Emm9625's picture
Upload README.md with huggingface_hub
6637124 verified
metadata
tags:
  - sentence-transformers
  - feature-extraction
  - sentence-similarity
  - mteb
  - llama-cpp
  - gguf-my-repo
datasets:
  - jinaai/negation-dataset
language: en
inference: false
license: apache-2.0
base_model: jinaai/jina-embeddings-v2-small-en
model-index:
  - name: jina-embedding-s-en-v2
    results:
      - task:
          type: Classification
        dataset:
          name: MTEB AmazonCounterfactualClassification (en)
          type: mteb/amazon_counterfactual
          config: en
          split: test
          revision: e8379541af4e31359cca9fbcf4b00f2671dba205
        metrics:
          - type: accuracy
            value: 71.35820895522387
          - type: ap
            value: 33.99931933598115
          - type: f1
            value: 65.3853685535555
      - task:
          type: Classification
        dataset:
          name: MTEB AmazonPolarityClassification
          type: mteb/amazon_polarity
          config: default
          split: test
          revision: e2d317d38cd51312af73b3d32a06d1a08b442046
        metrics:
          - type: accuracy
            value: 82.90140000000001
          - type: ap
            value: 78.01434597815617
          - type: f1
            value: 82.83357802722676
      - task:
          type: Classification
        dataset:
          name: MTEB AmazonReviewsClassification (en)
          type: mteb/amazon_reviews_multi
          config: en
          split: test
          revision: 1399c76144fd37290681b995c656ef9b2e06e26d
        metrics:
          - type: accuracy
            value: 40.88999999999999
          - type: f1
            value: 39.209432767163456
      - task:
          type: Retrieval
        dataset:
          name: MTEB ArguAna
          type: arguana
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 23.257
          - type: map_at_10
            value: 37.946000000000005
          - type: map_at_100
            value: 39.17
          - type: map_at_1000
            value: 39.181
          - type: map_at_3
            value: 32.99
          - type: map_at_5
            value: 35.467999999999996
          - type: mrr_at_1
            value: 23.541999999999998
          - type: mrr_at_10
            value: 38.057
          - type: mrr_at_100
            value: 39.289
          - type: mrr_at_1000
            value: 39.299
          - type: mrr_at_3
            value: 33.096
          - type: mrr_at_5
            value: 35.628
          - type: ndcg_at_1
            value: 23.257
          - type: ndcg_at_10
            value: 46.729
          - type: ndcg_at_100
            value: 51.900999999999996
          - type: ndcg_at_1000
            value: 52.16
          - type: ndcg_at_3
            value: 36.323
          - type: ndcg_at_5
            value: 40.766999999999996
          - type: precision_at_1
            value: 23.257
          - type: precision_at_10
            value: 7.510999999999999
          - type: precision_at_100
            value: 0.976
          - type: precision_at_1000
            value: 0.1
          - type: precision_at_3
            value: 15.339
          - type: precision_at_5
            value: 11.350999999999999
          - type: recall_at_1
            value: 23.257
          - type: recall_at_10
            value: 75.107
          - type: recall_at_100
            value: 97.58200000000001
          - type: recall_at_1000
            value: 99.57300000000001
          - type: recall_at_3
            value: 46.017
          - type: recall_at_5
            value: 56.757000000000005
      - task:
          type: Clustering
        dataset:
          name: MTEB ArxivClusteringP2P
          type: mteb/arxiv-clustering-p2p
          config: default
          split: test
          revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
        metrics:
          - type: v_measure
            value: 44.02420878391967
      - task:
          type: Clustering
        dataset:
          name: MTEB ArxivClusteringS2S
          type: mteb/arxiv-clustering-s2s
          config: default
          split: test
          revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
        metrics:
          - type: v_measure
            value: 35.16136856000258
      - task:
          type: Reranking
        dataset:
          name: MTEB AskUbuntuDupQuestions
          type: mteb/askubuntudupquestions-reranking
          config: default
          split: test
          revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
        metrics:
          - type: map
            value: 59.61809790513646
          - type: mrr
            value: 73.07215406938397
      - task:
          type: STS
        dataset:
          name: MTEB BIOSSES
          type: mteb/biosses-sts
          config: default
          split: test
          revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
        metrics:
          - type: cos_sim_pearson
            value: 82.0167350090749
          - type: cos_sim_spearman
            value: 80.51569002630401
          - type: euclidean_pearson
            value: 81.46820525099726
          - type: euclidean_spearman
            value: 80.51569002630401
          - type: manhattan_pearson
            value: 81.35596555056757
          - type: manhattan_spearman
            value: 80.12592210903303
      - task:
          type: Classification
        dataset:
          name: MTEB Banking77Classification
          type: mteb/banking77
          config: default
          split: test
          revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
        metrics:
          - type: accuracy
            value: 78.25
          - type: f1
            value: 77.34950913540605
      - task:
          type: Clustering
        dataset:
          name: MTEB BiorxivClusteringP2P
          type: mteb/biorxiv-clustering-p2p
          config: default
          split: test
          revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
        metrics:
          - type: v_measure
            value: 35.57238596005698
      - task:
          type: Clustering
        dataset:
          name: MTEB BiorxivClusteringS2S
          type: mteb/biorxiv-clustering-s2s
          config: default
          split: test
          revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
        metrics:
          - type: v_measure
            value: 29.066444306196683
      - task:
          type: Retrieval
        dataset:
          name: MTEB CQADupstackAndroidRetrieval
          type: BeIR/cqadupstack
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 31.891000000000002
          - type: map_at_10
            value: 42.772
          - type: map_at_100
            value: 44.108999999999995
          - type: map_at_1000
            value: 44.236
          - type: map_at_3
            value: 39.289
          - type: map_at_5
            value: 41.113
          - type: mrr_at_1
            value: 39.342
          - type: mrr_at_10
            value: 48.852000000000004
          - type: mrr_at_100
            value: 49.534
          - type: mrr_at_1000
            value: 49.582
          - type: mrr_at_3
            value: 46.089999999999996
          - type: mrr_at_5
            value: 47.685
          - type: ndcg_at_1
            value: 39.342
          - type: ndcg_at_10
            value: 48.988
          - type: ndcg_at_100
            value: 53.854
          - type: ndcg_at_1000
            value: 55.955
          - type: ndcg_at_3
            value: 43.877
          - type: ndcg_at_5
            value: 46.027
          - type: precision_at_1
            value: 39.342
          - type: precision_at_10
            value: 9.285
          - type: precision_at_100
            value: 1.488
          - type: precision_at_1000
            value: 0.194
          - type: precision_at_3
            value: 20.696
          - type: precision_at_5
            value: 14.878
          - type: recall_at_1
            value: 31.891000000000002
          - type: recall_at_10
            value: 60.608
          - type: recall_at_100
            value: 81.025
          - type: recall_at_1000
            value: 94.883
          - type: recall_at_3
            value: 45.694
          - type: recall_at_5
            value: 51.684
          - type: map_at_1
            value: 28.778
          - type: map_at_10
            value: 37.632
          - type: map_at_100
            value: 38.800000000000004
          - type: map_at_1000
            value: 38.934999999999995
          - type: map_at_3
            value: 35.293
          - type: map_at_5
            value: 36.547000000000004
          - type: mrr_at_1
            value: 35.35
          - type: mrr_at_10
            value: 42.936
          - type: mrr_at_100
            value: 43.69
          - type: mrr_at_1000
            value: 43.739
          - type: mrr_at_3
            value: 41.062
          - type: mrr_at_5
            value: 42.097
          - type: ndcg_at_1
            value: 35.35
          - type: ndcg_at_10
            value: 42.528
          - type: ndcg_at_100
            value: 46.983000000000004
          - type: ndcg_at_1000
            value: 49.187999999999995
