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metadata
base_model: Alibaba-NLP/gte-Qwen2-7B-instruct
license: apache-2.0
tags:
  - mteb
  - sentence-transformers
  - transformers
  - Qwen2
  - sentence-similarity
  - llama-cpp
  - gguf-my-repo
model-index:
  - name: gte-qwen2-7B-instruct
    results:
      - task:
          type: Classification
        dataset:
          name: MTEB AmazonCounterfactualClassification (en)
          type: mteb/amazon_counterfactual
          config: en
          split: test
          revision: e8379541af4e31359cca9fbcf4b00f2671dba205
        metrics:
          - type: accuracy
            value: 91.31343283582089
          - type: ap
            value: 67.64251402604096
          - type: f1
            value: 87.53372530755692
      - task:
          type: Classification
        dataset:
          name: MTEB AmazonPolarityClassification
          type: mteb/amazon_polarity
          config: default
          split: test
          revision: e2d317d38cd51312af73b3d32a06d1a08b442046
        metrics:
          - type: accuracy
            value: 97.497825
          - type: ap
            value: 96.30329547047529
          - type: f1
            value: 97.49769793778039
      - task:
          type: Classification
        dataset:
          name: MTEB AmazonReviewsClassification (en)
          type: mteb/amazon_reviews_multi
          config: en
          split: test
          revision: 1399c76144fd37290681b995c656ef9b2e06e26d
        metrics:
          - type: accuracy
            value: 62.564
          - type: f1
            value: 60.975777935041066
      - task:
          type: Retrieval
        dataset:
          name: MTEB ArguAna
          type: mteb/arguana
          config: default
          split: test
          revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
        metrics:
          - type: map_at_1
            value: 36.486000000000004
          - type: map_at_10
            value: 54.842
          - type: map_at_100
            value: 55.206999999999994
          - type: map_at_1000
            value: 55.206999999999994
          - type: map_at_3
            value: 49.893
          - type: map_at_5
            value: 53.105000000000004
          - type: mrr_at_1
            value: 37.34
          - type: mrr_at_10
            value: 55.143
          - type: mrr_at_100
            value: 55.509
          - type: mrr_at_1000
            value: 55.509
          - type: mrr_at_3
            value: 50.212999999999994
          - type: mrr_at_5
            value: 53.432
          - type: ndcg_at_1
            value: 36.486000000000004
          - type: ndcg_at_10
            value: 64.273
          - type: ndcg_at_100
            value: 65.66199999999999
          - type: ndcg_at_1000
            value: 65.66199999999999
          - type: ndcg_at_3
            value: 54.352999999999994
          - type: ndcg_at_5
            value: 60.131
          - type: precision_at_1
            value: 36.486000000000004
          - type: precision_at_10
            value: 9.395000000000001
          - type: precision_at_100
            value: 0.996
          - type: precision_at_1000
            value: 0.1
          - type: precision_at_3
            value: 22.428
          - type: precision_at_5
            value: 16.259
          - type: recall_at_1
            value: 36.486000000000004
          - type: recall_at_10
            value: 93.95400000000001
          - type: recall_at_100
            value: 99.644
          - type: recall_at_1000
            value: 99.644
          - type: recall_at_3
            value: 67.283
          - type: recall_at_5
            value: 81.294
      - task:
          type: Clustering
        dataset:
          name: MTEB ArxivClusteringP2P
          type: mteb/arxiv-clustering-p2p
          config: default
          split: test
          revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
        metrics:
          - type: v_measure
            value: 56.461169803700564
      - task:
          type: Clustering
        dataset:
          name: MTEB ArxivClusteringS2S
          type: mteb/arxiv-clustering-s2s
          config: default
          split: test
          revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
        metrics:
          - type: v_measure
            value: 51.73600434466286
      - task:
          type: Reranking
        dataset:
          name: MTEB AskUbuntuDupQuestions
          type: mteb/askubuntudupquestions-reranking
          config: default
          split: test
          revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
        metrics:
          - type: map
            value: 67.57827065898053
          - type: mrr
            value: 79.08136569493911
      - task:
          type: STS
        dataset:
          name: MTEB BIOSSES
          type: mteb/biosses-sts
          config: default
          split: test
          revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
        metrics:
          - type: cos_sim_pearson
            value: 83.53324575999243
          - type: cos_sim_spearman
            value: 81.37173362822374
          - type: euclidean_pearson
            value: 82.19243335103444
          - type: euclidean_spearman
            value: 81.33679307304334
          - type: manhattan_pearson
            value: 82.38752665975699
          - type: manhattan_spearman
            value: 81.31510583189689
      - task:
          type: Classification
        dataset:
          name: MTEB Banking77Classification
          type: mteb/banking77
          config: default
          split: test
          revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
        metrics:
          - type: accuracy
            value: 87.56818181818181
          - type: f1
            value: 87.25826722019875
      - task:
          type: Clustering
        dataset:
          name: MTEB BiorxivClusteringP2P
          type: mteb/biorxiv-clustering-p2p
          config: default
          split: test
          revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
        metrics:
          - type: v_measure
            value: 50.09239610327673
      - task:
          type: Clustering
        dataset:
          name: MTEB BiorxivClusteringS2S
          type: mteb/biorxiv-clustering-s2s
          config: default
          split: test
          revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
        metrics:
          - type: v_measure
            value: 46.64733054606282
      - task:
          type: Retrieval
        dataset:
          name: MTEB CQADupstackAndroidRetrieval
          type: BeIR/cqadupstack
          config: default
          split: test
          revision: f46a197baaae43b4f621051089b82a364682dfeb
        metrics:
          - type: map_at_1
            value: 33.997
          - type: map_at_10
            value: 48.176
          - type: map_at_100
            value: 49.82
          - type: map_at_1000
            value: 49.924
          - type: map_at_3
            value: 43.626
          - type: map_at_5
            value: 46.275
          - type: mrr_at_1
            value: 42.059999999999995
          - type: mrr_at_10
            value: 53.726
          - type: mrr_at_100
            value: 54.398
          - type: mrr_at_1000
            value: 54.416
          - type: mrr_at_3
            value: 50.714999999999996
          - type: mrr_at_5
            value: 52.639
          - type: ndcg_at_1
            value: 42.059999999999995
          - type: ndcg_at_10
            value: 55.574999999999996
          - type: ndcg_at_100
            value: 60.744
          - type: ndcg_at_1000
            value: 61.85699999999999
          - type: ndcg_at_3
            value: 49.363
          - type: ndcg_at_5
            value: 52.44
          - type: precision_at_1
            value: 42.059999999999995
          - type: precision_at_10
            value: 11.101999999999999
          - type: precision_at_100
            value: 1.73
          - type: precision_at_1000
            value: 0.218
          - type: precision_at_3
            value: 24.464
          - type: precision_at_5
            value: 18.026
          - type: recall_at_1
            value: 33.997
          - type: recall_at_10
            value: 70.35900000000001
          - type: recall_at_100
            value: 91.642
          - type: recall_at_1000
            value: 97.977
          - type: recall_at_3
            value: 52.76
          - type: recall_at_5
            value: 61.148
      - task:
          type: Retrieval
        dataset:
          name: MTEB CQADupstackEnglishRetrieval
          type: BeIR/cqadupstack
          config: default
          split: test
          revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
        metrics:
          - type: map_at_1
            value: 35.884
          - type: map_at_10
            value: 48.14
          - type: map_at_100
            value: 49.5
          - type: map_at_1000
            value: 49.63
          - type: map_at_3
            value: 44.646
          - type: map_at_5
            value: 46.617999999999995
          - type: mrr_at_1
            value: 44.458999999999996
          - type: mrr_at_10
            value: 53.751000000000005
          - type: mrr_at_100
            value: 54.37800000000001
          - type: mrr_at_1000
            value: 54.415
          - type: mrr_at_3
            value: 51.815
          - type: mrr_at_5
            value: 52.882
          - type: ndcg_at_1
            value: 44.458999999999996
          - type: ndcg_at_10
            value: 54.157
          - type: ndcg_at_100
            value: 58.362
          - type: ndcg_at_1000
            value: 60.178
          - type: ndcg_at_3
            value: 49.661
          - type: ndcg_at_5
            value: 51.74999999999999
          - type: precision_at_1
            value: 44.458999999999996
          - type: precision_at_10
            value: 10.248
          - type: precision_at_100
            value: 1.5890000000000002
          - type: precision_at_1000
            value: 0.207
          - type: precision_at_3
            value: 23.928
          - type: precision_at_5
            value: 16.878999999999998
          - type: recall_at_1
            value: 35.884
          - type: recall_at_10
            value: 64.798
          - type: recall_at_100
            value: 82.345
          - type: recall_at_1000
            value: 93.267
          - type: recall_at_3
            value: 51.847
          - type: recall_at_5
            value: 57.601
      - task:
          type: Retrieval
        dataset:
          name: MTEB CQADupstackGamingRetrieval
          type: BeIR/cqadupstack
          config: default
          split: test
          revision: 4885aa143210c98657558c04aaf3dc47cfb54340
        metrics:
          - type: map_at_1
            value: 39.383
          - type: map_at_10
            value: 53.714
          - type: map_at_100
            value: 54.838
          - type: map_at_1000
            value: 54.87800000000001
          - type: map_at_3
            value: 50.114999999999995
          - type: map_at_5
            value: 52.153000000000006
          - type: mrr_at_1
            value: 45.016
          - type: mrr_at_10
            value: 56.732000000000006
          - type: mrr_at_100
            value: 57.411
          - type: mrr_at_1000
            value: 57.431
          - type: mrr_at_3
            value: 54.044000000000004
          - type: mrr_at_5
            value: 55.639
          - type: ndcg_at_1
            value: 45.016
          - type: ndcg_at_10
            value: 60.228
          - type: ndcg_at_100
            value: 64.277
          - type: ndcg_at_1000
            value: 65.07
          - type: ndcg_at_3
            value: 54.124
          - type: ndcg_at_5
            value: 57.147000000000006
          - type: precision_at_1
            value: 45.016
          - type: precision_at_10
            value: 9.937
          - type: precision_at_100
            value: 1.288
          - type: precision_at_1000
            value: 0.13899999999999998
          - type: precision_at_3
            value: 24.471999999999998
          - type: precision_at_5
            value: 16.991
          - type: recall_at_1
            value: 39.383
          - type: recall_at_10
            value: 76.175
          - type: recall_at_100
            value: 93.02
          - type: recall_at_1000
            value: 98.60900000000001
          - type: recall_at_3
            value: 60.265
          - type: recall_at_5
            value: 67.46600000000001
      - task:
          type: Retrieval
        dataset:
          name: MTEB CQADupstackGisRetrieval
          type: BeIR/cqadupstack
          config: default
          split: test
          revision: 5003b3064772da1887988e05400cf3806fe491f2
        metrics:
          - type: map_at_1
            value: 27.426000000000002
          - type: map_at_10
            value: 37.397000000000006
          - type: map_at_100
            value: 38.61
          - type: map_at_1000
            value: 38.678000000000004
          - type: map_at_3
            value: 34.150999999999996
          - type: map_at_5
            value: 36.137
          - type: mrr_at_1
            value: 29.944
          - type: mrr_at_10
            value: 39.654
          - type: mrr_at_100
            value: 40.638000000000005
          - type: mrr_at_1000
            value: 40.691
          - type: mrr_at_3
            value: 36.817
          - type: mrr_at_5
            value: 38.524
          - type: ndcg_at_1
            value: 29.944
          - type: ndcg_at_10
            value: 43.094
          - type: ndcg_at_100
            value: 48.789
          - type: ndcg_at_1000
            value: 50.339999999999996
          - type: ndcg_at_3
            value: 36.984
          - type: ndcg_at_5
            value: 40.248
          - type: precision_at_1
            value: 29.944
          - type: precision_at_10
            value: 6.78
          - type: precision_at_100
            value: 1.024
          - type: precision_at_1000
            value: 0.11800000000000001
          - type: precision_at_3
            value: 15.895000000000001
          - type: precision_at_5
            value: 11.39
          - type: recall_at_1
            value: 27.426000000000002
          - type: recall_at_10
            value: 58.464000000000006
          - type: recall_at_100
            value: 84.193
          - type: recall_at_1000
            value: 95.52000000000001
          - type: recall_at_3
            value: 42.172
          - type: recall_at_5
            value: 50.101
      - task:
          type: Retrieval
        dataset:
          name: MTEB CQADupstackMathematicaRetrieval
          type: BeIR/cqadupstack
          config: default
          split: test
          revision: 90fceea13679c63fe563ded68f3b6f06e50061de
        metrics:
          - type: map_at_1
            value: 19.721
          - type: map_at_10
            value: 31.604
          - type: map_at_100
            value: 32.972
          - type: map_at_1000
            value: 33.077
          - type: map_at_3
            value: 27.218999999999998
          - type: map_at_5
            value: 29.53
          - type: mrr_at_1
            value: 25
          - type: mrr_at_10
            value: 35.843
          - type: mrr_at_100
            value: 36.785000000000004
          - type: mrr_at_1000
            value: 36.842000000000006
          - type: mrr_at_3
            value: 32.193
          - type: mrr_at_5
            value: 34.264
          - type: ndcg_at_1
            value: 25
          - type: ndcg_at_10
            value: 38.606
          - type: ndcg_at_100
            value: 44.272
          - type: ndcg_at_1000
            value: 46.527
          - type: ndcg_at_3
            value: 30.985000000000003
          - type: ndcg_at_5
            value: 34.43
          - type: precision_at_1
            value: 25
          - type: precision_at_10
            value: 7.811
          - type: precision_at_100
            value: 1.203
          - type: precision_at_1000
            value: 0.15
          - type: precision_at_3
            value: 15.423
          - type: precision_at_5
            value: 11.791
          - type: recall_at_1
            value: 19.721
          - type: recall_at_10
            value: 55.625
          - type: recall_at_100
            value: 79.34400000000001
          - type: recall_at_1000
            value: 95.208
          - type: recall_at_3
            value: 35.19
          - type: recall_at_5
            value: 43.626
      - task:
          type: Retrieval
        dataset:
          name: MTEB CQADupstackPhysicsRetrieval
          type: BeIR/cqadupstack
          config: default
          split: test
          revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
        metrics:
          - type: map_at_1
            value: 33.784
          - type: map_at_10
            value: 47.522
          - type: map_at_100
            value: 48.949999999999996
          - type: map_at_1000
            value: 49.038
          - type: map_at_3
            value: 43.284
          - type: map_at_5
            value: 45.629
          - type: mrr_at_1
            value: 41.482
          - type: mrr_at_10
            value: 52.830999999999996
          - type: mrr_at_100
            value: 53.559999999999995
          - type: mrr_at_1000
            value: 53.588
          - type: mrr_at_3
            value: 50.016000000000005
          - type: mrr_at_5
            value: 51.614000000000004
          - type: ndcg_at_1
            value: 41.482
          - type: ndcg_at_10
            value: 54.569
          - type: ndcg_at_100
            value: 59.675999999999995
          - type: ndcg_at_1000
            value: 60.989000000000004
          - type: ndcg_at_3
            value: 48.187000000000005
          - type: ndcg_at_5
            value: 51.183
          - type: precision_at_1
            value: 41.482
          - type: precision_at_10
            value: 10.221
          - type: precision_at_100
            value: 1.486
          - type: precision_at_1000
            value: 0.17500000000000002
          - type: precision_at_3
            value: 23.548
          - type: precision_at_5
            value: 16.805
          - type: recall_at_1
            value: 33.784
          - type: recall_at_10
            value: 69.798
          - type: recall_at_100
            value: 90.098
          - type: recall_at_1000
            value: 98.176
          - type: recall_at_3
            value: 52.127
          - type: recall_at_5
            value: 59.861
      - task:
          type: Retrieval
        dataset:
          name: MTEB CQADupstackProgrammersRetrieval
          type: BeIR/cqadupstack
          config: default
          split: test
          revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
        metrics:
          - type: map_at_1
            value: 28.038999999999998
          - type: map_at_10
            value: 41.904
          - type: map_at_100
            value: 43.36
          - type: map_at_1000
            value: 43.453
          - type: map_at_3
            value: 37.785999999999994
          - type: map_at_5
            value: 40.105000000000004
          - type: mrr_at_1
            value: 35.046
          - type: mrr_at_10
            value: 46.926
          - type: mrr_at_100
            value: 47.815000000000005
          - type: mrr_at_1000
            value: 47.849000000000004
          - type: mrr_at_3
            value: 44.273
          - type: mrr_at_5
            value: 45.774
          - type: ndcg_at_1
            value: 35.046
          - type: ndcg_at_10
            value: 48.937000000000005
          - type: ndcg_at_100
            value: 54.544000000000004
          - type: ndcg_at_1000
            value: 56.069
          - type: ndcg_at_3
            value: 42.858000000000004
          - type: ndcg_at_5
            value: 45.644
          - type: precision_at_1
            value: 35.046
          - type: precision_at_10
            value: 9.452
          - type: precision_at_100
            value: 1.429
          - type: precision_at_1000
            value: 0.173
          - type: precision_at_3
            value: 21.346999999999998
          - type: precision_at_5
            value: 15.342
          - type: recall_at_1
            value: 28.038999999999998
          - type: recall_at_10
            value: 64.59700000000001
          - type: recall_at_100
            value: 87.735
          - type: recall_at_1000
            value: 97.41300000000001
          - type: recall_at_3
            value: 47.368
          - type: recall_at_5
            value: 54.93900000000001
      - task:
          type: Retrieval
        dataset:
          name: MTEB CQADupstackRetrieval
          type: BeIR/cqadupstack
          config: default
          split: test
          revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
        metrics:
          - type: map_at_1
            value: 28.17291666666667
          - type: map_at_10
            value: 40.025749999999995
          - type: map_at_100
            value: 41.39208333333333
          - type: map_at_1000
            value: 41.499249999999996
          - type: map_at_3
            value: 36.347
          - type: map_at_5
            value: 38.41391666666667
          - type: mrr_at_1
            value: 33.65925
          - type: mrr_at_10
            value: 44.085499999999996
          - type: mrr_at_100
            value: 44.94116666666667
          - type: mrr_at_1000
            value: 44.9855
          - type: mrr_at_3
            value: 41.2815
          - type: mrr_at_5
            value: 42.91491666666666
          - type: ndcg_at_1
            value: 33.65925
          - type: ndcg_at_10
            value: 46.430833333333325
          - type: ndcg_at_100
            value: 51.761
          - type: ndcg_at_1000
            value: 53.50899999999999
          - type: ndcg_at_3
            value: 40.45133333333333
          - type: ndcg_at_5
            value: 43.31483333333334
          - type: precision_at_1
            value: 33.65925
          - type: precision_at_10
            value: 8.4995
          - type: precision_at_100
            value: 1.3210000000000004
          - type: precision_at_1000
            value: 0.16591666666666666
          - type: precision_at_3
            value: 19.165083333333335
          - type: precision_at_5
            value: 13.81816666666667
          - type: recall_at_1
            value: 28.17291666666667
          - type: recall_at_10
            value: 61.12624999999999
          - type: recall_at_100
            value: 83.97266666666667
          - type: recall_at_1000
            value: 95.66550000000001
          - type: recall_at_3
            value: 44.661249999999995
          - type: recall_at_5
            value: 51.983333333333334
          - type: map_at_1
            value: 17.936
          - type: map_at_10
            value: 27.399
          - type: map_at_100
            value: 28.632
          - type: map_at_1000
            value: 28.738000000000003
          - type: map_at_3
            value: 24.456
          - type: map_at_5
