at_3
      value: 21.295
    - type: mrr_at_5
      value: 22.314
    - type: ndcg_at_1
      value: 18.025
    - type: ndcg_at_10
      value: 22.559
    - type: ndcg_at_100
      value: 26.045
    - type: ndcg_at_1000
      value: 28.785
    - type: ndcg_at_20
      value: 23.727999999999998
    - type: ndcg_at_3
      value: 19.914
    - type: ndcg_at_5
      value: 21.241
    - type: precision_at_1
      value: 18.025
    - type: precision_at_10
      value: 4.102
    - type: precision_at_100
      value: 0.715
    - type: precision_at_1000
      value: 0.11800000000000001
    - type: precision_at_20
      value: 2.452
    - type: precision_at_3
      value: 9.447999999999999
    - type: precision_at_5
      value: 6.827999999999999
    - type: recall_at_1
      value: 14.568
    - type: recall_at_10
      value: 28.677999999999997
    - type: recall_at_100
      value: 44.362
    - type: recall_at_1000
      value: 63.705999999999996
    - type: recall_at_20
      value: 32.932
    - type: recall_at_3
      value: 21.029999999999998
    - type: recall_at_5
      value: 24.573
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack-gaming
      name: MTEB CQADupstackGamingRetrieval
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 25.104
    - type: map_at_10
      value: 33.857
    - type: map_at_100
      value: 34.808
    - type: map_at_1000
      value: 34.904
    - type: map_at_20
      value: 34.404
    - type: map_at_3
      value: 31.176
    - type: map_at_5
      value: 32.626
    - type: mrr_at_1
      value: 28.84
    - type: mrr_at_10
      value: 36.817
    - type: mrr_at_100
      value: 37.633
    - type: mrr_at_1000
      value: 37.698
    - type: mrr_at_20
      value: 37.312
    - type: mrr_at_3
      value: 34.451
    - type: mrr_at_5
      value: 35.748999999999995
    - type: ndcg_at_1
      value: 28.84
    - type: ndcg_at_10
      value: 38.745000000000005
    - type: ndcg_at_100
      value: 43.183
    - type: ndcg_at_1000
      value: 45.419
    - type: ndcg_at_20
      value: 40.571
    - type: ndcg_at_3
      value: 33.751
    - type: ndcg_at_5
      value: 36.042
    - type: precision_at_1
      value: 28.84
    - type: precision_at_10
      value: 6.389
    - type: precision_at_100
      value: 0.941
    - type: precision_at_1000
      value: 0.12
    - type: precision_at_20
      value: 3.6929999999999996
    - type: precision_at_3
      value: 15.068000000000001
    - type: precision_at_5
      value: 10.583
    - type: recall_at_1
      value: 25.104
    - type: recall_at_10
      value: 50.749
    - type: recall_at_100
      value: 70.336
    - type: recall_at_1000
      value: 86.591
    - type: recall_at_20
      value: 57.473
    - type: recall_at_3
      value: 37.230000000000004
    - type: recall_at_5
      value: 42.774
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack-gis
      name: MTEB CQADupstackGisRetrieval
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 12.712000000000002
    - type: map_at_10
      value: 18.064
    - type: map_at_100
      value: 18.775
    - type: map_at_1000
      value: 18.886
    - type: map_at_20
      value: 18.375
    - type: map_at_3
      value: 16.304
    - type: map_at_5
      value: 17.183999999999997
    - type: mrr_at_1
      value: 13.672
    - type: mrr_at_10
      value: 19.392
    - type: mrr_at_100
      value: 20.088
    - type: mrr_at_1000
      value: 20.186999999999998
    - type: mrr_at_20
      value: 19.721
    - type: mrr_at_3
      value: 17.495
    - type: mrr_at_5
      value: 18.473
    - type: ndcg_at_1
      value: 13.672
    - type: ndcg_at_10
      value: 21.427
    - type: ndcg_at_100
      value: 25.448999999999998
    - type: ndcg_at_1000
      value: 28.78
    - type: ndcg_at_20
      value: 22.56
    - type: ndcg_at_3
      value: 17.752000000000002
    - type: ndcg_at_5
      value: 19.356
    - type: precision_at_1
      value: 13.672
    - type: precision_at_10
      value: 3.5029999999999997
    - type: precision_at_100
      value: 0.5910000000000001
    - type: precision_at_1000
      value: 0.092
    - type: precision_at_20
      value: 2.011
    - type: precision_at_3
      value: 7.571
    - type: precision_at_5