          - type: ndcg_at_3
            value: 39.271
          - type: ndcg_at_5
            value: 40.654
          - type: precision_at_1
            value: 35.35
          - type: precision_at_10
            value: 7.828
          - type: precision_at_100
            value: 1.3010000000000002
          - type: precision_at_1000
            value: 0.17700000000000002
          - type: precision_at_3
            value: 18.96
          - type: precision_at_5
            value: 13.120999999999999
          - type: recall_at_1
            value: 28.778
          - type: recall_at_10
            value: 50.775000000000006
          - type: recall_at_100
            value: 69.66799999999999
          - type: recall_at_1000
            value: 83.638
          - type: recall_at_3
            value: 40.757
          - type: recall_at_5
            value: 44.86
          - type: map_at_1
            value: 37.584
          - type: map_at_10
            value: 49.69
          - type: map_at_100
            value: 50.639
          - type: map_at_1000
            value: 50.702999999999996
          - type: map_at_3
            value: 46.61
          - type: map_at_5
            value: 48.486000000000004
          - type: mrr_at_1
            value: 43.009
          - type: mrr_at_10
            value: 52.949999999999996
          - type: mrr_at_100
            value: 53.618
          - type: mrr_at_1000
            value: 53.65299999999999
          - type: mrr_at_3
            value: 50.605999999999995
          - type: mrr_at_5
            value: 52.095
          - type: ndcg_at_1
            value: 43.009
          - type: ndcg_at_10
            value: 55.278000000000006
          - type: ndcg_at_100
            value: 59.134
          - type: ndcg_at_1000
            value: 60.528999999999996
          - type: ndcg_at_3
            value: 50.184
          - type: ndcg_at_5
            value: 52.919000000000004
          - type: precision_at_1
            value: 43.009
          - type: precision_at_10
            value: 8.821
          - type: precision_at_100
            value: 1.161
          - type: precision_at_1000
            value: 0.133
          - type: precision_at_3
            value: 22.424
          - type: precision_at_5
            value: 15.436
          - type: recall_at_1
            value: 37.584
          - type: recall_at_10
            value: 68.514
          - type: recall_at_100
            value: 85.099
          - type: recall_at_1000
            value: 95.123
          - type: recall_at_3
            value: 55.007
          - type: recall_at_5
            value: 61.714999999999996
          - type: map_at_1
            value: 24.7
          - type: map_at_10
            value: 32.804
          - type: map_at_100
            value: 33.738
          - type: map_at_1000
            value: 33.825
          - type: map_at_3
            value: 30.639
          - type: map_at_5
            value: 31.781
          - type: mrr_at_1
            value: 26.328000000000003
          - type: mrr_at_10
            value: 34.679
          - type: mrr_at_100
            value: 35.510000000000005
          - type: mrr_at_1000
            value: 35.577999999999996
          - type: mrr_at_3
            value: 32.58
          - type: mrr_at_5
            value: 33.687
          - type: ndcg_at_1
            value: 26.328000000000003
          - type: ndcg_at_10
            value: 37.313
          - type: ndcg_at_100
            value: 42.004000000000005
          - type: ndcg_at_1000
            value: 44.232
          - type: ndcg_at_3
            value: 33.076
          - type: ndcg_at_5
            value: 34.966
          - type: precision_at_1
            value: 26.328000000000003
          - type: precision_at_10
            value: 5.627
          - type: precision_at_100
            value: 0.8410000000000001
          - type: precision_at_1000
            value: 0.106
          - type: precision_at_3
            value: 14.011000000000001
          - type: precision_at_5
            value: 9.582
          - type: recall_at_1
            value: 24.7
          - type: recall_at_10
            value: 49.324
          - type: recall_at_100
            value: 71.018
          - type: recall_at_1000
            value: 87.905
          - type: recall_at_3
            value: 37.7
          - type: recall_at_5
            value: 42.281
          - type: map_at_1
            value: 14.350999999999999
          - type: map_at_10
            value: 21.745
          - type: map_at_100
            value: 22.731
          - type: map_at_1000
            value: 22.852
          - type: map_at_3
            value: 19.245
          - type: map_at_5
            value: 20.788
          - type: mrr_at_1
            value: 18.159
          - type: mrr_at_10
            value: 25.833000000000002
          - type: mrr_at_100
            value: 26.728
          - type: mrr_at_1000
            value: 26.802
          - type: mrr_at_3
            value: 23.383000000000003
          - type: mrr_at_5
            value: 24.887999999999998
          - type: ndcg_at_1
            value: 18.159
          - type: ndcg_at_10
            value: 26.518000000000004
          - type: ndcg_at_100
            value: 31.473000000000003
          - type: ndcg_at_1000
            value: 34.576
          - type: ndcg_at_3
            value: 21.907
          - type: ndcg_at_5
            value: 24.39
          - type: precision_at_1
            value: 18.159
          - type: precision_at_10
            value: 4.938
          - type: precision_at_100
            value: 0.853
          - type: precision_at_1000
            value: 0.125
          - type: precision_at_3
            value: 10.655000000000001
          - type: precision_at_5
            value: 7.985
          - type: recall_at_1
            value: 14.350999999999999
          - type: recall_at_10
            value: 37.284
          - type: recall_at_100
            value: 59.11300000000001
          - type: recall_at_1000
            value: 81.634
          - type: recall_at_3
            value: 24.753
          - type: recall_at_5
            value: 30.979
          - type: map_at_1
            value: 26.978
          - type: map_at_10
            value: 36.276
          - type: map_at_100
            value: 37.547000000000004
          - type: map_at_1000
            value: 37.678
          - type: map_at_3
            value: 33.674
          - type: map_at_5
            value: 35.119
          - type: mrr_at_1
            value: 32.916000000000004
          - type: mrr_at_10
            value: 41.798
          - type: mrr_at_100
            value: 42.72
          - type: mrr_at_1000
            value: 42.778
          - type: mrr_at_3
            value: 39.493
          - type: mrr_at_5
            value: 40.927
          - type: ndcg_at_1
            value: 32.916000000000004
          - type: ndcg_at_10
            value: 41.81
          - type: ndcg_at_100
            value: 47.284
          - type: ndcg_at_1000
            value: 49.702
          - type: ndcg_at_3
            value: 37.486999999999995
          - type: ndcg_at_5
            value: 39.597
          - type: precision_at_1
            value: 32.916000000000004
          - type: precision_at_10
            value: 7.411
          - type: precision_at_100
            value: 1.189
          - type: precision_at_1000
            value: 0.158
          - type: precision_at_3
            value: 17.581
          - type: precision_at_5
            value: 12.397
          - type: recall_at_1
            value: 26.978
          - type: recall_at_10
            value: 52.869
          - type: recall_at_100
            value: 75.78399999999999
          - type: recall_at_1000
            value: 91.545
          - type: recall_at_3
            value: 40.717
          - type: recall_at_5
            value: 46.168
          - type: map_at_1
            value: 24.641
          - type: map_at_10
            value: 32.916000000000004
          - type: map_at_100
            value: 34.165
          - type: map_at_1000
            value: 34.286
          - type: map_at_3
            value: 30.335
          - type: map_at_5
            value: 31.569000000000003
          - type: mrr_at_1
            value: 30.593999999999998
          - type: mrr_at_10
            value: 38.448
          - type: mrr_at_100
            value: 39.299
          - type: mrr_at_1000
            value: 39.362
          - type: mrr_at_3
            value: 36.244
          - type: mrr_at_5
            value: 37.232
          - type: ndcg_at_1
            value: 30.593999999999998
          - type: ndcg_at_10
            value: 38.2
          - type: ndcg_at_100
            value: 43.742
          - type: ndcg_at_1000
            value: 46.217000000000006
          - type: ndcg_at_3
            value: 33.925
          - type: ndcg_at_5
            value: 35.394
          - type: precision_at_1
            value: 30.593999999999998
          - type: precision_at_10
            value: 6.895
          - type: precision_at_100
            value: 1.1320000000000001
          - type: precision_at_1000
            value: 0.153