            value: 26.06
          - type: mrr_at_1
            value: 19.224
          - type: mrr_at_10
            value: 28.998
          - type: mrr_at_100
            value: 30.11
          - type: mrr_at_1000
            value: 30.177
          - type: mrr_at_3
            value: 26.247999999999998
          - type: mrr_at_5
            value: 27.708
          - type: ndcg_at_1
            value: 19.224
          - type: ndcg_at_10
            value: 32.911
          - type: ndcg_at_100
            value: 38.873999999999995
          - type: ndcg_at_1000
            value: 41.277
          - type: ndcg_at_3
            value: 27.142
          - type: ndcg_at_5
            value: 29.755
          - type: precision_at_1
            value: 19.224
          - type: precision_at_10
            value: 5.6930000000000005
          - type: precision_at_100
            value: 0.9259999999999999
          - type: precision_at_1000
            value: 0.126
          - type: precision_at_3
            value: 12.138
          - type: precision_at_5
            value: 8.909
          - type: recall_at_1
            value: 17.936
          - type: recall_at_10
            value: 48.096
          - type: recall_at_100
            value: 75.389
          - type: recall_at_1000
            value: 92.803
          - type: recall_at_3
            value: 32.812999999999995
          - type: recall_at_5
            value: 38.851
      - task:
          type: Retrieval
        dataset:
          name: MTEB CQADupstackStatsRetrieval
          type: BeIR/cqadupstack
          config: default
          split: test
          revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
        metrics:
          - type: map_at_1
            value: 24.681
          - type: map_at_10
            value: 34.892
          - type: map_at_100
            value: 35.996
          - type: map_at_1000
            value: 36.083
          - type: map_at_3
            value: 31.491999999999997
          - type: map_at_5
            value: 33.632
          - type: mrr_at_1
            value: 28.528
          - type: mrr_at_10
            value: 37.694
          - type: mrr_at_100
            value: 38.613
          - type: mrr_at_1000
            value: 38.668
          - type: mrr_at_3
            value: 34.714
          - type: mrr_at_5
            value: 36.616
          - type: ndcg_at_1
            value: 28.528
          - type: ndcg_at_10
            value: 40.703
          - type: ndcg_at_100
            value: 45.993
          - type: ndcg_at_1000
            value: 47.847
          - type: ndcg_at_3
            value: 34.622
          - type: ndcg_at_5
            value: 38.035999999999994
          - type: precision_at_1
            value: 28.528
          - type: precision_at_10
            value: 6.902
          - type: precision_at_100
            value: 1.0370000000000001
          - type: precision_at_1000
            value: 0.126
          - type: precision_at_3
            value: 15.798000000000002
          - type: precision_at_5
            value: 11.655999999999999
          - type: recall_at_1
            value: 24.681
          - type: recall_at_10
            value: 55.81
          - type: recall_at_100
            value: 79.785
          - type: recall_at_1000
            value: 92.959
          - type: recall_at_3
            value: 39.074
          - type: recall_at_5
            value: 47.568
      - task:
          type: Retrieval
        dataset:
          name: MTEB CQADupstackTexRetrieval
          type: BeIR/cqadupstack
          config: default
          split: test
          revision: 46989137a86843e03a6195de44b09deda022eec7
        metrics:
          - type: map_at_1
            value: 18.627
          - type: map_at_10
            value: 27.872000000000003
          - type: map_at_100
            value: 29.237999999999996
          - type: map_at_1000
            value: 29.363
          - type: map_at_3
            value: 24.751
          - type: map_at_5
            value: 26.521
          - type: mrr_at_1
            value: 23.021
          - type: mrr_at_10
            value: 31.924000000000003
          - type: mrr_at_100
            value: 32.922000000000004
          - type: mrr_at_1000
            value: 32.988
          - type: mrr_at_3
            value: 29.192
          - type: mrr_at_5
            value: 30.798
          - type: ndcg_at_1
            value: 23.021
          - type: ndcg_at_10
            value: 33.535
          - type: ndcg_at_100
            value: 39.732
          - type: ndcg_at_1000
            value: 42.201
          - type: ndcg_at_3
            value: 28.153
          - type: ndcg_at_5
            value: 30.746000000000002
          - type: precision_at_1
            value: 23.021
          - type: precision_at_10
            value: 6.459
          - type: precision_at_100
            value: 1.1320000000000001
          - type: precision_at_1000
            value: 0.153
          - type: precision_at_3
            value: 13.719000000000001
          - type: precision_at_5
            value: 10.193000000000001
          - type: recall_at_1
            value: 18.627
          - type: recall_at_10
            value: 46.463
          - type: recall_at_100
            value: 74.226
          - type: recall_at_1000
            value: 91.28500000000001
          - type: recall_at_3
            value: 31.357000000000003
          - type: recall_at_5
            value: 38.067
      - task:
          type: Retrieval
        dataset:
          name: MTEB CQADupstackUnixRetrieval
          type: BeIR/cqadupstack
          config: default
          split: test
          revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
        metrics:
          - type: map_at_1
            value: 31.457
          - type: map_at_10
            value: 42.888
          - type: map_at_100
            value: 44.24
          - type: map_at_1000
            value: 44.327
          - type: map_at_3
            value: 39.588
          - type: map_at_5
            value: 41.423
          - type: mrr_at_1
            value: 37.126999999999995
          - type: mrr_at_10
            value: 47.083000000000006
          - type: mrr_at_100
            value: 47.997
          - type: mrr_at_1000
            value: 48.044
          - type: mrr_at_3
            value: 44.574000000000005
          - type: mrr_at_5
            value: 46.202
          - type: ndcg_at_1
            value: 37.126999999999995
          - type: ndcg_at_10
            value: 48.833
          - type: ndcg_at_100
            value: 54.327000000000005
          - type: ndcg_at_1000
            value: 56.011
          - type: ndcg_at_3
            value: 43.541999999999994
          - type: ndcg_at_5
            value: 46.127
          - type: precision_at_1
            value: 37.126999999999995
          - type: precision_at_10
            value: 8.376999999999999
          - type: precision_at_100
            value: 1.2309999999999999
          - type: precision_at_1000
            value: 0.146
          - type: precision_at_3
            value: 20.211000000000002
          - type: precision_at_5
            value: 14.16
          - type: recall_at_1
            value: 31.457
          - type: recall_at_10
            value: 62.369
          - type: recall_at_100
            value: 85.444
          - type: recall_at_1000
            value: 96.65599999999999
          - type: recall_at_3
            value: 47.961
          - type: recall_at_5
            value: 54.676
      - task:
          type: Retrieval
        dataset:
          name: MTEB CQADupstackWebmastersRetrieval
          type: BeIR/cqadupstack
          config: default
          split: test
          revision: 160c094312a0e1facb97e55eeddb698c0abe3571
        metrics:
          - type: map_at_1
            value: 27.139999999999997
          - type: map_at_10
            value: 38.801
          - type: map_at_100
            value: 40.549
          - type: map_at_1000
            value: 40.802
          - type: map_at_3
            value: 35.05
          - type: map_at_5
            value: 36.884
          - type: mrr_at_1
            value: 33.004
          - type: mrr_at_10
            value: 43.864
          - type: mrr_at_100
            value: 44.667
          - type: mrr_at_1000
            value: 44.717
          - type: mrr_at_3
            value: 40.777
          - type: mrr_at_5
            value: 42.319
          - type: ndcg_at_1
            value: 33.004
          - type: ndcg_at_10
            value: 46.022
          - type: ndcg_at_100
            value: 51.542
          - type: ndcg_at_1000
            value: 53.742000000000004
          - type: ndcg_at_3
            value: 39.795
          - type: ndcg_at_5
            value: 42.272
          - type: precision_at_1
            value: 33.004
          - type: precision_at_10
            value: 9.012
          - type: precision_at_100
            value: 1.7770000000000001
          - type: precision_at_1000
            value: 0.26
          - type: precision_at_3
            value: 19.038
          - type: precision_at_5
            value: 13.675999999999998
          - type: recall_at_1
            value: 27.139999999999997
          - type: recall_at_10
            value: 60.961
          - type: recall_at_100
            value: 84.451
          - type: recall_at_1000
            value: 98.113
          - type: recall_at_3
            value: 43.001
          - type: recall_at_5
            value: 49.896
      - task:
          type: Retrieval
        dataset:
          name: MTEB ClimateFEVER
          type: mteb/climate-fever
          config: default
          split: test
          revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
        metrics:
          - type: map_at_1
            value: 22.076999999999998
          - type: map_at_10
            value: 35.44
          - type: map_at_100
            value: 37.651
          - type: map_at_1000
            value: 37.824999999999996
          - type: map_at_3
            value: 30.764999999999997
          - type: map_at_5
            value: 33.26
          - type: mrr_at_1
            value: 50.163000000000004
          - type: mrr_at_10
            value: 61.207
          - type: mrr_at_100
            value: 61.675000000000004
          - type: mrr_at_1000
            value: 61.692
          - type: mrr_at_3
            value: 58.60999999999999
          - type: mrr_at_5
            value: 60.307
          - type: ndcg_at_1
            value: 50.163000000000004
          - type: ndcg_at_10
            value: 45.882
          - type: ndcg_at_100
            value: 53.239999999999995
          - type: ndcg_at_1000
            value: 55.852000000000004
          - type: ndcg_at_3
            value: 40.514
          - type: ndcg_at_5
            value: 42.038
          - type: precision_at_1
            value: 50.163000000000004
          - type: precision_at_10
            value: 13.466000000000001
          - type: precision_at_100
            value: 2.164
          - type: precision_at_1000
            value: 0.266
          - type: precision_at_3
            value: 29.707
          - type: precision_at_5
            value: 21.694
          - type: recall_at_1
            value: 22.076999999999998
          - type: recall_at_10
            value: 50.193
          - type: recall_at_100
            value: 74.993
          - type: recall_at_1000
            value: 89.131
          - type: recall_at_3
            value: 35.472
          - type: recall_at_5
            value: 41.814
      - task:
          type: Retrieval
        dataset:
          name: MTEB DBPedia
          type: mteb/dbpedia
          config: default
          split: test
          revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
        metrics:
          - type: map_at_1
            value: 9.953
          - type: map_at_10
            value: 24.515
          - type: map_at_100
            value: 36.173
          - type: map_at_1000
            value: 38.351
          - type: map_at_3
            value: 16.592000000000002
          - type: map_at_5
            value: 20.036
          - type: mrr_at_1
            value: 74.25
          - type: mrr_at_10
            value: 81.813
          - type: mrr_at_100
            value: 82.006
          - type: mrr_at_1000
            value: 82.011
          - type: mrr_at_3
            value: 80.875
          - type: mrr_at_5
            value: 81.362
          - type: ndcg_at_1
            value: 62.5
          - type: ndcg_at_10
            value: 52.42
          - type: ndcg_at_100
            value: 56.808
          - type: ndcg_at_1000
            value: 63.532999999999994
          - type: ndcg_at_3
            value: 56.654
          - type: ndcg_at_5
            value: 54.18300000000001
          - type: precision_at_1
            value: 74.25
          - type: precision_at_10
            value: 42.699999999999996
          - type: precision_at_100
            value: 13.675
          - type: precision_at_1000
            value: 2.664
          - type: precision_at_3
            value: 60.5
          - type: precision_at_5
            value: 52.800000000000004
          - type: recall_at_1
            value: 9.953
          - type: recall_at_10
            value: 30.253999999999998
          - type: recall_at_100
            value: 62.516000000000005
          - type: recall_at_1000
            value: 84.163
          - type: recall_at_3
            value: 18.13
          - type: recall_at_5
            value: 22.771
      - task:
          type: Classification
        dataset:
          name: MTEB EmotionClassification
          type: mteb/emotion
          config: default
          split: test
          revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
        metrics:
          - type: accuracy
            value: 79.455
          - type: f1
            value: 74.16798697647569
      - task:
          type: Retrieval
        dataset:
          name: MTEB FEVER
          type: mteb/fever
          config: default
          split: test
          revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
        metrics:
          - type: map_at_1
            value: 87.531
          - type: map_at_10
            value: 93.16799999999999
          - type: map_at_100
            value: 93.341
          - type: map_at_1000
            value: 93.349
          - type: map_at_3
            value: 92.444
          - type: map_at_5
            value: 92.865
          - type: mrr_at_1
            value: 94.014
          - type: mrr_at_10
            value: 96.761
          - type: mrr_at_100
            value: 96.762
          - type: mrr_at_1000
            value: 96.762
          - type: mrr_at_3
            value: 96.672
          - type: mrr_at_5
            value: 96.736
          - type: ndcg_at_1
            value: 94.014
          - type: ndcg_at_10
            value: 95.112
          - type: ndcg_at_100
            value: 95.578
          - type: ndcg_at_1000
            value: 95.68900000000001
          - type: ndcg_at_3
            value: 94.392
          - type: ndcg_at_5
            value: 94.72500000000001
          - type: precision_at_1
            value: 94.014
          - type: precision_at_10
            value: 11.065
          - type: precision_at_100
            value: 1.157
          - type: precision_at_1000
            value: 0.11800000000000001
          - type: precision_at_3
            value: 35.259
          - type: precision_at_5
            value: 21.599
          - type: recall_at_1
            value: 87.531
          - type: recall_at_10
            value: 97.356
          - type: recall_at_100
            value: 98.965
          - type: recall_at_1000
            value: 99.607
          - type: recall_at_3
            value: 95.312
          - type: recall_at_5
            value: 96.295
      - task:
          type: Retrieval
        dataset:
          name: MTEB FiQA2018
          type: mteb/fiqa
          config: default
          split: test
          revision: 27a168819829fe9bcd655c2df245fb19452e8e06
        metrics:
          - type: map_at_1
            value: 32.055
          - type: map_at_10
            value: 53.114
          - type: map_at_100
            value: 55.235
          - type: map_at_1000
            value: 55.345
          - type: map_at_3
            value: 45.854
          - type: map_at_5
            value: 50.025
          - type: mrr_at_1
            value: 60.34
          - type: mrr_at_10
            value: 68.804
          - type: mrr_at_100
            value: 69.309
          - type: mrr_at_1000
            value: 69.32199999999999
          - type: mrr_at_3
            value: 66.40899999999999
          - type: mrr_at_5
            value: 67.976
          - type: ndcg_at_1
            value: 60.34
          - type: ndcg_at_10
            value: 62.031000000000006
          - type: ndcg_at_100
            value: 68.00500000000001
          - type: ndcg_at_1000
            value: 69.286
          - type: ndcg_at_3
            value: 56.355999999999995
          - type: ndcg_at_5
            value: 58.687
          - type: precision_at_1
            value: 60.34
          - type: precision_at_10
            value: 17.176
          - type: precision_at_100
            value: 2.36
          - type: precision_at_1000
            value: 0.259
          - type: precision_at_3
            value: 37.14
          - type: precision_at_5
            value: 27.809
          - type: recall_at_1
            value: 32.055
          - type: recall_at_10
            value: 70.91
          - type: recall_at_100
            value: 91.83
          - type: recall_at_1000
            value: 98.871
          - type: recall_at_3
            value: 51.202999999999996
          - type: recall_at_5
            value: 60.563
      - task:
          type: Retrieval
        dataset:
          name: MTEB HotpotQA
          type: mteb/hotpotqa
          config: default
          split: test
          revision: ab518f4d6fcca38d87c25209f94beba119d02014
        metrics:
          - type: map_at_1
            value: 43.68
          - type: map_at_10
            value: 64.389
          - type: map_at_100
            value: 65.24
          - type: map_at_1000
            value: 65.303
          - type: map_at_3
            value: 61.309000000000005
          - type: map_at_5
            value: 63.275999999999996
          - type: mrr_at_1
            value: 87.36
          - type: mrr_at_10
            value: 91.12
          - type: mrr_at_100
            value: 91.227
          - type: mrr_at_1000
            value: 91.229
          - type: mrr_at_3
            value: 90.57600000000001
          - type: mrr_at_5
            value: 90.912
          - type: ndcg_at_1
            value: 87.36
          - type: ndcg_at_10
            value: 73.076
          - type: ndcg_at_100
            value: 75.895
          - type: ndcg_at_1000
            value: 77.049
          - type: ndcg_at_3
            value: 68.929
          - type: ndcg_at_5
            value: 71.28
          - type: precision_at_1
            value: 87.36
          - type: precision_at_10
            value: 14.741000000000001
          - type: precision_at_100
            value: 1.694
          - type: precision_at_1000
            value: 0.185
          - type: precision_at_3
            value: 43.043
          - type: precision_at_5
            value: 27.681
          - type: recall_at_1
            value: 43.68
          - type: recall_at_10
            value: 73.707
          - type: recall_at_100
            value: 84.7
          - type: recall_at_1000
            value: 92.309
          - type: recall_at_3
            value: 64.564
          - type: recall_at_5
            value: 69.203
      - task:
          type: Classification
        dataset:
          name: MTEB ImdbClassification
          type: mteb/imdb
          config: default
          split: test
          revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
        metrics:
          - type: accuracy
            value: 96.75399999999999
          - type: ap
            value: 95.29389839242187
          - type: f1
            value: 96.75348377433475
      - task:
          type: Retrieval
        dataset:
          name: MTEB MSMARCO
          type: mteb/msmarco
          config: default
          split: dev
          revision: c5a29a104738b98a9e76336939199e264163d4a0
        metrics:
          - type: map_at_1
            value: 25.176
          - type: map_at_10
            value: 38.598
          - type: map_at_100
            value: 39.707
          - type: map_at_1000
            value: 39.744
          - type: map_at_3
            value: 34.566
          - type: map_at_5
            value: 36.863
          - type: mrr_at_1
            value: 25.874000000000002
          - type: mrr_at_10
            value: 39.214
          - type: mrr_at_100
            value: 40.251
          - type: mrr_at_1000
            value: 40.281
          - type: mrr_at_3
            value: 35.291
          - type: mrr_at_5
            value: 37.545
          - type: ndcg_at_1
            value: 25.874000000000002
          - type: ndcg_at_10
            value: 45.98
          - type: ndcg_at_100
            value: 51.197
          - type: ndcg_at_1000
            value: 52.073
          - type: ndcg_at_3
            value: 37.785999999999994
          - type: ndcg_at_5
            value: 41.870000000000005
          - type: precision_at_1
            value: 25.874000000000002
          - type: precision_at_10
            value: 7.181
          - type: precision_at_100
            value: 0.979
          - type: precision_at_1000
            value: 0.106
          - type: precision_at_3
            value: 16.051000000000002
          - type: precision_at_5
            value: 11.713
          - type: recall_at_1
            value: 25.176
          - type: recall_at_10
            value: 68.67699999999999
          - type: recall_at_100
            value: 92.55
          - type: recall_at_1000
            value: 99.164
          - type: recall_at_3
            value: 46.372
          - type: recall_at_5
            value: 56.16
      - task:
          type: Classification
        dataset:
          name: MTEB MTOPDomainClassification (en)
          type: mteb/mtop_domain
          config: en
          split: test
          revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
        metrics:
          - type: accuracy
            value: 99.03784769721841
          - type: f1
            value: 98.97791641821495
      - task:
          type: Classification
        dataset:
          name: MTEB MTOPIntentClassification (en)
          type: mteb/mtop_intent
          config: en
          split: test
          revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
        metrics:
          - type: accuracy
            value: 91.88326493388054
          - type: f1
            value: 73.74809928034335
      - task:
          type: Classification
        dataset:
          name: MTEB MassiveIntentClassification (en)
          type: mteb/amazon_massive_intent
          config: en
