ret-phi2-v0 / README.md
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metadata
license: mit
tags:
  - mteb
model-index:
  - name: ret-phi2-v0
    results:
      - task:
          type: Retrieval
        dataset:
          type: arguana
          name: MTEB ArguAna
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 24.609
          - type: map_at_10
            value: 39.404
          - type: map_at_100
            value: 40.421
          - type: map_at_1000
            value: 40.437
          - type: map_at_3
            value: 34.258
          - type: map_at_5
            value: 37.078
          - type: mrr_at_1
            value: 24.822
          - type: mrr_at_10
            value: 39.48
          - type: mrr_at_100
            value: 40.498
          - type: mrr_at_1000
            value: 40.513
          - type: mrr_at_3
            value: 34.436
          - type: mrr_at_5
            value: 37.156
          - type: ndcg_at_1
            value: 24.609
          - type: ndcg_at_10
            value: 48.274
          - type: ndcg_at_100
            value: 52.654
          - type: ndcg_at_1000
            value: 53.037
          - type: ndcg_at_3
            value: 37.558
          - type: ndcg_at_5
            value: 42.678
          - type: precision_at_1
            value: 24.609
          - type: precision_at_10
            value: 7.688000000000001
          - type: precision_at_100
            value: 0.962
          - type: precision_at_1000
            value: 0.099
          - type: precision_at_3
            value: 15.717999999999998
          - type: precision_at_5
            value: 11.935
          - type: recall_at_1
            value: 24.609
          - type: recall_at_10
            value: 76.885
          - type: recall_at_100
            value: 96.15899999999999
          - type: recall_at_1000
            value: 99.14699999999999
          - type: recall_at_3
            value: 47.155
          - type: recall_at_5
            value: 59.673
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackAndroidRetrieval
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 27.916
          - type: map_at_10
            value: 36.125
          - type: map_at_100
            value: 37.423
          - type: map_at_1000
            value: 37.545
          - type: map_at_3
            value: 33.019
          - type: map_at_5
            value: 34.977000000000004
          - type: mrr_at_1
            value: 33.906
          - type: mrr_at_10
            value: 41.832
          - type: mrr_at_100
            value: 42.667
          - type: mrr_at_1000
            value: 42.72
          - type: mrr_at_3
            value: 39.103
          - type: mrr_at_5
            value: 40.763
          - type: ndcg_at_1
            value: 33.906
          - type: ndcg_at_10
            value: 41.514
          - type: ndcg_at_100
            value: 46.855000000000004
          - type: ndcg_at_1000
            value: 49.199
          - type: ndcg_at_3
            value: 36.666
          - type: ndcg_at_5
            value: 39.281
          - type: precision_at_1
            value: 33.906
          - type: precision_at_10
            value: 7.553999999999999
          - type: precision_at_100
            value: 1.239
          - type: precision_at_1000
            value: 0.168
          - type: precision_at_3
            value: 16.929
          - type: precision_at_5
            value: 12.504000000000001
          - type: recall_at_1
            value: 27.916
          - type: recall_at_10
            value: 51.785000000000004
          - type: recall_at_100
            value: 74.566
          - type: recall_at_1000
            value: 90.092
          - type: recall_at_3
            value: 37.917
          - type: recall_at_5
            value: 44.919
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackEnglishRetrieval
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 26.905
          - type: map_at_10
            value: 36.664
          - type: map_at_100
            value: 37.796
          - type: map_at_1000
            value: 37.911
          - type: map_at_3
            value: 34.009
          - type: map_at_5
            value: 35.354
          - type: mrr_at_1
            value: 34.459
          - type: mrr_at_10
            value: 42.836
          - type: mrr_at_100
            value: 43.54
          - type: mrr_at_1000
            value: 43.589
          - type: mrr_at_3
            value: 40.754000000000005
          - type: mrr_at_5
            value: 41.849
          - type: ndcg_at_1
            value: 34.459
          - type: ndcg_at_10
            value: 42.268
          - type: ndcg_at_100
            value: 46.527
          - type: ndcg_at_1000
            value: 48.667
          - type: ndcg_at_3
            value: 38.408
          - type: ndcg_at_5
            value: 39.889
          - type: precision_at_1
            value: 34.459
          - type: precision_at_10
            value: 8
          - type: precision_at_100
            value: 1.269
          - type: precision_at_1000
            value: 0.174
          - type: precision_at_3
            value: 18.705
          - type: precision_at_5
            value: 13.083
          - type: recall_at_1
            value: 26.905
          - type: recall_at_10
            value: 52.378
          - type: recall_at_100
            value: 70.419
          - type: recall_at_1000
            value: 84.165
          - type: recall_at_3
            value: 40.467999999999996
          - type: recall_at_5
            value: 44.911
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackGamingRetrieval
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 34.475
          - type: map_at_10
            value: 45.221000000000004
          - type: map_at_100
            value: 46.215
          - type: map_at_1000
            value: 46.276
          - type: map_at_3
            value: 42.487
          - type: map_at_5
            value: 43.948
          - type: mrr_at_1
            value: 38.871
          - type: mrr_at_10
            value: 48.521
          - type: mrr_at_100
            value: 49.172
          - type: mrr_at_1000
            value: 49.207
          - type: mrr_at_3
            value: 46.123
          - type: mrr_at_5
            value: 47.452
          - type: ndcg_at_1