          - type: precision_at_3
            value: 16.096
          - type: precision_at_5
            value: 11.05
          - type: recall_at_1
            value: 24.641
          - type: recall_at_10
            value: 48.588
          - type: recall_at_100
            value: 72.841
          - type: recall_at_1000
            value: 89.535
          - type: recall_at_3
            value: 36.087
          - type: recall_at_5
            value: 40.346
          - type: map_at_1
            value: 24.79425
          - type: map_at_10
            value: 33.12033333333333
          - type: map_at_100
            value: 34.221333333333334
          - type: map_at_1000
            value: 34.3435
          - type: map_at_3
            value: 30.636583333333338
          - type: map_at_5
            value: 31.974083333333326
          - type: mrr_at_1
            value: 29.242416666666664
          - type: mrr_at_10
            value: 37.11675
          - type: mrr_at_100
            value: 37.93783333333334
          - type: mrr_at_1000
            value: 38.003083333333336
          - type: mrr_at_3
            value: 34.904666666666664
          - type: mrr_at_5
            value: 36.12916666666667
          - type: ndcg_at_1
            value: 29.242416666666664
          - type: ndcg_at_10
            value: 38.03416666666667
          - type: ndcg_at_100
            value: 42.86674999999999
          - type: ndcg_at_1000
            value: 45.34550000000001
          - type: ndcg_at_3
            value: 33.76466666666666
          - type: ndcg_at_5
            value: 35.668666666666674
          - type: precision_at_1
            value: 29.242416666666664
          - type: precision_at_10
            value: 6.589833333333334
          - type: precision_at_100
            value: 1.0693333333333332
          - type: precision_at_1000
            value: 0.14641666666666667
          - type: precision_at_3
            value: 15.430749999999998
          - type: precision_at_5
            value: 10.833833333333333
          - type: recall_at_1
            value: 24.79425
          - type: recall_at_10
            value: 48.582916666666655
          - type: recall_at_100
            value: 69.88499999999999
          - type: recall_at_1000
            value: 87.211
          - type: recall_at_3
            value: 36.625499999999995
          - type: recall_at_5
            value: 41.553999999999995
          - type: map_at_1
            value: 22.767
          - type: map_at_10
            value: 28.450999999999997
          - type: map_at_100
            value: 29.332
          - type: map_at_1000
            value: 29.426000000000002
          - type: map_at_3
            value: 26.379
          - type: map_at_5
            value: 27.584999999999997
          - type: mrr_at_1
            value: 25.46
          - type: mrr_at_10
            value: 30.974
          - type: mrr_at_100
            value: 31.784000000000002
          - type: mrr_at_1000
            value: 31.857999999999997
          - type: mrr_at_3
            value: 28.962
          - type: mrr_at_5
            value: 30.066
          - type: ndcg_at_1
            value: 25.46
          - type: ndcg_at_10
            value: 32.041
          - type: ndcg_at_100
            value: 36.522
          - type: ndcg_at_1000
            value: 39.101
          - type: ndcg_at_3
            value: 28.152
          - type: ndcg_at_5
            value: 30.03
          - type: precision_at_1
            value: 25.46
          - type: precision_at_10
            value: 4.893
          - type: precision_at_100
            value: 0.77
          - type: precision_at_1000
            value: 0.107
          - type: precision_at_3
            value: 11.605
          - type: precision_at_5
            value: 8.19
          - type: recall_at_1
            value: 22.767
          - type: recall_at_10
            value: 40.71
          - type: recall_at_100
            value: 61.334999999999994
          - type: recall_at_1000
            value: 80.567
          - type: recall_at_3
            value: 30.198000000000004
          - type: recall_at_5
            value: 34.803
          - type: map_at_1
            value: 16.722
          - type: map_at_10
            value: 22.794
          - type: map_at_100
            value: 23.7
          - type: map_at_1000
            value: 23.822
          - type: map_at_3
            value: 20.781
          - type: map_at_5
            value: 22.024
          - type: mrr_at_1
            value: 20.061999999999998
          - type: mrr_at_10
            value: 26.346999999999998
          - type: mrr_at_100
            value: 27.153
          - type: mrr_at_1000
            value: 27.233
          - type: mrr_at_3
            value: 24.375
          - type: mrr_at_5
            value: 25.593
          - type: ndcg_at_1
            value: 20.061999999999998
          - type: ndcg_at_10
            value: 26.785999999999998
          - type: ndcg_at_100
            value: 31.319999999999997
          - type: ndcg_at_1000
            value: 34.346
          - type: ndcg_at_3
            value: 23.219
          - type: ndcg_at_5
            value: 25.107000000000003
          - type: precision_at_1
            value: 20.061999999999998
          - type: precision_at_10
            value: 4.78
          - type: precision_at_100
            value: 0.83
          - type: precision_at_1000
            value: 0.125
          - type: precision_at_3
            value: 10.874
          - type: precision_at_5
            value: 7.956
          - type: recall_at_1
            value: 16.722
          - type: recall_at_10
            value: 35.204
          - type: recall_at_100
            value: 55.797
          - type: recall_at_1000
            value: 77.689
          - type: recall_at_3
            value: 25.245
          - type: recall_at_5
            value: 30.115
          - type: map_at_1
            value: 24.842
          - type: map_at_10
            value: 32.917
          - type: map_at_100
            value: 33.961000000000006
          - type: map_at_1000
            value: 34.069
          - type: map_at_3
            value: 30.595
          - type: map_at_5
            value: 31.837
          - type: mrr_at_1
            value: 29.011
          - type: mrr_at_10
            value: 36.977
          - type: mrr_at_100
            value: 37.814
          - type: mrr_at_1000
            value: 37.885999999999996
          - type: mrr_at_3
            value: 34.966
          - type: mrr_at_5
            value: 36.043
          - type: ndcg_at_1
            value: 29.011
          - type: ndcg_at_10
            value: 37.735
          - type: ndcg_at_100
            value: 42.683
          - type: ndcg_at_1000
            value: 45.198
          - type: ndcg_at_3
            value: 33.650000000000006
          - type: ndcg_at_5
            value: 35.386
          - type: precision_at_1
            value: 29.011
          - type: precision_at_10
            value: 6.259
          - type: precision_at_100
            value: 0.984
          - type: precision_at_1000
            value: 0.13
          - type: precision_at_3
            value: 15.329999999999998
          - type: precision_at_5
            value: 10.541
          - type: recall_at_1
            value: 24.842
          - type: recall_at_10
            value: 48.304
          - type: recall_at_100
            value: 70.04899999999999
          - type: recall_at_1000
            value: 87.82600000000001
          - type: recall_at_3
            value: 36.922
          - type: recall_at_5
            value: 41.449999999999996
          - type: map_at_1
            value: 24.252000000000002
          - type: map_at_10
            value: 32.293
          - type: map_at_100
            value: 33.816
          - type: map_at_1000
            value: 34.053
          - type: map_at_3
            value: 29.781999999999996
          - type: map_at_5
            value: 31.008000000000003
          - type: mrr_at_1
            value: 29.051
          - type: mrr_at_10
            value: 36.722
          - type: mrr_at_100
            value: 37.663000000000004
          - type: mrr_at_1000
            value: 37.734
          - type: mrr_at_3
            value: 34.354
          - type: mrr_at_5
            value: 35.609
          - type: ndcg_at_1
            value: 29.051
          - type: ndcg_at_10
            value: 37.775999999999996
          - type: ndcg_at_100
            value: 43.221
          - type: ndcg_at_1000
            value: 46.116
          - type: ndcg_at_3
            value: 33.403
          - type: ndcg_at_5
            value: 35.118
          - type: precision_at_1
            value: 29.051
          - type: precision_at_10
            value: 7.332
          - type: precision_at_100
            value: 1.49
          - type: precision_at_1000
            value: 0.23600000000000002
          - type: precision_at_3
            value: 15.415000000000001
          - type: precision_at_5
            value: 11.107
          - type: recall_at_1
            value: 24.252000000000002
          - type: recall_at_10
            value: 47.861