      value: 5.537
    - type: recall_at_1
      value: 12.712000000000002
    - type: recall_at_10
      value: 30.596
    - type: recall_at_100
      value: 49.909
    - type: recall_at_1000
      value: 76.01400000000001
    - type: recall_at_20
      value: 34.903
    - type: recall_at_3
      value: 20.721999999999998
    - type: recall_at_5
      value: 24.428
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack-mathematica
      name: MTEB CQADupstackMathematicaRetrieval
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 7.48
    - type: map_at_10
      value: 12.089
    - type: map_at_100
      value: 12.974
    - type: map_at_1000
      value: 13.099
    - type: map_at_20
      value: 12.537
    - type: map_at_3
      value: 10.402000000000001
    - type: map_at_5
      value: 11.261000000000001
    - type: mrr_at_1
      value: 9.577
    - type: mrr_at_10
      value: 15.043999999999999
    - type: mrr_at_100
      value: 15.909
    - type: mrr_at_1000
      value: 15.998000000000001
    - type: mrr_at_20
      value: 15.512999999999998
    - type: mrr_at_3
      value: 13.184000000000001
    - type: mrr_at_5
      value: 14.066999999999998
    - type: ndcg_at_1
      value: 9.577
    - type: ndcg_at_10
      value: 15.511
    - type: ndcg_at_100
      value: 20.193
    - type: ndcg_at_1000
      value: 23.691000000000003
    - type: ndcg_at_20
      value: 17.176
    - type: ndcg_at_3
      value: 12.134
    - type: ndcg_at_5
      value: 13.506000000000002
    - type: precision_at_1
      value: 9.577
    - type: precision_at_10
      value: 3.159
    - type: precision_at_100
      value: 0.634
    - type: precision_at_1000
      value: 0.106
    - type: precision_at_20
      value: 2.009
    - type: precision_at_3
      value: 6.012
    - type: precision_at_5
      value: 4.627
    - type: recall_at_1
      value: 7.48
    - type: recall_at_10
      value: 23.134
    - type: recall_at_100
      value: 44.254
    - type: recall_at_1000
      value: 70.35
    - type: recall_at_20
      value: 29.383
    - type: recall_at_3
      value: 13.84
    - type: recall_at_5
      value: 17.175
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack-physics
      name: MTEB CQADupstackPhysicsRetrieval
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 18.035
    - type: map_at_10
      value: 24.007
    - type: map_at_100
      value: 25.113999999999997
    - type: map_at_1000
      value: 25.245
    - type: map_at_20
      value: 24.587
    - type: map_at_3
      value: 21.921
    - type: map_at_5
      value: 22.917
    - type: mrr_at_1
      value: 22.233
    - type: mrr_at_10
      value: 28.479
    - type: mrr_at_100
      value: 29.412
    - type: mrr_at_1000
      value: 29.49
    - type: mrr_at_20
      value: 29.031000000000002
    - type: mrr_at_3
      value: 26.275
    - type: mrr_at_5
      value: 27.400999999999996
    - type: ndcg_at_1
      value: 22.233
    - type: ndcg_at_10
      value: 28.382
    - type: ndcg_at_100
      value: 33.86
    - type: ndcg_at_1000
      value: 36.903000000000006
    - type: ndcg_at_20
      value: 30.341
    - type: ndcg_at_3
      value: 24.695
    - type: ndcg_at_5
      value: 26.13
    - type: precision_at_1
      value: 22.233
    - type: precision_at_10
      value: 5.2170000000000005
    - type: precision_at_100
      value: 0.95
    - type: precision_at_1000
      value: 0.13899999999999998
    - type: precision_at_20
      value: 3.2239999999999998
    - type: precision_at_3
      value: 11.485
    - type: precision_at_5
      value: 8.181
    - type: recall_at_1
      value: 18.035
    - type: recall_at_10
      value: 37.222
    - type: recall_at_100
      value: 61.602000000000004
    - type: recall_at_1000
      value: 82.92
    - type: recall_at_20
      value: 44.221
    - type: recall_at_3
      value: 26.625
    - type: recall_at_5
      value: 30.461
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack-programmers
      name: MTEB CQADupstackProgrammersRetrieval
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 13.281
    - type: map_at_10
      value: 17.756
    - type: map_at_100
      value: 18.785
    - type: map_at_1000
      value: 18.921