            value: 38.871
          - type: ndcg_at_10
            value: 50.739999999999995
          - type: ndcg_at_100
            value: 54.849000000000004
          - type: ndcg_at_1000
            value: 56.3
          - type: ndcg_at_3
            value: 45.762
          - type: ndcg_at_5
            value: 48.03
          - type: precision_at_1
            value: 38.871
          - type: precision_at_10
            value: 8.107000000000001
          - type: precision_at_100
            value: 1.11
          - type: precision_at_1000
            value: 0.129
          - type: precision_at_3
            value: 20.209
          - type: precision_at_5
            value: 13.767999999999999
          - type: recall_at_1
            value: 34.475
          - type: recall_at_10
            value: 63.82299999999999
          - type: recall_at_100
            value: 81.761
          - type: recall_at_1000
            value: 92.604
          - type: recall_at_3
            value: 50.331
          - type: recall_at_5
            value: 56.003
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackGisRetrieval
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 21.689
          - type: map_at_10
            value: 28.363
          - type: map_at_100
            value: 29.324
          - type: map_at_1000
            value: 29.416999999999998
          - type: map_at_3
            value: 26.064
          - type: map_at_5
            value: 27.423
          - type: mrr_at_1
            value: 22.938
          - type: mrr_at_10
            value: 29.786
          - type: mrr_at_100
            value: 30.688
          - type: mrr_at_1000
            value: 30.763
          - type: mrr_at_3
            value: 27.533
          - type: mrr_at_5
            value: 28.860999999999997
          - type: ndcg_at_1
            value: 22.938
          - type: ndcg_at_10
            value: 32.461
          - type: ndcg_at_100
            value: 37.492
          - type: ndcg_at_1000
            value: 39.925
          - type: ndcg_at_3
            value: 27.916
          - type: ndcg_at_5
            value: 30.287
          - type: precision_at_1
            value: 22.938
          - type: precision_at_10
            value: 4.96
          - type: precision_at_100
            value: 0.7929999999999999
          - type: precision_at_1000
            value: 0.104
          - type: precision_at_3
            value: 11.676
          - type: precision_at_5
            value: 8.339
          - type: recall_at_1
            value: 21.689
          - type: recall_at_10
            value: 43.702000000000005
          - type: recall_at_100
            value: 67.23400000000001
          - type: recall_at_1000
            value: 85.688
          - type: recall_at_3
            value: 31.526
          - type: recall_at_5
            value: 37.262
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackMathematicaRetrieval
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 14.094000000000001
          - type: map_at_10
            value: 21.310000000000002
          - type: map_at_100
            value: 22.427
          - type: map_at_1000
            value: 22.545
          - type: map_at_3
            value: 18.83
          - type: map_at_5
            value: 20.225
          - type: mrr_at_1
            value: 17.413
          - type: mrr_at_10
            value: 25.430000000000003
          - type: mrr_at_100
            value: 26.418000000000003
          - type: mrr_at_1000
            value: 26.494
          - type: mrr_at_3
            value: 22.989
          - type: mrr_at_5
            value: 24.388
          - type: ndcg_at_1
            value: 17.413
          - type: ndcg_at_10
            value: 26.223000000000003
          - type: ndcg_at_100
            value: 31.838
          - type: ndcg_at_1000
            value: 34.678
          - type: ndcg_at_3
            value: 21.677
          - type: ndcg_at_5
            value: 23.838
          - type: precision_at_1
            value: 17.413
          - type: precision_at_10
            value: 4.9750000000000005
          - type: precision_at_100
            value: 0.8999999999999999
          - type: precision_at_1000
            value: 0.128
          - type: precision_at_3
            value: 10.697
          - type: precision_at_5
            value: 7.91
          - type: recall_at_1
            value: 14.094000000000001
          - type: recall_at_10
            value: 37.230999999999995
          - type: recall_at_100
            value: 62.062
          - type: recall_at_1000
            value: 82.204
          - type: recall_at_3
            value: 24.766
          - type: recall_at_5
            value: 30.173
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackPhysicsRetrieval
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 27.256999999999998
          - type: map_at_10
            value: 36.869
          - type: map_at_100
            value: 38.145
          - type: map_at_1000
            value: 38.255
          - type: map_at_3
            value: 34.161
          - type: map_at_5
            value: 35.504000000000005
          - type: mrr_at_1
            value: 32.531
          - type: mrr_at_10
            value: 41.957
          - type: mrr_at_100
            value: 42.766
          - type: mrr_at_1000
            value: 42.815999999999995
          - type: mrr_at_3
            value: 39.589
          - type: mrr_at_5
            value: 40.749
          - type: ndcg_at_1
            value: 32.531
          - type: ndcg_at_10
            value: 42.54
          - type: ndcg_at_100
            value: 47.948
          - type: ndcg_at_1000
            value: 50.056999999999995
          - type: ndcg_at_3
            value: 37.775999999999996
          - type: ndcg_at_5
            value: 39.667
          - type: precision_at_1
            value: 32.531
          - type: precision_at_10
            value: 7.7
          - type: precision_at_100
            value: 1.213
          - type: precision_at_1000
            value: 0.154
          - type: precision_at_3
            value: 17.806
          - type: precision_at_5
            value: 12.493
          - type: recall_at_1
            value: 27.256999999999998
          - type: recall_at_10
            value: 54.217999999999996
          - type: recall_at_100