          - type: recall_at_100
            value: 72.21600000000001
          - type: recall_at_1000
            value: 90.886
          - type: recall_at_3
            value: 35.533
          - type: recall_at_5
            value: 39.959
          - type: map_at_1
            value: 20.025000000000002
          - type: map_at_10
            value: 27.154
          - type: map_at_100
            value: 28.118
          - type: map_at_1000
            value: 28.237000000000002
          - type: map_at_3
            value: 25.017
          - type: map_at_5
            value: 25.832
          - type: mrr_at_1
            value: 21.627
          - type: mrr_at_10
            value: 28.884999999999998
          - type: mrr_at_100
            value: 29.741
          - type: mrr_at_1000
            value: 29.831999999999997
          - type: mrr_at_3
            value: 26.741
          - type: mrr_at_5
            value: 27.628000000000004
          - type: ndcg_at_1
            value: 21.627
          - type: ndcg_at_10
            value: 31.436999999999998
          - type: ndcg_at_100
            value: 36.181000000000004
          - type: ndcg_at_1000
            value: 38.986
          - type: ndcg_at_3
            value: 27.025
          - type: ndcg_at_5
            value: 28.436
          - type: precision_at_1
            value: 21.627
          - type: precision_at_10
            value: 5.009
          - type: precision_at_100
            value: 0.7929999999999999
          - type: precision_at_1000
            value: 0.11299999999999999
          - type: precision_at_3
            value: 11.522
          - type: precision_at_5
            value: 7.763000000000001
          - type: recall_at_1
            value: 20.025000000000002
          - type: recall_at_10
            value: 42.954
          - type: recall_at_100
            value: 64.67500000000001
          - type: recall_at_1000
            value: 85.301
          - type: recall_at_3
            value: 30.892999999999997
          - type: recall_at_5
            value: 34.288000000000004
      - task:
          type: Retrieval
        dataset:
          name: MTEB ClimateFEVER
          type: climate-fever
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 10.079
          - type: map_at_10
            value: 16.930999999999997
          - type: map_at_100
            value: 18.398999999999997
          - type: map_at_1000
            value: 18.561
          - type: map_at_3
            value: 14.294
          - type: map_at_5
            value: 15.579
          - type: mrr_at_1
            value: 22.606
          - type: mrr_at_10
            value: 32.513
          - type: mrr_at_100
            value: 33.463
          - type: mrr_at_1000
            value: 33.513999999999996
          - type: mrr_at_3
            value: 29.479
          - type: mrr_at_5
            value: 31.3
          - type: ndcg_at_1
            value: 22.606
          - type: ndcg_at_10
            value: 24.053
          - type: ndcg_at_100
            value: 30.258000000000003
          - type: ndcg_at_1000
            value: 33.516
          - type: ndcg_at_3
            value: 19.721
          - type: ndcg_at_5
            value: 21.144
          - type: precision_at_1
            value: 22.606
          - type: precision_at_10
            value: 7.55
          - type: precision_at_100
            value: 1.399
          - type: precision_at_1000
            value: 0.2
          - type: precision_at_3
            value: 14.701
          - type: precision_at_5
            value: 11.192
          - type: recall_at_1
            value: 10.079
          - type: recall_at_10
            value: 28.970000000000002
          - type: recall_at_100
            value: 50.805
          - type: recall_at_1000
            value: 69.378
          - type: recall_at_3
            value: 18.199
          - type: recall_at_5
            value: 22.442
      - task:
          type: Retrieval
        dataset:
          name: MTEB DBPedia
          type: dbpedia-entity
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 7.794
          - type: map_at_10
            value: 15.165999999999999
          - type: map_at_100
            value: 20.508000000000003
          - type: map_at_1000
            value: 21.809
          - type: map_at_3
            value: 11.568000000000001
          - type: map_at_5
            value: 13.059000000000001
          - type: mrr_at_1
            value: 56.49999999999999
          - type: mrr_at_10
            value: 65.90899999999999
          - type: mrr_at_100
            value: 66.352
          - type: mrr_at_1000
            value: 66.369
          - type: mrr_at_3
            value: 64
          - type: mrr_at_5
            value: 65.10000000000001
          - type: ndcg_at_1
            value: 44.25
          - type: ndcg_at_10
            value: 32.649
          - type: ndcg_at_100
            value: 36.668
          - type: ndcg_at_1000
            value: 43.918
          - type: ndcg_at_3
            value: 37.096000000000004
          - type: ndcg_at_5
            value: 34.048
          - type: precision_at_1
            value: 56.49999999999999
          - type: precision_at_10
            value: 25.45
          - type: precision_at_100
            value: 8.055
          - type: precision_at_1000
            value: 1.7489999999999999
          - type: precision_at_3
            value: 41
          - type: precision_at_5
            value: 32.85
          - type: recall_at_1
            value: 7.794
          - type: recall_at_10
            value: 20.101
          - type: recall_at_100
            value: 42.448
          - type: recall_at_1000
            value: 65.88000000000001
          - type: recall_at_3
            value: 12.753
          - type: recall_at_5
            value: 15.307
      - task:
          type: Classification
        dataset:
          name: MTEB EmotionClassification
          type: mteb/emotion
          config: default
          split: test
          revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
        metrics:
          - type: accuracy
            value: 44.01
          - type: f1
            value: 38.659680951114964
      - task:
          type: Retrieval
        dataset:
          name: MTEB FEVER
          type: fever
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 49.713
          - type: map_at_10
            value: 61.79
          - type: map_at_100
            value: 62.28
          - type: map_at_1000
            value: 62.297000000000004
          - type: map_at_3
            value: 59.361
          - type: map_at_5
            value: 60.92100000000001
          - type: mrr_at_1
            value: 53.405
          - type: mrr_at_10
            value: 65.79899999999999
          - type: mrr_at_100
            value: 66.219
          - type: mrr_at_1000
            value: 66.227
          - type: mrr_at_3
            value: 63.431000000000004
          - type: mrr_at_5
            value: 64.98
          - type: ndcg_at_1
            value: 53.405
          - type: ndcg_at_10
            value: 68.01899999999999
          - type: ndcg_at_100
            value: 70.197
          - type: ndcg_at_1000
            value: 70.571
          - type: ndcg_at_3
            value: 63.352
          - type: ndcg_at_5
            value: 66.018
          - type: precision_at_1
            value: 53.405
          - type: precision_at_10
            value: 9.119
          - type: precision_at_100
            value: 1.03
          - type: precision_at_1000
            value: 0.107
          - type: precision_at_3
            value: 25.602999999999998
          - type: precision_at_5
            value: 16.835
          - type: recall_at_1
            value: 49.713
          - type: recall_at_10
            value: 83.306
          - type: recall_at_100
            value: 92.92
          - type: recall_at_1000
            value: 95.577
          - type: recall_at_3
            value: 70.798
          - type: recall_at_5
            value: 77.254
      - task:
          type: Retrieval
        dataset:
          name: MTEB FiQA2018
          type: fiqa
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 15.310000000000002
          - type: map_at_10
            value: 26.204
          - type: map_at_100
            value: 27.932000000000002
          - type: map_at_1000
            value: 28.121000000000002
          - type: map_at_3
            value: 22.481
          - type: map_at_5
            value: 24.678
          - type: mrr_at_1
            value: 29.784
          - type: mrr_at_10
            value: 39.582
          - type: mrr_at_100
            value: 40.52
          - type: mrr_at_1000
            value: 40.568
          - type: mrr_at_3
            value: 37.114000000000004
          - type: mrr_at_5
            value: 38.596000000000004
          - type: ndcg_at_1
            value: 29.784
          - type: ndcg_at_10
            value: 33.432
          - type: ndcg_at_100
            value: 40.281
          - type: ndcg_at_1000
            value: 43.653999999999996
          - type: ndcg_at_3
            value: 29.612
          - type: ndcg_at_5
            value: 31.223