    - type: map_at_20
      value: 18.209
    - type: map_at_3
      value: 15.817999999999998
    - type: map_at_5
      value: 16.939
    - type: mrr_at_1
      value: 16.096
    - type: mrr_at_10
      value: 21.079
    - type: mrr_at_100
      value: 22.061
    - type: mrr_at_1000
      value: 22.151
    - type: mrr_at_20
      value: 21.557000000000002
    - type: mrr_at_3
      value: 19.006999999999998
    - type: mrr_at_5
      value: 20.171
    - type: ndcg_at_1
      value: 16.096
    - type: ndcg_at_10
      value: 21.278
    - type: ndcg_at_100
      value: 26.687
    - type: ndcg_at_1000
      value: 30.016
    - type: ndcg_at_20
      value: 22.871
    - type: ndcg_at_3
      value: 17.705000000000002
    - type: ndcg_at_5
      value: 19.427
    - type: precision_at_1
      value: 16.096
    - type: precision_at_10
      value: 3.893
    - type: precision_at_100
      value: 0.792
    - type: precision_at_1000
      value: 0.124
    - type: precision_at_20
      value: 2.414
    - type: precision_at_3
      value: 8.029
    - type: precision_at_5
      value: 6.119
    - type: recall_at_1
      value: 13.281
    - type: recall_at_10
      value: 28.849000000000004
    - type: recall_at_100
      value: 53.010999999999996
    - type: recall_at_1000
      value: 76.512
    - type: recall_at_20
      value: 34.547
    - type: recall_at_3
      value: 19.177
    - type: recall_at_5
      value: 23.455000000000002
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack
      name: MTEB CQADupstackRetrieval
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 14.161583333333333
    - type: map_at_10
      value: 19.378833333333333
    - type: map_at_100
      value: 20.27525
    - type: map_at_1000
      value: 20.394499999999997
    - type: map_at_20
      value: 19.831333333333333
    - type: map_at_3
      value: 17.55408333333333
    - type: map_at_5
      value: 18.52841666666667
    - type: mrr_at_1
      value: 17.00033333333333
    - type: mrr_at_10
      value: 22.41916666666667
    - type: mrr_at_100
      value: 23.252666666666666
    - type: mrr_at_1000
      value: 23.337583333333335
    - type: mrr_at_20
      value: 22.866666666666667
    - type: mrr_at_3
      value: 20.56991666666667
    - type: mrr_at_5
      value: 21.567666666666664
    - type: ndcg_at_1
      value: 17.00033333333333
    - type: ndcg_at_10
      value: 22.96475
    - type: ndcg_at_100
      value: 27.526833333333332
    - type: ndcg_at_1000
      value: 30.597416666666668
    - type: ndcg_at_20
      value: 24.52133333333333
    - type: ndcg_at_3
      value: 19.60108333333334
    - type: ndcg_at_5
      value: 21.089750000000002
    - type: precision_at_1
      value: 17.00033333333333
    - type: precision_at_10
      value: 4.10625
    - type: precision_at_100
      value: 0.7497499999999999
    - type: precision_at_1000
      value: 0.11733333333333335
    - type: precision_at_20
      value: 2.499416666666667
    - type: precision_at_3
      value: 9.041
    - type: precision_at_5
      value: 6.554250000000001
    - type: recall_at_1
      value: 14.161583333333333
    - type: recall_at_10
      value: 30.899916666666666
    - type: recall_at_100
      value: 51.66383333333333
    - type: recall_at_1000
      value: 74.103
    - type: recall_at_20
      value: 36.698
    - type: recall_at_3
      value: 21.398
    - type: recall_at_5
      value: 25.241750000000003
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack-stats
      name: MTEB CQADupstackStatsRetrieval
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 13.036
    - type: map_at_10
      value: 17.142
    - type: map_at_100
      value: 17.915
    - type: map_at_1000
      value: 18.002000000000002
    - type: map_at_20
      value: 17.558
    - type: map_at_3
      value: 15.459
    - type: map_at_5
      value: 16.474
    - type: mrr_at_1
      value: 14.877
    - type: mrr_at_10
      value: 19.365
    - type: mrr_at_100
      value: 20.085
    - type: mrr_at_1000
      value: 20.165
    - type: mrr_at_20
      value: 19.75
    - type: mrr_at_3
      value: 17.638
    - type: mrr_at_5
      value: 18.673000000000002
    - type: ndcg_at_1
      value: 14.877