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 85.41358439811701
          - type: f1
            value: 83.503679460639
      - task:
          type: Classification
        dataset:
          name: MTEB MassiveScenarioClassification (en)
          type: mteb/amazon_massive_scenario
          config: en
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 89.77135171486215
          - type: f1
            value: 88.89843747468366
      - task:
          type: Clustering
        dataset:
          name: MTEB MedrxivClusteringP2P
          type: mteb/medrxiv-clustering-p2p
          config: default
          split: test
          revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
        metrics:
          - type: v_measure
            value: 46.22695362087359
      - task:
          type: Clustering
        dataset:
          name: MTEB MedrxivClusteringS2S
          type: mteb/medrxiv-clustering-s2s
          config: default
          split: test
          revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
        metrics:
          - type: v_measure
            value: 44.132372165849425
      - task:
          type: Reranking
        dataset:
          name: MTEB MindSmallReranking
          type: mteb/mind_small
          config: default
          split: test
          revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
        metrics:
          - type: map
            value: 33.35680810650402
          - type: mrr
            value: 34.72625715637218
      - task:
          type: Retrieval
        dataset:
          name: MTEB NFCorpus
          type: mteb/nfcorpus
          config: default
          split: test
          revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
        metrics:
          - type: map_at_1
            value: 7.165000000000001
          - type: map_at_10
            value: 15.424
          - type: map_at_100
            value: 20.28
          - type: map_at_1000
            value: 22.065
          - type: map_at_3
            value: 11.236
          - type: map_at_5
            value: 13.025999999999998
          - type: mrr_at_1
            value: 51.702999999999996
          - type: mrr_at_10
            value: 59.965
          - type: mrr_at_100
            value: 60.667
          - type: mrr_at_1000
            value: 60.702999999999996
          - type: mrr_at_3
            value: 58.772000000000006
          - type: mrr_at_5
            value: 59.267
          - type: ndcg_at_1
            value: 49.536
          - type: ndcg_at_10
            value: 40.6
          - type: ndcg_at_100
            value: 37.848
          - type: ndcg_at_1000
            value: 46.657
          - type: ndcg_at_3
            value: 46.117999999999995
          - type: ndcg_at_5
            value: 43.619
          - type: precision_at_1
            value: 51.393
          - type: precision_at_10
            value: 30.31
          - type: precision_at_100
            value: 9.972
          - type: precision_at_1000
            value: 2.329
          - type: precision_at_3
            value: 43.137
          - type: precision_at_5
            value: 37.585
          - type: recall_at_1
            value: 7.165000000000001
          - type: recall_at_10
            value: 19.689999999999998
          - type: recall_at_100
            value: 39.237
          - type: recall_at_1000
            value: 71.417
          - type: recall_at_3
            value: 12.247
          - type: recall_at_5
            value: 14.902999999999999
      - task:
          type: Retrieval
        dataset:
          name: MTEB NQ
          type: mteb/nq
          config: default
          split: test
          revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
        metrics:
          - type: map_at_1
            value: 42.653999999999996
          - type: map_at_10
            value: 59.611999999999995
          - type: map_at_100
            value: 60.32300000000001
          - type: map_at_1000
            value: 60.336
          - type: map_at_3
            value: 55.584999999999994
          - type: map_at_5
            value: 58.19
          - type: mrr_at_1
            value: 47.683
          - type: mrr_at_10
            value: 62.06700000000001
          - type: mrr_at_100
            value: 62.537
          - type: mrr_at_1000
            value: 62.544999999999995
          - type: mrr_at_3
            value: 59.178
          - type: mrr_at_5
            value: 61.034
          - type: ndcg_at_1
            value: 47.654
          - type: ndcg_at_10
            value: 67.001
          - type: ndcg_at_100
            value: 69.73899999999999
          - type: ndcg_at_1000
            value: 69.986
          - type: ndcg_at_3
            value: 59.95700000000001
          - type: ndcg_at_5
            value: 64.025
          - type: precision_at_1
            value: 47.654
          - type: precision_at_10
            value: 10.367999999999999
          - type: precision_at_100
            value: 1.192
          - type: precision_at_1000
            value: 0.121
          - type: precision_at_3
            value: 26.651000000000003
          - type: precision_at_5
            value: 18.459
          - type: recall_at_1
            value: 42.653999999999996
          - type: recall_at_10
            value: 86.619
          - type: recall_at_100
            value: 98.04899999999999
          - type: recall_at_1000
            value: 99.812
          - type: recall_at_3
            value: 68.987
          - type: recall_at_5
            value: 78.158
      - task:
          type: Retrieval
        dataset:
          name: MTEB QuoraRetrieval
          type: mteb/quora
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 72.538
          - type: map_at_10
            value: 86.702
          - type: map_at_100
            value: 87.31
          - type: map_at_1000
            value: 87.323
          - type: map_at_3
            value: 83.87
          - type: map_at_5
            value: 85.682
          - type: mrr_at_1
            value: 83.31
          - type: mrr_at_10
            value: 89.225
          - type: mrr_at_100
            value: 89.30399999999999
          - type: mrr_at_1000
            value: 89.30399999999999
          - type: mrr_at_3
            value: 88.44300000000001
          - type: mrr_at_5
            value: 89.005
          - type: ndcg_at_1
            value: 83.32000000000001
          - type: ndcg_at_10
            value: 90.095
          - type: ndcg_at_100
            value: 91.12
          - type: ndcg_at_1000
            value: 91.179
          - type: ndcg_at_3
            value: 87.606
          - type: ndcg_at_5
            value: 89.031
          - type: precision_at_1
            value: 83.32000000000001
          - type: precision_at_10
            value: 13.641
          - type: precision_at_100
            value: 1.541
          - type: precision_at_1000
            value: 0.157
          - type: precision_at_3
            value: 38.377
          - type: precision_at_5
            value: 25.162000000000003
          - type: recall_at_1
            value: 72.538
          - type: recall_at_10
            value: 96.47200000000001
          - type: recall_at_100
            value: 99.785
          - type: recall_at_1000
            value: 99.99900000000001
          - type: recall_at_3
            value: 89.278
          - type: recall_at_5
            value: 93.367
      - task:
          type: Clustering
        dataset:
          name: MTEB RedditClustering
          type: mteb/reddit-clustering
          config: default
          split: test
          revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
        metrics:
          - type: v_measure
            value: 73.55219145406065
      - task:
          type: Clustering
        dataset:
          name: MTEB RedditClusteringP2P
          type: mteb/reddit-clustering-p2p
          config: default
          split: test
          revision: 282350215ef01743dc01b456c7f5241fa8937f16
        metrics:
          - type: v_measure
            value: 74.13437105242755
      - task:
          type: Retrieval
        dataset:
          name: MTEB SCIDOCS
          type: mteb/scidocs
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 6.873
          - type: map_at_10
            value: 17.944
          - type: map_at_100
            value: 21.171
          - type: map_at_1000
            value: 21.528
          - type: map_at_3
            value: 12.415
          - type: map_at_5
            value: 15.187999999999999
          - type: mrr_at_1
            value: 33.800000000000004
          - type: mrr_at_10
            value: 46.455
          - type: mrr_at_100
            value: 47.378
          - type: mrr_at_1000
            value: 47.394999999999996
          - type: mrr_at_3
            value: 42.367
          - type: mrr_at_5
            value: 44.972
          - type: ndcg_at_1
            value: 33.800000000000004
          - type: ndcg_at_10
            value: 28.907
          - type: ndcg_at_100
            value: 39.695
          - type: ndcg_at_1000
            value: 44.582
          - type: ndcg_at_3
            value: 26.949
          - type: ndcg_at_5
            value: 23.988
          - type: precision_at_1
            value: 33.800000000000004
          - type: precision_at_10
            value: 15.079999999999998
          - type: precision_at_100
            value: 3.056
          - type: precision_at_1000
            value: 0.42100000000000004
          - type: precision_at_3
            value: 25.167
          - type: precision_at_5
            value: 21.26
          - type: recall_at_1
            value: 6.873
          - type: recall_at_10
            value: 30.568
          - type: recall_at_100
            value: 62.062
          - type: recall_at_1000
            value: 85.37700000000001
          - type: recall_at_3
            value: 15.312999999999999
          - type: recall_at_5
            value: 21.575
      - task:
          type: STS
        dataset:
          name: MTEB SICK-R
          type: mteb/sickr-sts
          config: default
          split: test
          revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
        metrics:
          - type: cos_sim_pearson
            value: 82.37009118256057
          - type: cos_sim_spearman
            value: 79.27986395671529
          - type: euclidean_pearson
            value: 79.18037715442115
          - type: euclidean_spearman
            value: 79.28004791561621
          - type: manhattan_pearson
            value: 79.34062972800541
          - type: manhattan_spearman
            value: 79.43106695543402
      - task:
          type: STS
        dataset:
          name: MTEB STS12
          type: mteb/sts12-sts
          config: default
          split: test
          revision: a0d554a64d88156834ff5ae9920b964011b16384
        metrics:
          - type: cos_sim_pearson
            value: 87.48474767383833
          - type: cos_sim_spearman
            value: 79.54505388752513
          - type: euclidean_pearson
            value: 83.43282704179565
          - type: euclidean_spearman
            value: 79.54579919925405
          - type: manhattan_pearson
            value: 83.77564492427952
          - type: manhattan_spearman
            value: 79.84558396989286
      - task:
          type: STS
        dataset:
          name: MTEB STS13
          type: mteb/sts13-sts
          config: default
          split: test
          revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
        metrics:
          - type: cos_sim_pearson
            value: 88.803698035802
          - type: cos_sim_spearman
            value: 88.83451367754881
          - type: euclidean_pearson
            value: 88.28939285711628
          - type: euclidean_spearman
            value: 88.83528996073112
          - type: manhattan_pearson
            value: 88.28017412671795
          - type: manhattan_spearman
            value: 88.9228828016344
      - task:
          type: STS
        dataset:
          name: MTEB STS14
          type: mteb/sts14-sts
          config: default
          split: test
          revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
        metrics:
          - type: cos_sim_pearson
            value: 85.27469288153428
          - type: cos_sim_spearman
            value: 83.87477064876288
          - type: euclidean_pearson
            value: 84.2601737035379
          - type: euclidean_spearman
            value: 83.87431082479074
          - type: manhattan_pearson
            value: 84.3621547772745
          - type: manhattan_spearman
            value: 84.12094375000423
      - task:
          type: STS
        dataset:
          name: MTEB STS15
          type: mteb/sts15-sts
          config: default
          split: test
          revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
        metrics:
          - type: cos_sim_pearson
            value: 88.12749863201587
          - type: cos_sim_spearman
            value: 88.54287568368565
          - type: euclidean_pearson
            value: 87.90429700607999
          - type: euclidean_spearman
            value: 88.5437689576261
          - type: manhattan_pearson
            value: 88.19276653356833
          - type: manhattan_spearman
            value: 88.99995393814679
      - task:
          type: STS
        dataset:
          name: MTEB STS16
          type: mteb/sts16-sts
          config: default
          split: test
          revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
        metrics:
          - type: cos_sim_pearson
            value: 85.68398747560902
          - type: cos_sim_spearman
            value: 86.48815303460574
          - type: euclidean_pearson
            value: 85.52356631237954
          - type: euclidean_spearman
            value: 86.486391949551
          - type: manhattan_pearson
            value: 85.67267981761788
          - type: manhattan_spearman
            value: 86.7073696332485
      - task:
          type: STS
        dataset:
          name: MTEB STS17 (en-en)
          type: mteb/sts17-crosslingual-sts
          config: en-en
          split: test
          revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
        metrics:
          - type: cos_sim_pearson
            value: 88.9057107443124
          - type: cos_sim_spearman
            value: 88.7312168757697
          - type: euclidean_pearson
            value: 88.72810439714794
          - type: euclidean_spearman
            value: 88.71976185854771
          - type: manhattan_pearson
            value: 88.50433745949111
          - type: manhattan_spearman
            value: 88.51726175544195
      - task:
          type: STS
        dataset:
          name: MTEB STS22 (en)
          type: mteb/sts22-crosslingual-sts
          config: en
          split: test
          revision: eea2b4fe26a775864c896887d910b76a8098ad3f
        metrics:
          - type: cos_sim_pearson
            value: 67.59391795109886
          - type: cos_sim_spearman
            value: 66.87613008631367
          - type: euclidean_pearson
            value: 69.23198488262217
          - type: euclidean_spearman
            value: 66.85427723013692
          - type: manhattan_pearson
            value: 69.50730124841084
          - type: manhattan_spearman
            value: 67.10404669820792
      - task:
          type: STS
        dataset:
          name: MTEB STSBenchmark
          type: mteb/stsbenchmark-sts
          config: default
          split: test
          revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
        metrics:
          - type: cos_sim_pearson
            value: 87.0820605344619
          - type: cos_sim_spearman
            value: 86.8518089863434
          - type: euclidean_pearson
            value: 86.31087134689284
          - type: euclidean_spearman
            value: 86.8518520517941
          - type: manhattan_pearson
            value: 86.47203796160612
          - type: manhattan_spearman
            value: 87.1080149734421
      - task:
          type: Reranking
        dataset:
          name: MTEB SciDocsRR
          type: mteb/scidocs-reranking
          config: default
          split: test
          revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
        metrics:
          - type: map
            value: 89.09255369305481
          - type: mrr
            value: 97.10323445617563
      - task:
          type: Retrieval
        dataset:
          name: MTEB SciFact
          type: mteb/scifact
          config: default
          split: test
          revision: 0228b52cf27578f30900b9e5271d331663a030d7
        metrics:
          - type: map_at_1
            value: 61.260999999999996
          - type: map_at_10
            value: 74.043
          - type: map_at_100
            value: 74.37700000000001
          - type: map_at_1000
            value: 74.384
          - type: map_at_3
            value: 71.222
          - type: map_at_5
            value: 72.875
          - type: mrr_at_1
            value: 64.333
          - type: mrr_at_10
            value: 74.984
          - type: mrr_at_100
            value: 75.247
          - type: mrr_at_1000
            value: 75.25500000000001
          - type: mrr_at_3
            value: 73.167
          - type: mrr_at_5
            value: 74.35000000000001
          - type: ndcg_at_1
            value: 64.333
          - type: ndcg_at_10
            value: 79.06
          - type: ndcg_at_100
            value: 80.416
          - type: ndcg_at_1000
            value: 80.55600000000001
          - type: ndcg_at_3
            value: 74.753
          - type: ndcg_at_5
            value: 76.97500000000001
          - type: precision_at_1
            value: 64.333
          - type: precision_at_10
            value: 10.567
          - type: precision_at_100
            value: 1.1199999999999999
          - type: precision_at_1000
            value: 0.11299999999999999
          - type: precision_at_3
            value: 29.889
          - type: precision_at_5
            value: 19.533
          - type: recall_at_1
            value: 61.260999999999996
          - type: recall_at_10
            value: 93.167
          - type: recall_at_100
            value: 99
          - type: recall_at_1000
            value: 100
          - type: recall_at_3
            value: 81.667
          - type: recall_at_5
            value: 87.394
      - task:
          type: PairClassification
        dataset:
          name: MTEB SprintDuplicateQuestions
          type: mteb/sprintduplicatequestions-pairclassification
          config: default
          split: test
          revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
        metrics:
          - type: cos_sim_accuracy
            value: 99.71980198019801
          - type: cos_sim_ap
            value: 92.81616007802704
          - type: cos_sim_f1
            value: 85.17548454688318
          - type: cos_sim_precision
            value: 89.43894389438944
          - type: cos_sim_recall
            value: 81.3
          - type: dot_accuracy
            value: 99.71980198019801
          - type: dot_ap
            value: 92.81398760591358
          - type: dot_f1
            value: 85.17548454688318
          - type: dot_precision
            value: 89.43894389438944
          - type: dot_recall
            value: 81.3
          - type: euclidean_accuracy
            value: 99.71980198019801
          - type: euclidean_ap
            value: 92.81560637245072
          - type: euclidean_f1
            value: 85.17548454688318
          - type: euclidean_precision
            value: 89.43894389438944
          - type: euclidean_recall
            value: 81.3
          - type: manhattan_accuracy
            value: 99.73069306930694
          - type: manhattan_ap
            value: 93.14005487480794
          - type: manhattan_f1
            value: 85.56263269639068
          - type: manhattan_precision
            value: 91.17647058823529
          - type: manhattan_recall
            value: 80.60000000000001
          - type: max_accuracy
            value: 99.73069306930694
          - type: max_ap
            value: 93.14005487480794
          - type: max_f1
            value: 85.56263269639068
      - task:
          type: Clustering
        dataset:
          name: MTEB StackExchangeClustering
          type: mteb/stackexchange-clustering
          config: default
          split: test
          revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
        metrics:
          - type: v_measure
            value: 79.86443362395185
      - task:
          type: Clustering
        dataset:
          name: MTEB StackExchangeClusteringP2P
          type: mteb/stackexchange-clustering-p2p
          config: default
          split: test
          revision: 815ca46b2622cec33ccafc3735d572c266efdb44
        metrics:
          - type: v_measure
            value: 49.40897096662564
      - task:
          type: Reranking
        dataset:
          name: MTEB StackOverflowDupQuestions
          type: mteb/stackoverflowdupquestions-reranking
          config: default
          split: test
          revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
        metrics:
          - type: map
            value: 55.66040806627947
          - type: mrr
            value: 56.58670475766064
      - task:
          type: Summarization
        dataset:
          name: MTEB SummEval
          type: mteb/summeval
          config: default
          split: test
          revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
        metrics:
          - type: cos_sim_pearson
            value: 31.51015090598575
          - type: cos_sim_spearman
            value: 31.35016454939226
          - type: dot_pearson
            value: 31.5150068731
          - type: dot_spearman
            value: 31.34790869023487
      - task:
          type: Retrieval
        dataset:
          name: MTEB TRECCOVID
          type: mteb/trec-covid
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 0.254
          - type: map_at_10
            value: 2.064
          - type: map_at_100
            value: 12.909
          - type: map_at_1000
            value: 31.761
          - type: map_at_3
            value: 0.738
          - type: map_at_5
            value: 1.155
          - type: mrr_at_1
            value: 96
          - type: mrr_at_10
            value: 98
          - type: mrr_at_100
            value: 98
          - type: mrr_at_1000
            value: 98
          - type: mrr_at_3
            value: 98
          - type: mrr_at_5
            value: 98
          - type: ndcg_at_1
            value: 93
          - type: ndcg_at_10
            value: 82.258
          - type: ndcg_at_100
            value: 64.34
          - type: ndcg_at_1000
            value: 57.912
          - type: ndcg_at_3
            value: 90.827
          - type: ndcg_at_5
            value: 86.79
          - type: precision_at_1
            value: 96
          - type: precision_at_10
            value: 84.8
          - type: precision_at_100
            value: 66
          - type: precision_at_1000
            value: 25.356
          - type: precision_at_3
            value: 94.667