          - type: precision_at_1
            value: 29.784
          - type: precision_at_10
            value: 9.645
          - type: precision_at_100
            value: 1.645
          - type: precision_at_1000
            value: 0.22499999999999998
          - type: precision_at_3
            value: 20.165
          - type: precision_at_5
            value: 15.401000000000002
          - type: recall_at_1
            value: 15.310000000000002
          - type: recall_at_10
            value: 40.499
          - type: recall_at_100
            value: 66.643
          - type: recall_at_1000
            value: 87.059
          - type: recall_at_3
            value: 27.492
          - type: recall_at_5
            value: 33.748
      - task:
          type: Retrieval
        dataset:
          name: MTEB HotpotQA
          type: hotpotqa
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 33.599000000000004
          - type: map_at_10
            value: 47.347
          - type: map_at_100
            value: 48.191
          - type: map_at_1000
            value: 48.263
          - type: map_at_3
            value: 44.698
          - type: map_at_5
            value: 46.278999999999996
          - type: mrr_at_1
            value: 67.19800000000001
          - type: mrr_at_10
            value: 74.054
          - type: mrr_at_100
            value: 74.376
          - type: mrr_at_1000
            value: 74.392
          - type: mrr_at_3
            value: 72.849
          - type: mrr_at_5
            value: 73.643
          - type: ndcg_at_1
            value: 67.19800000000001
          - type: ndcg_at_10
            value: 56.482
          - type: ndcg_at_100
            value: 59.694
          - type: ndcg_at_1000
            value: 61.204
          - type: ndcg_at_3
            value: 52.43299999999999
          - type: ndcg_at_5
            value: 54.608000000000004
          - type: precision_at_1
            value: 67.19800000000001
          - type: precision_at_10
            value: 11.613999999999999
          - type: precision_at_100
            value: 1.415
          - type: precision_at_1000
            value: 0.16199999999999998
          - type: precision_at_3
            value: 32.726
          - type: precision_at_5
            value: 21.349999999999998
          - type: recall_at_1
            value: 33.599000000000004
          - type: recall_at_10
            value: 58.069
          - type: recall_at_100
            value: 70.736
          - type: recall_at_1000
            value: 80.804
          - type: recall_at_3
            value: 49.088
          - type: recall_at_5
            value: 53.376000000000005
      - task:
          type: Classification
        dataset:
          name: MTEB ImdbClassification
          type: mteb/imdb
          config: default
          split: test
          revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
        metrics:
          - type: accuracy
            value: 73.64359999999999
          - type: ap
            value: 67.54685976014599
          - type: f1
            value: 73.55148707559482
      - task:
          type: Retrieval
        dataset:
          name: MTEB MSMARCO
          type: msmarco
          config: default
          split: dev
          revision: None
        metrics:
          - type: map_at_1
            value: 19.502
          - type: map_at_10
            value: 30.816
          - type: map_at_100
            value: 32.007999999999996
          - type: map_at_1000
            value: 32.067
          - type: map_at_3
            value: 27.215
          - type: map_at_5
            value: 29.304000000000002
          - type: mrr_at_1
            value: 20.072000000000003
          - type: mrr_at_10
            value: 31.406
          - type: mrr_at_100
            value: 32.549
          - type: mrr_at_1000
            value: 32.602
          - type: mrr_at_3
            value: 27.839000000000002
          - type: mrr_at_5
            value: 29.926000000000002
          - type: ndcg_at_1
            value: 20.086000000000002
          - type: ndcg_at_10
            value: 37.282
          - type: ndcg_at_100
            value: 43.206
          - type: ndcg_at_1000
            value: 44.690000000000005
          - type: ndcg_at_3
            value: 29.932
          - type: ndcg_at_5
            value: 33.668
          - type: precision_at_1
            value: 20.086000000000002
          - type: precision_at_10
            value: 5.961
          - type: precision_at_100
            value: 0.898
          - type: precision_at_1000
            value: 0.10200000000000001
          - type: precision_at_3
            value: 12.856000000000002
          - type: precision_at_5
            value: 9.596
          - type: recall_at_1
            value: 19.502
          - type: recall_at_10
            value: 57.182
          - type: recall_at_100
            value: 84.952
          - type: recall_at_1000
            value: 96.34700000000001
          - type: recall_at_3
            value: 37.193
          - type: recall_at_5
            value: 46.157
      - task:
          type: Classification
        dataset:
          name: MTEB MTOPDomainClassification (en)
          type: mteb/mtop_domain
          config: en
          split: test
          revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
        metrics:
          - type: accuracy
            value: 93.96488828089375
          - type: f1
            value: 93.32119260543482
      - task:
          type: Classification
        dataset:
          name: MTEB MTOPIntentClassification (en)
          type: mteb/mtop_intent
          config: en
          split: test
          revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
        metrics:
          - type: accuracy
            value: 72.4965800273598
          - type: f1
            value: 49.34896217536082
      - task:
          type: Classification
        dataset:
          name: MTEB MassiveIntentClassification (en)
          type: mteb/amazon_massive_intent
          config: en
          split: test
          revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
        metrics:
          - type: accuracy
            value: 67.60928043039678
          - type: f1
            value: 64.34244712074538
      - task:
          type: Classification
        dataset:
          name: MTEB MassiveScenarioClassification (en)
          type: mteb/amazon_massive_scenario
          config: en
          split: test
          revision: 7d571f92784cd94a019292a1f45445077d0ef634
        metrics:
          - type: accuracy
            value: 69.75453934095493
          - type: f1
            value: 68.39224867489249
      - task:
          type: Clustering
        dataset:
          name: MTEB MedrxivClusteringP2P
          type: mteb/medrxiv-clustering-p2p
          config: default
          split: test
          revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
        metrics:
          - type: v_measure
            value: 31.862573504920082
      - task:
          type: Clustering
        dataset:
          name: MTEB MedrxivClusteringS2S
          type: mteb/medrxiv-clustering-s2s
          config: default
          split: test
          revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
        metrics:
          - type: v_measure
            value: 27.511123551196803
      - task:
          type: Reranking
        dataset:
          name: MTEB MindSmallReranking
          type: mteb/mind_small
          config: default
          split: test
          revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
        metrics:
          - type: map
            value: 30.99145104942086
          - type: mrr
            value: 32.03606480418627
      - task:
          type: Retrieval
        dataset:
          name: MTEB NFCorpus
          type: nfcorpus
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 5.015
          - type: map_at_10
            value: 11.054
          - type: map_at_100
            value: 13.773
          - type: map_at_1000
            value: 15.082999999999998
          - type: map_at_3
            value: 8.253
          - type: map_at_5
            value: 9.508999999999999
          - type: mrr_at_1
            value: 42.105
          - type: mrr_at_10
            value: 50.44499999999999
          - type: mrr_at_100
            value: 51.080000000000005
          - type: mrr_at_1000
            value: 51.129999999999995
          - type: mrr_at_3
            value: 48.555
          - type: mrr_at_5
            value: 49.84
          - type: ndcg_at_1
            value: 40.402
          - type: ndcg_at_10
            value: 30.403000000000002
          - type: ndcg_at_100
            value: 28.216
          - type: ndcg_at_1000
            value: 37.021
          - type: ndcg_at_3
            value: 35.53
          - type: ndcg_at_5
            value: 33.202999999999996
          - type: precision_at_1
            value: 42.105
          - type: precision_at_10
            value: 22.353
          - type: precision_at_100
            value: 7.266
          - type: precision_at_1000
            value: 2.011
          - type: precision_at_3