    - type: ndcg_at_10
      value: 20.199
    - type: ndcg_at_100
      value: 24.275
    - type: ndcg_at_1000
      value: 26.933
    - type: ndcg_at_20
      value: 21.683
    - type: ndcg_at_3
      value: 16.925
    - type: ndcg_at_5
      value: 18.565
    - type: precision_at_1
      value: 14.877
    - type: precision_at_10
      value: 3.374
    - type: precision_at_100
      value: 0.59
    - type: precision_at_1000
      value: 0.087
    - type: precision_at_20
      value: 2.04
    - type: precision_at_3
      value: 7.515
    - type: precision_at_5
      value: 5.491
    - type: recall_at_1
      value: 13.036
    - type: recall_at_10
      value: 27.750000000000004
    - type: recall_at_100
      value: 46.798
    - type: recall_at_1000
      value: 67.372
    - type: recall_at_20
      value: 33.406000000000006
    - type: recall_at_3
      value: 18.381
    - type: recall_at_5
      value: 22.559
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack-tex
      name: MTEB CQADupstackTexRetrieval
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 8.448
    - type: map_at_10
      value: 11.978
    - type: map_at_100
      value: 12.736
    - type: map_at_1000
      value: 12.848
    - type: map_at_20
      value: 12.354
    - type: map_at_3
      value: 10.687000000000001
    - type: map_at_5
      value: 11.344
    - type: mrr_at_1
      value: 10.771
    - type: mrr_at_10
      value: 14.753
    - type: mrr_at_100
      value: 15.501000000000001
    - type: mrr_at_1000
      value: 15.592
    - type: mrr_at_20
      value: 15.148
    - type: mrr_at_3
      value: 13.425999999999998
    - type: mrr_at_5
      value: 14.059
    - type: ndcg_at_1
      value: 10.771
    - type: ndcg_at_10
      value: 14.788
    - type: ndcg_at_100
      value: 18.769
    - type: ndcg_at_1000
      value: 21.939
    - type: ndcg_at_20
      value: 16.113
    - type: ndcg_at_3
      value: 12.356
    - type: ndcg_at_5
      value: 13.316
    - type: precision_at_1
      value: 10.771
    - type: precision_at_10
      value: 2.842
    - type: precision_at_100
      value: 0.58
    - type: precision_at_1000
      value: 0.099
    - type: precision_at_20
      value: 1.807
    - type: precision_at_3
      value: 5.976
    - type: precision_at_5
      value: 4.322
    - type: recall_at_1
      value: 8.448
    - type: recall_at_10
      value: 20.666
    - type: recall_at_100
      value: 39.111000000000004
    - type: recall_at_1000
      value: 62.673
    - type: recall_at_20
      value: 25.686999999999998
    - type: recall_at_3
      value: 13.572999999999999
    - type: recall_at_5
      value: 16.239
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack-unix
      name: MTEB CQADupstackUnixRetrieval
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 14.025000000000002
    - type: map_at_10
      value: 18.605
    - type: map_at_100
      value: 19.442999999999998
    - type: map_at_1000
      value: 19.569
    - type: map_at_20
      value: 19.070999999999998
    - type: map_at_3
      value: 17.072000000000003
    - type: map_at_5
      value: 17.866
    - type: mrr_at_1
      value: 16.511
    - type: mrr_at_10
      value: 21.633
    - type: mrr_at_100
      value: 22.419
    - type: mrr_at_1000
      value: 22.521
    - type: mrr_at_20
      value: 22.063
    - type: mrr_at_3
      value: 19.932
    - type: mrr_at_5
      value: 20.864
    - type: ndcg_at_1
      value: 16.511
    - type: ndcg_at_10
      value: 21.931
    - type: ndcg_at_100
      value: 26.088
    - type: ndcg_at_1000
      value: 29.564
    - type: ndcg_at_20
      value: 23.557
    - type: ndcg_at_3
      value: 18.869
    - type: ndcg_at_5
      value: 20.203
    - type: precision_at_1
      value: 16.511
    - type: precision_at_10
      value: 3.7220000000000004
    - type: precision_at_100
      value: 0.637
    - type: precision_at_1000
      value: 0.105
    - type: precision_at_20
      value: 2.299
    - type: precision_at_3
      value: 8.52
    - type: precision_at_5
      value: 6.007
    - type: recall_at_1
      value: 14.025000000000002
    - type: recall_at_10
      value: 29.24
    - type: recall_at_100
      value: 47.771
    - type: recall_at_1000