            value: 76.98
          - type: recall_at_1000
            value: 90.913
          - type: recall_at_3
            value: 41.144999999999996
          - type: recall_at_5
            value: 45.674
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackProgrammersRetrieval
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 23.249
          - type: map_at_10
            value: 32.278
          - type: map_at_100
            value: 33.585
          - type: map_at_1000
            value: 33.69
          - type: map_at_3
            value: 29.776000000000003
          - type: map_at_5
            value: 31.096
          - type: mrr_at_1
            value: 28.425
          - type: mrr_at_10
            value: 37.124
          - type: mrr_at_100
            value: 38.053
          - type: mrr_at_1000
            value: 38.111
          - type: mrr_at_3
            value: 34.989
          - type: mrr_at_5
            value: 36.159
          - type: ndcg_at_1
            value: 28.425
          - type: ndcg_at_10
            value: 37.472
          - type: ndcg_at_100
            value: 43.261
          - type: ndcg_at_1000
            value: 45.540000000000006
          - type: ndcg_at_3
            value: 33.334
          - type: ndcg_at_5
            value: 35.082
          - type: precision_at_1
            value: 28.425
          - type: precision_at_10
            value: 6.758
          - type: precision_at_100
            value: 1.15
          - type: precision_at_1000
            value: 0.151
          - type: precision_at_3
            value: 16.058
          - type: precision_at_5
            value: 11.164
          - type: recall_at_1
            value: 23.249
          - type: recall_at_10
            value: 48.094
          - type: recall_at_100
            value: 72.988
          - type: recall_at_1000
            value: 88.625
          - type: recall_at_3
            value: 36.342999999999996
          - type: recall_at_5
            value: 41.187000000000005
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackRetrieval
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 23.019250000000003
          - type: map_at_10
            value: 30.98783333333333
          - type: map_at_100
            value: 32.07916666666667
          - type: map_at_1000
            value: 32.193333333333335
          - type: map_at_3
            value: 28.572916666666664
          - type: map_at_5
            value: 29.886083333333335
          - type: mrr_at_1
            value: 27.01383333333333
          - type: mrr_at_10
            value: 34.78475
          - type: mrr_at_100
            value: 35.628416666666666
          - type: mrr_at_1000
            value: 35.696250000000006
          - type: mrr_at_3
            value: 32.63225
          - type: mrr_at_5
            value: 33.8265
          - type: ndcg_at_1
            value: 27.01383333333333
          - type: ndcg_at_10
            value: 35.75991666666666
          - type: ndcg_at_100
            value: 40.696416666666664
          - type: ndcg_at_1000
            value: 43.18933333333333
          - type: ndcg_at_3
            value: 31.56075
          - type: ndcg_at_5
            value: 33.47166666666667
          - type: precision_at_1
            value: 27.01383333333333
          - type: precision_at_10
            value: 6.201416666666667
          - type: precision_at_100
            value: 1.0189166666666667
          - type: precision_at_1000
            value: 0.13999999999999999
          - type: precision_at_3
            value: 14.448249999999998
          - type: precision_at_5
            value: 10.209333333333333
          - type: recall_at_1
            value: 23.019250000000003
          - type: recall_at_10
            value: 46.17675
          - type: recall_at_100
            value: 68.06741666666667
          - type: recall_at_1000
            value: 85.66791666666667
          - type: recall_at_3
            value: 34.435500000000005
          - type: recall_at_5
            value: 39.362
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackStatsRetrieval
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 21.754
          - type: map_at_10
            value: 27.815
          - type: map_at_100
            value: 28.776000000000003
          - type: map_at_1000
            value: 28.874
          - type: map_at_3
            value: 25.822
          - type: map_at_5
            value: 26.562
          - type: mrr_at_1
            value: 23.926
          - type: mrr_at_10
            value: 30.148000000000003
          - type: mrr_at_100
            value: 31.035
          - type: mrr_at_1000
            value: 31.116
          - type: mrr_at_3
            value: 28.349000000000004
          - type: mrr_at_5
            value: 29.108
          - type: ndcg_at_1
            value: 23.926
          - type: ndcg_at_10
            value: 31.635
          - type: ndcg_at_100
            value: 36.457
          - type: ndcg_at_1000
            value: 38.944
          - type: ndcg_at_3
            value: 27.857
          - type: ndcg_at_5
            value: 29.017
          - type: precision_at_1
            value: 23.926
          - type: precision_at_10
            value: 4.984999999999999
          - type: precision_at_100
            value: 0.8019999999999999
          - type: precision_at_1000
            value: 0.108
          - type: precision_at_3
            value: 11.759
          - type: precision_at_5
            value: 7.914000000000001
          - type: recall_at_1
            value: 21.754
          - type: recall_at_10
            value: 41.117
          - type: recall_at_100
            value: 63.123
          - type: recall_at_1000
            value: 81.399
          - type: recall_at_3
            value: 30.556
          - type: recall_at_5
            value: 33.571
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackTexRetrieval
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 15.204999999999998
          - type: map_at_10
            value: 21.166
          - type: map_at_100
            value: 22.127
          - type: map_at_1000
            value: 22.239
          - type: map_at_3
            value: 19.342000000000002
          - type: map_at_5
            value: 20.329
          - type: mrr_at_1
            value: 18.340999999999998