            value: 32.921
          - type: precision_at_5
            value: 28.297
          - type: recall_at_1
            value: 5.015
          - type: recall_at_10
            value: 14.393
          - type: recall_at_100
            value: 28.893
          - type: recall_at_1000
            value: 60.18
          - type: recall_at_3
            value: 9.184000000000001
          - type: recall_at_5
            value: 11.39
      - task:
          type: Retrieval
        dataset:
          name: MTEB NQ
          type: nq
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 29.524
          - type: map_at_10
            value: 44.182
          - type: map_at_100
            value: 45.228
          - type: map_at_1000
            value: 45.265
          - type: map_at_3
            value: 39.978
          - type: map_at_5
            value: 42.482
          - type: mrr_at_1
            value: 33.256
          - type: mrr_at_10
            value: 46.661
          - type: mrr_at_100
            value: 47.47
          - type: mrr_at_1000
            value: 47.496
          - type: mrr_at_3
            value: 43.187999999999995
          - type: mrr_at_5
            value: 45.330999999999996
          - type: ndcg_at_1
            value: 33.227000000000004
          - type: ndcg_at_10
            value: 51.589
          - type: ndcg_at_100
            value: 56.043
          - type: ndcg_at_1000
            value: 56.937000000000005
          - type: ndcg_at_3
            value: 43.751
          - type: ndcg_at_5
            value: 47.937000000000005
          - type: precision_at_1
            value: 33.227000000000004
          - type: precision_at_10
            value: 8.556999999999999
          - type: precision_at_100
            value: 1.103
          - type: precision_at_1000
            value: 0.11900000000000001
          - type: precision_at_3
            value: 19.921
          - type: precision_at_5
            value: 14.396999999999998
          - type: recall_at_1
            value: 29.524
          - type: recall_at_10
            value: 71.615
          - type: recall_at_100
            value: 91.056
          - type: recall_at_1000
            value: 97.72800000000001
          - type: recall_at_3
            value: 51.451
          - type: recall_at_5
            value: 61.119
      - task:
          type: Retrieval
        dataset:
          name: MTEB QuoraRetrieval
          type: quora
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 69.596
          - type: map_at_10
            value: 83.281
          - type: map_at_100
            value: 83.952
          - type: map_at_1000
            value: 83.97200000000001
          - type: map_at_3
            value: 80.315
          - type: map_at_5
            value: 82.223
          - type: mrr_at_1
            value: 80.17
          - type: mrr_at_10
            value: 86.522
          - type: mrr_at_100
            value: 86.644
          - type: mrr_at_1000
            value: 86.64500000000001
          - type: mrr_at_3
            value: 85.438
          - type: mrr_at_5
            value: 86.21799999999999
          - type: ndcg_at_1
            value: 80.19
          - type: ndcg_at_10
            value: 87.19
          - type: ndcg_at_100
            value: 88.567
          - type: ndcg_at_1000
            value: 88.70400000000001
          - type: ndcg_at_3
            value: 84.17999999999999
          - type: ndcg_at_5
            value: 85.931
          - type: precision_at_1
            value: 80.19
          - type: precision_at_10
            value: 13.209000000000001
          - type: precision_at_100
            value: 1.518
          - type: precision_at_1000
            value: 0.157
          - type: precision_at_3
            value: 36.717
          - type: precision_at_5
            value: 24.248
          - type: recall_at_1
            value: 69.596
          - type: recall_at_10
            value: 94.533
          - type: recall_at_100
            value: 99.322
          - type: recall_at_1000
            value: 99.965
          - type: recall_at_3
            value: 85.911
          - type: recall_at_5
            value: 90.809
      - task:
          type: Clustering
        dataset:
          name: MTEB RedditClustering
          type: mteb/reddit-clustering
          config: default
          split: test
          revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
        metrics:
          - type: v_measure
            value: 49.27650627571912
      - task:
          type: Clustering
        dataset:
          name: MTEB RedditClusteringP2P
          type: mteb/reddit-clustering-p2p
          config: default
          split: test
          revision: 282350215ef01743dc01b456c7f5241fa8937f16
        metrics:
          - type: v_measure
            value: 57.08550946534183
      - task:
          type: Retrieval
        dataset:
          name: MTEB SCIDOCS
          type: scidocs
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 4.568
          - type: map_at_10
            value: 10.862
          - type: map_at_100
            value: 12.757
          - type: map_at_1000
            value: 13.031
          - type: map_at_3
            value: 7.960000000000001
          - type: map_at_5
            value: 9.337
          - type: mrr_at_1
            value: 22.5
          - type: mrr_at_10
            value: 32.6
          - type: mrr_at_100
            value: 33.603
          - type: mrr_at_1000
            value: 33.672000000000004
          - type: mrr_at_3
            value: 29.299999999999997
          - type: mrr_at_5
            value: 31.25
          - type: ndcg_at_1
            value: 22.5
          - type: ndcg_at_10
            value: 18.605
          - type: ndcg_at_100
            value: 26.029999999999998
          - type: ndcg_at_1000
            value: 31.256
          - type: ndcg_at_3
            value: 17.873
          - type: ndcg_at_5
            value: 15.511
          - type: precision_at_1
            value: 22.5
          - type: precision_at_10
            value: 9.58
          - type: precision_at_100
            value: 2.033
          - type: precision_at_1000
            value: 0.33
          - type: precision_at_3
            value: 16.633
          - type: precision_at_5
            value: 13.54
          - type: recall_at_1
            value: 4.568
          - type: recall_at_10
            value: 19.402
          - type: recall_at_100
            value: 41.277
          - type: recall_at_1000
            value: 66.963
          - type: recall_at_3
            value: 10.112
          - type: recall_at_5
            value: 13.712
      - task:
          type: STS
        dataset:
          name: MTEB SICK-R
          type: mteb/sickr-sts
          config: default
          split: test
          revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
        metrics:
          - type: cos_sim_pearson
            value: 83.31992291680787
          - type: cos_sim_spearman
            value: 76.7212346922664
          - type: euclidean_pearson
            value: 80.42189271706478
          - type: euclidean_spearman
            value: 76.7212342532493
          - type: manhattan_pearson
            value: 80.33171093031578
          - type: manhattan_spearman
            value: 76.63192883074694
      - task:
          type: STS
        dataset:
          name: MTEB STS12
          type: mteb/sts12-sts
          config: default
          split: test
          revision: a0d554a64d88156834ff5ae9920b964011b16384
        metrics:
          - type: cos_sim_pearson
            value: 83.16654278886763
          - type: cos_sim_spearman
            value: 73.66390263429565
          - type: euclidean_pearson
            value: 79.7485360086639
          - type: euclidean_spearman
            value: 73.66389870373436
          - type: manhattan_pearson
            value: 79.73652237443706
          - type: manhattan_spearman
            value: 73.65296117151647
      - task:
          type: STS
        dataset:
          name: MTEB STS13
          type: mteb/sts13-sts
          config: default
          split: test
          revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
        metrics:
          - type: cos_sim_pearson
            value: 82.40389689929246
          - type: cos_sim_spearman
            value: 83.29727595993955
          - type: euclidean_pearson
            value: 82.23970587854079
          - type: euclidean_spearman
            value: 83.29727595993955
          - type: manhattan_pearson
            value: 82.18823600831897
          - type: manhattan_spearman
            value: 83.20746192209594
      - task:
          type: STS
        dataset:
          name: MTEB STS14
          type: mteb/sts14-sts
          config: default
          split: test
          revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
        metrics:
          - type: cos_sim_pearson
            value: 81.73505246913413
          - type: cos_sim_spearman
            value: 79.1686548248754
          - type: euclidean_pearson
            value: 80.48889135993412
          - type: euclidean_spearman
            value: 79.16864112930354