      value: 73.37599999999999
    - type: recall_at_20
      value: 35.148
    - type: recall_at_3
      value: 20.721
    - type: recall_at_5
      value: 24.162
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack-webmasters
      name: MTEB CQADupstackWebmastersRetrieval
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 14.610000000000001
    - type: map_at_10
      value: 20.089000000000002
    - type: map_at_100
      value: 21.105
    - type: map_at_1000
      value: 21.275
    - type: map_at_20
      value: 20.604
    - type: map_at_3
      value: 18.323
    - type: map_at_5
      value: 19.192
    - type: mrr_at_1
      value: 18.182000000000002
    - type: mrr_at_10
      value: 23.458000000000002
    - type: mrr_at_100
      value: 24.379
    - type: mrr_at_1000
      value: 24.474999999999998
    - type: mrr_at_20
      value: 23.973
    - type: mrr_at_3
      value: 21.64
    - type: mrr_at_5
      value: 22.579
    - type: ndcg_at_1
      value: 18.182000000000002
    - type: ndcg_at_10
      value: 23.842
    - type: ndcg_at_100
      value: 28.604000000000003
    - type: ndcg_at_1000
      value: 32.192
    - type: ndcg_at_20
      value: 25.507
    - type: ndcg_at_3
      value: 20.937
    - type: ndcg_at_5
      value: 22.125
    - type: precision_at_1
      value: 18.182000000000002
    - type: precision_at_10
      value: 4.526
    - type: precision_at_100
      value: 0.955
    - type: precision_at_1000
      value: 0.17500000000000002
    - type: precision_at_20
      value: 2.846
    - type: precision_at_3
      value: 10.079
    - type: precision_at_5
      value: 7.194000000000001
    - type: recall_at_1
      value: 14.610000000000001
    - type: recall_at_10
      value: 31.086999999999996
    - type: recall_at_100
      value: 53.032000000000004
    - type: recall_at_1000
      value: 77.781
    - type: recall_at_20
      value: 37.801
    - type: recall_at_3
      value: 22.078999999999997
    - type: recall_at_5
      value: 25.572
  - task:
      type: Retrieval
    dataset:
      type: mteb/cqadupstack-wordpress
      name: MTEB CQADupstackWordpressRetrieval
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 8.484
    - type: map_at_10
      value: 12.614
    - type: map_at_100
      value: 13.439
    - type: map_at_1000
      value: 13.536999999999999
    - type: map_at_20
      value: 13.055
    - type: map_at_3
      value: 11.036
    - type: map_at_5
      value: 11.927999999999999
    - type: mrr_at_1
      value: 9.612
    - type: mrr_at_10
      value: 14.105
    - type: mrr_at_100
      value: 14.953
    - type: mrr_at_1000
      value: 15.043000000000001
    - type: mrr_at_20
      value: 14.578
    - type: mrr_at_3
      value: 12.477
    - type: mrr_at_5
      value: 13.420000000000002
    - type: ndcg_at_1
      value: 9.612
    - type: ndcg_at_10
      value: 15.476999999999999
    - type: ndcg_at_100
      value: 19.822
    - type: ndcg_at_1000
      value: 22.872
    - type: ndcg_at_20
      value: 17.081
    - type: ndcg_at_3
      value: 12.328999999999999
    - type: ndcg_at_5
      value: 13.861
    - type: precision_at_1
      value: 9.612
    - type: precision_at_10
      value: 2.625
    - type: precision_at_100
      value: 0.51
    - type: precision_at_1000
      value: 0.082
    - type: precision_at_20
      value: 1.664
    - type: precision_at_3
      value: 5.484
    - type: precision_at_5
      value: 4.1770000000000005
    - type: recall_at_1
      value: 8.484
    - type: recall_at_10
      value: 23.087
    - type: recall_at_100
      value: 43.352000000000004
    - type: recall_at_1000
      value: 67.247
    - type: recall_at_20
      value: 29.187
    - type: recall_at_3
      value: 14.521999999999998
    - type: recall_at_5
      value: 18.218999999999998
  - task:
      type: Classification
    dataset:
      type: mteb/emotion
      name: MTEB EmotionClassification
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 39.095
    - type: f1
      value: 35.03781407521973
  - task:
      type: Classification
    dataset:
      type: mteb/imdb
      name: MTEB ImdbClassification
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 67.87360000000001
