Add MTEB meta

README.md

@@ -8,13 +8,2529 @@ model-index:
 - name: SGPT-5.8B-weightedmean-msmarco-specb-bitfit
   results:
   - task:
-      type: text-classification
+      type: Classification
+    dataset:
+      type: mteb/amazon_counterfactual
+      name: MTEB AmazonCounterfactualClassification (en)
+      config: en
+      split: test
+    metrics:
+    - type: accuracy
+      value: 69.22388059701493
+    - type: ap
+      value: 32.04724673950256
+    - type: f1
+      value: 63.25719825770428
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_polarity
+      name: MTEB AmazonPolarityClassification
+      config: default
+      split: test
+    metrics:
+    - type: accuracy
+      value: 71.26109999999998
+    - type: ap
+      value: 66.16336378255403
+    - type: f1
+      value: 70.89719145825303
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_reviews_multi
+      name: MTEB AmazonReviewsClassification (en)
+      config: en
+      split: test
+    metrics:
+    - type: accuracy
+      value: 39.19199999999999
+    - type: f1
+      value: 38.580766731113826
+  - task:
+      type: Retrieval
+    dataset:
+      type: arguana
+      name: MTEB ArguAna
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 27.311999999999998
+    - type: map_at_10
+      value: 42.620000000000005
+    - type: map_at_100
+      value: 43.707
+    - type: map_at_1000
+      value: 43.714999999999996
+    - type: map_at_3
+      value: 37.624
+    - type: map_at_5
+      value: 40.498
+    - type: mrr_at_1
+      value: 27.667
+    - type: mrr_at_10
+      value: 42.737
+    - type: mrr_at_100
+      value: 43.823
+    - type: mrr_at_1000
+      value: 43.830999999999996
+    - type: mrr_at_3
+      value: 37.743
+    - type: mrr_at_5
+      value: 40.616
+    - type: ndcg_at_1
+      value: 27.311999999999998
+    - type: ndcg_at_10
+      value: 51.37500000000001
+    - type: ndcg_at_100
+      value: 55.778000000000006
+    - type: ndcg_at_1000
+      value: 55.96600000000001
+    - type: ndcg_at_3
+      value: 41.087
+    - type: ndcg_at_5
+      value: 46.269
+    - type: precision_at_1
+      value: 27.311999999999998
+    - type: precision_at_10
+      value: 7.945
+    - type: precision_at_100
+      value: 0.9820000000000001
+    - type: precision_at_1000
+      value: 0.1
+    - type: precision_at_3
+      value: 17.046
+    - type: precision_at_5
+      value: 12.745000000000001
+    - type: recall_at_1
+      value: 27.311999999999998
+    - type: recall_at_10
+      value: 79.445
+    - type: recall_at_100
+      value: 98.151
+    - type: recall_at_1000
+      value: 99.57300000000001
+    - type: recall_at_3
+      value: 51.13799999999999
+    - type: recall_at_5
+      value: 63.727000000000004
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/arxiv-clustering-p2p
+      name: MTEB ArxivClusteringP2P
+      config: default
+      split: test
+    metrics:
+    - type: v_measure
+      value: 45.59037428592033
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/arxiv-clustering-s2s
+      name: MTEB ArxivClusteringS2S
+      config: default
+      split: test
+    metrics:
+    - type: v_measure
+      value: 38.86371701986363
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/askubuntudupquestions-reranking
+      name: MTEB AskUbuntuDupQuestions
+      config: default
+      split: test
+    metrics:
+    - type: map
+      value: 61.625568691427766
+    - type: mrr
+      value: 75.83256386580486
+  - task:
+      type: STS
+    dataset:
+      type: mteb/biosses-sts
+      name: MTEB BIOSSES
+      config: default
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: 89.96074355094802
+    - type: cos_sim_spearman
+      value: 86.2501580394454
+    - type: euclidean_pearson
+      value: 82.18427440380462
+    - type: euclidean_spearman
+      value: 80.14760935017947
+    - type: manhattan_pearson
+      value: 82.24621578156392
+    - type: manhattan_spearman
+      value: 80.00363016590163
+  - task:
+      type: Classification
     dataset:
       type: mteb/banking77
-      name: MTEB Banking77
+      name: MTEB Banking77Classification
+      config: default
+      split: test
+    metrics:
+    - type: accuracy
+      value: 84.49350649350649
+    - type: f1
+      value: 84.4249343233736
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/biorxiv-clustering-p2p
+      name: MTEB BiorxivClusteringP2P
+      config: default
+      split: test
+    metrics:
+    - type: v_measure
+      value: 36.551459722989385
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/biorxiv-clustering-s2s
+      name: MTEB BiorxivClusteringS2S
+      config: default
+      split: test
+    metrics:
+    - type: v_measure
+      value: 33.69901851846774
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackAndroidRetrieval
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 30.499
+    - type: map_at_10
+      value: 41.208
+    - type: map_at_100
+      value: 42.638
+    - type: map_at_1000
+      value: 42.754
+    - type: map_at_3
+      value: 37.506
+    - type: map_at_5
+      value: 39.422000000000004
+    - type: mrr_at_1
+      value: 37.339
+    - type: mrr_at_10
+      value: 47.051
+    - type: mrr_at_100
+      value: 47.745
+    - type: mrr_at_1000
+      value: 47.786
+    - type: mrr_at_3
+      value: 44.086999999999996
+    - type: mrr_at_5
+      value: 45.711
+    - type: ndcg_at_1
+      value: 37.339
+    - type: ndcg_at_10
+      value: 47.666
+    - type: ndcg_at_100
+      value: 52.994
+    - type: ndcg_at_1000
+      value: 54.928999999999995
+    - type: ndcg_at_3
+      value: 41.982
+    - type: ndcg_at_5
+      value: 44.42
+    - type: precision_at_1
+      value: 37.339
+    - type: precision_at_10
+      value: 9.127
+    - type: precision_at_100
+      value: 1.4749999999999999
+    - type: precision_at_1000
+      value: 0.194
+    - type: precision_at_3
+      value: 20.076
+    - type: precision_at_5
+      value: 14.449000000000002
+    - type: recall_at_1
+      value: 30.499
+    - type: recall_at_10
+      value: 60.328
+    - type: recall_at_100
+      value: 82.57900000000001
+    - type: recall_at_1000
+      value: 95.074
+    - type: recall_at_3
+      value: 44.17
+    - type: recall_at_5
+      value: 50.94
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackEnglishRetrieval
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 30.613
+    - type: map_at_10
+      value: 40.781
+    - type: map_at_100
+      value: 42.018
+    - type: map_at_1000
+      value: 42.132999999999996
+    - type: map_at_3
+      value: 37.816
+    - type: map_at_5
+      value: 39.389
+    - type: mrr_at_1
+      value: 38.408
+    - type: mrr_at_10
+      value: 46.631
+    - type: mrr_at_100
+      value: 47.332
+    - type: mrr_at_1000
+      value: 47.368
+    - type: mrr_at_3
+      value: 44.384
+    - type: mrr_at_5
+      value: 45.661
+    - type: ndcg_at_1
+      value: 38.408
+    - type: ndcg_at_10
+      value: 46.379999999999995
+    - type: ndcg_at_100
+      value: 50.81
+    - type: ndcg_at_1000
+      value: 52.663000000000004
+    - type: ndcg_at_3
+      value: 42.18
+    - type: ndcg_at_5
+      value: 43.974000000000004
+    - type: precision_at_1
+      value: 38.408
+    - type: precision_at_10
+      value: 8.656
+    - type: precision_at_100
+      value: 1.3860000000000001
+    - type: precision_at_1000
+      value: 0.184
+    - type: precision_at_3
+      value: 20.276