          - type: mrr_at_10
            value: 24.562
          - type: mrr_at_100
            value: 25.462
          - type: mrr_at_1000
            value: 25.541000000000004
          - type: mrr_at_3
            value: 22.694
          - type: mrr_at_5
            value: 23.694000000000003
          - type: ndcg_at_1
            value: 18.340999999999998
          - type: ndcg_at_10
            value: 25.055
          - type: ndcg_at_100
            value: 29.82
          - type: ndcg_at_1000
            value: 32.68
          - type: ndcg_at_3
            value: 21.676000000000002
          - type: ndcg_at_5
            value: 23.153000000000002
          - type: precision_at_1
            value: 18.340999999999998
          - type: precision_at_10
            value: 4.425
          - type: precision_at_100
            value: 0.779
          - type: precision_at_1000
            value: 0.117
          - type: precision_at_3
            value: 10.106
          - type: precision_at_5
            value: 7.199
          - type: recall_at_1
            value: 15.204999999999998
          - type: recall_at_10
            value: 33.542
          - type: recall_at_100
            value: 55.093
          - type: recall_at_1000
            value: 75.64699999999999
          - type: recall_at_3
            value: 23.892
          - type: recall_at_5
            value: 27.789
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackUnixRetrieval
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 23.714
          - type: map_at_10
            value: 30.636000000000003
          - type: map_at_100
            value: 31.653
          - type: map_at_1000
            value: 31.762
          - type: map_at_3
            value: 28.51
          - type: map_at_5
            value: 29.715999999999998
          - type: mrr_at_1
            value: 27.612
          - type: mrr_at_10
            value: 34.269
          - type: mrr_at_100
            value: 35.149
          - type: mrr_at_1000
            value: 35.225
          - type: mrr_at_3
            value: 32.338
          - type: mrr_at_5
            value: 33.341
          - type: ndcg_at_1
            value: 27.612
          - type: ndcg_at_10
            value: 34.854
          - type: ndcg_at_100
            value: 39.800999999999995
          - type: ndcg_at_1000
            value: 42.400999999999996
          - type: ndcg_at_3
            value: 31.005
          - type: ndcg_at_5
            value: 32.727000000000004
          - type: precision_at_1
            value: 27.612
          - type: precision_at_10
            value: 5.578
          - type: precision_at_100
            value: 0.907
          - type: precision_at_1000
            value: 0.124
          - type: precision_at_3
            value: 13.619
          - type: precision_at_5
            value: 9.403
          - type: recall_at_1
            value: 23.714
          - type: recall_at_10
            value: 44.262
          - type: recall_at_100
            value: 66.079
          - type: recall_at_1000
            value: 84.405
          - type: recall_at_3
            value: 33.547
          - type: recall_at_5
            value: 37.951
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackWebmastersRetrieval
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 22.838
          - type: map_at_10
            value: 31.244
          - type: map_at_100
            value: 32.469
          - type: map_at_1000
            value: 32.679
          - type: map_at_3
            value: 28.644
          - type: map_at_5
            value: 30.179000000000002
          - type: mrr_at_1
            value: 27.075
          - type: mrr_at_10
            value: 35.039
          - type: mrr_at_100
            value: 35.909
          - type: mrr_at_1000
            value: 35.99
          - type: mrr_at_3
            value: 33.004
          - type: mrr_at_5
            value: 34.397
          - type: ndcg_at_1
            value: 27.075
          - type: ndcg_at_10
            value: 36.319
          - type: ndcg_at_100
            value: 41.066
          - type: ndcg_at_1000
            value: 44.272
          - type: ndcg_at_3
            value: 32.361000000000004
          - type: ndcg_at_5
            value: 34.544999999999995
          - type: precision_at_1
            value: 27.075
          - type: precision_at_10
            value: 6.957000000000001
          - type: precision_at_100
            value: 1.346
          - type: precision_at_1000
            value: 0.215
          - type: precision_at_3
            value: 15.217
          - type: precision_at_5
            value: 11.304
          - type: recall_at_1
            value: 22.838
          - type: recall_at_10
            value: 45.737
          - type: recall_at_100
            value: 67.723
          - type: recall_at_1000
            value: 89.293
          - type: recall_at_3
            value: 34.666999999999994
          - type: recall_at_5
            value: 40.208
      - task:
          type: Retrieval
        dataset:
          type: BeIR/cqadupstack
          name: MTEB CQADupstackWordpressRetrieval
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 17.135
          - type: map_at_10
            value: 24.163
          - type: map_at_100
            value: 25.009999999999998
          - type: map_at_1000
            value: 25.127
          - type: map_at_3
            value: 22.211
          - type: map_at_5
            value: 23.32
          - type: mrr_at_1
            value: 18.669
          - type: mrr_at_10
            value: 25.913000000000004
          - type: mrr_at_100
            value: 26.682
          - type: mrr_at_1000
            value: 26.783
          - type: mrr_at_3
            value: 24.122
          - type: mrr_at_5
            value: 25.157
          - type: ndcg_at_1
            value: 18.669
          - type: ndcg_at_10
            value: 28.038
          - type: ndcg_at_100
            value: 32.443
          - type: ndcg_at_1000
            value: 35.609
          - type: ndcg_at_3
            value: 24.291
          - type: ndcg_at_5
            value: 26.144000000000002
          - type: precision_at_1
            value: 18.669
          - type: precision_at_10
            value: 4.417999999999999
          - type: precision_at_100