          - type: precision_at_5
            value: 90.4
          - type: recall_at_1
            value: 0.254
          - type: recall_at_10
            value: 2.1950000000000003
          - type: recall_at_100
            value: 16.088
          - type: recall_at_1000
            value: 54.559000000000005
          - type: recall_at_3
            value: 0.75
          - type: recall_at_5
            value: 1.191
      - task:
          type: Retrieval
        dataset:
          name: MTEB Touche2020
          type: mteb/touche2020
          config: default
          split: test
          revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
        metrics:
          - type: map_at_1
            value: 2.976
          - type: map_at_10
            value: 11.389000000000001
          - type: map_at_100
            value: 18.429000000000002
          - type: map_at_1000
            value: 20.113
          - type: map_at_3
            value: 6.483
          - type: map_at_5
            value: 8.770999999999999
          - type: mrr_at_1
            value: 40.816
          - type: mrr_at_10
            value: 58.118
          - type: mrr_at_100
            value: 58.489999999999995
          - type: mrr_at_1000
            value: 58.489999999999995
          - type: mrr_at_3
            value: 53.061
          - type: mrr_at_5
            value: 57.041
          - type: ndcg_at_1
            value: 40.816
          - type: ndcg_at_10
            value: 30.567
          - type: ndcg_at_100
            value: 42.44
          - type: ndcg_at_1000
            value: 53.480000000000004
          - type: ndcg_at_3
            value: 36.016
          - type: ndcg_at_5
            value: 34.257
          - type: precision_at_1
            value: 42.857
          - type: precision_at_10
            value: 25.714
          - type: precision_at_100
            value: 8.429
          - type: precision_at_1000
            value: 1.5939999999999999
          - type: precision_at_3
            value: 36.735
          - type: precision_at_5
            value: 33.878
          - type: recall_at_1
            value: 2.976
          - type: recall_at_10
            value: 17.854999999999997
          - type: recall_at_100
            value: 51.833
          - type: recall_at_1000
            value: 86.223
          - type: recall_at_3
            value: 7.887
          - type: recall_at_5
            value: 12.026
      - task:
          type: Classification
        dataset:
          name: MTEB ToxicConversationsClassification
          type: mteb/toxic_conversations_50k
          config: default
          split: test
          revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
        metrics:
          - type: accuracy
            value: 85.1174
          - type: ap
            value: 30.169441069345748
          - type: f1
            value: 69.79254701873245
      - task:
          type: Classification
        dataset:
          name: MTEB TweetSentimentExtractionClassification
          type: mteb/tweet_sentiment_extraction
          config: default
          split: test
          revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
        metrics:
          - type: accuracy
            value: 72.58347481607245
          - type: f1
            value: 72.74877295564937
      - task:
          type: Clustering
        dataset:
          name: MTEB TwentyNewsgroupsClustering
          type: mteb/twentynewsgroups-clustering
          config: default
          split: test
          revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
        metrics:
          - type: v_measure
            value: 53.90586138221305
      - task:
          type: PairClassification
        dataset:
          name: MTEB TwitterSemEval2015
          type: mteb/twittersemeval2015-pairclassification
          config: default
          split: test
          revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
        metrics:
          - type: cos_sim_accuracy
            value: 87.35769207844072
          - type: cos_sim_ap
            value: 77.9645072410354
          - type: cos_sim_f1
            value: 71.32352941176471
          - type: cos_sim_precision
            value: 66.5903890160183
          - type: cos_sim_recall
            value: 76.78100263852242
          - type: dot_accuracy
            value: 87.37557370209214
          - type: dot_ap
            value: 77.96250046429908
          - type: dot_f1
            value: 71.28932757557064
          - type: dot_precision
            value: 66.95249130938586
          - type: dot_recall
            value: 76.22691292875989
          - type: euclidean_accuracy
            value: 87.35173153722357
          - type: euclidean_ap
            value: 77.96520460741593
          - type: euclidean_f1
            value: 71.32470733210104
          - type: euclidean_precision
            value: 66.91329479768785
          - type: euclidean_recall
            value: 76.35883905013192
          - type: manhattan_accuracy
            value: 87.25636287774931
          - type: manhattan_ap
            value: 77.77752485611796
          - type: manhattan_f1
            value: 71.18148599269183
          - type: manhattan_precision
            value: 66.10859728506787
          - type: manhattan_recall
            value: 77.0976253298153
          - type: max_accuracy
            value: 87.37557370209214
          - type: max_ap
            value: 77.96520460741593
          - type: max_f1
            value: 71.32470733210104
      - task:
          type: PairClassification
        dataset:
          name: MTEB TwitterURLCorpus
          type: mteb/twitterurlcorpus-pairclassification
          config: default
          split: test
          revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
        metrics:
          - type: cos_sim_accuracy
            value: 89.38176737687739
          - type: cos_sim_ap
            value: 86.58811861657401
          - type: cos_sim_f1
            value: 79.09430644097604
          - type: cos_sim_precision
            value: 75.45085977911366
          - type: cos_sim_recall
            value: 83.10748383122882
          - type: dot_accuracy
            value: 89.38370784336554
          - type: dot_ap
            value: 86.58840606004333
          - type: dot_f1
            value: 79.10179860068133
          - type: dot_precision
            value: 75.44546153308643
          - type: dot_recall
            value: 83.13058207576223
          - type: euclidean_accuracy
            value: 89.38564830985369
          - type: euclidean_ap
            value: 86.58820721061164
          - type: euclidean_f1
            value: 79.09070942235888
          - type: euclidean_precision
            value: 75.38729937194697
          - type: euclidean_recall
            value: 83.17677856482906
          - type: manhattan_accuracy
            value: 89.40699344122326
          - type: manhattan_ap
            value: 86.60631843011362
          - type: manhattan_f1
            value: 79.14949970570925
          - type: manhattan_precision
            value: 75.78191039729502
          - type: manhattan_recall
            value: 82.83030489682784
          - type: max_accuracy
            value: 89.40699344122326
          - type: max_ap
            value: 86.60631843011362
          - type: max_f1
            value: 79.14949970570925
      - task:
          type: STS
        dataset:
          name: MTEB AFQMC
          type: C-MTEB/AFQMC
          config: default
          split: validation
          revision: b44c3b011063adb25877c13823db83bb193913c4
        metrics:
          - type: cos_sim_pearson
            value: 65.58442135663871
          - type: cos_sim_spearman
            value: 72.2538631361313
          - type: euclidean_pearson
            value: 70.97255486607429
          - type: euclidean_spearman
            value: 72.25374250228647
          - type: manhattan_pearson
            value: 70.83250199989911
          - type: manhattan_spearman
            value: 72.14819496536272
      - task:
          type: STS
        dataset:
          name: MTEB ATEC
          type: C-MTEB/ATEC
          config: default
          split: test
          revision: 0f319b1142f28d00e055a6770f3f726ae9b7d865
        metrics:
          - type: cos_sim_pearson
            value: 59.99478404929932
          - type: cos_sim_spearman
            value: 62.61836216999812
          - type: euclidean_pearson
            value: 66.86429811933593
          - type: euclidean_spearman
            value: 62.6183520374191
          - type: manhattan_pearson
            value: 66.8063778911633
          - type: manhattan_spearman
            value: 62.569607573241115
      - task:
          type: Classification
        dataset:
          name: MTEB AmazonReviewsClassification (zh)
          type: mteb/amazon_reviews_multi
          config: zh
          split: test
          revision: 1399c76144fd37290681b995c656ef9b2e06e26d
        metrics:
          - type: accuracy
            value: 53.98400000000001
          - type: f1
            value: 51.21447361350723
      - task:
          type: STS
        dataset:
          name: MTEB BQ
          type: C-MTEB/BQ
          config: default
          split: test
          revision: e3dda5e115e487b39ec7e618c0c6a29137052a55
        metrics:
          - type: cos_sim_pearson
            value: 79.11941660686553
          - type: cos_sim_spearman
            value: 81.25029594540435
          - type: euclidean_pearson
            value: 82.06973504238826
          - type: euclidean_spearman
            value: 81.2501989488524
          - type: manhattan_pearson
            value: 82.10094630392753
          - type: manhattan_spearman
            value: 81.27987244392389
      - task:
          type: Clustering
        dataset:
          name: MTEB CLSClusteringP2P
          type: C-MTEB/CLSClusteringP2P
          config: default
          split: test
          revision: 4b6227591c6c1a73bc76b1055f3b7f3588e72476
        metrics:
          - type: v_measure
            value: 47.07270168705156
      - task:
          type: Clustering
        dataset:
          name: MTEB CLSClusteringS2S
          type: C-MTEB/CLSClusteringS2S
          config: default
          split: test
          revision: e458b3f5414b62b7f9f83499ac1f5497ae2e869f
        metrics:
          - type: v_measure
            value: 45.98511703185043
      - task:
          type: Reranking
        dataset:
          name: MTEB CMedQAv1
          type: C-MTEB/CMedQAv1-reranking
          config: default
          split: test
          revision: 8d7f1e942507dac42dc58017c1a001c3717da7df
        metrics:
          - type: map
            value: 88.19895157194931
          - type: mrr
            value: 90.21424603174603
      - task:
          type: Reranking
        dataset:
          name: MTEB CMedQAv2
          type: C-MTEB/CMedQAv2-reranking
          config: default
          split: test
          revision: 23d186750531a14a0357ca22cd92d712fd512ea0
        metrics:
          - type: map
            value: 88.03317320980119
          - type: mrr
            value: 89.9461507936508
      - task:
          type: Retrieval
        dataset:
          name: MTEB CmedqaRetrieval
          type: C-MTEB/CmedqaRetrieval
          config: default
          split: dev
          revision: cd540c506dae1cf9e9a59c3e06f42030d54e7301
        metrics:
          - type: map_at_1
            value: 29.037000000000003
          - type: map_at_10
            value: 42.001
          - type: map_at_100
            value: 43.773
          - type: map_at_1000
            value: 43.878
          - type: map_at_3
            value: 37.637
          - type: map_at_5
            value: 40.034
          - type: mrr_at_1
            value: 43.136
          - type: mrr_at_10
            value: 51.158
          - type: mrr_at_100
            value: 52.083
          - type: mrr_at_1000
            value: 52.12
          - type: mrr_at_3
            value: 48.733
          - type: mrr_at_5
            value: 50.025
          - type: ndcg_at_1
            value: 43.136
          - type: ndcg_at_10
            value: 48.685
          - type: ndcg_at_100
            value: 55.513
          - type: ndcg_at_1000
            value: 57.242000000000004
          - type: ndcg_at_3
            value: 43.329
          - type: ndcg_at_5
            value: 45.438
          - type: precision_at_1
            value: 43.136
          - type: precision_at_10
            value: 10.56
          - type: precision_at_100
            value: 1.6129999999999998
          - type: precision_at_1000
            value: 0.184
          - type: precision_at_3
            value: 24.064
          - type: precision_at_5
            value: 17.269000000000002
          - type: recall_at_1
            value: 29.037000000000003
          - type: recall_at_10
            value: 59.245000000000005
          - type: recall_at_100
            value: 87.355
          - type: recall_at_1000
            value: 98.74000000000001
          - type: recall_at_3
            value: 42.99
          - type: recall_at_5
            value: 49.681999999999995
      - task:
          type: PairClassification
        dataset:
          name: MTEB Cmnli
          type: C-MTEB/CMNLI
          config: default
          split: validation
          revision: 41bc36f332156f7adc9e38f53777c959b2ae9766
        metrics:
          - type: cos_sim_accuracy
            value: 82.68190018039687
          - type: cos_sim_ap
            value: 90.18017125327886
          - type: cos_sim_f1
            value: 83.64080906868193
          - type: cos_sim_precision
            value: 79.7076890489303
          - type: cos_sim_recall
            value: 87.98223053542202
          - type: dot_accuracy
            value: 82.68190018039687
          - type: dot_ap
            value: 90.18782350103646
          - type: dot_f1
            value: 83.64242087729039
          - type: dot_precision
            value: 79.65313028764805
          - type: dot_recall
            value: 88.05237315875614
          - type: euclidean_accuracy
            value: 82.68190018039687
          - type: euclidean_ap
            value: 90.1801957900632
          - type: euclidean_f1
            value: 83.63636363636364
          - type: euclidean_precision
            value: 79.52772506852203
          - type: euclidean_recall
            value: 88.19265840542437
          - type: manhattan_accuracy
            value: 82.14070956103427
          - type: manhattan_ap
            value: 89.96178420101427
          - type: manhattan_f1
            value: 83.21087838578791
          - type: manhattan_precision
            value: 78.35605121850475
          - type: manhattan_recall
            value: 88.70703764320785
          - type: max_accuracy
            value: 82.68190018039687
          - type: max_ap
            value: 90.18782350103646
          - type: max_f1
            value: 83.64242087729039
      - task:
          type: Retrieval
        dataset:
          name: MTEB CovidRetrieval
          type: C-MTEB/CovidRetrieval
          config: default
          split: dev
          revision: 1271c7809071a13532e05f25fb53511ffce77117
        metrics:
          - type: map_at_1
            value: 72.234
          - type: map_at_10
            value: 80.10000000000001
          - type: map_at_100
            value: 80.36
          - type: map_at_1000
            value: 80.363
          - type: map_at_3
            value: 78.315
          - type: map_at_5
            value: 79.607
          - type: mrr_at_1
            value: 72.392
          - type: mrr_at_10
            value: 80.117
          - type: mrr_at_100
            value: 80.36999999999999
          - type: mrr_at_1000
            value: 80.373
          - type: mrr_at_3
            value: 78.469
          - type: mrr_at_5
            value: 79.633
          - type: ndcg_at_1
            value: 72.392
          - type: ndcg_at_10
            value: 83.651
          - type: ndcg_at_100
            value: 84.749
          - type: ndcg_at_1000
            value: 84.83000000000001
          - type: ndcg_at_3
            value: 80.253
          - type: ndcg_at_5
            value: 82.485
          - type: precision_at_1
            value: 72.392
          - type: precision_at_10
            value: 9.557
          - type: precision_at_100
            value: 1.004
          - type: precision_at_1000
            value: 0.101
          - type: precision_at_3
            value: 28.732000000000003
          - type: precision_at_5
            value: 18.377
          - type: recall_at_1
            value: 72.234
          - type: recall_at_10
            value: 94.573
          - type: recall_at_100
            value: 99.368
          - type: recall_at_1000
            value: 100
          - type: recall_at_3
            value: 85.669
          - type: recall_at_5
            value: 91.01700000000001
      - task:
          type: Retrieval
        dataset:
          name: MTEB DuRetrieval
          type: C-MTEB/DuRetrieval
          config: default
          split: dev
          revision: a1a333e290fe30b10f3f56498e3a0d911a693ced
        metrics:
          - type: map_at_1
            value: 26.173999999999996
          - type: map_at_10
            value: 80.04
          - type: map_at_100
            value: 82.94500000000001
          - type: map_at_1000
            value: 82.98100000000001
          - type: map_at_3
            value: 55.562999999999995
          - type: map_at_5
            value: 69.89800000000001
          - type: mrr_at_1
            value: 89.5
          - type: mrr_at_10
            value: 92.996
          - type: mrr_at_100
            value: 93.06400000000001
          - type: mrr_at_1000
            value: 93.065
          - type: mrr_at_3
            value: 92.658
          - type: mrr_at_5
            value: 92.84599999999999
          - type: ndcg_at_1
            value: 89.5
          - type: ndcg_at_10
            value: 87.443
          - type: ndcg_at_100
            value: 90.253
          - type: ndcg_at_1000
            value: 90.549
          - type: ndcg_at_3
            value: 85.874
          - type: ndcg_at_5
            value: 84.842
          - type: precision_at_1
            value: 89.5
          - type: precision_at_10
            value: 41.805
          - type: precision_at_100
            value: 4.827
          - type: precision_at_1000
            value: 0.49
          - type: precision_at_3
            value: 76.85
          - type: precision_at_5
            value: 64.8
          - type: recall_at_1
            value: 26.173999999999996
          - type: recall_at_10
            value: 89.101
          - type: recall_at_100
            value: 98.08099999999999
          - type: recall_at_1000
            value: 99.529
          - type: recall_at_3
            value: 57.902
          - type: recall_at_5
            value: 74.602
      - task:
          type: Retrieval
        dataset:
          name: MTEB EcomRetrieval
          type: C-MTEB/EcomRetrieval
          config: default
          split: dev
          revision: 687de13dc7294d6fd9be10c6945f9e8fec8166b9
        metrics:
          - type: map_at_1
            value: 56.10000000000001
          - type: map_at_10
            value: 66.15299999999999
          - type: map_at_100
            value: 66.625
          - type: map_at_1000
            value: 66.636
          - type: map_at_3
            value: 63.632999999999996
          - type: map_at_5
            value: 65.293
          - type: mrr_at_1
            value: 56.10000000000001
          - type: mrr_at_10
            value: 66.15299999999999
          - type: mrr_at_100
            value: 66.625
          - type: mrr_at_1000
            value: 66.636
          - type: mrr_at_3
            value: 63.632999999999996
          - type: mrr_at_5
            value: 65.293
          - type: ndcg_at_1
            value: 56.10000000000001
          - type: ndcg_at_10
            value: 71.146
          - type: ndcg_at_100
            value: 73.27799999999999
          - type: ndcg_at_1000
            value: 73.529
          - type: ndcg_at_3
            value: 66.09
          - type: ndcg_at_5
            value: 69.08999999999999
          - type: precision_at_1
            value: 56.10000000000001
          - type: precision_at_10
            value: 8.68
          - type: precision_at_100
            value: 0.964
          - type: precision_at_1000
            value: 0.098
          - type: precision_at_3
            value: 24.4
          - type: precision_at_5
            value: 16.1
          - type: recall_at_1
            value: 56.10000000000001
          - type: recall_at_10
            value: 86.8
          - type: recall_at_100
            value: 96.39999999999999
          - type: recall_at_1000
            value: 98.3
          - type: recall_at_3
            value: 73.2
          - type: recall_at_5
            value: 80.5
      - task:
          type: Classification
        dataset:
          name: MTEB IFlyTek
          type: C-MTEB/IFlyTek-classification
          config: default
          split: validation
          revision: 421605374b29664c5fc098418fe20ada9bd55f8a
        metrics:
          - type: accuracy
            value: 54.52096960369373
          - type: f1
            value: 40.930845295808695
      - task:
          type: Classification
        dataset:
          name: MTEB JDReview
          type: C-MTEB/JDReview-classification
          config: default
          split: test
          revision: b7c64bd89eb87f8ded463478346f76731f07bf8b
        metrics:
          - type: accuracy
            value: 86.51031894934334
          - type: ap
            value: 55.9516014323483
          - type: f1
            value: 81.54813679326381
      - task:
          type: STS
        dataset:
          name: MTEB LCQMC
          type: C-MTEB/LCQMC
          config: default
          split: test
          revision: 17f9b096f80380fce5ed12a9be8be7784b337daf
        metrics:
          - type: cos_sim_pearson
            value: 69.67437838574276
          - type: cos_sim_spearman
            value: 73.81314174653045
          - type: euclidean_pearson
            value: 72.63430276680275
          - type: euclidean_spearman
            value: 73.81358736777001
          - type: manhattan_pearson
            value: 72.58743833842829
          - type: manhattan_spearman
            value: 73.7590419009179
      - task:
          type: Reranking
        dataset:
          name: MTEB MMarcoReranking
          type: C-MTEB/Mmarco-reranking
          config: default
          split: dev
          revision: None
        metrics:
          - type: map
            value: 31.648613483640254
          - type: mrr
            value: 30.37420634920635
      - task:
          type: Retrieval
        dataset:
          name: MTEB MMarcoRetrieval
          type: C-MTEB/MMarcoRetrieval
          config: default
          split: dev
          revision: 539bbde593d947e2a124ba72651aafc09eb33fc2
        metrics:
          - type: map_at_1
            value: 73.28099999999999
          - type: map_at_10
            value: 81.977
          - type: map_at_100