+    - type: precision_at_5
+      value: 14.241999999999999
+    - type: recall_at_1
+      value: 30.613
+    - type: recall_at_10
+      value: 56.44
+    - type: recall_at_100
+      value: 75.044
+    - type: recall_at_1000
+      value: 86.426
+    - type: recall_at_3
+      value: 43.766
+    - type: recall_at_5
+      value: 48.998000000000005
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackGamingRetrieval
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 37.370999999999995
+    - type: map_at_10
+      value: 49.718
+    - type: map_at_100
+      value: 50.737
+    - type: map_at_1000
+      value: 50.79
+    - type: map_at_3
+      value: 46.231
+    - type: map_at_5
+      value: 48.329
+    - type: mrr_at_1
+      value: 42.884
+    - type: mrr_at_10
+      value: 53.176
+    - type: mrr_at_100
+      value: 53.81700000000001
+    - type: mrr_at_1000
+      value: 53.845
+    - type: mrr_at_3
+      value: 50.199000000000005
+    - type: mrr_at_5
+      value: 52.129999999999995
+    - type: ndcg_at_1
+      value: 42.884
+    - type: ndcg_at_10
+      value: 55.826
+    - type: ndcg_at_100
+      value: 59.93000000000001
+    - type: ndcg_at_1000
+      value: 61.013
+    - type: ndcg_at_3
+      value: 49.764
+    - type: ndcg_at_5
+      value: 53.025999999999996
+    - type: precision_at_1
+      value: 42.884
+    - type: precision_at_10
+      value: 9.046999999999999
+    - type: precision_at_100
+      value: 1.212
+    - type: precision_at_1000
+      value: 0.135
+    - type: precision_at_3
+      value: 22.131999999999998
+    - type: precision_at_5
+      value: 15.524
+    - type: recall_at_1
+      value: 37.370999999999995
+    - type: recall_at_10
+      value: 70.482
+    - type: recall_at_100
+      value: 88.425
+    - type: recall_at_1000
+      value: 96.03399999999999
+    - type: recall_at_3
+      value: 54.43
+    - type: recall_at_5
+      value: 62.327999999999996
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackGisRetrieval
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 22.875999999999998
+    - type: map_at_10
+      value: 31.715
+    - type: map_at_100
+      value: 32.847
+    - type: map_at_1000
+      value: 32.922000000000004
+    - type: map_at_3
+      value: 29.049999999999997
+    - type: map_at_5
+      value: 30.396
+    - type: mrr_at_1
+      value: 24.52
+    - type: mrr_at_10
+      value: 33.497
+    - type: mrr_at_100
+      value: 34.455000000000005
+    - type: mrr_at_1000
+      value: 34.510000000000005
+    - type: mrr_at_3
+      value: 30.791
+    - type: mrr_at_5
+      value: 32.175
+    - type: ndcg_at_1
+      value: 24.52
+    - type: ndcg_at_10
+      value: 36.95
+    - type: ndcg_at_100
+      value: 42.238
+    - type: ndcg_at_1000
+      value: 44.147999999999996
+    - type: ndcg_at_3
+      value: 31.435000000000002
+    - type: ndcg_at_5
+      value: 33.839000000000006
+    - type: precision_at_1
+      value: 24.52
+    - type: precision_at_10
+      value: 5.9319999999999995
+    - type: precision_at_100
+      value: 0.901
+    - type: precision_at_1000
+      value: 0.11
+    - type: precision_at_3
+      value: 13.446
+    - type: precision_at_5
+      value: 9.469
+    - type: recall_at_1
+      value: 22.875999999999998
+    - type: recall_at_10
+      value: 51.38
+    - type: recall_at_100
+      value: 75.31099999999999
+    - type: recall_at_1000
+      value: 89.718
+    - type: recall_at_3
+      value: 36.26
+    - type: recall_at_5
+      value: 42.248999999999995
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackMathematicaRetrieval
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 14.984
+    - type: map_at_10
+      value: 23.457
+    - type: map_at_100
+      value: 24.723
+    - type: map_at_1000
+      value: 24.846
+    - type: map_at_3
+      value: 20.873
+    - type: map_at_5
+      value: 22.357
+    - type: mrr_at_1
+      value: 18.159
+    - type: mrr_at_10
+      value: 27.431
+    - type: mrr_at_100
+      value: 28.449
+    - type: mrr_at_1000
+      value: 28.52
+    - type: mrr_at_3
+      value: 24.979000000000003
+    - type: mrr_at_5
+      value: 26.447
+    - type: ndcg_at_1
+      value: 18.159
+    - type: ndcg_at_10
+      value: 28.627999999999997
+    - type: ndcg_at_100
+      value: 34.741
+    - type: ndcg_at_1000
+      value: 37.516
+    - type: ndcg_at_3
+      value: 23.902
+    - type: ndcg_at_5
+      value: 26.294
+    - type: precision_at_1
+      value: 18.159
+    - type: precision_at_10
+      value: 5.485
+    - type: precision_at_100
+      value: 0.985
+    - type: precision_at_1000
+      value: 0.136
+    - type: precision_at_3
+      value: 11.774
+    - type: precision_at_5
+      value: 8.731
+    - type: recall_at_1
+      value: 14.984
+    - type: recall_at_10
+      value: 40.198
+    - type: recall_at_100
+      value: 67.11500000000001
+    - type: recall_at_1000
+      value: 86.497
+    - type: recall_at_3
+      value: 27.639000000000003
+    - type: recall_at_5
+      value: 33.595000000000006
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackPhysicsRetrieval
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 29.067
+    - type: map_at_10
+      value: 39.457
+    - type: map_at_100
+      value: 40.83
+    - type: map_at_1000
+      value: 40.94
+    - type: map_at_3
+      value: 35.995
+    - type: map_at_5
+      value: 38.159
+    - type: mrr_at_1
+      value: 34.937000000000005
+    - type: mrr_at_10
+      value: 44.755
+    - type: mrr_at_100
+      value: 45.549
+    - type: mrr_at_1000
+      value: 45.589
+    - type: mrr_at_3
+      value: 41.947
+    - type: mrr_at_5
+      value: 43.733
+    - type: ndcg_at_1
+      value: 34.937000000000005
+    - type: ndcg_at_10
+      value: 45.573
+    - type: ndcg_at_100
+      value: 51.266999999999996
+    - type: ndcg_at_1000
+      value: 53.184
+    - type: ndcg_at_3
+      value: 39.961999999999996
+    - type: ndcg_at_5
+      value: 43.02
+    - type: precision_at_1
+      value: 34.937000000000005
+    - type: precision_at_10
+      value: 8.296000000000001
+    - type: precision_at_100
+      value: 1.32
+    - type: precision_at_1000
+      value: 0.167
+    - type: precision_at_3
+      value: 18.8
+    - type: precision_at_5
+      value: 13.763
+    - type: recall_at_1
+      value: 29.067
+    - type: recall_at_10
+      value: 58.298
+    - type: recall_at_100
+      value: 82.25099999999999
+    - type: recall_at_1000
+      value: 94.476
+    - type: recall_at_3
+      value: 42.984
+    - type: recall_at_5
+      value: 50.658
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackProgrammersRetrieval
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 25.985999999999997
+    - type: map_at_10
+      value: 35.746
+    - type: map_at_100
+      value: 37.067
+    - type: map_at_1000
+      value: 37.191
+    - type: map_at_3
+      value: 32.599000000000004
+    - type: map_at_5
+      value: 34.239000000000004
+    - type: mrr_at_1
+      value: 31.735000000000003
+    - type: mrr_at_10
+      value: 40.515
+    - type: mrr_at_100
+      value: 41.459
+    - type: mrr_at_1000
+      value: 41.516
+    - type: mrr_at_3
+      value: 37.938
+    - type: mrr_at_5
+      value: 39.25
+    - type: ndcg_at_1
+      value: 31.735000000000003
+    - type: ndcg_at_10
+      value: 41.484
+    - type: ndcg_at_100
+      value: 47.047
+    - type: ndcg_at_1000
+      value: 49.427