    - type: ap
      value: 62.5359530212091
    - type: f1
      value: 67.76861907065303
  - task:
      type: Classification
    dataset:
      type: mteb/mtop_domain
      name: MTEB MTOPDomainClassification (en)
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 89.98176014591884
    - type: f1
      value: 89.12439802681382
  - task:
      type: Classification
    dataset:
      type: mteb/mtop_intent
      name: MTEB MTOPIntentClassification (en)
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 66.42954856361149
    - type: f1
      value: 46.845543295765395
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_intent
      name: MTEB MassiveIntentClassification (en)
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 65.15131136516476
    - type: f1
      value: 63.15954994502248
  - task:
      type: Classification
    dataset:
      type: mteb/amazon_massive_scenario
      name: MTEB MassiveScenarioClassification (en)
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 70.74983187626093
    - type: f1
      value: 69.86842975748304
  - task:
      type: Clustering
    dataset:
      type: mteb/medrxiv-clustering-p2p
      name: MTEB MedrxivClusteringP2P
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 28.540533318170436
    - 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: 24.72766780458758
    - 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: 29.041674385781967
    - type: mrr
      value: 29.79989064897717
  - task:
      type: Clustering
    dataset:
      type: mteb/reddit-clustering
      name: MTEB RedditClustering
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 35.536820860805534
    - 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: 47.42966991443242
    - type: v_measures
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  - task:
      type: STS
    dataset:
      type: mteb/sickr-sts
      name: MTEB SICK-R
      config: default
      split: test
      revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
    metrics:
    - type: cos_sim_pearson
      value: 79.02197797488559
    - type: cos_sim_spearman
      value: 71.7037151299904
    - type: euclidean_pearson
      value: 76.1707252695092
    - type: euclidean_spearman
      value: 71.57310842242731
    - type: manhattan_pearson
      value: 76.03615971307154
    - type: manhattan_spearman
      value: 71.53631984773847
  - task:
      type: STS
    dataset:
      type: mteb/sts12-sts
      name: MTEB STS12
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 79.02494360083622
    - type: cos_sim_spearman
      value: 69.72575299384381
    - type: euclidean_pearson
      value: 75.74354904408656
    - type: euclidean_spearman
      value: 69.54484408453516
    - type: manhattan_pearson
      value: 75.77951962076156
    - type: manhattan_spearman
      value: 69.6354936146991
  - task:
      type: STS
    dataset:
      type: mteb/sts13-sts
      name: MTEB STS13
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 75.08237871140905
    - type: cos_sim_spearman
      value: 76.43254419101892
    - type: euclidean_pearson
      value: 77.01392166862142
    - type: euclidean_spearman
      value: 77.25873928927386
    - type: manhattan_pearson
      value: 76.8322542796806
    - type: manhattan_spearman
      value: 77.06622162313037
  - task:
      type: STS
    dataset:
      type: mteb/sts14-sts
      name: MTEB STS14
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 76.15651557768992
    - type: cos_sim_spearman
      value: 73.66468164294979
    - type: euclidean_pearson
      value: 76.01343601779764
    - type: euclidean_spearman
      value: 74.26813269648791
    - type: manhattan_pearson
      value: 75.81532622772455
    - type: manhattan_spearman
      value: 74.11890179466049
  - task:
      type: STS
    dataset:
      type: mteb/sts15-sts
      name: MTEB STS15
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 81.80212103727666
    - type: cos_sim_spearman
      value: 82.61832225494061
    - type: euclidean_pearson
      value: 81.83006587249692
    - type: euclidean_spearman
      value: 82.61429686151203
    - type: manhattan_pearson
      value: 81.76278849963437
    - type: manhattan_spearman