          - type: manhattan_pearson
            value: 80.40720651057302
          - type: manhattan_spearman
            value: 79.0640155089286
      - task:
          type: STS
        dataset:
          name: MTEB STS15
          type: mteb/sts15-sts
          config: default
          split: test
          revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
        metrics:
          - type: cos_sim_pearson
            value: 86.3953512879065
          - type: cos_sim_spearman
            value: 87.29947322714338
          - type: euclidean_pearson
            value: 86.59759438529645
          - type: euclidean_spearman
            value: 87.29947511092824
          - type: manhattan_pearson
            value: 86.52097806169155
          - type: manhattan_spearman
            value: 87.22987242146534
      - task:
          type: STS
        dataset:
          name: MTEB STS16
          type: mteb/sts16-sts
          config: default
          split: test
          revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
        metrics:
          - type: cos_sim_pearson
            value: 82.48565753792056
          - type: cos_sim_spearman
            value: 83.6049720319893
          - type: euclidean_pearson
            value: 82.56452023172913
          - type: euclidean_spearman
            value: 83.60490168191697
          - type: manhattan_pearson
            value: 82.58079941137872
          - type: manhattan_spearman
            value: 83.60975807374051
      - 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: 88.18239976618212
          - type: cos_sim_spearman
            value: 88.23061724730616
          - type: euclidean_pearson
            value: 87.78482472776658
          - type: euclidean_spearman
            value: 88.23061724730616
          - type: manhattan_pearson
            value: 87.75059641730239
          - type: manhattan_spearman
            value: 88.22527413524622
      - task:
          type: STS
        dataset:
          name: MTEB STS22 (en)
          type: mteb/sts22-crosslingual-sts
          config: en
          split: test
          revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
        metrics:
          - type: cos_sim_pearson
            value: 63.42816418706765
          - type: cos_sim_spearman
            value: 63.4569864520124
          - type: euclidean_pearson
            value: 64.35405409953853
          - type: euclidean_spearman
            value: 63.4569864520124
          - type: manhattan_pearson
            value: 63.96649236073056
          - type: manhattan_spearman
            value: 63.01448583722708
      - task:
          type: STS
        dataset:
          name: MTEB STSBenchmark
          type: mteb/stsbenchmark-sts
          config: default
          split: test
          revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
        metrics:
          - type: cos_sim_pearson
            value: 83.41659638047614
          - type: cos_sim_spearman
            value: 84.03893866106175
          - type: euclidean_pearson
            value: 84.2251203953798
          - type: euclidean_spearman
            value: 84.03893866106175
          - type: manhattan_pearson
            value: 84.22733643205514
          - type: manhattan_spearman
            value: 84.06504411263612
      - task:
          type: Reranking
        dataset:
          name: MTEB SciDocsRR
          type: mteb/scidocs-reranking
          config: default
          split: test
          revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
        metrics:
          - type: map
            value: 79.75608022582414
          - type: mrr
            value: 94.0947732369301
      - task:
          type: Retrieval
        dataset:
          name: MTEB SciFact
          type: scifact
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 50.161
          - type: map_at_10
            value: 59.458999999999996
          - type: map_at_100
            value: 60.156
          - type: map_at_1000
            value: 60.194
          - type: map_at_3
            value: 56.45400000000001
          - type: map_at_5
            value: 58.165
          - type: mrr_at_1
            value: 53.333
          - type: mrr_at_10
            value: 61.050000000000004
          - type: mrr_at_100
            value: 61.586
          - type: mrr_at_1000
            value: 61.624
          - type: mrr_at_3
            value: 58.889
          - type: mrr_at_5
            value: 60.122
          - type: ndcg_at_1
            value: 53.333
          - type: ndcg_at_10
            value: 63.888999999999996
          - type: ndcg_at_100
            value: 66.963
          - type: ndcg_at_1000
            value: 68.062
          - type: ndcg_at_3
            value: 59.01
          - type: ndcg_at_5
            value: 61.373999999999995
          - type: precision_at_1
            value: 53.333
          - type: precision_at_10
            value: 8.633000000000001
          - type: precision_at_100
            value: 1.027
          - type: precision_at_1000
            value: 0.11199999999999999
          - type: precision_at_3
            value: 23.111
          - type: precision_at_5
            value: 15.467
          - type: recall_at_1
            value: 50.161
          - type: recall_at_10
            value: 75.922
          - type: recall_at_100
            value: 90
          - type: recall_at_1000
            value: 98.667
          - type: recall_at_3
            value: 62.90599999999999
          - type: recall_at_5
            value: 68.828
      - task:
          type: PairClassification
        dataset:
          name: MTEB SprintDuplicateQuestions
          type: mteb/sprintduplicatequestions-pairclassification
          config: default
          split: test
          revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
        metrics:
          - type: cos_sim_accuracy
            value: 99.81188118811882
          - type: cos_sim_ap
            value: 95.11619225962413
          - type: cos_sim_f1
            value: 90.35840484603736
          - type: cos_sim_precision
            value: 91.23343527013252
          - type: cos_sim_recall
            value: 89.5
          - type: dot_accuracy
            value: 99.81188118811882
          - type: dot_ap
            value: 95.11619225962413
          - type: dot_f1
            value: 90.35840484603736
          - type: dot_precision
            value: 91.23343527013252
          - type: dot_recall
            value: 89.5
          - type: euclidean_accuracy
            value: 99.81188118811882
          - type: euclidean_ap
            value: 95.11619225962413
          - type: euclidean_f1
            value: 90.35840484603736
          - type: euclidean_precision
            value: 91.23343527013252
          - type: euclidean_recall
            value: 89.5
          - type: manhattan_accuracy
            value: 99.80891089108911
          - type: manhattan_ap
            value: 95.07294266220966
          - type: manhattan_f1
            value: 90.21794221996959
          - type: manhattan_precision
            value: 91.46968139773895
          - type: manhattan_recall
            value: 89
          - type: max_accuracy
            value: 99.81188118811882
          - type: max_ap
            value: 95.11619225962413
          - type: max_f1
            value: 90.35840484603736
      - task:
          type: Clustering
        dataset:
          name: MTEB StackExchangeClustering
          type: mteb/stackexchange-clustering
          config: default
          split: test
          revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
        metrics:
          - type: v_measure
            value: 55.3481874105239
      - task:
          type: Clustering
        dataset:
          name: MTEB StackExchangeClusteringP2P
          type: mteb/stackexchange-clustering-p2p
          config: default
          split: test
          revision: 815ca46b2622cec33ccafc3735d572c266efdb44
        metrics:
          - type: v_measure
            value: 34.421291695525
      - task:
          type: Reranking
        dataset:
          name: MTEB StackOverflowDupQuestions
          type: mteb/stackoverflowdupquestions-reranking
          config: default
          split: test
          revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
        metrics:
          - type: map
            value: 49.98746633276634
          - type: mrr
            value: 50.63143249724133
      - task:
          type: Summarization
        dataset:
          name: MTEB SummEval
          type: mteb/summeval
          config: default
          split: test
          revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
        metrics:
          - type: cos_sim_pearson
            value: 31.009961979844036
          - type: cos_sim_spearman
            value: 30.558416108881044
          - type: dot_pearson
            value: 31.009964941134253
          - type: dot_spearman
            value: 30.545760761761393
      - task:
          type: Retrieval
        dataset:
          name: MTEB TRECCOVID
          type: trec-covid
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 0.207
          - type: map_at_10