+    - type: ndcg_at_3
+      value: 36.254999999999995
+    - type: ndcg_at_5
+      value: 38.375
+    - type: precision_at_1
+      value: 31.735000000000003
+    - type: precision_at_10
+      value: 7.66
+    - type: precision_at_100
+      value: 1.234
+    - type: precision_at_1000
+      value: 0.16
+    - type: precision_at_3
+      value: 17.427999999999997
+    - type: precision_at_5
+      value: 12.328999999999999
+    - type: recall_at_1
+      value: 25.985999999999997
+    - type: recall_at_10
+      value: 53.761
+    - type: recall_at_100
+      value: 77.149
+    - type: recall_at_1000
+      value: 93.342
+    - type: recall_at_3
+      value: 39.068000000000005
+    - type: recall_at_5
+      value: 44.693
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackRetrieval
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 24.949749999999998
+    - type: map_at_10
+      value: 34.04991666666667
+    - type: map_at_100
+      value: 35.26825
+    - type: map_at_1000
+      value: 35.38316666666667
+    - type: map_at_3
+      value: 31.181333333333335
+    - type: map_at_5
+      value: 32.77391666666667
+    - type: mrr_at_1
+      value: 29.402833333333334
+    - type: mrr_at_10
+      value: 38.01633333333333
+    - type: mrr_at_100
+      value: 38.88033333333334
+    - type: mrr_at_1000
+      value: 38.938500000000005
+    - type: mrr_at_3
+      value: 35.5175
+    - type: mrr_at_5
+      value: 36.93808333333333
+    - type: ndcg_at_1
+      value: 29.402833333333334
+    - type: ndcg_at_10
+      value: 39.403166666666664
+    - type: ndcg_at_100
+      value: 44.66408333333333
+    - type: ndcg_at_1000
+      value: 46.96283333333333
+    - type: ndcg_at_3
+      value: 34.46633333333334
+    - type: ndcg_at_5
+      value: 36.78441666666667
+    - type: precision_at_1
+      value: 29.402833333333334
+    - type: precision_at_10
+      value: 6.965833333333333
+    - type: precision_at_100
+      value: 1.1330833333333334
+    - type: precision_at_1000
+      value: 0.15158333333333335
+    - type: precision_at_3
+      value: 15.886666666666665
+    - type: precision_at_5
+      value: 11.360416666666667
+    - type: recall_at_1
+      value: 24.949749999999998
+    - type: recall_at_10
+      value: 51.29325
+    - type: recall_at_100
+      value: 74.3695
+    - type: recall_at_1000
+      value: 90.31299999999999
+    - type: recall_at_3
+      value: 37.580083333333334
+    - type: recall_at_5
+      value: 43.529666666666664
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackStatsRetrieval
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 22.081999999999997
+    - type: map_at_10
+      value: 29.215999999999998
+    - type: map_at_100
+      value: 30.163
+    - type: map_at_1000
+      value: 30.269000000000002
+    - type: map_at_3
+      value: 26.942
+    - type: map_at_5
+      value: 28.236
+    - type: mrr_at_1
+      value: 24.847
+    - type: mrr_at_10
+      value: 31.918999999999997
+    - type: mrr_at_100
+      value: 32.817
+    - type: mrr_at_1000
+      value: 32.897
+    - type: mrr_at_3
+      value: 29.831000000000003
+    - type: mrr_at_5
+      value: 31.019999999999996
+    - type: ndcg_at_1
+      value: 24.847
+    - type: ndcg_at_10
+      value: 33.4
+    - type: ndcg_at_100
+      value: 38.354
+    - type: ndcg_at_1000
+      value: 41.045
+    - type: ndcg_at_3
+      value: 29.236
+    - type: ndcg_at_5
+      value: 31.258000000000003
+    - type: precision_at_1
+      value: 24.847
+    - type: precision_at_10
+      value: 5.353
+    - type: precision_at_100
+      value: 0.853
+    - type: precision_at_1000
+      value: 0.116
+    - type: precision_at_3
+      value: 12.679000000000002
+    - type: precision_at_5
+      value: 8.988
+    - type: recall_at_1
+      value: 22.081999999999997
+    - type: recall_at_10
+      value: 43.505
+    - type: recall_at_100
+      value: 66.45400000000001
+    - type: recall_at_1000
+      value: 86.378
+    - type: recall_at_3
+      value: 32.163000000000004
+    - type: recall_at_5
+      value: 37.059999999999995
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackTexRetrieval
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 15.540000000000001
+    - type: map_at_10
+      value: 22.362000000000002
+    - type: map_at_100
+      value: 23.435
+    - type: map_at_1000
+      value: 23.564
+    - type: map_at_3
+      value: 20.143
+    - type: map_at_5
+      value: 21.324
+    - type: mrr_at_1
+      value: 18.892
+    - type: mrr_at_10
+      value: 25.942999999999998
+    - type: mrr_at_100
+      value: 26.883000000000003
+    - type: mrr_at_1000
+      value: 26.968999999999998
+    - type: mrr_at_3
+      value: 23.727
+    - type: mrr_at_5
+      value: 24.923000000000002
+    - type: ndcg_at_1
+      value: 18.892
+    - type: ndcg_at_10
+      value: 26.811
+    - type: ndcg_at_100
+      value: 32.066
+    - type: ndcg_at_1000
+      value: 35.166
+    - type: ndcg_at_3
+      value: 22.706
+    - type: ndcg_at_5
+      value: 24.508
+    - type: precision_at_1
+      value: 18.892
+    - type: precision_at_10
+      value: 4.942
+    - type: precision_at_100
+      value: 0.878
+    - type: precision_at_1000
+      value: 0.131
+    - type: precision_at_3
+      value: 10.748000000000001
+    - type: precision_at_5
+      value: 7.784000000000001
+    - type: recall_at_1
+      value: 15.540000000000001
+    - type: recall_at_10
+      value: 36.742999999999995
+    - type: recall_at_100
+      value: 60.525
+    - type: recall_at_1000
+      value: 82.57600000000001
+    - type: recall_at_3
+      value: 25.252000000000002
+    - type: recall_at_5
+      value: 29.872
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackUnixRetrieval
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 24.453
+    - type: map_at_10
+      value: 33.363
+    - type: map_at_100
+      value: 34.579
+    - type: map_at_1000
+      value: 34.686
+    - type: map_at_3
+      value: 30.583
+    - type: map_at_5
+      value: 32.118
+    - type: mrr_at_1
+      value: 28.918
+    - type: mrr_at_10
+      value: 37.675
+    - type: mrr_at_100
+      value: 38.567
+    - type: mrr_at_1000
+      value: 38.632
+    - type: mrr_at_3
+      value: 35.260999999999996
+    - type: mrr_at_5
+      value: 36.576
+    - type: ndcg_at_1
+      value: 28.918
+    - type: ndcg_at_10
+      value: 38.736
+    - type: ndcg_at_100
+      value: 44.261
+    - type: ndcg_at_1000
+      value: 46.72
+    - type: ndcg_at_3
+      value: 33.81
+    - type: ndcg_at_5
+      value: 36.009
+    - type: precision_at_1
+      value: 28.918
+    - type: precision_at_10
+      value: 6.586
+    - type: precision_at_100
+      value: 1.047
+    - type: precision_at_1000
+      value: 0.13699999999999998
+    - type: precision_at_3
+      value: 15.360999999999999
+    - type: precision_at_5
+      value: 10.857999999999999
+    - type: recall_at_1
+      value: 24.453
+    - type: recall_at_10
+      value: 50.885999999999996
+    - type: recall_at_100
+      value: 75.03
+    - type: recall_at_1000
+      value: 92.123
+    - type: recall_at_3
+      value: 37.138
+    - type: recall_at_5
+      value: 42.864999999999995
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackWebmastersRetrieval
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 24.57
+    - type: map_at_10
+      value: 33.672000000000004
+    - type: map_at_100
+      value: 35.244