            value: 82.222
          - type: map_at_1000
            value: 82.22699999999999
          - type: map_at_3
            value: 80.441
          - type: map_at_5
            value: 81.46600000000001
          - type: mrr_at_1
            value: 75.673
          - type: mrr_at_10
            value: 82.41000000000001
          - type: mrr_at_100
            value: 82.616
          - type: mrr_at_1000
            value: 82.621
          - type: mrr_at_3
            value: 81.094
          - type: mrr_at_5
            value: 81.962
          - type: ndcg_at_1
            value: 75.673
          - type: ndcg_at_10
            value: 85.15599999999999
          - type: ndcg_at_100
            value: 86.151
          - type: ndcg_at_1000
            value: 86.26899999999999
          - type: ndcg_at_3
            value: 82.304
          - type: ndcg_at_5
            value: 84.009
          - type: precision_at_1
            value: 75.673
          - type: precision_at_10
            value: 10.042
          - type: precision_at_100
            value: 1.052
          - type: precision_at_1000
            value: 0.106
          - type: precision_at_3
            value: 30.673000000000002
          - type: precision_at_5
            value: 19.326999999999998
          - type: recall_at_1
            value: 73.28099999999999
          - type: recall_at_10
            value: 94.446
          - type: recall_at_100
            value: 98.737
          - type: recall_at_1000
            value: 99.649
          - type: recall_at_3
            value: 86.984
          - type: recall_at_5
            value: 91.024
      - task:
          type: Classification
        dataset:
          name: MTEB MassiveIntentClassification (zh-CN)
          type: mteb/amazon_massive_intent
          config: zh-CN
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 81.08607935440484
          - type: f1
            value: 78.24879986066307
      - task:
          type: Classification
        dataset:
          name: MTEB MassiveScenarioClassification (zh-CN)
          type: mteb/amazon_massive_scenario
          config: zh-CN
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 86.05917955615332
          - type: f1
            value: 85.05279279434997
      - task:
          type: Retrieval
        dataset:
          name: MTEB MedicalRetrieval
          type: C-MTEB/MedicalRetrieval
          config: default
          split: dev
          revision: 2039188fb5800a9803ba5048df7b76e6fb151fc6
        metrics:
          - type: map_at_1
            value: 56.2
          - type: map_at_10
            value: 62.57899999999999
          - type: map_at_100
            value: 63.154999999999994
          - type: map_at_1000
            value: 63.193
          - type: map_at_3
            value: 61.217
          - type: map_at_5
            value: 62.012
          - type: mrr_at_1
            value: 56.3
          - type: mrr_at_10
            value: 62.629000000000005
          - type: mrr_at_100
            value: 63.205999999999996
          - type: mrr_at_1000
            value: 63.244
          - type: mrr_at_3
            value: 61.267
          - type: mrr_at_5
            value: 62.062
          - type: ndcg_at_1
            value: 56.2
          - type: ndcg_at_10
            value: 65.592
          - type: ndcg_at_100
            value: 68.657
          - type: ndcg_at_1000
            value: 69.671
          - type: ndcg_at_3
            value: 62.808
          - type: ndcg_at_5
            value: 64.24499999999999
          - type: precision_at_1
            value: 56.2
          - type: precision_at_10
            value: 7.5
          - type: precision_at_100
            value: 0.899
          - type: precision_at_1000
            value: 0.098
          - type: precision_at_3
            value: 22.467000000000002
          - type: precision_at_5
            value: 14.180000000000001
          - type: recall_at_1
            value: 56.2
          - type: recall_at_10
            value: 75
          - type: recall_at_100
            value: 89.9
          - type: recall_at_1000
            value: 97.89999999999999
          - type: recall_at_3
            value: 67.4
          - type: recall_at_5
            value: 70.89999999999999
      - task:
          type: Classification
        dataset:
          name: MTEB MultilingualSentiment
          type: C-MTEB/MultilingualSentiment-classification
          config: default
          split: validation
          revision: 46958b007a63fdbf239b7672c25d0bea67b5ea1a
        metrics:
          - type: accuracy
            value: 76.87666666666667
          - type: f1
            value: 76.7317686219665
      - task:
          type: PairClassification
        dataset:
          name: MTEB Ocnli
          type: C-MTEB/OCNLI
          config: default
          split: validation
          revision: 66e76a618a34d6d565d5538088562851e6daa7ec
        metrics:
          - type: cos_sim_accuracy
            value: 79.64266377910124
          - type: cos_sim_ap
            value: 84.78274442344829
          - type: cos_sim_f1
            value: 81.16947472745292
          - type: cos_sim_precision
            value: 76.47058823529412
          - type: cos_sim_recall
            value: 86.48363252375924
          - type: dot_accuracy
            value: 79.64266377910124
          - type: dot_ap
            value: 84.7851404063692
          - type: dot_f1
            value: 81.16947472745292
          - type: dot_precision
            value: 76.47058823529412
          - type: dot_recall
            value: 86.48363252375924
          - type: euclidean_accuracy
            value: 79.64266377910124
          - type: euclidean_ap
            value: 84.78068373762378
          - type: euclidean_f1
            value: 81.14794656110837
          - type: euclidean_precision
            value: 76.35009310986965
          - type: euclidean_recall
            value: 86.58922914466737
          - type: manhattan_accuracy
            value: 79.48023822414727
          - type: manhattan_ap
            value: 84.72928897427576
          - type: manhattan_f1
            value: 81.32084770823064
          - type: manhattan_precision
            value: 76.24768946395564
          - type: manhattan_recall
            value: 87.11721224920802
          - type: max_accuracy
            value: 79.64266377910124
          - type: max_ap
            value: 84.7851404063692
          - type: max_f1
            value: 81.32084770823064
      - task:
          type: Classification
        dataset:
          name: MTEB OnlineShopping
          type: C-MTEB/OnlineShopping-classification
          config: default
          split: test
          revision: e610f2ebd179a8fda30ae534c3878750a96db120
        metrics:
          - type: accuracy
            value: 94.3
          - type: ap
            value: 92.8664032274438
          - type: f1
            value: 94.29311102997727
      - task:
          type: STS
        dataset:
          name: MTEB PAWSX
          type: C-MTEB/PAWSX
          config: default
          split: test
          revision: 9c6a90e430ac22b5779fb019a23e820b11a8b5e1
        metrics:
          - type: cos_sim_pearson
            value: 48.51392279882909
          - type: cos_sim_spearman
            value: 54.06338895994974
          - type: euclidean_pearson
            value: 52.58480559573412
          - type: euclidean_spearman
            value: 54.06417276612201
          - type: manhattan_pearson
            value: 52.69525121721343
          - type: manhattan_spearman
            value: 54.048147455389675
      - task:
          type: STS
        dataset:
          name: MTEB QBQTC
          type: C-MTEB/QBQTC
          config: default
          split: test
          revision: 790b0510dc52b1553e8c49f3d2afb48c0e5c48b7
        metrics:
          - type: cos_sim_pearson
            value: 29.728387290757325
          - type: cos_sim_spearman
            value: 31.366121633635284
          - type: euclidean_pearson
            value: 29.14588368552961
          - type: euclidean_spearman
            value: 31.36764411112844
          - type: manhattan_pearson
            value: 29.63517350523121
          - type: manhattan_spearman
            value: 31.94157020583762
      - task:
          type: STS
        dataset:
          name: MTEB STS22 (zh)
          type: mteb/sts22-crosslingual-sts
          config: zh
          split: test
          revision: eea2b4fe26a775864c896887d910b76a8098ad3f
        metrics:
          - type: cos_sim_pearson
            value: 63.64868296271406
          - type: cos_sim_spearman
            value: 66.12800618164744
          - type: euclidean_pearson
            value: 63.21405767340238
          - type: euclidean_spearman
            value: 66.12786567790748
          - type: manhattan_pearson
            value: 64.04300276525848
          - type: manhattan_spearman
            value: 66.5066857145652
      - task:
          type: STS
        dataset:
          name: MTEB STSB
          type: C-MTEB/STSB
          config: default
          split: test
          revision: 0cde68302b3541bb8b3c340dc0644b0b745b3dc0
        metrics:
          - type: cos_sim_pearson
            value: 81.2302623912794
          - type: cos_sim_spearman
            value: 81.16833673266562
          - type: euclidean_pearson
            value: 79.47647843876024
          - type: euclidean_spearman
            value: 81.16944349524972
          - type: manhattan_pearson
            value: 79.84947238492208
          - type: manhattan_spearman
            value: 81.64626599410026
      - task:
          type: Reranking
        dataset:
          name: MTEB T2Reranking
          type: C-MTEB/T2Reranking
          config: default
          split: dev
          revision: 76631901a18387f85eaa53e5450019b87ad58ef9
        metrics:
          - type: map
            value: 67.80129586475687
          - type: mrr
            value: 77.77402311635554
      - task:
          type: Retrieval
        dataset:
          name: MTEB T2Retrieval
          type: C-MTEB/T2Retrieval
          config: default
          split: dev
          revision: 8731a845f1bf500a4f111cf1070785c793d10e64
        metrics:
          - type: map_at_1
            value: 28.666999999999998
          - type: map_at_10
            value: 81.063
          - type: map_at_100
            value: 84.504
          - type: map_at_1000
            value: 84.552
          - type: map_at_3
            value: 56.897
          - type: map_at_5
            value: 70.073
          - type: mrr_at_1
            value: 92.087
          - type: mrr_at_10
            value: 94.132
          - type: mrr_at_100
            value: 94.19800000000001
          - type: mrr_at_1000
            value: 94.19999999999999
          - type: mrr_at_3
            value: 93.78999999999999
          - type: mrr_at_5
            value: 94.002
          - type: ndcg_at_1
            value: 92.087
          - type: ndcg_at_10
            value: 87.734
          - type: ndcg_at_100
            value: 90.736
          - type: ndcg_at_1000
            value: 91.184
          - type: ndcg_at_3
            value: 88.78
          - type: ndcg_at_5
            value: 87.676
          - type: precision_at_1
            value: 92.087
          - type: precision_at_10
            value: 43.46
          - type: precision_at_100
            value: 5.07
          - type: precision_at_1000
            value: 0.518
          - type: precision_at_3
            value: 77.49000000000001
          - type: precision_at_5
            value: 65.194
          - type: recall_at_1
            value: 28.666999999999998
          - type: recall_at_10
            value: 86.632
          - type: recall_at_100
            value: 96.646
          - type: recall_at_1000
            value: 98.917
          - type: recall_at_3
            value: 58.333999999999996
          - type: recall_at_5
            value: 72.974
      - task:
          type: Classification
        dataset:
          name: MTEB TNews
          type: C-MTEB/TNews-classification
          config: default
          split: validation
          revision: 317f262bf1e6126357bbe89e875451e4b0938fe4
        metrics:
          - type: accuracy
            value: 52.971999999999994
          - type: f1
            value: 50.2898280984929
      - task:
          type: Clustering
        dataset:
          name: MTEB ThuNewsClusteringP2P
          type: C-MTEB/ThuNewsClusteringP2P
          config: default
          split: test
          revision: 5798586b105c0434e4f0fe5e767abe619442cf93
        metrics:
          - type: v_measure
            value: 86.0797948663824
      - task:
          type: Clustering
        dataset:
          name: MTEB ThuNewsClusteringS2S
          type: C-MTEB/ThuNewsClusteringS2S
          config: default
          split: test
          revision: 8a8b2caeda43f39e13c4bc5bea0f8a667896e10d
        metrics:
          - type: v_measure
            value: 85.10759092255017
      - task:
          type: Retrieval
        dataset:
          name: MTEB VideoRetrieval
          type: C-MTEB/VideoRetrieval
          config: default
          split: dev
          revision: 58c2597a5943a2ba48f4668c3b90d796283c5639
        metrics:
          - type: map_at_1
            value: 65.60000000000001
          - type: map_at_10
            value: 74.773
          - type: map_at_100
            value: 75.128
          - type: map_at_1000
            value: 75.136
          - type: map_at_3
            value: 73.05
          - type: map_at_5
            value: 74.13499999999999
          - type: mrr_at_1
            value: 65.60000000000001
          - type: mrr_at_10
            value: 74.773
          - type: mrr_at_100
            value: 75.128
          - type: mrr_at_1000
            value: 75.136
          - type: mrr_at_3
            value: 73.05
          - type: mrr_at_5
            value: 74.13499999999999
          - type: ndcg_at_1
            value: 65.60000000000001
          - type: ndcg_at_10
            value: 78.84299999999999
          - type: ndcg_at_100
            value: 80.40899999999999
          - type: ndcg_at_1000
            value: 80.57
          - type: ndcg_at_3
            value: 75.40599999999999
          - type: ndcg_at_5
            value: 77.351
          - type: precision_at_1
            value: 65.60000000000001
          - type: precision_at_10
            value: 9.139999999999999
          - type: precision_at_100
            value: 0.984
          - type: precision_at_1000
            value: 0.1
          - type: precision_at_3
            value: 27.400000000000002
          - type: precision_at_5
            value: 17.380000000000003
          - type: recall_at_1
            value: 65.60000000000001
          - type: recall_at_10
            value: 91.4
          - type: recall_at_100
            value: 98.4
          - type: recall_at_1000
            value: 99.6
          - type: recall_at_3
            value: 82.19999999999999
          - type: recall_at_5
            value: 86.9
      - task:
          type: Classification
        dataset:
          name: MTEB Waimai
          type: C-MTEB/waimai-classification
          config: default
          split: test
          revision: 339287def212450dcaa9df8c22bf93e9980c7023
        metrics:
          - type: accuracy
            value: 89.47
          - type: ap
            value: 75.59561751845389
          - type: f1
            value: 87.95207751382563
      - task:
          type: Clustering
        dataset:
          name: MTEB AlloProfClusteringP2P
          type: lyon-nlp/alloprof
          config: default
          split: test
          revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b
        metrics:
          - type: v_measure
            value: 76.05592323841036
          - type: v_measure
            value: 64.51718058866508
      - task:
          type: Reranking
        dataset:
          name: MTEB AlloprofReranking
          type: lyon-nlp/mteb-fr-reranking-alloprof-s2p
          config: default
          split: test
          revision: 666fdacebe0291776e86f29345663dfaf80a0db9
        metrics:
          - type: map
            value: 73.08278490943373
          - type: mrr
            value: 74.66561454570449
      - task:
          type: Retrieval
        dataset:
          name: MTEB AlloprofRetrieval
          type: lyon-nlp/alloprof
          config: default
          split: test
          revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b
        metrics:
          - type: map_at_1
            value: 38.912
          - type: map_at_10
            value: 52.437999999999995
          - type: map_at_100
            value: 53.38
          - type: map_at_1000
            value: 53.427
          - type: map_at_3
            value: 48.879
          - type: map_at_5
            value: 50.934000000000005
          - type: mrr_at_1
            value: 44.085
          - type: mrr_at_10
            value: 55.337
          - type: mrr_at_100
            value: 56.016999999999996
          - type: mrr_at_1000
            value: 56.043
          - type: mrr_at_3
            value: 52.55499999999999
          - type: mrr_at_5
            value: 54.20399999999999
          - type: ndcg_at_1
            value: 44.085
          - type: ndcg_at_10
            value: 58.876
          - type: ndcg_at_100
            value: 62.714000000000006
          - type: ndcg_at_1000
            value: 63.721000000000004
          - type: ndcg_at_3
            value: 52.444
          - type: ndcg_at_5
            value: 55.692
          - type: precision_at_1
            value: 44.085
          - type: precision_at_10
            value: 9.21
          - type: precision_at_100
            value: 1.164
          - type: precision_at_1000
            value: 0.128
          - type: precision_at_3
            value: 23.043
          - type: precision_at_5
            value: 15.898000000000001
          - type: recall_at_1
            value: 38.912
          - type: recall_at_10
            value: 75.577
          - type: recall_at_100
            value: 92.038
          - type: recall_at_1000
            value: 99.325
          - type: recall_at_3
            value: 58.592
          - type: recall_at_5
            value: 66.235
      - task:
          type: Classification
        dataset:
          name: MTEB AmazonReviewsClassification (fr)
          type: mteb/amazon_reviews_multi
          config: fr
          split: test
          revision: 1399c76144fd37290681b995c656ef9b2e06e26d
        metrics:
          - type: accuracy
            value: 55.532000000000004
          - type: f1
            value: 52.5783943471605
      - task:
          type: Retrieval
        dataset:
          name: MTEB BSARDRetrieval
          type: maastrichtlawtech/bsard
          config: default
          split: test
          revision: 5effa1b9b5fa3b0f9e12523e6e43e5f86a6e6d59
        metrics:
          - type: map_at_1
            value: 8.108
          - type: map_at_10
            value: 14.710999999999999
          - type: map_at_100
            value: 15.891
          - type: map_at_1000
            value: 15.983
          - type: map_at_3
            value: 12.237
          - type: map_at_5
            value: 13.679
          - type: mrr_at_1
            value: 8.108
          - type: mrr_at_10
            value: 14.710999999999999
          - type: mrr_at_100
            value: 15.891
          - type: mrr_at_1000
            value: 15.983
          - type: mrr_at_3
            value: 12.237
          - type: mrr_at_5
            value: 13.679
          - type: ndcg_at_1
            value: 8.108
          - type: ndcg_at_10
            value: 18.796
          - type: ndcg_at_100
            value: 25.098
          - type: ndcg_at_1000
            value: 27.951999999999998
          - type: ndcg_at_3
            value: 13.712
          - type: ndcg_at_5
            value: 16.309
          - type: precision_at_1
            value: 8.108
          - type: precision_at_10
            value: 3.198
          - type: precision_at_100
            value: 0.626
          - type: precision_at_1000
            value: 0.086
          - type: precision_at_3
            value: 6.006
          - type: precision_at_5
            value: 4.865
          - type: recall_at_1
            value: 8.108
          - type: recall_at_10
            value: 31.982
          - type: recall_at_100
            value: 62.613
          - type: recall_at_1000
            value: 86.036
          - type: recall_at_3
            value: 18.018
          - type: recall_at_5
            value: 24.324
      - task:
          type: Clustering
        dataset:
          name: MTEB HALClusteringS2S
          type: lyon-nlp/clustering-hal-s2s
          config: default
          split: test
          revision: e06ebbbb123f8144bef1a5d18796f3dec9ae2915
        metrics:
          - type: v_measure
            value: 30.833269778867116
      - task:
          type: Clustering
        dataset:
          name: MTEB MLSUMClusteringP2P
          type: mlsum
          config: default
          split: test
          revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7
        metrics:
          - type: v_measure
            value: 50.0281928004713
          - type: v_measure
            value: 43.699961510636534
      - task:
          type: Classification
        dataset:
          name: MTEB MTOPDomainClassification (fr)
          type: mteb/mtop_domain
          config: fr
          split: test
          revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
        metrics:
          - type: accuracy
            value: 96.68963357344191
          - type: f1
            value: 96.45175170820961
      - task:
          type: Classification
        dataset:
          name: MTEB MTOPIntentClassification (fr)
          type: mteb/mtop_intent
          config: fr
          split: test
          revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
        metrics:
          - type: accuracy
            value: 87.46946445349202
          - type: f1
            value: 65.79860440988624
      - task:
          type: Classification
        dataset:
          name: MTEB MasakhaNEWSClassification (fra)
          type: masakhane/masakhanews
          config: fra
          split: test
          revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
        metrics:
          - type: accuracy
            value: 82.60663507109005
          - type: f1
            value: 77.20462646604777
      - task:
          type: Clustering
        dataset:
          name: MTEB MasakhaNEWSClusteringP2P (fra)
          type: masakhane/masakhanews
          config: fra
          split: test
          revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
        metrics:
          - type: v_measure
            value: 60.19311264967803
          - type: v_measure
            value: 63.6235764409785
      - task:
          type: Classification
        dataset:
          name: MTEB MassiveIntentClassification (fr)
          type: mteb/amazon_massive_intent
          config: fr
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 81.65097511768661
          - type: f1