            value: 1.6
          - type: map_at_100
            value: 8.594
          - type: map_at_1000
            value: 20.213
          - type: map_at_3
            value: 0.585
          - type: map_at_5
            value: 0.9039999999999999
          - type: mrr_at_1
            value: 78
          - type: mrr_at_10
            value: 87.4
          - type: mrr_at_100
            value: 87.4
          - type: mrr_at_1000
            value: 87.4
          - type: mrr_at_3
            value: 86.667
          - type: mrr_at_5
            value: 87.06700000000001
          - type: ndcg_at_1
            value: 73
          - type: ndcg_at_10
            value: 65.18
          - type: ndcg_at_100
            value: 49.631
          - type: ndcg_at_1000
            value: 43.498999999999995
          - type: ndcg_at_3
            value: 71.83800000000001
          - type: ndcg_at_5
            value: 69.271
          - type: precision_at_1
            value: 78
          - type: precision_at_10
            value: 69.19999999999999
          - type: precision_at_100
            value: 50.980000000000004
          - type: precision_at_1000
            value: 19.426
          - type: precision_at_3
            value: 77.333
          - type: precision_at_5
            value: 74
          - type: recall_at_1
            value: 0.207
          - type: recall_at_10
            value: 1.822
          - type: recall_at_100
            value: 11.849
          - type: recall_at_1000
            value: 40.492
          - type: recall_at_3
            value: 0.622
          - type: recall_at_5
            value: 0.9809999999999999
      - task:
          type: Retrieval
        dataset:
          name: MTEB Touche2020
          type: webis-touche2020
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 2.001
          - type: map_at_10
            value: 10.376000000000001
          - type: map_at_100
            value: 16.936999999999998
          - type: map_at_1000
            value: 18.615000000000002
          - type: map_at_3
            value: 5.335999999999999
          - type: map_at_5
            value: 7.374
          - type: mrr_at_1
            value: 20.408
          - type: mrr_at_10
            value: 38.29
          - type: mrr_at_100
            value: 39.33
          - type: mrr_at_1000
            value: 39.347
          - type: mrr_at_3
            value: 32.993
          - type: mrr_at_5
            value: 36.973
          - type: ndcg_at_1
            value: 17.347
          - type: ndcg_at_10
            value: 23.515
          - type: ndcg_at_100
            value: 37.457
          - type: ndcg_at_1000
            value: 49.439
          - type: ndcg_at_3
            value: 22.762999999999998
          - type: ndcg_at_5
            value: 22.622
          - type: precision_at_1
            value: 20.408
          - type: precision_at_10
            value: 22.448999999999998
          - type: precision_at_100
            value: 8.184
          - type: precision_at_1000
            value: 1.608
          - type: precision_at_3
            value: 25.85
          - type: precision_at_5
            value: 25.306
          - type: recall_at_1
            value: 2.001
          - type: recall_at_10
            value: 17.422
          - type: recall_at_100
            value: 51.532999999999994
          - type: recall_at_1000
            value: 87.466
          - type: recall_at_3
            value: 6.861000000000001
          - type: recall_at_5
            value: 10.502
      - task:
          type: Classification
        dataset:
          name: MTEB ToxicConversationsClassification
          type: mteb/toxic_conversations_50k
          config: default
          split: test
          revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
        metrics:
          - type: accuracy
            value: 71.54419999999999
          - type: ap
            value: 14.372170450843907
          - type: f1
            value: 54.94420257390529
      - task:
          type: Classification
        dataset:
          name: MTEB TweetSentimentExtractionClassification
          type: mteb/tweet_sentiment_extraction
          config: default
          split: test
          revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
        metrics:
          - type: accuracy
            value: 59.402942840973395
          - type: f1
            value: 59.4166538875571
      - task:
          type: Clustering
        dataset:
          name: MTEB TwentyNewsgroupsClustering
          type: mteb/twentynewsgroups-clustering
          config: default
          split: test
          revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
        metrics:
          - type: v_measure
            value: 41.569064336457906
      - task:
          type: PairClassification
        dataset:
          name: MTEB TwitterSemEval2015
          type: mteb/twittersemeval2015-pairclassification
          config: default
          split: test
          revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
        metrics:
          - type: cos_sim_accuracy
            value: 85.31322644096085
          - type: cos_sim_ap
            value: 72.14518894837381
          - type: cos_sim_f1
            value: 66.67489813557229
          - type: cos_sim_precision
            value: 62.65954977953121
          - type: cos_sim_recall
            value: 71.2401055408971
          - type: dot_accuracy
            value: 85.31322644096085
          - type: dot_ap
            value: 72.14521480685293
          - type: dot_f1
            value: 66.67489813557229
          - type: dot_precision
            value: 62.65954977953121
          - type: dot_recall
            value: 71.2401055408971
          - type: euclidean_accuracy
            value: 85.31322644096085
          - type: euclidean_ap
            value: 72.14520820485349
          - type: euclidean_f1
            value: 66.67489813557229
          - type: euclidean_precision
            value: 62.65954977953121
          - type: euclidean_recall
            value: 71.2401055408971
          - type: manhattan_accuracy
            value: 85.21785778148656
          - type: manhattan_ap
            value: 72.01177147657364
          - type: manhattan_f1
            value: 66.62594673833374
          - type: manhattan_precision
            value: 62.0336669699727
          - type: manhattan_recall
            value: 71.95250659630607
          - type: max_accuracy
            value: 85.31322644096085
          - type: max_ap
            value: 72.14521480685293
          - type: max_f1
            value: 66.67489813557229
      - task:
          type: PairClassification
        dataset:
          name: MTEB TwitterURLCorpus
          type: mteb/twitterurlcorpus-pairclassification
          config: default
          split: test
          revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
        metrics:
          - type: cos_sim_accuracy
            value: 89.12756626693057
          - type: cos_sim_ap
            value: 86.05430786440826
          - type: cos_sim_f1
            value: 78.27759692216631
          - type: cos_sim_precision
            value: 75.33466248931929
          - type: cos_sim_recall
            value: 81.45980905451185
          - type: dot_accuracy
            value: 89.12950673341872
          - type: dot_ap
            value: 86.05431161145492
          - type: dot_f1
            value: 78.27759692216631
          - type: dot_precision
            value: 75.33466248931929
          - type: dot_recall
            value: 81.45980905451185
          - type: euclidean_accuracy
            value: 89.12756626693057
          - type: euclidean_ap
            value: 86.05431303247397
          - type: euclidean_f1
            value: 78.27759692216631
          - type: euclidean_precision
            value: 75.33466248931929
          - type: euclidean_recall
            value: 81.45980905451185
          - type: manhattan_accuracy
            value: 89.04994760740482
          - type: manhattan_ap
            value: 86.00860610892074
          - type: manhattan_f1
            value: 78.1846776005392
          - type: manhattan_precision
            value: 76.10438839480975
          - type: manhattan_recall
            value: 80.3818909762858
          - type: max_accuracy
            value: 89.12950673341872
          - type: max_ap
            value: 86.05431303247397
          - type: max_f1
            value: 78.27759692216631

Emm9625/jina-embeddings-v2-small-en-Q8_0-GGUF

This model was converted to GGUF format from jinaai/jina-embeddings-v2-small-en 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 Emm9625/jina-embeddings-v2-small-en-Q8_0-GGUF --hf-file jina-embeddings-v2-small-en-q8_0.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo Emm9625/jina-embeddings-v2-small-en-Q8_0-GGUF --hf-file jina-embeddings-v2-small-en-q8_0.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 Emm9625/jina-embeddings-v2-small-en-Q8_0-GGUF --hf-file jina-embeddings-v2-small-en-q8_0.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo Emm9625/jina-embeddings-v2-small-en-Q8_0-GGUF --hf-file jina-embeddings-v2-small-en-q8_0.gguf -c 2048