+    - type: map_at_1000
+      value: 35.467
+    - type: map_at_3
+      value: 30.712
+    - type: map_at_5
+      value: 32.383
+    - type: mrr_at_1
+      value: 29.644
+    - type: mrr_at_10
+      value: 38.344
+    - type: mrr_at_100
+      value: 39.219
+    - type: mrr_at_1000
+      value: 39.282000000000004
+    - type: mrr_at_3
+      value: 35.771
+    - type: mrr_at_5
+      value: 37.273
+    - type: ndcg_at_1
+      value: 29.644
+    - type: ndcg_at_10
+      value: 39.567
+    - type: ndcg_at_100
+      value: 45.097
+    - type: ndcg_at_1000
+      value: 47.923
+    - type: ndcg_at_3
+      value: 34.768
+    - type: ndcg_at_5
+      value: 37.122
+    - type: precision_at_1
+      value: 29.644
+    - type: precision_at_10
+      value: 7.5889999999999995
+    - type: precision_at_100
+      value: 1.478
+    - type: precision_at_1000
+      value: 0.23500000000000001
+    - type: precision_at_3
+      value: 16.337
+    - type: precision_at_5
+      value: 12.055
+    - type: recall_at_1
+      value: 24.57
+    - type: recall_at_10
+      value: 51.00900000000001
+    - type: recall_at_100
+      value: 75.423
+    - type: recall_at_1000
+      value: 93.671
+    - type: recall_at_3
+      value: 36.925999999999995
+    - type: recall_at_5
+      value: 43.245
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackWordpressRetrieval
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 21.356
+    - type: map_at_10
+      value: 27.904
+    - type: map_at_100
+      value: 28.938000000000002
+    - type: map_at_1000
+      value: 29.036
+    - type: map_at_3
+      value: 25.726
+    - type: map_at_5
+      value: 26.935
+    - type: mrr_at_1
+      value: 22.551
+    - type: mrr_at_10
+      value: 29.259
+    - type: mrr_at_100
+      value: 30.272
+    - type: mrr_at_1000
+      value: 30.348000000000003
+    - type: mrr_at_3
+      value: 27.295
+    - type: mrr_at_5
+      value: 28.358
+    - type: ndcg_at_1
+      value: 22.551
+    - type: ndcg_at_10
+      value: 31.817
+    - type: ndcg_at_100
+      value: 37.164
+    - type: ndcg_at_1000
+      value: 39.82
+    - type: ndcg_at_3
+      value: 27.595999999999997
+    - type: ndcg_at_5
+      value: 29.568
+    - type: precision_at_1
+      value: 22.551
+    - type: precision_at_10
+      value: 4.917
+    - type: precision_at_100
+      value: 0.828
+    - type: precision_at_1000
+      value: 0.11399999999999999
+    - type: precision_at_3
+      value: 11.583
+    - type: precision_at_5
+      value: 8.133
+    - type: recall_at_1
+      value: 21.356
+    - type: recall_at_10
+      value: 42.489
+    - type: recall_at_100
+      value: 67.128
+    - type: recall_at_1000
+      value: 87.441
+    - type: recall_at_3
+      value: 31.165
+    - type: recall_at_5
+      value: 35.853
+  - task:
+      type: Retrieval
+    dataset:
+      type: climate-fever
+      name: MTEB ClimateFEVER
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 12.306000000000001
+    - type: map_at_10
+      value: 21.523
+    - type: map_at_100
+      value: 23.358
+    - type: map_at_1000
+      value: 23.541
+    - type: map_at_3
+      value: 17.809
+    - type: map_at_5
+      value: 19.631
+    - type: mrr_at_1
+      value: 27.948
+    - type: mrr_at_10
+      value: 40.355000000000004
+    - type: mrr_at_100
+      value: 41.166000000000004
+    - type: mrr_at_1000
+      value: 41.203
+    - type: mrr_at_3
+      value: 36.819
+    - type: mrr_at_5
+      value: 38.958999999999996
+    - type: ndcg_at_1
+      value: 27.948
+    - type: ndcg_at_10
+      value: 30.462
+    - type: ndcg_at_100
+      value: 37.473
+    - type: ndcg_at_1000
+      value: 40.717999999999996
+    - type: ndcg_at_3
+      value: 24.646
+    - type: ndcg_at_5
+      value: 26.642
+    - type: precision_at_1
+      value: 27.948
+    - type: precision_at_10
+      value: 9.648
+    - type: precision_at_100
+      value: 1.7239999999999998
+    - type: precision_at_1000
+      value: 0.232
+    - type: precision_at_3
+      value: 18.48
+    - type: precision_at_5
+      value: 14.293
+    - type: recall_at_1
+      value: 12.306000000000001
+    - type: recall_at_10
+      value: 37.181
+    - type: recall_at_100
+      value: 61.148
+    - type: recall_at_1000
+      value: 79.401
+    - type: recall_at_3
+      value: 22.883
+    - type: recall_at_5
+      value: 28.59
+  - task:
+      type: Retrieval
+    dataset:
+      type: dbpedia-entity
+      name: MTEB DBPedia
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 9.357
+    - type: map_at_10
+      value: 18.849
+    - type: map_at_100
+      value: 25.369000000000003
+    - type: map_at_1000
+      value: 26.950000000000003
+    - type: map_at_3
+      value: 13.625000000000002
+    - type: map_at_5
+      value: 15.956999999999999
+    - type: mrr_at_1
+      value: 67.75
+    - type: mrr_at_10
+      value: 74.734
+    - type: mrr_at_100
+      value: 75.1
+    - type: mrr_at_1000
+      value: 75.10900000000001
+    - type: mrr_at_3
+      value: 73.542
+    - type: mrr_at_5
+      value: 74.167
+    - type: ndcg_at_1
+      value: 55.375
+    - type: ndcg_at_10
+      value: 39.873999999999995
+    - type: ndcg_at_100
+      value: 43.098
+    - type: ndcg_at_1000
+      value: 50.69200000000001
+    - type: ndcg_at_3
+      value: 44.856
+    - type: ndcg_at_5
+      value: 42.138999999999996
+    - type: precision_at_1
+      value: 67.75
+    - type: precision_at_10
+      value: 31.1
+    - type: precision_at_100
+      value: 9.303
+    - type: precision_at_1000
+      value: 2.0060000000000002
+    - type: precision_at_3
+      value: 48.25
+    - type: precision_at_5
+      value: 40.949999999999996
+    - type: recall_at_1
+      value: 9.357
+    - type: recall_at_10
+      value: 23.832
+    - type: recall_at_100
+      value: 47.906
+    - type: recall_at_1000
+      value: 71.309
+    - type: recall_at_3
+      value: 14.512
+    - type: recall_at_5
+      value: 18.3
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/emotion
+      name: MTEB EmotionClassification
+      config: default
+      split: test
+    metrics:
+    - type: accuracy
+      value: 49.655
+    - type: f1
+      value: 45.51976190938951
+  - task:
+      type: Retrieval
+    dataset:
+      type: fever
+      name: MTEB FEVER
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 62.739999999999995
+    - type: map_at_10
+      value: 73.07000000000001
+    - type: map_at_100
+      value: 73.398
+    - type: map_at_1000
+      value: 73.41
+    - type: map_at_3
+      value: 71.33800000000001
+    - type: map_at_5
+      value: 72.423
+    - type: mrr_at_1
+      value: 67.777
+    - type: mrr_at_10
+      value: 77.873
+    - type: mrr_at_100
+      value: 78.091
+    - type: mrr_at_1000
+      value: 78.094
+    - type: mrr_at_3
+      value: 76.375
+    - type: mrr_at_5
+      value: 77.316
+    - type: ndcg_at_1
+      value: 67.777
+    - type: ndcg_at_10
+      value: 78.24
+    - type: ndcg_at_100
+      value: 79.557
+    - type: ndcg_at_1000
+      value: 79.814
+    - type: ndcg_at_3
+      value: 75.125
+    - type: ndcg_at_5
+      value: 76.834
+    - type: precision_at_1
+      value: 67.777
+    - type: precision_at_10
+      value: 9.832
+    - type: precision_at_100
+      value: 1.061
+    - type: precision_at_1000
+      value: 0.11
+    - type: precision_at_3
+      value: 29.433
+    - type: precision_at_5