            value: 78.77796091490924
      - task:
          type: Classification
        dataset:
          name: MTEB MassiveScenarioClassification (fr)
          type: mteb/amazon_massive_scenario
          config: fr
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 86.64425016812373
          - type: f1
            value: 85.4912728670017
      - task:
          type: Retrieval
        dataset:
          name: MTEB MintakaRetrieval (fr)
          type: jinaai/mintakaqa
          config: fr
          split: test
          revision: efa78cc2f74bbcd21eff2261f9e13aebe40b814e
        metrics:
          - type: map_at_1
            value: 35.913000000000004
          - type: map_at_10
            value: 48.147
          - type: map_at_100
            value: 48.91
          - type: map_at_1000
            value: 48.949
          - type: map_at_3
            value: 45.269999999999996
          - type: map_at_5
            value: 47.115
          - type: mrr_at_1
            value: 35.913000000000004
          - type: mrr_at_10
            value: 48.147
          - type: mrr_at_100
            value: 48.91
          - type: mrr_at_1000
            value: 48.949
          - type: mrr_at_3
            value: 45.269999999999996
          - type: mrr_at_5
            value: 47.115
          - type: ndcg_at_1
            value: 35.913000000000004
          - type: ndcg_at_10
            value: 54.03
          - type: ndcg_at_100
            value: 57.839
          - type: ndcg_at_1000
            value: 58.925000000000004
          - type: ndcg_at_3
            value: 48.217999999999996
          - type: ndcg_at_5
            value: 51.56699999999999
          - type: precision_at_1
            value: 35.913000000000004
          - type: precision_at_10
            value: 7.244000000000001
          - type: precision_at_100
            value: 0.9039999999999999
          - type: precision_at_1000
            value: 0.099
          - type: precision_at_3
            value: 18.905
          - type: precision_at_5
            value: 12.981000000000002
          - type: recall_at_1
            value: 35.913000000000004
          - type: recall_at_10
            value: 72.441
          - type: recall_at_100
            value: 90.41799999999999
          - type: recall_at_1000
            value: 99.099
          - type: recall_at_3
            value: 56.716
          - type: recall_at_5
            value: 64.90599999999999
      - task:
          type: PairClassification
        dataset:
          name: MTEB OpusparcusPC (fr)
          type: GEM/opusparcus
          config: fr
          split: test
          revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
        metrics:
          - type: cos_sim_accuracy
            value: 99.90069513406156
          - type: cos_sim_ap
            value: 100
          - type: cos_sim_f1
            value: 99.95032290114257
          - type: cos_sim_precision
            value: 100
          - type: cos_sim_recall
            value: 99.90069513406156
          - type: dot_accuracy
            value: 99.90069513406156
          - type: dot_ap
            value: 100
          - type: dot_f1
            value: 99.95032290114257
          - type: dot_precision
            value: 100
          - type: dot_recall
            value: 99.90069513406156
          - type: euclidean_accuracy
            value: 99.90069513406156
          - type: euclidean_ap
            value: 100
          - type: euclidean_f1
            value: 99.95032290114257
          - type: euclidean_precision
            value: 100
          - type: euclidean_recall
            value: 99.90069513406156
          - type: manhattan_accuracy
            value: 99.90069513406156
          - type: manhattan_ap
            value: 100
          - type: manhattan_f1
            value: 99.95032290114257
          - type: manhattan_precision
            value: 100
          - type: manhattan_recall
            value: 99.90069513406156
          - type: max_accuracy
            value: 99.90069513406156
          - type: max_ap
            value: 100
          - type: max_f1
            value: 99.95032290114257
      - task:
          type: PairClassification
        dataset:
          name: MTEB PawsX (fr)
          type: paws-x
          config: fr
          split: test
          revision: 8a04d940a42cd40658986fdd8e3da561533a3646
        metrics:
          - type: cos_sim_accuracy
            value: 75.25
          - type: cos_sim_ap
            value: 80.86376001270014
          - type: cos_sim_f1
            value: 73.65945437441204
          - type: cos_sim_precision
            value: 64.02289452166802
          - type: cos_sim_recall
            value: 86.71096345514951
          - type: dot_accuracy
            value: 75.25
          - type: dot_ap
            value: 80.93686107633002
          - type: dot_f1
            value: 73.65945437441204
          - type: dot_precision
            value: 64.02289452166802
          - type: dot_recall
            value: 86.71096345514951
          - type: euclidean_accuracy
            value: 75.25
          - type: euclidean_ap
            value: 80.86379136218862
          - type: euclidean_f1
            value: 73.65945437441204
          - type: euclidean_precision
            value: 64.02289452166802
          - type: euclidean_recall
            value: 86.71096345514951
          - type: manhattan_accuracy
            value: 75.3
          - type: manhattan_ap
            value: 80.87826606097734
          - type: manhattan_f1
            value: 73.68421052631581
          - type: manhattan_precision
            value: 64
          - type: manhattan_recall
            value: 86.82170542635659
          - type: max_accuracy
            value: 75.3
          - type: max_ap
            value: 80.93686107633002
          - type: max_f1
            value: 73.68421052631581
      - task:
          type: STS
        dataset:
          name: MTEB SICKFr
          type: Lajavaness/SICK-fr
          config: default
          split: test
          revision: e077ab4cf4774a1e36d86d593b150422fafd8e8a
        metrics:
          - type: cos_sim_pearson
            value: 81.42349425981143
          - type: cos_sim_spearman
            value: 78.90454327031226
          - type: euclidean_pearson
            value: 78.39086497435166
          - type: euclidean_spearman
            value: 78.9046133980509
          - type: manhattan_pearson
            value: 78.63743094286502
          - type: manhattan_spearman
            value: 79.12136348449269
      - task:
          type: STS
        dataset:
          name: MTEB STS22 (fr)
          type: mteb/sts22-crosslingual-sts
          config: fr
          split: test
          revision: eea2b4fe26a775864c896887d910b76a8098ad3f
        metrics:
          - type: cos_sim_pearson
            value: 81.452697919749
          - type: cos_sim_spearman
            value: 82.58116836039301
          - type: euclidean_pearson
            value: 81.04038478932786
          - type: euclidean_spearman
            value: 82.58116836039301
          - type: manhattan_pearson
            value: 81.37075396187771
          - type: manhattan_spearman
            value: 82.73678231355368
      - task:
          type: STS
        dataset:
          name: MTEB STSBenchmarkMultilingualSTS (fr)
          type: stsb_multi_mt
          config: fr
          split: test
          revision: 93d57ef91790589e3ce9c365164337a8a78b7632
        metrics:
          - type: cos_sim_pearson
            value: 85.7419764013806
          - type: cos_sim_spearman
            value: 85.46085808849622
          - type: euclidean_pearson
            value: 83.70449639870063
          - type: euclidean_spearman
            value: 85.46159013076233
          - type: manhattan_pearson
            value: 83.95259510313929
          - type: manhattan_spearman
            value: 85.8029724659458
      - task:
          type: Summarization
        dataset:
          name: MTEB SummEvalFr
          type: lyon-nlp/summarization-summeval-fr-p2p
          config: default
          split: test
          revision: b385812de6a9577b6f4d0f88c6a6e35395a94054
        metrics:
          - type: cos_sim_pearson
            value: 32.61063271753325
          - type: cos_sim_spearman
            value: 31.454589417353603
          - type: dot_pearson
            value: 32.6106288643431
          - type: dot_spearman
            value: 31.454589417353603
      - task:
          type: Reranking
        dataset:
          name: MTEB SyntecReranking
          type: lyon-nlp/mteb-fr-reranking-syntec-s2p
          config: default
          split: test
          revision: b205c5084a0934ce8af14338bf03feb19499c84d
        metrics:
          - type: map
            value: 84.31666666666666
          - type: mrr
            value: 84.31666666666666
      - task:
          type: Retrieval
        dataset:
          name: MTEB SyntecRetrieval
          type: lyon-nlp/mteb-fr-retrieval-syntec-s2p
          config: default
          split: test
          revision: 77f7e271bf4a92b24fce5119f3486b583ca016ff
        metrics:
          - type: map_at_1
            value: 63
          - type: map_at_10
            value: 73.471
          - type: map_at_100
            value: 73.87
          - type: map_at_1000
            value: 73.87
          - type: map_at_3
            value: 70.5
          - type: map_at_5
            value: 73.05
          - type: mrr_at_1
            value: 63
          - type: mrr_at_10
            value: 73.471
          - type: mrr_at_100
            value: 73.87
          - type: mrr_at_1000
            value: 73.87
          - type: mrr_at_3
            value: 70.5
          - type: mrr_at_5
            value: 73.05
          - type: ndcg_at_1
            value: 63
          - type: ndcg_at_10
            value: 78.255
          - type: ndcg_at_100
            value: 79.88
          - type: ndcg_at_1000
            value: 79.88
          - type: ndcg_at_3
            value: 72.702
          - type: ndcg_at_5
            value: 77.264
          - type: precision_at_1
            value: 63
          - type: precision_at_10
            value: 9.3
          - type: precision_at_100
            value: 1
          - type: precision_at_1000
            value: 0.1
          - type: precision_at_3
            value: 26.333000000000002
          - type: precision_at_5
            value: 18
          - type: recall_at_1
            value: 63
          - type: recall_at_10
            value: 93
          - type: recall_at_100
            value: 100
          - type: recall_at_1000
            value: 100
          - type: recall_at_3
            value: 79
          - type: recall_at_5
            value: 90
      - task:
          type: Retrieval
        dataset:
          name: MTEB XPQARetrieval (fr)
          type: jinaai/xpqa
          config: fr
          split: test
          revision: c99d599f0a6ab9b85b065da6f9d94f9cf731679f
        metrics:
          - type: map_at_1
            value: 40.338
          - type: map_at_10
            value: 61.927
          - type: map_at_100
            value: 63.361999999999995
          - type: map_at_1000
            value: 63.405
          - type: map_at_3
            value: 55.479
          - type: map_at_5
            value: 59.732
          - type: mrr_at_1
            value: 63.551
          - type: mrr_at_10
            value: 71.006
          - type: mrr_at_100
            value: 71.501
          - type: mrr_at_1000
            value: 71.509
          - type: mrr_at_3
            value: 69.07
          - type: mrr_at_5
            value: 70.165
          - type: ndcg_at_1
            value: 63.551
          - type: ndcg_at_10
            value: 68.297
          - type: ndcg_at_100
            value: 73.13199999999999
          - type: ndcg_at_1000
            value: 73.751
          - type: ndcg_at_3
            value: 62.999
          - type: ndcg_at_5
            value: 64.89
          - type: precision_at_1
            value: 63.551
          - type: precision_at_10
            value: 15.661
          - type: precision_at_100
            value: 1.9789999999999999
          - type: precision_at_1000
            value: 0.207
          - type: precision_at_3
            value: 38.273
          - type: precision_at_5
            value: 27.61
          - type: recall_at_1
            value: 40.338
          - type: recall_at_10
            value: 77.267
          - type: recall_at_100
            value: 95.892
          - type: recall_at_1000
            value: 99.75500000000001
          - type: recall_at_3
            value: 60.36
          - type: recall_at_5
            value: 68.825
      - task:
          type: Clustering
        dataset:
          name: MTEB 8TagsClustering
          type: PL-MTEB/8tags-clustering
          config: default
          split: test
          revision: None
        metrics:
          - type: v_measure
            value: 51.36126303874126
      - task:
          type: Classification
        dataset:
          name: MTEB AllegroReviews
          type: PL-MTEB/allegro-reviews
          config: default
          split: test
          revision: None
        metrics:
          - type: accuracy
            value: 67.13717693836979
          - type: f1
            value: 57.27609848003782
      - task:
          type: Retrieval
        dataset:
          name: MTEB ArguAna-PL
          type: clarin-knext/arguana-pl
          config: default
          split: test
          revision: 63fc86750af76253e8c760fc9e534bbf24d260a2
        metrics:
          - type: map_at_1
            value: 35.276999999999994
          - type: map_at_10
            value: 51.086
          - type: map_at_100
            value: 51.788000000000004
          - type: map_at_1000
            value: 51.791
          - type: map_at_3
            value: 46.147
          - type: map_at_5
            value: 49.078
          - type: mrr_at_1
            value: 35.917
          - type: mrr_at_10
            value: 51.315999999999995
          - type: mrr_at_100
            value: 52.018
          - type: mrr_at_1000
            value: 52.022
          - type: mrr_at_3
            value: 46.349000000000004
          - type: mrr_at_5
            value: 49.297000000000004
          - type: ndcg_at_1
            value: 35.276999999999994
          - type: ndcg_at_10
            value: 59.870999999999995
          - type: ndcg_at_100
            value: 62.590999999999994
          - type: ndcg_at_1000
            value: 62.661
          - type: ndcg_at_3
            value: 49.745
          - type: ndcg_at_5
            value: 55.067
          - type: precision_at_1
            value: 35.276999999999994
          - type: precision_at_10
            value: 8.791
          - type: precision_at_100
            value: 0.991
          - type: precision_at_1000
            value: 0.1
          - type: precision_at_3
            value: 20.057
          - type: precision_at_5
            value: 14.637
          - type: recall_at_1
            value: 35.276999999999994
          - type: recall_at_10
            value: 87.909
          - type: recall_at_100
            value: 99.14699999999999
          - type: recall_at_1000
            value: 99.644
          - type: recall_at_3
            value: 60.171
          - type: recall_at_5
            value: 73.18599999999999
      - task:
          type: Classification
        dataset:
          name: MTEB CBD
          type: PL-MTEB/cbd
          config: default
          split: test
          revision: None
        metrics:
          - type: accuracy
            value: 78.03000000000002
          - type: ap
            value: 29.12548553897622
          - type: f1
            value: 66.54857118886073
      - task:
          type: PairClassification
        dataset:
          name: MTEB CDSC-E
          type: PL-MTEB/cdsce-pairclassification
          config: default
          split: test
          revision: None
        metrics:
          - type: cos_sim_accuracy
            value: 89
          - type: cos_sim_ap
            value: 76.75437826834582
          - type: cos_sim_f1
            value: 66.4850136239782
          - type: cos_sim_precision
            value: 68.92655367231639
          - type: cos_sim_recall
            value: 64.21052631578948
          - type: dot_accuracy
            value: 89
          - type: dot_ap
            value: 76.75437826834582
          - type: dot_f1
            value: 66.4850136239782
          - type: dot_precision
            value: 68.92655367231639
          - type: dot_recall
            value: 64.21052631578948
          - type: euclidean_accuracy
            value: 89
          - type: euclidean_ap
            value: 76.75437826834582
          - type: euclidean_f1
            value: 66.4850136239782
          - type: euclidean_precision
            value: 68.92655367231639
          - type: euclidean_recall
            value: 64.21052631578948
          - type: manhattan_accuracy
            value: 89
          - type: manhattan_ap
            value: 76.66074220647083
          - type: manhattan_f1
            value: 66.47058823529412
          - type: manhattan_precision
            value: 75.33333333333333
          - type: manhattan_recall
            value: 59.473684210526315
          - type: max_accuracy
            value: 89
          - type: max_ap
            value: 76.75437826834582
          - type: max_f1
            value: 66.4850136239782
      - task:
          type: STS
        dataset:
          name: MTEB CDSC-R
          type: PL-MTEB/cdscr-sts
          config: default
          split: test
          revision: None
        metrics:
          - type: cos_sim_pearson
            value: 93.12903172428328
          - type: cos_sim_spearman
            value: 92.66381487060741
          - type: euclidean_pearson
            value: 90.37278396708922
          - type: euclidean_spearman
            value: 92.66381487060741
          - type: manhattan_pearson
            value: 90.32503296540962
          - type: manhattan_spearman
            value: 92.6902938354313
      - task:
          type: Retrieval
        dataset:
          name: MTEB DBPedia-PL
          type: clarin-knext/dbpedia-pl
          config: default
          split: test
          revision: 76afe41d9af165cc40999fcaa92312b8b012064a
        metrics:
          - type: map_at_1
            value: 8.83
          - type: map_at_10
            value: 18.326
          - type: map_at_100
            value: 26.496
          - type: map_at_1000
            value: 28.455000000000002
          - type: map_at_3
            value: 12.933
          - type: map_at_5
            value: 15.168000000000001
          - type: mrr_at_1
            value: 66
          - type: mrr_at_10
            value: 72.76700000000001
          - type: mrr_at_100
            value: 73.203
          - type: mrr_at_1000
            value: 73.219
          - type: mrr_at_3
            value: 71.458
          - type: mrr_at_5
            value: 72.246
          - type: ndcg_at_1
            value: 55.375
          - type: ndcg_at_10
            value: 41.3
          - type: ndcg_at_100
            value: 45.891
          - type: ndcg_at_1000
            value: 52.905
          - type: ndcg_at_3
            value: 46.472
          - type: ndcg_at_5
            value: 43.734
          - type: precision_at_1
            value: 66
          - type: precision_at_10
            value: 33.074999999999996
          - type: precision_at_100
            value: 11.094999999999999
          - type: precision_at_1000
            value: 2.374
          - type: precision_at_3
            value: 48.583
          - type: precision_at_5
            value: 42
          - type: recall_at_1
            value: 8.83
          - type: recall_at_10
            value: 22.587
          - type: recall_at_100
            value: 50.61600000000001
          - type: recall_at_1000
            value: 73.559
          - type: recall_at_3
            value: 13.688
          - type: recall_at_5
            value: 16.855
      - task:
          type: Retrieval
        dataset:
          name: MTEB FiQA-PL
          type: clarin-knext/fiqa-pl
          config: default
          split: test
          revision: 2e535829717f8bf9dc829b7f911cc5bbd4e6608e
        metrics:
          - type: map_at_1
            value: 20.587
          - type: map_at_10
            value: 33.095
          - type: map_at_100
            value: 35.24
          - type: map_at_1000
            value: 35.429
          - type: map_at_3
            value: 28.626
          - type: map_at_5
            value: 31.136999999999997
          - type: mrr_at_1
            value: 40.586
          - type: mrr_at_10
            value: 49.033
          - type: mrr_at_100
            value: 49.952999999999996
          - type: mrr_at_1000
            value: 49.992
          - type: mrr_at_3
            value: 46.553
          - type: mrr_at_5
            value: 48.035
          - type: ndcg_at_1
            value: 40.586
          - type: ndcg_at_10
            value: 41.046
          - type: ndcg_at_100
            value: 48.586
          - type: ndcg_at_1000
            value: 51.634
          - type: ndcg_at_3
            value: 36.773
          - type: ndcg_at_5
            value: 38.389
          - type: precision_at_1
            value: 40.586
          - type: precision_at_10
            value: 11.466
          - type: precision_at_100
            value: 1.909
          - type: precision_at_1000
            value: 0.245
          - type: precision_at_3
            value: 24.434
          - type: precision_at_5
            value: 18.426000000000002
          - type: recall_at_1
            value: 20.587
          - type: recall_at_10
            value: 47.986000000000004
          - type: recall_at_100
            value: 75.761
          - type: recall_at_1000
            value: 94.065
          - type: recall_at_3
            value: 33.339
          - type: recall_at_5
            value: 39.765
      - task:
          type: Retrieval
        dataset:
          name: MTEB HotpotQA-PL
          type: clarin-knext/hotpotqa-pl
          config: default
          split: test
          revision: a0bd479ac97b4ccb5bd6ce320c415d0bb4beb907
        metrics:
          - type: map_at_1
            value: 40.878
          - type: map_at_10
            value: 58.775999999999996
          - type: map_at_100
            value: 59.632
          - type: map_at_1000
            value: 59.707
          - type: map_at_3
            value: 56.074
          - type: map_at_5
            value: 57.629
          - type: mrr_at_1
            value: 81.756
          - type: mrr_at_10
            value: 86.117
          - type: mrr_at_100
            value: 86.299
          - type: mrr_at_1000
            value: 86.30600000000001
          - type: mrr_at_3
            value: 85.345
          - type: mrr_at_5
            value: 85.832
          - type: ndcg_at_1
            value: 81.756
          - type: ndcg_at_10
            value: 67.608
          - type: ndcg_at_100
            value: 70.575
          - type: ndcg_at_1000
            value: 71.99600000000001