      value: 82.54152053739365
  - task:
      type: STS
    dataset:
      type: mteb/sts16-sts
      name: MTEB STS16
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 77.75548172603382
    - type: cos_sim_spearman
      value: 79.48976464310448
    - type: euclidean_pearson
      value: 78.54266801280951
    - type: euclidean_spearman
      value: 79.30766703387586
    - type: manhattan_pearson
      value: 78.28008795002846
    - type: manhattan_spearman
      value: 79.07395809817007
  - 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: 83.813657478234
    - type: cos_sim_spearman
      value: 84.38223117622964
    - type: euclidean_pearson
      value: 84.57065602789609
    - type: euclidean_spearman
      value: 83.8380794185294
    - type: manhattan_pearson
      value: 84.42039206232738
    - type: manhattan_spearman
      value: 83.74732339282085
  - 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: 50.88695953591733
    - type: cos_sim_spearman
      value: 60.61167810477114
    - type: euclidean_pearson
      value: 55.81887963485168
    - type: euclidean_spearman
      value: 60.28385340456606
    - type: manhattan_pearson
      value: 56.03578991214848
    - type: manhattan_spearman
      value: 59.94178607215249
  - task:
      type: STS
    dataset:
      type: mteb/stsbenchmark-sts
      name: MTEB STSBenchmark
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 78.97129674864591
    - type: cos_sim_spearman
      value: 78.60681572589853
    - type: euclidean_pearson
      value: 79.71108582359511
    - type: euclidean_spearman
      value: 78.71541582168763
    - type: manhattan_pearson
      value: 79.55279136411954
    - type: manhattan_spearman
      value: 78.57797218212967
  - task:
      type: Reranking
    dataset:
      type: mteb/scidocs-reranking
      name: MTEB SciDocsRR
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 72.91005664580126
    - type: mrr
      value: 91.49957703879274
  - task:
      type: PairClassification
    dataset:
      type: mteb/sprintduplicatequestions-pairclassification
      name: MTEB SprintDuplicateQuestions
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.73960396039604
    - type: cos_sim_ap
      value: 92.14278266682584
    - type: cos_sim_f1
      value: 86.90890990542557
    - type: cos_sim_precision
      value: 86.5213082259663
    - type: cos_sim_recall
      value: 87.3
    - type: dot_accuracy
      value: 99.49801980198019
    - type: dot_ap
      value: 77.95867119922542
    - type: dot_f1
      value: 71.30528586839266
    - type: dot_precision
      value: 77.40046838407494
    - type: dot_recall
      value: 66.10000000000001
    - type: euclidean_accuracy
      value: 99.73861386138614
    - type: euclidean_ap
      value: 92.13035792099073
    - type: euclidean_f1
      value: 86.81102362204726
    - type: euclidean_precision
      value: 85.46511627906976
    - type: euclidean_recall
      value: 88.2
    - type: manhattan_accuracy
      value: 99.73762376237623
    - type: manhattan_ap
      value: 92.12382961875572
    - type: manhattan_f1
      value: 86.85770750988142
    - type: manhattan_precision
      value: 85.83984375
    - type: manhattan_recall
      value: 87.9
    - type: max_accuracy
      value: 99.73960396039604
    - type: max_ap
      value: 92.14278266682584
    - type: max_f1
      value: 86.90890990542557
  - task:
      type: Clustering
    dataset:
      type: mteb/stackexchange-clustering
      name: MTEB StackExchangeClustering
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 46.543842750900396
    - 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: 30.878511440057455
    - 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: 44.48878112961158
    - type: mrr
      value: 45.088675621763855
  - task:
      type: Summarization
    dataset:
      type: mteb/summeval
      name: MTEB SummEval
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 30.941315767578654
    - type: cos_sim_spearman
      value: 29.329027079065966
    - type: dot_pearson
      value: 25.836517566143634
    - type: dot_spearman
      value: 26.352097845535162
  - task:
      type: Classification
    dataset:
      type: mteb/toxic_conversations_50k