+      value: 18.665000000000003
+    - type: recall_at_1
+      value: 62.739999999999995
+    - type: recall_at_10
+      value: 89.505
+    - type: recall_at_100
+      value: 95.102
+    - type: recall_at_1000
+      value: 96.825
+    - type: recall_at_3
+      value: 81.028
+    - type: recall_at_5
+      value: 85.28099999999999
+  - task:
+      type: Retrieval
+    dataset:
+      type: fiqa
+      name: MTEB FiQA2018
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 18.467
+    - type: map_at_10
+      value: 30.020999999999997
+    - type: map_at_100
+      value: 31.739
+    - type: map_at_1000
+      value: 31.934
+    - type: map_at_3
+      value: 26.003
+    - type: map_at_5
+      value: 28.338
+    - type: mrr_at_1
+      value: 35.339999999999996
+    - type: mrr_at_10
+      value: 44.108999999999995
+    - type: mrr_at_100
+      value: 44.993
+    - type: mrr_at_1000
+      value: 45.042
+    - type: mrr_at_3
+      value: 41.667
+    - type: mrr_at_5
+      value: 43.14
+    - type: ndcg_at_1
+      value: 35.339999999999996
+    - type: ndcg_at_10
+      value: 37.202
+    - type: ndcg_at_100
+      value: 43.852999999999994
+    - type: ndcg_at_1000
+      value: 47.235
+    - type: ndcg_at_3
+      value: 33.5
+    - type: ndcg_at_5
+      value: 34.985
+    - type: precision_at_1
+      value: 35.339999999999996
+    - type: precision_at_10
+      value: 10.247
+    - type: precision_at_100
+      value: 1.7149999999999999
+    - type: precision_at_1000
+      value: 0.232
+    - type: precision_at_3
+      value: 22.222
+    - type: precision_at_5
+      value: 16.573999999999998
+    - type: recall_at_1
+      value: 18.467
+    - type: recall_at_10
+      value: 44.080999999999996
+    - type: recall_at_100
+      value: 68.72200000000001
+    - type: recall_at_1000
+      value: 89.087
+    - type: recall_at_3
+      value: 30.567
+    - type: recall_at_5
+      value: 36.982
+  - task:
+      type: Retrieval
+    dataset:
+      type: hotpotqa
+      name: MTEB HotpotQA
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 35.726
+    - type: map_at_10
+      value: 50.207
+    - type: map_at_100
+      value: 51.05499999999999
+    - type: map_at_1000
+      value: 51.12799999999999
+    - type: map_at_3
+      value: 47.576
+    - type: map_at_5
+      value: 49.172
+    - type: mrr_at_1
+      value: 71.452
+    - type: mrr_at_10
+      value: 77.41900000000001
+    - type: mrr_at_100
+      value: 77.711
+    - type: mrr_at_1000
+      value: 77.723
+    - type: mrr_at_3
+      value: 76.39399999999999
+    - type: mrr_at_5
+      value: 77.00099999999999
+    - type: ndcg_at_1
+      value: 71.452
+    - type: ndcg_at_10
+      value: 59.260999999999996
+    - type: ndcg_at_100
+      value: 62.424
+    - type: ndcg_at_1000
+      value: 63.951
+    - type: ndcg_at_3
+      value: 55.327000000000005
+    - type: ndcg_at_5
+      value: 57.416999999999994
+    - type: precision_at_1
+      value: 71.452
+    - type: precision_at_10
+      value: 12.061
+    - type: precision_at_100
+      value: 1.455
+    - type: precision_at_1000
+      value: 0.166
+    - type: precision_at_3
+      value: 34.36
+    - type: precision_at_5
+      value: 22.266
+    - type: recall_at_1
+      value: 35.726
+    - type: recall_at_10
+      value: 60.304
+    - type: recall_at_100
+      value: 72.75500000000001
+    - type: recall_at_1000
+      value: 82.978
+    - type: recall_at_3
+      value: 51.54
+    - type: recall_at_5
+      value: 55.665
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/imdb
+      name: MTEB ImdbClassification
+      config: default
+      split: test
+    metrics:
+    - type: accuracy
+      value: 66.63759999999999
+    - type: ap
+      value: 61.48938261286748
+    - type: f1
+      value: 66.35089269264965
+  - task:
+      type: Retrieval
+    dataset:
+      type: msmarco
+      name: MTEB MSMARCO
+      config: default
+      split: validation
+    metrics:
+    - type: map_at_1
+      value: 20.842
+    - type: map_at_10
+      value: 32.992
+    - type: map_at_100
+      value: 34.236
+    - type: map_at_1000
+      value: 34.286
+    - type: map_at_3
+      value: 29.049000000000003
+    - type: map_at_5
+      value: 31.391999999999996
+    - type: mrr_at_1
+      value: 21.375
+    - type: mrr_at_10
+      value: 33.581
+    - type: mrr_at_100
+      value: 34.760000000000005
+    - type: mrr_at_1000
+      value: 34.803
+    - type: mrr_at_3
+      value: 29.704000000000004
+    - type: mrr_at_5
+      value: 32.015
+    - type: ndcg_at_1
+      value: 21.375
+    - type: ndcg_at_10
+      value: 39.905
+    - type: ndcg_at_100
+      value: 45.843
+    - type: ndcg_at_1000
+      value: 47.083999999999996
+    - type: ndcg_at_3
+      value: 31.918999999999997
+    - type: ndcg_at_5
+      value: 36.107
+    - type: precision_at_1
+      value: 21.375
+    - type: precision_at_10
+      value: 6.393
+    - type: precision_at_100
+      value: 0.935
+    - type: precision_at_1000
+      value: 0.104
+    - type: precision_at_3
+      value: 13.663
+    - type: precision_at_5
+      value: 10.324
+    - type: recall_at_1
+      value: 20.842
+    - type: recall_at_10
+      value: 61.17
+    - type: recall_at_100
+      value: 88.518
+    - type: recall_at_1000
+      value: 97.993
+    - type: recall_at_3
+      value: 39.571
+    - type: recall_at_5
+      value: 49.653999999999996
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_domain
+      name: MTEB MTOPDomainClassification (en)
+      config: en
+      split: test
+    metrics:
+    - type: accuracy
+      value: 93.46557227542178
+    - type: f1
+      value: 92.87345917772146
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_intent
+      name: MTEB MTOPIntentClassification (en)
+      config: en
+      split: test
     metrics:
     - type: accuracy
-      value: 0.8449350649350649
+      value: 72.42134062927497
+    - type: f1
+      value: 55.03624810959269
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (en)
+      config: en
+      split: test
+    metrics:
+    - type: accuracy
+      value: 70.3866845998655
+    - type: f1
+      value: 68.9674519872921
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (en)
+      config: en
+      split: test
+    metrics:
+    - type: accuracy
+      value: 76.27774041694687
+    - type: f1
+      value: 76.72936190462792
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/medrxiv-clustering-p2p
+      name: MTEB MedrxivClusteringP2P
+      config: default
+      split: test
+    metrics:
+    - type: v_measure
+      value: 31.511745925773337
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/medrxiv-clustering-s2s
+      name: MTEB MedrxivClusteringS2S
+      config: default
+      split: test
+    metrics:
+    - type: v_measure
+      value: 28.764235987575365
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/mind_small
+      name: MTEB MindSmallReranking
+      config: default
+      split: test
+    metrics:
+    - type: map
+      value: 32.29353136386601
+    - type: mrr
+      value: 33.536774455851685
+  - task:
+      type: Retrieval
+    dataset:
+      type: nfcorpus
+      name: MTEB NFCorpus
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 5.702
+    - type: map_at_10
+      value: 13.642000000000001
+    - type: map_at_100
+      value: 17.503
+    - type: map_at_1000
+      value: 19.126
+    - type: map_at_3
+      value: 9.748
+    - type: map_at_5