          - type: ndcg_at_3
            value: 63.723
          - type: ndcg_at_5
            value: 65.70700000000001
          - type: precision_at_1
            value: 81.756
          - type: precision_at_10
            value: 13.619
          - type: precision_at_100
            value: 1.5939999999999999
          - type: precision_at_1000
            value: 0.178
          - type: precision_at_3
            value: 39.604
          - type: precision_at_5
            value: 25.332
          - type: recall_at_1
            value: 40.878
          - type: recall_at_10
            value: 68.096
          - type: recall_at_100
            value: 79.696
          - type: recall_at_1000
            value: 89.082
          - type: recall_at_3
            value: 59.406000000000006
          - type: recall_at_5
            value: 63.329
      - task:
          type: Retrieval
        dataset:
          name: MTEB MSMARCO-PL
          type: clarin-knext/msmarco-pl
          config: default
          split: test
          revision: 8634c07806d5cce3a6138e260e59b81760a0a640
        metrics:
          - type: map_at_1
            value: 2.1839999999999997
          - type: map_at_10
            value: 11.346
          - type: map_at_100
            value: 30.325000000000003
          - type: map_at_1000
            value: 37.806
          - type: map_at_3
            value: 4.842
          - type: map_at_5
            value: 6.891
          - type: mrr_at_1
            value: 86.047
          - type: mrr_at_10
            value: 89.14699999999999
          - type: mrr_at_100
            value: 89.46600000000001
          - type: mrr_at_1000
            value: 89.46600000000001
          - type: mrr_at_3
            value: 89.14699999999999
          - type: mrr_at_5
            value: 89.14699999999999
          - type: ndcg_at_1
            value: 67.829
          - type: ndcg_at_10
            value: 62.222
          - type: ndcg_at_100
            value: 55.337
          - type: ndcg_at_1000
            value: 64.076
          - type: ndcg_at_3
            value: 68.12700000000001
          - type: ndcg_at_5
            value: 64.987
          - type: precision_at_1
            value: 86.047
          - type: precision_at_10
            value: 69.535
          - type: precision_at_100
            value: 32.93
          - type: precision_at_1000
            value: 6.6049999999999995
          - type: precision_at_3
            value: 79.845
          - type: precision_at_5
            value: 75.349
          - type: recall_at_1
            value: 2.1839999999999997
          - type: recall_at_10
            value: 12.866
          - type: recall_at_100
            value: 43.505
          - type: recall_at_1000
            value: 72.366
          - type: recall_at_3
            value: 4.947
          - type: recall_at_5
            value: 7.192
      - task:
          type: Classification
        dataset:
          name: MTEB MassiveIntentClassification (pl)
          type: mteb/amazon_massive_intent
          config: pl
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 80.75319435104238
          - type: f1
            value: 77.58961444860606
      - task:
          type: Classification
        dataset:
          name: MTEB MassiveScenarioClassification (pl)
          type: mteb/amazon_massive_scenario
          config: pl
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 85.54472091459313
          - type: f1
            value: 84.29498563572106
      - task:
          type: Retrieval
        dataset:
          name: MTEB NFCorpus-PL
          type: clarin-knext/nfcorpus-pl
          config: default
          split: test
          revision: 9a6f9567fda928260afed2de480d79c98bf0bec0
        metrics:
          - type: map_at_1
            value: 4.367
          - type: map_at_10
            value: 10.38
          - type: map_at_100
            value: 13.516
          - type: map_at_1000
            value: 14.982000000000001
          - type: map_at_3
            value: 7.367
          - type: map_at_5
            value: 8.59
          - type: mrr_at_1
            value: 41.486000000000004
          - type: mrr_at_10
            value: 48.886
          - type: mrr_at_100
            value: 49.657000000000004
          - type: mrr_at_1000
            value: 49.713
          - type: mrr_at_3
            value: 46.904
          - type: mrr_at_5
            value: 48.065000000000005
          - type: ndcg_at_1
            value: 40.402
          - type: ndcg_at_10
            value: 30.885
          - type: ndcg_at_100
            value: 28.393
          - type: ndcg_at_1000
            value: 37.428
          - type: ndcg_at_3
            value: 35.394999999999996
          - type: ndcg_at_5
            value: 33.391999999999996
          - type: precision_at_1
            value: 41.486000000000004
          - type: precision_at_10
            value: 23.437
          - type: precision_at_100
            value: 7.638
          - type: precision_at_1000
            value: 2.0389999999999997
          - type: precision_at_3
            value: 32.817
          - type: precision_at_5
            value: 28.915999999999997
          - type: recall_at_1
            value: 4.367
          - type: recall_at_10
            value: 14.655000000000001
          - type: recall_at_100
            value: 29.665999999999997
          - type: recall_at_1000
            value: 62.073
          - type: recall_at_3
            value: 8.51
          - type: recall_at_5
            value: 10.689
      - task:
          type: Retrieval
        dataset:
          name: MTEB NQ-PL
          type: clarin-knext/nq-pl
          config: default
          split: test
          revision: f171245712cf85dd4700b06bef18001578d0ca8d
        metrics:
          - type: map_at_1
            value: 28.616000000000003
          - type: map_at_10
            value: 41.626000000000005
          - type: map_at_100
            value: 42.689
          - type: map_at_1000
            value: 42.733
          - type: map_at_3
            value: 37.729
          - type: map_at_5
            value: 39.879999999999995
          - type: mrr_at_1
            value: 32.068000000000005
          - type: mrr_at_10
            value: 44.029
          - type: mrr_at_100
            value: 44.87
          - type: mrr_at_1000
            value: 44.901
          - type: mrr_at_3
            value: 40.687
          - type: mrr_at_5
            value: 42.625
          - type: ndcg_at_1
            value: 32.068000000000005
          - type: ndcg_at_10
            value: 48.449999999999996
          - type: ndcg_at_100
            value: 53.13
          - type: ndcg_at_1000
            value: 54.186
          - type: ndcg_at_3
            value: 40.983999999999995
          - type: ndcg_at_5
            value: 44.628
          - type: precision_at_1
            value: 32.068000000000005
          - type: precision_at_10
            value: 7.9750000000000005
          - type: precision_at_100
            value: 1.061
          - type: precision_at_1000
            value: 0.116
          - type: precision_at_3
            value: 18.404999999999998
          - type: precision_at_5
            value: 13.111
          - type: recall_at_1
            value: 28.616000000000003
          - type: recall_at_10
            value: 66.956
          - type: recall_at_100
            value: 87.657
          - type: recall_at_1000
            value: 95.548
          - type: recall_at_3
            value: 47.453
          - type: recall_at_5
            value: 55.87800000000001
      - task:
          type: Classification
        dataset:
          name: MTEB PAC
          type: laugustyniak/abusive-clauses-pl
          config: default
          split: test
          revision: None
        metrics:
          - type: accuracy
            value: 69.04141326382856
          - type: ap
            value: 77.47589122111044
          - type: f1
            value: 66.6332277374775
      - task:
          type: PairClassification
        dataset:
          name: MTEB PPC
          type: PL-MTEB/ppc-pairclassification
          config: default
          split: test
          revision: None
        metrics:
          - type: cos_sim_accuracy
            value: 86.4
          - type: cos_sim_ap
            value: 94.1044939667201
          - type: cos_sim_f1
            value: 88.78048780487805
          - type: cos_sim_precision
            value: 87.22044728434504
          - type: cos_sim_recall
            value: 90.39735099337747
          - type: dot_accuracy
            value: 86.4
          - type: dot_ap
            value: 94.1044939667201
          - type: dot_f1
            value: 88.78048780487805
          - type: dot_precision
            value: 87.22044728434504
          - type: dot_recall
            value: 90.39735099337747
          - type: euclidean_accuracy
            value: 86.4
          - type: euclidean_ap
            value: 94.1044939667201
          - type: euclidean_f1
            value: 88.78048780487805
          - type: euclidean_precision
            value: 87.22044728434504
          - type: euclidean_recall
            value: 90.39735099337747
          - type: manhattan_accuracy
            value: 86.4
          - type: manhattan_ap
            value: 94.11438365697387
          - type: manhattan_f1
            value: 88.77968877968877
          - type: manhattan_precision
            value: 87.84440842787681
          - type: manhattan_recall
            value: 89.73509933774835
          - type: max_accuracy
            value: 86.4
          - type: max_ap
            value: 94.11438365697387
          - type: max_f1
            value: 88.78048780487805
      - task:
          type: PairClassification
        dataset:
          name: MTEB PSC
          type: PL-MTEB/psc-pairclassification
          config: default
          split: test
          revision: None
        metrics:
          - type: cos_sim_accuracy
            value: 97.86641929499072
          - type: cos_sim_ap
            value: 99.36904211868182
          - type: cos_sim_f1
            value: 96.56203288490283
          - type: cos_sim_precision
            value: 94.72140762463343
          - type: cos_sim_recall
            value: 98.47560975609755
          - type: dot_accuracy
            value: 97.86641929499072
          - type: dot_ap
            value: 99.36904211868183
          - type: dot_f1
            value: 96.56203288490283
          - type: dot_precision
            value: 94.72140762463343
          - type: dot_recall
            value: 98.47560975609755
          - type: euclidean_accuracy
            value: 97.86641929499072
          - type: euclidean_ap
            value: 99.36904211868183
          - type: euclidean_f1
            value: 96.56203288490283
          - type: euclidean_precision
            value: 94.72140762463343
          - type: euclidean_recall
            value: 98.47560975609755
          - type: manhattan_accuracy
            value: 98.14471243042672
          - type: manhattan_ap
            value: 99.43359540492416
          - type: manhattan_f1
            value: 96.98795180722892
          - type: manhattan_precision
            value: 95.83333333333334
          - type: manhattan_recall
            value: 98.17073170731707
          - type: max_accuracy
            value: 98.14471243042672
          - type: max_ap
            value: 99.43359540492416
          - type: max_f1
            value: 96.98795180722892
      - task:
          type: Classification
        dataset:
          name: MTEB PolEmo2.0-IN
          type: PL-MTEB/polemo2_in
          config: default
          split: test
          revision: None
        metrics:
          - type: accuracy
            value: 89.39058171745152
          - type: f1
            value: 86.8552093529568
      - task:
          type: Classification
        dataset:
          name: MTEB PolEmo2.0-OUT
          type: PL-MTEB/polemo2_out
          config: default
          split: test
          revision: None
        metrics:
          - type: accuracy
            value: 74.97975708502024
          - type: f1
            value: 58.73081628832407
      - task:
          type: Retrieval
        dataset:
          name: MTEB Quora-PL
          type: clarin-knext/quora-pl
          config: default
          split: test
          revision: 0be27e93455051e531182b85e85e425aba12e9d4
        metrics:
          - type: map_at_1
            value: 64.917
          - type: map_at_10
            value: 78.74600000000001
          - type: map_at_100
            value: 79.501
          - type: map_at_1000
            value: 79.524
          - type: map_at_3
            value: 75.549
          - type: map_at_5
            value: 77.495
          - type: mrr_at_1
            value: 74.9
          - type: mrr_at_10
            value: 82.112
          - type: mrr_at_100
            value: 82.314
          - type: mrr_at_1000
            value: 82.317
          - type: mrr_at_3
            value: 80.745
          - type: mrr_at_5
            value: 81.607
          - type: ndcg_at_1
            value: 74.83999999999999
          - type: ndcg_at_10
            value: 83.214
          - type: ndcg_at_100
            value: 84.997
          - type: ndcg_at_1000
            value: 85.207
          - type: ndcg_at_3
            value: 79.547
          - type: ndcg_at_5
            value: 81.46600000000001
          - type: precision_at_1
            value: 74.83999999999999
          - type: precision_at_10
            value: 12.822
          - type: precision_at_100
            value: 1.506
          - type: precision_at_1000
            value: 0.156
          - type: precision_at_3
            value: 34.903
          - type: precision_at_5
            value: 23.16
          - type: recall_at_1
            value: 64.917
          - type: recall_at_10
            value: 92.27199999999999
          - type: recall_at_100
            value: 98.715
          - type: recall_at_1000
            value: 99.854
          - type: recall_at_3
            value: 82.04599999999999
          - type: recall_at_5
            value: 87.2
      - task:
          type: Retrieval
        dataset:
          name: MTEB SCIDOCS-PL
          type: clarin-knext/scidocs-pl
          config: default
          split: test
          revision: 45452b03f05560207ef19149545f168e596c9337
        metrics:
          - type: map_at_1
            value: 3.51
          - type: map_at_10
            value: 9.046999999999999
          - type: map_at_100
            value: 10.823
          - type: map_at_1000
            value: 11.144
          - type: map_at_3
            value: 6.257
          - type: map_at_5
            value: 7.648000000000001
          - type: mrr_at_1
            value: 17.299999999999997
          - type: mrr_at_10
            value: 27.419
          - type: mrr_at_100
            value: 28.618
          - type: mrr_at_1000
            value: 28.685
          - type: mrr_at_3
            value: 23.817
          - type: mrr_at_5
            value: 25.927
          - type: ndcg_at_1
            value: 17.299999999999997
          - type: ndcg_at_10
            value: 16.084
          - type: ndcg_at_100
            value: 23.729
          - type: ndcg_at_1000
            value: 29.476999999999997
          - type: ndcg_at_3
            value: 14.327000000000002
          - type: ndcg_at_5
            value: 13.017999999999999
          - type: precision_at_1
            value: 17.299999999999997
          - type: precision_at_10
            value: 8.63
          - type: precision_at_100
            value: 1.981
          - type: precision_at_1000
            value: 0.336
          - type: precision_at_3
            value: 13.4
          - type: precision_at_5
            value: 11.700000000000001
          - type: recall_at_1
            value: 3.51
          - type: recall_at_10
            value: 17.518
          - type: recall_at_100
            value: 40.275
          - type: recall_at_1000
            value: 68.203
          - type: recall_at_3
            value: 8.155
          - type: recall_at_5
            value: 11.875
      - task:
          type: PairClassification
        dataset:
          name: MTEB SICK-E-PL
          type: PL-MTEB/sicke-pl-pairclassification
          config: default
          split: test
          revision: None
        metrics:
          - type: cos_sim_accuracy
            value: 86.30248675091724
          - type: cos_sim_ap
            value: 83.6756734006714
          - type: cos_sim_f1
            value: 74.97367497367497
          - type: cos_sim_precision
            value: 73.91003460207612
          - type: cos_sim_recall
            value: 76.06837606837607
          - type: dot_accuracy
            value: 86.30248675091724
          - type: dot_ap
            value: 83.6756734006714
          - type: dot_f1
            value: 74.97367497367497
          - type: dot_precision
            value: 73.91003460207612
          - type: dot_recall
            value: 76.06837606837607
          - type: euclidean_accuracy
            value: 86.30248675091724
          - type: euclidean_ap
            value: 83.67566984333091
          - type: euclidean_f1
            value: 74.97367497367497
          - type: euclidean_precision
            value: 73.91003460207612
          - type: euclidean_recall
            value: 76.06837606837607
          - type: manhattan_accuracy
            value: 86.28210354667753
          - type: manhattan_ap
            value: 83.64216119130171
          - type: manhattan_f1
            value: 74.92152075340078
          - type: manhattan_precision
            value: 73.4107997265892
          - type: manhattan_recall
            value: 76.49572649572649
          - type: max_accuracy
            value: 86.30248675091724
          - type: max_ap
            value: 83.6756734006714
          - type: max_f1
            value: 74.97367497367497
      - task:
          type: STS
        dataset:
          name: MTEB SICK-R-PL
          type: PL-MTEB/sickr-pl-sts
          config: default
          split: test
          revision: None
        metrics:
          - type: cos_sim_pearson
            value: 82.23295940859121
          - type: cos_sim_spearman
            value: 78.89329160768719
          - type: euclidean_pearson
            value: 79.56019107076818
          - type: euclidean_spearman
            value: 78.89330209904084
          - type: manhattan_pearson
            value: 79.76098513973719
          - type: manhattan_spearman
            value: 79.05490162570123
      - task:
          type: STS
        dataset:
          name: MTEB STS22 (pl)
          type: mteb/sts22-crosslingual-sts
          config: pl
          split: test
          revision: eea2b4fe26a775864c896887d910b76a8098ad3f
        metrics:
          - type: cos_sim_pearson
            value: 37.732606308062486
          - type: cos_sim_spearman
            value: 41.01645667030284
          - type: euclidean_pearson
            value: 26.61722556367085
          - type: euclidean_spearman
            value: 41.01645667030284
          - type: manhattan_pearson
            value: 26.60917378970807
          - type: manhattan_spearman
            value: 41.51335727617614
      - task:
          type: Retrieval
        dataset:
          name: MTEB SciFact-PL
          type: clarin-knext/scifact-pl
          config: default
          split: test
          revision: 47932a35f045ef8ed01ba82bf9ff67f6e109207e
        metrics:
          - type: map_at_1
            value: 54.31700000000001
          - type: map_at_10
            value: 65.564
          - type: map_at_100
            value: 66.062
          - type: map_at_1000
            value: 66.08699999999999
          - type: map_at_3
            value: 62.592999999999996
          - type: map_at_5
            value: 63.888
          - type: mrr_at_1
            value: 56.99999999999999
          - type: mrr_at_10
            value: 66.412
          - type: mrr_at_100
            value: 66.85900000000001
          - type: mrr_at_1000
            value: 66.88
          - type: mrr_at_3
            value: 64.22200000000001
          - type: mrr_at_5
            value: 65.206
          - type: ndcg_at_1
            value: 56.99999999999999
          - type: ndcg_at_10
            value: 70.577
          - type: ndcg_at_100
            value: 72.879
          - type: ndcg_at_1000
            value: 73.45
          - type: ndcg_at_3
            value: 65.5
          - type: ndcg_at_5
            value: 67.278
          - type: precision_at_1
            value: 56.99999999999999
          - type: precision_at_10
            value: 9.667
          - type: precision_at_100
            value: 1.083
          - type: precision_at_1000
            value: 0.11299999999999999
          - type: precision_at_3
            value: 26
          - type: precision_at_5
            value: 16.933
          - type: recall_at_1
            value: 54.31700000000001
          - type: recall_at_10
            value: 85.056
          - type: recall_at_100
            value: 95.667
          - type: recall_at_1000
            value: 100
          - type: recall_at_3
            value: 71
          - type: recall_at_5
            value: 75.672
      - task:
          type: Retrieval
        dataset:
          name: MTEB TRECCOVID-PL
          type: clarin-knext/trec-covid-pl
          config: default
          split: test
          revision: 81bcb408f33366c2a20ac54adafad1ae7e877fdd
        metrics:
          - type: map_at_1
            value: 0.245
          - type: map_at_10
            value: 2.051
          - type: map_at_100
            value: 12.009
          - type: map_at_1000
            value: 27.448
          - type: map_at_3
            value: 0.721
          - type: map_at_5
            value: 1.13
          - type: mrr_at_1
            value: 88
          - type: mrr_at_10
            value: 93
          - type: mrr_at_100
            value: 93
          - type: mrr_at_1000
            value: 93
          - type: mrr_at_3
            value: 93
          - type: mrr_at_5
            value: 93
          - type: ndcg_at_1
            value: 85
          - type: ndcg_at_10
            value: 80.303
          - type: ndcg_at_100
            value: 61.23499999999999
          - type: ndcg_at_1000
            value: 52.978
          - type: ndcg_at_3
            value: 84.419
          - type: ndcg_at_5
            value: 82.976
          - type: precision_at_1
            value: 88
          - type: precision_at_10
            value: 83.39999999999999
          - type: precision_at_100
            value: 61.96
          - type: precision_at_1000
            value: 22.648
          - type: precision_at_3
            value: 89.333
          - type: precision_at_5
            value: 87.2
          - type: recall_at_1
            value: 0.245
          - type: recall_at_10
            value: 2.193
          - type: recall_at_100
            value: 14.938
          - type: recall_at_1000
            value: 48.563
          - type: recall_at_3
            value: 0.738
          - type: recall_at_5
            value: 1.173