            value: 0.719
          - type: precision_at_1000
            value: 0.108
          - type: precision_at_3
            value: 10.598
          - type: precision_at_5
            value: 7.431
          - type: recall_at_1
            value: 17.135
          - type: recall_at_10
            value: 38.232
          - type: recall_at_100
            value: 58.781000000000006
          - type: recall_at_1000
            value: 82.98
          - type: recall_at_3
            value: 28.067999999999998
          - type: recall_at_5
            value: 32.696
      - task:
          type: Retrieval
        dataset:
          type: climate-fever
          name: MTEB ClimateFEVER
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 11.318
          - type: map_at_10
            value: 20.830000000000002
          - type: map_at_100
            value: 22.948
          - type: map_at_1000
            value: 23.138
          - type: map_at_3
            value: 17.022000000000002
          - type: map_at_5
            value: 18.921
          - type: mrr_at_1
            value: 25.602999999999998
          - type: mrr_at_10
            value: 38.513999999999996
          - type: mrr_at_100
            value: 39.467
          - type: mrr_at_1000
            value: 39.503
          - type: mrr_at_3
            value: 34.766999999999996
          - type: mrr_at_5
            value: 37.024
          - type: ndcg_at_1
            value: 25.602999999999998
          - type: ndcg_at_10
            value: 29.609999999999996
          - type: ndcg_at_100
            value: 37.525999999999996
          - type: ndcg_at_1000
            value: 40.68
          - type: ndcg_at_3
            value: 23.552999999999997
          - type: ndcg_at_5
            value: 25.747999999999998
          - type: precision_at_1
            value: 25.602999999999998
          - type: precision_at_10
            value: 9.569999999999999
          - type: precision_at_100
            value: 1.798
          - type: precision_at_1000
            value: 0.23900000000000002
          - type: precision_at_3
            value: 17.785
          - type: precision_at_5
            value: 14.033000000000001
          - type: recall_at_1
            value: 11.318
          - type: recall_at_10
            value: 36.605
          - type: recall_at_100
            value: 63.666
          - type: recall_at_1000
            value: 80.97
          - type: recall_at_3
            value: 22.161
          - type: recall_at_5
            value: 27.99
      - task:
          type: Retrieval
        dataset:
          type: dbpedia-entity
          name: MTEB DBPedia
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 8.318
          - type: map_at_10
            value: 18.602
          - type: map_at_100
            value: 26.378
          - type: map_at_1000
            value: 28.149
          - type: map_at_3
            value: 13.36
          - type: map_at_5
            value: 15.482999999999999
          - type: mrr_at_1
            value: 66.75
          - type: mrr_at_10
            value: 74.47
          - type: mrr_at_100
            value: 74.816
          - type: mrr_at_1000
            value: 74.823
          - type: mrr_at_3
            value: 73.208
          - type: mrr_at_5
            value: 73.871
          - type: ndcg_at_1
            value: 53.87499999999999
          - type: ndcg_at_10
            value: 40.511
          - type: ndcg_at_100
            value: 44.973
          - type: ndcg_at_1000
            value: 52.33
          - type: ndcg_at_3
            value: 44.896
          - type: ndcg_at_5
            value: 42.137
          - type: precision_at_1
            value: 66.75
          - type: precision_at_10
            value: 32.225
          - type: precision_at_100
            value: 10.543
          - type: precision_at_1000
            value: 2.251
          - type: precision_at_3
            value: 48.5
          - type: precision_at_5
            value: 40.849999999999994
          - type: recall_at_1
            value: 8.318
          - type: recall_at_10
            value: 24.163
          - type: recall_at_100
            value: 50.824999999999996
          - type: recall_at_1000
            value: 73.623
          - type: recall_at_3
            value: 14.863999999999999
          - type: recall_at_5
            value: 18.052
      - task:
          type: Retrieval
        dataset:
          type: fever
          name: MTEB FEVER
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 64.228
          - type: map_at_10
            value: 75.004
          - type: map_at_100
            value: 75.25500000000001
          - type: map_at_1000
            value: 75.268
          - type: map_at_3
            value: 73.295
          - type: map_at_5
            value: 74.401
          - type: mrr_at_1
            value: 69.06700000000001
          - type: mrr_at_10
            value: 79.477
          - type: mrr_at_100
            value: 79.629
          - type: mrr_at_1000
            value: 79.631
          - type: mrr_at_3
            value: 77.985
          - type: mrr_at_5
            value: 79.00500000000001
          - type: ndcg_at_1
            value: 69.06700000000001
          - type: ndcg_at_10
            value: 80.138
          - type: ndcg_at_100
            value: 81.143
          - type: ndcg_at_1000
            value: 81.37299999999999
          - type: ndcg_at_3
            value: 77.074
          - type: ndcg_at_5
            value: 78.873
          - type: precision_at_1
            value: 69.06700000000001
          - type: precision_at_10
            value: 10.05
          - type: precision_at_100
            value: 1.072
          - type: precision_at_1000
            value: 0.11100000000000002
          - type: precision_at_3
            value: 30.188
          - type: precision_at_5
            value: 19.157
          - type: recall_at_1
            value: 64.228
          - type: recall_at_10
            value: 91.5
          - type: recall_at_100
            value: 95.69800000000001
          - type: recall_at_1000
            value: 97.16900000000001
          - type: recall_at_3
            value: 83.26599999999999
          - type: recall_at_5
            value: 87.744
      - task:
          type: Retrieval
        dataset:
          type: fiqa