+      value: 11.642
+    - type: mrr_at_1
+      value: 45.82
+    - type: mrr_at_10
+      value: 54.821
+    - type: mrr_at_100
+      value: 55.422000000000004
+    - type: mrr_at_1000
+      value: 55.452999999999996
+    - type: mrr_at_3
+      value: 52.373999999999995
+    - type: mrr_at_5
+      value: 53.937000000000005
+    - type: ndcg_at_1
+      value: 44.272
+    - type: ndcg_at_10
+      value: 36.213
+    - type: ndcg_at_100
+      value: 33.829
+    - type: ndcg_at_1000
+      value: 42.557
+    - type: ndcg_at_3
+      value: 40.814
+    - type: ndcg_at_5
+      value: 39.562000000000005
+    - type: precision_at_1
+      value: 45.511
+    - type: precision_at_10
+      value: 27.214
+    - type: precision_at_100
+      value: 8.941
+    - type: precision_at_1000
+      value: 2.1870000000000003
+    - type: precision_at_3
+      value: 37.874
+    - type: precision_at_5
+      value: 34.489
+    - type: recall_at_1
+      value: 5.702
+    - type: recall_at_10
+      value: 17.638
+    - type: recall_at_100
+      value: 34.419
+    - type: recall_at_1000
+      value: 66.41
+    - type: recall_at_3
+      value: 10.914
+    - type: recall_at_5
+      value: 14.032
+  - task:
+      type: Retrieval
+    dataset:
+      type: nq
+      name: MTEB NQ
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 30.567
+    - type: map_at_10
+      value: 45.01
+    - type: map_at_100
+      value: 46.091
+    - type: map_at_1000
+      value: 46.126
+    - type: map_at_3
+      value: 40.897
+    - type: map_at_5
+      value: 43.301
+    - type: mrr_at_1
+      value: 34.56
+    - type: mrr_at_10
+      value: 47.725
+    - type: mrr_at_100
+      value: 48.548
+    - type: mrr_at_1000
+      value: 48.571999999999996
+    - type: mrr_at_3
+      value: 44.361
+    - type: mrr_at_5
+      value: 46.351
+    - type: ndcg_at_1
+      value: 34.531
+    - type: ndcg_at_10
+      value: 52.410000000000004
+    - type: ndcg_at_100
+      value: 56.999
+    - type: ndcg_at_1000
+      value: 57.830999999999996
+    - type: ndcg_at_3
+      value: 44.734
+    - type: ndcg_at_5
+      value: 48.701
+    - type: precision_at_1
+      value: 34.531
+    - type: precision_at_10
+      value: 8.612
+    - type: precision_at_100
+      value: 1.118
+    - type: precision_at_1000
+      value: 0.12
+    - type: precision_at_3
+      value: 20.307
+    - type: precision_at_5
+      value: 14.519000000000002
+    - type: recall_at_1
+      value: 30.567
+    - type: recall_at_10
+      value: 72.238
+    - type: recall_at_100
+      value: 92.154
+    - type: recall_at_1000
+      value: 98.375
+    - type: recall_at_3
+      value: 52.437999999999995
+    - type: recall_at_5
+      value: 61.516999999999996
+  - task:
+      type: Retrieval
+    dataset:
+      type: quora
+      name: MTEB QuoraRetrieval
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 65.98
+    - type: map_at_10
+      value: 80.05600000000001
+    - type: map_at_100
+      value: 80.76299999999999
+    - type: map_at_1000
+      value: 80.786
+    - type: map_at_3
+      value: 76.848
+    - type: map_at_5
+      value: 78.854
+    - type: mrr_at_1
+      value: 75.86
+    - type: mrr_at_10
+      value: 83.397
+    - type: mrr_at_100
+      value: 83.555
+    - type: mrr_at_1000
+      value: 83.557
+    - type: mrr_at_3
+      value: 82.033
+    - type: mrr_at_5
+      value: 82.97
+    - type: ndcg_at_1
+      value: 75.88000000000001
+    - type: ndcg_at_10
+      value: 84.58099999999999
+    - type: ndcg_at_100
+      value: 86.151
+    - type: ndcg_at_1000
+      value: 86.315
+    - type: ndcg_at_3
+      value: 80.902
+    - type: ndcg_at_5
+      value: 82.953
+    - type: precision_at_1
+      value: 75.88000000000001
+    - type: precision_at_10
+      value: 12.986
+    - type: precision_at_100
+      value: 1.5110000000000001
+    - type: precision_at_1000
+      value: 0.156
+    - type: precision_at_3
+      value: 35.382999999999996
+    - type: precision_at_5
+      value: 23.555999999999997
+    - type: recall_at_1
+      value: 65.98
+    - type: recall_at_10
+      value: 93.716
+    - type: recall_at_100
+      value: 99.21799999999999
+    - type: recall_at_1000
+      value: 99.97
+    - type: recall_at_3
+      value: 83.551
+    - type: recall_at_5
+      value: 88.998
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/reddit-clustering
+      name: MTEB RedditClustering
+      config: default
+      split: test
+    metrics:
+    - type: v_measure
+      value: 40.45148482612238
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/reddit-clustering-p2p
+      name: MTEB RedditClusteringP2P
+      config: default
+      split: test
+    metrics:
+    - type: v_measure
+      value: 55.749490673039126
+  - task:
+      type: Retrieval
+    dataset:
+      type: scidocs
+      name: MTEB SCIDOCS
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 4.903
+    - type: map_at_10
+      value: 11.926
+    - type: map_at_100
+      value: 13.916999999999998
+    - type: map_at_1000
+      value: 14.215
+    - type: map_at_3
+      value: 8.799999999999999
+    - type: map_at_5
+      value: 10.360999999999999
+    - type: mrr_at_1
+      value: 24.099999999999998
+    - type: mrr_at_10
+      value: 34.482
+    - type: mrr_at_100
+      value: 35.565999999999995
+    - type: mrr_at_1000
+      value: 35.619
+    - type: mrr_at_3
+      value: 31.433
+    - type: mrr_at_5
+      value: 33.243
+    - type: ndcg_at_1
+      value: 24.099999999999998
+    - type: ndcg_at_10
+      value: 19.872999999999998
+    - type: ndcg_at_100
+      value: 27.606
+    - type: ndcg_at_1000
+      value: 32.811
+    - type: ndcg_at_3
+      value: 19.497999999999998
+    - type: ndcg_at_5
+      value: 16.813
+    - type: precision_at_1
+      value: 24.099999999999998
+    - type: precision_at_10
+      value: 10.08
+    - type: precision_at_100
+      value: 2.122
+    - type: precision_at_1000
+      value: 0.337
+    - type: precision_at_3
+      value: 18.2
+    - type: precision_at_5
+      value: 14.62
+    - type: recall_at_1
+      value: 4.903
+    - type: recall_at_10
+      value: 20.438000000000002
+    - type: recall_at_100
+      value: 43.043
+    - type: recall_at_1000
+      value: 68.41000000000001
+    - type: recall_at_3
+      value: 11.068
+    - type: recall_at_5
+      value: 14.818000000000001
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sickr-sts
+      name: MTEB SICK-R
+      config: default
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: 78.58086597995997
+    - type: cos_sim_spearman
+      value: 69.63214182814991
+    - type: euclidean_pearson
+      value: 72.76175489042691
+    - type: euclidean_spearman
+      value: 67.84965161872971
+    - type: manhattan_pearson
+      value: 72.73812689782592
+    - type: manhattan_spearman
+      value: 67.83610439531277
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts12-sts
+      name: MTEB STS12
+      config: default
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: 75.13970861325006
+    - type: cos_sim_spearman
+      value: 67.5020551515597
+    - type: euclidean_pearson
+      value: 66.33415412418276
+    - type: euclidean_spearman
+      value: 66.82145056673268
+    - type: manhattan_pearson
+      value: 66.55489484006415
+    - type: manhattan_spearman
+      value: 66.95147433279057
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts13-sts