Yingda/gte-Qwen2-7B-instruct-Q5_K_M-GGUF

This model was converted to GGUF format from Alibaba-NLP/gte-Qwen2-7B-instruct using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model.

Use with llama.cpp

Install llama.cpp through brew (works on Mac and Linux)

brew install llama.cpp

Invoke the llama.cpp server or the CLI.

CLI:

llama-cli --hf-repo Yingda/gte-Qwen2-7B-instruct-Q5_K_M-GGUF --hf-file gte-qwen2-7b-instruct-q5_k_m.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo Yingda/gte-Qwen2-7B-instruct-Q5_K_M-GGUF --hf-file gte-qwen2-7b-instruct-q5_k_m.gguf -c 2048

Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.

Step 1: Clone llama.cpp from GitHub.

git clone https://github.com/ggerganov/llama.cpp

Step 2: Move into the llama.cpp folder and build it with LLAMA_CURL=1 flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).

cd llama.cpp && LLAMA_CURL=1 make

Step 3: Run inference through the main binary.

./llama-cli --hf-repo Yingda/gte-Qwen2-7B-instruct-Q5_K_M-GGUF --hf-file gte-qwen2-7b-instruct-q5_k_m.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo Yingda/gte-Qwen2-7B-instruct-Q5_K_M-GGUF --hf-file gte-qwen2-7b-instruct-q5_k_m.gguf -c 2048