          name: MTEB FiQA2018
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 20.61
          - type: map_at_10
            value: 33.507
          - type: map_at_100
            value: 35.33
          - type: map_at_1000
            value: 35.489
          - type: map_at_3
            value: 29.345
          - type: map_at_5
            value: 31.834
          - type: mrr_at_1
            value: 40.278000000000006
          - type: mrr_at_10
            value: 49.212
          - type: mrr_at_100
            value: 50.124
          - type: mrr_at_1000
            value: 50.153999999999996
          - type: mrr_at_3
            value: 46.991
          - type: mrr_at_5
            value: 48.449
          - type: ndcg_at_1
            value: 40.278000000000006
          - type: ndcg_at_10
            value: 41.08
          - type: ndcg_at_100
            value: 47.865
          - type: ndcg_at_1000
            value: 50.566
          - type: ndcg_at_3
            value: 37.855
          - type: ndcg_at_5
            value: 39.24
          - type: precision_at_1
            value: 40.278000000000006
          - type: precision_at_10
            value: 11.126999999999999
          - type: precision_at_100
            value: 1.81
          - type: precision_at_1000
            value: 0.22899999999999998
          - type: precision_at_3
            value: 25
          - type: precision_at_5
            value: 18.457
          - type: recall_at_1
            value: 20.61
          - type: recall_at_10
            value: 47.3
          - type: recall_at_100
            value: 72.129
          - type: recall_at_1000
            value: 88.25
          - type: recall_at_3
            value: 34.307
          - type: recall_at_5
            value: 41.182
      - task:
          type: Retrieval
        dataset:
          type: hotpotqa
          name: MTEB HotpotQA
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 37.873000000000005
          - type: map_at_10
            value: 54.013
          - type: map_at_100
            value: 54.89000000000001
          - type: map_at_1000
            value: 54.959
          - type: map_at_3
            value: 51.185
          - type: map_at_5
            value: 52.933
          - type: mrr_at_1
            value: 75.74600000000001
          - type: mrr_at_10
            value: 81.599
          - type: mrr_at_100
            value: 81.833
          - type: mrr_at_1000
            value: 81.842
          - type: mrr_at_3
            value: 80.673
          - type: mrr_at_5
            value: 81.242
          - type: ndcg_at_1
            value: 75.74600000000001
          - type: ndcg_at_10
            value: 63.187000000000005
          - type: ndcg_at_100
            value: 66.345
          - type: ndcg_at_1000
            value: 67.77300000000001
          - type: ndcg_at_3
            value: 59.096000000000004
          - type: ndcg_at_5
            value: 61.332
          - type: precision_at_1
            value: 75.74600000000001
          - type: precision_at_10
            value: 12.848
          - type: precision_at_100
            value: 1.533
          - type: precision_at_1000
            value: 0.172
          - type: precision_at_3
            value: 36.786
          - type: precision_at_5
            value: 23.835
          - type: recall_at_1
            value: 37.873000000000005
          - type: recall_at_10
            value: 64.24
          - type: recall_at_100
            value: 76.651
          - type: recall_at_1000
            value: 86.212
          - type: recall_at_3
            value: 55.179
          - type: recall_at_5
            value: 59.587999999999994
      - task:
          type: Retrieval
        dataset:
          type: msmarco
          name: MTEB MSMARCO
          config: default
          split: dev
          revision: None
        metrics:
          - type: map_at_1
            value: 23.108
          - type: map_at_10
            value: 35.607
          - type: map_at_100
            value: 36.769
          - type: map_at_1000
            value: 36.815
          - type: map_at_3
            value: 31.576999999999998
          - type: map_at_5
            value: 33.939
          - type: mrr_at_1
            value: 23.768
          - type: mrr_at_10
            value: 36.203
          - type: mrr_at_100
            value: 37.299
          - type: mrr_at_1000
            value: 37.339
          - type: mrr_at_3
            value: 32.245000000000005
          - type: mrr_at_5
            value: 34.575
          - type: ndcg_at_1
            value: 23.768
          - type: ndcg_at_10
            value: 42.724000000000004
          - type: ndcg_at_100
            value: 48.241
          - type: ndcg_at_1000
            value: 49.346000000000004
          - type: ndcg_at_3
            value: 34.528
          - type: ndcg_at_5
            value: 38.746
          - type: precision_at_1
            value: 23.768
          - type: precision_at_10
            value: 6.755999999999999
          - type: precision_at_100
            value: 0.9520000000000001
          - type: precision_at_1000
            value: 0.105
          - type: precision_at_3
            value: 14.666
          - type: precision_at_5
            value: 10.923
          - type: recall_at_1
            value: 23.108
          - type: recall_at_10
            value: 64.676
          - type: recall_at_100
            value: 90.033
          - type: recall_at_1000
            value: 98.394
          - type: recall_at_3
            value: 42.421
          - type: recall_at_5
            value: 52.569
      - task:
          type: Retrieval
        dataset:
          type: nfcorpus
          name: MTEB NFCorpus
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 5.898
          - type: map_at_10
            value: 14.115
          - type: map_at_100
            value: 17.868000000000002
          - type: map_at_1000
            value: 19.425
          - type: map_at_3
            value: 10.385
          - type: map_at_5
            value: 12.064
          - type: mrr_at_1
            value: 50.464
          - type: mrr_at_10
            value: 59.265
          - type: mrr_at_100
            value: 59.63
          - type: mrr_at_1000
            value: 59.673
          - type: mrr_at_3
            value: 56.96600000000001