+      name: MTEB STS13
+      config: default
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: 78.85850536483447
+    - type: cos_sim_spearman
+      value: 79.1633350177206
+    - type: euclidean_pearson
+      value: 72.74090561408477
+    - type: euclidean_spearman
+      value: 73.57374448302961
+    - type: manhattan_pearson
+      value: 72.92980654233226
+    - type: manhattan_spearman
+      value: 73.72777155112588
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts14-sts
+      name: MTEB STS14
+      config: default
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: 79.51125593897028
+    - type: cos_sim_spearman
+      value: 74.46048326701329
+    - type: euclidean_pearson
+      value: 70.87726087052985
+    - type: euclidean_spearman
+      value: 67.7721470654411
+    - type: manhattan_pearson
+      value: 71.05892792135637
+    - type: manhattan_spearman
+      value: 67.93472619779037
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts15-sts
+      name: MTEB STS15
+      config: default
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: 83.8299348880489
+    - type: cos_sim_spearman
+      value: 84.47194637929275
+    - type: euclidean_pearson
+      value: 78.68768462480418
+    - type: euclidean_spearman
+      value: 79.80526323901917
+    - type: manhattan_pearson
+      value: 78.6810718151946
+    - type: manhattan_spearman
+      value: 79.7820584821254
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts16-sts
+      name: MTEB STS16
+      config: default
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: 79.99206664843005
+    - type: cos_sim_spearman
+      value: 80.96089203722137
+    - type: euclidean_pearson
+      value: 71.31216213716365
+    - type: euclidean_spearman
+      value: 71.45258140049407
+    - type: manhattan_pearson
+      value: 71.26140340402836
+    - type: manhattan_spearman
+      value: 71.3896894666943
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts17-crosslingual-sts
+      name: MTEB STS17 (en-en)
+      config: en-en
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: 87.35697089594868
+    - type: cos_sim_spearman
+      value: 87.78202647220289
+    - type: euclidean_pearson
+      value: 84.20969668786667
+    - type: euclidean_spearman
+      value: 83.91876425459982
+    - type: manhattan_pearson
+      value: 84.24429755612542
+    - type: manhattan_spearman
+      value: 83.98826315103398
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (en)
+      config: en
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: 69.06962775868384
+    - type: cos_sim_spearman
+      value: 69.34889515492327
+    - type: euclidean_pearson
+      value: 69.28108180412313
+    - type: euclidean_spearman
+      value: 69.6437114853659
+    - type: manhattan_pearson
+      value: 69.39974983734993
+    - type: manhattan_spearman
+      value: 69.69057284482079
+  - task:
+      type: STS
+    dataset:
+      type: mteb/stsbenchmark-sts
+      name: MTEB STSBenchmark
+      config: default
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: 82.42553734213958
+    - type: cos_sim_spearman
+      value: 81.38977341532744
+    - type: euclidean_pearson
+      value: 76.47494587945522
+    - type: euclidean_spearman
+      value: 75.92794860531089
+    - type: manhattan_pearson
+      value: 76.4768777169467
+    - type: manhattan_spearman
+      value: 75.9252673228599
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/scidocs-reranking
+      name: MTEB SciDocsRR
+      config: default
+      split: test
+    metrics:
+    - type: map
+      value: 80.78825425914722
+    - type: mrr
+      value: 94.60017197762296
+  - task:
+      type: Retrieval
+    dataset:
+      type: scifact
+      name: MTEB SciFact
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 60.633
+    - type: map_at_10
+      value: 70.197
+    - type: map_at_100
+      value: 70.758
+    - type: map_at_1000
+      value: 70.765
+    - type: map_at_3
+      value: 67.082
+    - type: map_at_5
+      value: 69.209
+    - type: mrr_at_1
+      value: 63.333
+    - type: mrr_at_10
+      value: 71.17
+    - type: mrr_at_100
+      value: 71.626
+    - type: mrr_at_1000
+      value: 71.633
+    - type: mrr_at_3
+      value: 68.833
+    - type: mrr_at_5
+      value: 70.6
+    - type: ndcg_at_1
+      value: 63.333
+    - type: ndcg_at_10
+      value: 74.697
+    - type: ndcg_at_100
+      value: 76.986
+    - type: ndcg_at_1000
+      value: 77.225
+    - type: ndcg_at_3
+      value: 69.527
+    - type: ndcg_at_5
+      value: 72.816
+    - type: precision_at_1
+      value: 63.333
+    - type: precision_at_10
+      value: 9.9
+    - type: precision_at_100
+      value: 1.103
+    - type: precision_at_1000
+      value: 0.11199999999999999
+    - type: precision_at_3
+      value: 26.889000000000003
+    - type: precision_at_5
+      value: 18.2
+    - type: recall_at_1
+      value: 60.633
+    - type: recall_at_10
+      value: 87.36699999999999
+    - type: recall_at_100
+      value: 97.333
+    - type: recall_at_1000
+      value: 99.333
+    - type: recall_at_3
+      value: 73.656
+    - type: recall_at_5
+      value: 82.083
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/sprintduplicatequestions-pairclassification
+      name: MTEB SprintDuplicateQuestions
+      config: default
+      split: test
+    metrics:
+    - type: cos_sim_accuracy
+      value: 99.76633663366337
+    - type: cos_sim_ap
+      value: 93.84024096781063
+    - type: cos_sim_f1
+      value: 88.08080808080808
+    - type: cos_sim_precision
+      value: 88.9795918367347
+    - type: cos_sim_recall
+      value: 87.2
+    - type: dot_accuracy
+      value: 99.46336633663367
+    - type: dot_ap
+      value: 75.78127156965245
+    - type: dot_f1
+      value: 71.41403865717193
+    - type: dot_precision
+      value: 72.67080745341616
+    - type: dot_recall
+      value: 70.19999999999999
+    - type: euclidean_accuracy
+      value: 99.67524752475248
+    - type: euclidean_ap
+      value: 88.61274955249769
+    - type: euclidean_f1
+      value: 82.30852211434735
+    - type: euclidean_precision
+      value: 89.34426229508196
+    - type: euclidean_recall
+      value: 76.3
+    - type: manhattan_accuracy
+      value: 99.67722772277227
+    - type: manhattan_ap
+      value: 88.77516158012779
+    - type: manhattan_f1
+      value: 82.36536430834212
+    - type: manhattan_precision
+      value: 87.24832214765101
+    - type: manhattan_recall
+      value: 78.0
+    - type: max_accuracy
+      value: 99.76633663366337
+    - type: max_ap
+      value: 93.84024096781063
+    - type: max_f1
+      value: 88.08080808080808
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/stackexchange-clustering
+      name: MTEB StackExchangeClustering
+      config: default
+      split: test
+    metrics:
+    - type: v_measure
+      value: 59.20812266121527
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/stackexchange-clustering-p2p
+      name: MTEB StackExchangeClusteringP2P
+      config: default
+      split: test
+    metrics:
+    - type: v_measure
+      value: 33.954248554638056
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/stackoverflowdupquestions-reranking
+      name: MTEB StackOverflowDupQuestions
+      config: default
+      split: test
+    metrics:
+    - type: map
+      value: 51.52800990025549
+    - type: mrr
+      value: 52.360394915541974
+  - task:
+      type: Summarization