      name: MTEB ToxicConversationsClassification
      config: default
      split: test
      revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
    metrics:
    - type: accuracy
      value: 64.013671875
    - type: ap
      value: 10.97313563679864
    - type: f1
      value: 48.85384219487
  - task:
      type: Classification
    dataset:
      type: mteb/tweet_sentiment_extraction
      name: MTEB TweetSentimentExtractionClassification
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 54.25863044708545
    - type: f1
      value: 54.478056275468234
  - task:
      type: Clustering
    dataset:
      type: mteb/twentynewsgroups-clustering
      name: MTEB TwentyNewsgroupsClustering
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 28.676358868345943
    - 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: 83.23895809739524
    - type: cos_sim_ap
      value: 63.43837390346798
    - type: cos_sim_f1
      value: 60.3425871234495
    - type: cos_sim_precision
      value: 54.63101604278074
    - type: cos_sim_recall
      value: 67.38786279683377
    - type: dot_accuracy
      value: 79.70435715562974
    - type: dot_ap
      value: 50.219858779642024
    - type: dot_f1
      value: 52.03935006079363
    - type: dot_precision
      value: 44.778390717139054
    - type: dot_recall
      value: 62.11081794195251
    - type: euclidean_accuracy
      value: 83.3581689217381
    - type: euclidean_ap
      value: 63.866502871821886
    - type: euclidean_f1
      value: 60.66180862501495
    - type: euclidean_precision
      value: 55.42457978607291
    - type: euclidean_recall
      value: 66.99208443271768
    - type: manhattan_accuracy
      value: 83.32836621565238
    - type: manhattan_ap
      value: 63.58246341419401
    - type: manhattan_f1
      value: 60.405654578979714
    - type: manhattan_precision
      value: 56.54775604142692
    - type: manhattan_recall
      value: 64.82849604221636
    - type: max_accuracy
      value: 83.3581689217381
    - type: max_ap
      value: 63.866502871821886
    - type: max_f1
      value: 60.66180862501495
  - task:
      type: PairClassification
    dataset:
      type: mteb/twitterurlcorpus-pairclassification
      name: MTEB TwitterURLCorpus
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 87.77894205767066
    - type: cos_sim_ap
      value: 83.5297230824822
    - type: cos_sim_f1
      value: 75.65036420395423
    - type: cos_sim_precision
      value: 73.11781609195403
    - type: cos_sim_recall
      value: 78.3646442870342
    - type: dot_accuracy
      value: 86.03058175185313
    - type: dot_ap
      value: 78.95144253575621
    - type: dot_f1
      value: 72.20582032897512
    - type: dot_precision
      value: 66.42524573202276
    - type: dot_recall
      value: 79.08838928241454
    - type: euclidean_accuracy
      value: 87.7265494624908
    - type: euclidean_ap
      value: 83.29997302389856
    - type: euclidean_f1
      value: 75.38237163905613
    - type: euclidean_precision
      value: 73.28582854649895
    - type: euclidean_recall
      value: 77.60240221743148
    - type: manhattan_accuracy
      value: 87.65475220242946
    - type: manhattan_ap
      value: 83.1779453049763
    - type: manhattan_f1
      value: 75.17620001483792
    - type: manhattan_precision
      value: 72.53400143163923
    - type: manhattan_recall
      value: 78.01817061903296
    - type: max_accuracy
      value: 87.77894205767066
    - type: max_ap
      value: 83.5297230824822
    - type: max_f1
      value: 75.65036420395423
---
# Giratina

This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).

## Merge Details
### Merge Method

This model was merged using the SLERP merge method.

### Models Merged

The following models were included in the merge:
* [Mihaiii/Wartortle](https://huggingface.co/Mihaiii/Wartortle)
* [TaylorAI/bge-micro-v2](https://huggingface.co/TaylorAI/bge-micro-v2)

### Configuration

The following YAML configuration was used to produce this model:

```yaml
models:
   - model: Mihaiii/Wartortle
   - model: TaylorAI/bge-micro-v2
merge_method: slerp
base_model: TaylorAI/bge-micro-v2
parameters:
  t:
    - value: 0.5
dtype: float32
```