          - type: mrr_at_5
            value: 58.282000000000004
          - type: ndcg_at_1
            value: 48.452
          - type: ndcg_at_10
            value: 37.819
          - type: ndcg_at_100
            value: 34.421
          - type: ndcg_at_1000
            value: 43.275999999999996
          - type: ndcg_at_3
            value: 44.037
          - type: ndcg_at_5
            value: 41.272
          - type: precision_at_1
            value: 50.15500000000001
          - type: precision_at_10
            value: 28.142
          - type: precision_at_100
            value: 8.780000000000001
          - type: precision_at_1000
            value: 2.185
          - type: precision_at_3
            value: 41.382999999999996
          - type: precision_at_5
            value: 35.975
          - type: recall_at_1
            value: 5.898
          - type: recall_at_10
            value: 18.584999999999997
          - type: recall_at_100
            value: 34.660000000000004
          - type: recall_at_1000
            value: 67.361
          - type: recall_at_3
            value: 11.774999999999999
          - type: recall_at_5
            value: 14.438999999999998
      - task:
          type: Retrieval
        dataset:
          type: nq
          name: MTEB NQ
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 32.976
          - type: map_at_10
            value: 48.672
          - type: map_at_100
            value: 49.622
          - type: map_at_1000
            value: 49.647999999999996
          - type: map_at_3
            value: 44.389
          - type: map_at_5
            value: 46.942
          - type: mrr_at_1
            value: 36.876999999999995
          - type: mrr_at_10
            value: 51.123
          - type: mrr_at_100
            value: 51.82299999999999
          - type: mrr_at_1000
            value: 51.839999999999996
          - type: mrr_at_3
            value: 47.658
          - type: mrr_at_5
            value: 49.756
          - type: ndcg_at_1
            value: 36.848
          - type: ndcg_at_10
            value: 56.389
          - type: ndcg_at_100
            value: 60.31100000000001
          - type: ndcg_at_1000
            value: 60.895999999999994
          - type: ndcg_at_3
            value: 48.469
          - type: ndcg_at_5
            value: 52.672
          - type: precision_at_1
            value: 36.848
          - type: precision_at_10
            value: 9.215
          - type: precision_at_100
            value: 1.141
          - type: precision_at_1000
            value: 0.12
          - type: precision_at_3
            value: 21.997
          - type: precision_at_5
            value: 15.672
          - type: recall_at_1
            value: 32.976
          - type: recall_at_10
            value: 77.301
          - type: recall_at_100
            value: 94.15299999999999
          - type: recall_at_1000
            value: 98.44500000000001
          - type: recall_at_3
            value: 56.979
          - type: recall_at_5
            value: 66.621
      - task:
          type: Retrieval
        dataset:
          type: quora
          name: MTEB QuoraRetrieval
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 70.53399999999999
          - type: map_at_10
            value: 84.248
          - type: map_at_100
            value: 84.887
          - type: map_at_1000
            value: 84.905
          - type: map_at_3
            value: 81.32000000000001
          - type: map_at_5
            value: 83.159
          - type: mrr_at_1
            value: 81.03
          - type: mrr_at_10
            value: 87.35199999999999
          - type: mrr_at_100
            value: 87.444
          - type: mrr_at_1000
            value: 87.445
          - type: mrr_at_3
            value: 86.343
          - type: mrr_at_5
            value: 87.04499999999999
          - type: ndcg_at_1
            value: 81.06
          - type: ndcg_at_10
            value: 88.102
          - type: ndcg_at_100
            value: 89.32
          - type: ndcg_at_1000
            value: 89.434
          - type: ndcg_at_3
            value: 85.19
          - type: ndcg_at_5
            value: 86.824
          - type: precision_at_1
            value: 81.06
          - type: precision_at_10
            value: 13.327
          - type: precision_at_100
            value: 1.526
          - type: precision_at_1000
            value: 0.157
          - type: precision_at_3
            value: 37.169999999999995
          - type: precision_at_5
            value: 24.462
          - type: recall_at_1
            value: 70.53399999999999
          - type: recall_at_10
            value: 95.383
          - type: recall_at_100
            value: 99.494
          - type: recall_at_1000
            value: 99.985
          - type: recall_at_3
            value: 87.031
          - type: recall_at_5
            value: 91.623
      - task:
          type: Retrieval
        dataset:
          type: scidocs
          name: MTEB SCIDOCS
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 4.3180000000000005
          - type: map_at_10
            value: 10.237
          - type: map_at_100
            value: 11.879000000000001
          - type: map_at_1000
            value: 12.124
          - type: map_at_3
            value: 7.617999999999999
          - type: map_at_5
            value: 8.883000000000001
          - type: mrr_at_1
            value: 21.2
          - type: mrr_at_10
            value: 31.016
          - type: mrr_at_100
            value: 32.062000000000005
          - type: mrr_at_1000
            value: 32.128
          - type: mrr_at_3
            value: 28.016999999999996
          - type: mrr_at_5
            value: 29.607
          - type: ndcg_at_1
            value: 21.2
          - type: ndcg_at_10
            value: 17.485
          - type: ndcg_at_100
            value: 24.162
          - type: ndcg_at_1000
            value: 28.825
          - type: ndcg_at_3
            value: 17.024
          - type: ndcg_at_5
            value: 14.594
          - type: precision_at_1
            value: 21.2
          - type: precision_at_10
            value: 8.92
          - type: precision_at_100
            value: 1.854
          - type: precision_at_1000
            value: 0.297
          - type: precision_at_3