+    dataset:
+      type: mteb/summeval
+      name: MTEB SummEval
+      config: default
+      split: test
+    metrics:
+    - type: cos_sim_pearson
+      value: 24.57438758817976
+    - type: cos_sim_spearman
+      value: 24.747448399760643
+    - type: dot_pearson
+      value: 26.589017584184987
+    - type: dot_spearman
+      value: 25.653620812462783
+  - task:
+      type: Retrieval
+    dataset:
+      type: trec-covid
+      name: MTEB TRECCOVID
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 0.253
+    - type: map_at_10
+      value: 2.1399999999999997
+    - type: map_at_100
+      value: 12.873000000000001
+    - type: map_at_1000
+      value: 31.002000000000002
+    - type: map_at_3
+      value: 0.711
+    - type: map_at_5
+      value: 1.125
+    - type: mrr_at_1
+      value: 96.0
+    - type: mrr_at_10
+      value: 98.0
+    - type: mrr_at_100
+      value: 98.0
+    - type: mrr_at_1000
+      value: 98.0
+    - type: mrr_at_3
+      value: 98.0
+    - type: mrr_at_5
+      value: 98.0
+    - type: ndcg_at_1
+      value: 94.0
+    - type: ndcg_at_10
+      value: 84.881
+    - type: ndcg_at_100
+      value: 64.694
+    - type: ndcg_at_1000
+      value: 56.85
+    - type: ndcg_at_3
+      value: 90.061
+    - type: ndcg_at_5
+      value: 87.155
+    - type: precision_at_1
+      value: 96.0
+    - type: precision_at_10
+      value: 88.8
+    - type: precision_at_100
+      value: 65.7
+    - type: precision_at_1000
+      value: 25.080000000000002
+    - type: precision_at_3
+      value: 92.667
+    - type: precision_at_5
+      value: 90.0
+    - type: recall_at_1
+      value: 0.253
+    - type: recall_at_10
+      value: 2.292
+    - type: recall_at_100
+      value: 15.78
+    - type: recall_at_1000
+      value: 53.015
+    - type: recall_at_3
+      value: 0.7270000000000001
+    - type: recall_at_5
+      value: 1.162
+  - task:
+      type: Retrieval
+    dataset:
+      type: webis-touche2020
+      name: MTEB Touche2020
+      config: default
+      split: test
+    metrics:
+    - type: map_at_1
+      value: 2.116
+    - type: map_at_10
+      value: 9.625
+    - type: map_at_100
+      value: 15.641
+    - type: map_at_1000
+      value: 17.127
+    - type: map_at_3
+      value: 4.316
+    - type: map_at_5
+      value: 6.208
+    - type: mrr_at_1
+      value: 32.653
+    - type: mrr_at_10
+      value: 48.083999999999996
+    - type: mrr_at_100
+      value: 48.631
+    - type: mrr_at_1000
+      value: 48.649
+    - type: mrr_at_3
+      value: 42.857
+    - type: mrr_at_5
+      value: 46.224
+    - type: ndcg_at_1
+      value: 29.592000000000002
+    - type: ndcg_at_10
+      value: 25.430999999999997
+    - type: ndcg_at_100
+      value: 36.344
+    - type: ndcg_at_1000
+      value: 47.676
+    - type: ndcg_at_3
+      value: 26.144000000000002
+    - type: ndcg_at_5
+      value: 26.304
+    - type: precision_at_1
+      value: 32.653
+    - type: precision_at_10
+      value: 24.082
+    - type: precision_at_100
+      value: 7.714
+    - type: precision_at_1000
+      value: 1.5310000000000001
+    - type: precision_at_3
+      value: 26.531
+    - type: precision_at_5
+      value: 26.939
+    - type: recall_at_1
+      value: 2.116
+    - type: recall_at_10
+      value: 16.794
+    - type: recall_at_100
+      value: 47.452
+    - type: recall_at_1000
+      value: 82.312
+    - type: recall_at_3
+      value: 5.306
+    - type: recall_at_5
+      value: 9.306000000000001
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/toxic_conversations_50k
+      name: MTEB ToxicConversationsClassification
+      config: default
+      split: test
+    metrics:
+    - type: accuracy
+      value: 67.709
+    - type: ap
+      value: 13.541535578501716
+    - type: f1
+      value: 52.569619919446794
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/tweet_sentiment_extraction
+      name: MTEB TweetSentimentExtractionClassification
+      config: default
+      split: test
+    metrics:
+    - type: accuracy
+      value: 56.850594227504246
+    - type: f1
+      value: 57.233377364910574
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/twentynewsgroups-clustering
+      name: MTEB TwentyNewsgroupsClustering
+      config: default
+      split: test
+    metrics:
+    - type: v_measure
+      value: 39.463722986090474
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/twittersemeval2015-pairclassification
+      name: MTEB TwitterSemEval2015
+      config: default
+      split: test
+    metrics:
+    - type: cos_sim_accuracy
+      value: 84.09131549144662
+    - type: cos_sim_ap
+      value: 66.86677647503386
+    - type: cos_sim_f1
+      value: 62.94631710362049
+    - type: cos_sim_precision
+      value: 59.73933649289099
+    - type: cos_sim_recall
+      value: 66.51715039577837
+    - type: dot_accuracy
+      value: 80.27656911247541
+    - type: dot_ap
+      value: 54.291720398612085
+    - type: dot_f1
+      value: 54.77150537634409
+    - type: dot_precision
+      value: 47.58660957571039
+    - type: dot_recall
+      value: 64.5118733509235
+    - type: euclidean_accuracy
+      value: 82.76211480002385
+    - type: euclidean_ap
+      value: 62.430397690753296
+    - type: euclidean_f1
+      value: 59.191590539356774
+    - type: euclidean_precision
+      value: 56.296119971435374
+    - type: euclidean_recall
+      value: 62.401055408970976
+    - type: manhattan_accuracy
+      value: 82.7561542588067
+    - type: manhattan_ap
+      value: 62.41882051995577
+    - type: manhattan_f1
+      value: 59.32101002778785
+    - type: manhattan_precision
+      value: 54.71361711611321
+    - type: manhattan_recall
+      value: 64.77572559366754
+    - type: max_accuracy
+      value: 84.09131549144662
+    - type: max_ap
+      value: 66.86677647503386
+    - type: max_f1
+      value: 62.94631710362049
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/twitterurlcorpus-pairclassification
+      name: MTEB TwitterURLCorpus
+      config: default
+      split: test
+    metrics:
+    - type: cos_sim_accuracy
+      value: 88.79574649745798
+    - type: cos_sim_ap
+      value: 85.28960532524223
+    - type: cos_sim_f1
+      value: 77.98460043358001
+    - type: cos_sim_precision
+      value: 75.78090948714224
+    - type: cos_sim_recall
+      value: 80.32029565753002
+    - type: dot_accuracy
+      value: 85.5939767920208
+    - type: dot_ap
+      value: 76.14131706694056
+    - type: dot_f1
+      value: 72.70246298696868
+    - type: dot_precision
+      value: 65.27012127894156
+    - type: dot_recall
+      value: 82.04496458269172
+    - type: euclidean_accuracy
+      value: 86.72332828812046
+    - type: euclidean_ap
+      value: 80.84854809178995
+    - type: euclidean_f1
+      value: 72.47657499809551
+    - type: euclidean_precision
+      value: 71.71717171717171
+    - type: euclidean_recall
+      value: 73.25223283030489
+    - type: manhattan_accuracy
+      value: 86.7563162184189
+    - type: manhattan_ap
+      value: 80.87598895575626
+    - type: manhattan_f1
+      value: 72.54617892068092
+    - type: manhattan_precision
+      value: 68.49268225960881
+    - type: manhattan_recall
+      value: 77.10963966738528
+    - type: max_accuracy
+      value: 88.79574649745798
+    - type: max_ap
+      value: 85.28960532524223
+    - type: max_f1
+      value: 77.98460043358001
 ---
 
 # SGPT-5.8B-weightedmean-msmarco-specb-bitfit