            value: 15.8
          - type: precision_at_5
            value: 12.58
          - type: recall_at_1
            value: 4.3180000000000005
          - type: recall_at_10
            value: 18.12
          - type: recall_at_100
            value: 37.628
          - type: recall_at_1000
            value: 60.324999999999996
          - type: recall_at_3
            value: 9.622
          - type: recall_at_5
            value: 12.772
      - task:
          type: Retrieval
        dataset:
          type: scifact
          name: MTEB SciFact
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 57.05
          - type: map_at_10
            value: 67.352
          - type: map_at_100
            value: 67.919
          - type: map_at_1000
            value: 67.944
          - type: map_at_3
            value: 64.78699999999999
          - type: map_at_5
            value: 66.216
          - type: mrr_at_1
            value: 60
          - type: mrr_at_10
            value: 68.535
          - type: mrr_at_100
            value: 68.988
          - type: mrr_at_1000
            value: 69.01
          - type: mrr_at_3
            value: 66.667
          - type: mrr_at_5
            value: 67.717
          - type: ndcg_at_1
            value: 60
          - type: ndcg_at_10
            value: 71.628
          - type: ndcg_at_100
            value: 74.076
          - type: ndcg_at_1000
            value: 74.717
          - type: ndcg_at_3
            value: 67.51
          - type: ndcg_at_5
            value: 69.393
          - type: precision_at_1
            value: 60
          - type: precision_at_10
            value: 9.433
          - type: precision_at_100
            value: 1.0699999999999998
          - type: precision_at_1000
            value: 0.11199999999999999
          - type: precision_at_3
            value: 26.444000000000003
          - type: precision_at_5
            value: 17.2
          - type: recall_at_1
            value: 57.05
          - type: recall_at_10
            value: 83.289
          - type: recall_at_100
            value: 94.267
          - type: recall_at_1000
            value: 99.333
          - type: recall_at_3
            value: 72.35000000000001
          - type: recall_at_5
            value: 77
      - task:
          type: Retrieval
        dataset:
          type: trec-covid
          name: MTEB TRECCOVID
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 0.242
          - type: map_at_10
            value: 2.153
          - type: map_at_100
            value: 13.045000000000002
          - type: map_at_1000
            value: 31.039
          - type: map_at_3
            value: 0.709
          - type: map_at_5
            value: 1.138
          - type: mrr_at_1
            value: 94
          - type: mrr_at_10
            value: 95.65
          - type: mrr_at_100
            value: 95.65
          - type: mrr_at_1000
            value: 95.65
          - type: mrr_at_3
            value: 95
          - type: mrr_at_5
            value: 95.39999999999999
          - type: ndcg_at_1
            value: 89
          - type: ndcg_at_10
            value: 83.39999999999999
          - type: ndcg_at_100
            value: 64.116
          - type: ndcg_at_1000
            value: 56.501000000000005
          - type: ndcg_at_3
            value: 88.061
          - type: ndcg_at_5
            value: 86.703
          - type: precision_at_1
            value: 94
          - type: precision_at_10
            value: 87.4
          - type: precision_at_100
            value: 65.58
          - type: precision_at_1000
            value: 25.113999999999997
          - type: precision_at_3
            value: 91.333
          - type: precision_at_5
            value: 90
          - type: recall_at_1
            value: 0.242
          - type: recall_at_10
            value: 2.267
          - type: recall_at_100
            value: 15.775
          - type: recall_at_1000
            value: 53.152
          - type: recall_at_3
            value: 0.721
          - type: recall_at_5
            value: 1.172
      - task:
          type: Retrieval
        dataset:
          type: webis-touche2020
          name: MTEB Touche2020
          config: default
          split: test
          revision: None
        metrics:
          - type: map_at_1
            value: 2.4619999999999997
          - type: map_at_10
            value: 10.086
          - type: map_at_100
            value: 16.265
          - type: map_at_1000
            value: 17.846
          - type: map_at_3
            value: 4.603
          - type: map_at_5
            value: 6.517
          - type: mrr_at_1
            value: 26.531
          - type: mrr_at_10
            value: 43.608000000000004
          - type: mrr_at_100
            value: 44.175
          - type: mrr_at_1000
            value: 44.190000000000005
          - type: mrr_at_3
            value: 37.755
          - type: mrr_at_5
            value: 41.531
          - type: ndcg_at_1
            value: 25.509999999999998
          - type: ndcg_at_10
            value: 25.663999999999998
          - type: ndcg_at_100
            value: 37.362
          - type: ndcg_at_1000
            value: 48.817
          - type: ndcg_at_3
            value: 23.223
          - type: ndcg_at_5
            value: 24.403
          - type: precision_at_1
            value: 26.531
          - type: precision_at_10
            value: 24.694
          - type: precision_at_100
            value: 7.776
          - type: precision_at_1000
            value: 1.541
          - type: precision_at_3
            value: 23.810000000000002
          - type: precision_at_5
            value: 25.306
          - type: recall_at_1
            value: 2.4619999999999997
          - type: recall_at_10
            value: 17.712
          - type: recall_at_100
            value: 48.232
          - type: recall_at_1000
            value: 83.348
          - type: recall_at_3
            value: 5.763
          - type: recall_at_5
            value: 9.577
datasets:
  - Tevatron/msmarco-passage-corpus
  - Tevatron/msmarco-passage
language:
  - en
library_name: sentence-transformers
pipeline_tag: sentence-similarity

Phi2 Model Trained for retrieval task using MSMarco Dataset

Trained for 1 epoch using the tevatron library

Ongoing work