Update README.md

README.md

@@ -5,6 +5,1158 @@ tags:
 - feature-extraction
 - sentence-similarity
 - transformers
+- mteb
+model-index:
+- name: mmlw-e5-base
+  results:
+  - task:
+      type: Clustering
+    dataset:
+      type: PL-MTEB/8tags-clustering
+      name: MTEB 8TagsClustering
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: v_measure
+      value: 30.249113010261492
+  - task:
+      type: Classification
+    dataset:
+      type: PL-MTEB/allegro-reviews
+      name: MTEB AllegroReviews
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 36.3817097415507
+    - type: f1
+      value: 32.77742158736663
+  - task:
+      type: Retrieval
+    dataset:
+      type: arguana-pl
+      name: MTEB ArguAna-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 32.646
+    - type: map_at_10
+      value: 49.488
+    - type: map_at_100
+      value: 50.190999999999995
+    - type: map_at_1000
+      value: 50.194
+    - type: map_at_3
+      value: 44.749
+    - type: map_at_5
+      value: 47.571999999999996
+    - type: mrr_at_1
+      value: 34.211000000000006
+    - type: mrr_at_10
+      value: 50.112
+    - type: mrr_at_100
+      value: 50.836000000000006
+    - type: mrr_at_1000
+      value: 50.839
+    - type: mrr_at_3
+      value: 45.614
+    - type: mrr_at_5
+      value: 48.242000000000004
+    - type: ndcg_at_1
+      value: 32.646
+    - type: ndcg_at_10
+      value: 58.396
+    - type: ndcg_at_100
+      value: 61.285000000000004
+    - type: ndcg_at_1000
+      value: 61.358999999999995
+    - type: ndcg_at_3
+      value: 48.759
+    - type: ndcg_at_5
+      value: 53.807
+    - type: precision_at_1
+      value: 32.646
+    - type: precision_at_10
+      value: 8.663
+    - type: precision_at_100
+      value: 0.9900000000000001
+    - type: precision_at_1000
+      value: 0.1
+    - type: precision_at_3
+      value: 20.128
+    - type: precision_at_5
+      value: 14.509
+    - type: recall_at_1
+      value: 32.646
+    - type: recall_at_10
+      value: 86.629
+    - type: recall_at_100
+      value: 99.004
+    - type: recall_at_1000
+      value: 99.57300000000001
+    - type: recall_at_3
+      value: 60.38400000000001
+    - type: recall_at_5
+      value: 72.54599999999999
+  - task:
+      type: Classification
+    dataset:
+      type: PL-MTEB/cbd
+      name: MTEB CBD
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 65.53999999999999
+    - type: ap
+      value: 19.75395945379771
+    - type: f1
+      value: 55.00481388401326
+  - task:
+      type: PairClassification
+    dataset:
+      type: PL-MTEB/cdsce-pairclassification
+      name: MTEB CDSC-E
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_accuracy
+      value: 89.5
+    - type: cos_sim_ap
+      value: 77.26879308078568
+    - type: cos_sim_f1
+      value: 65.13157894736842
+    - type: cos_sim_precision
+      value: 86.8421052631579
+    - type: cos_sim_recall
+      value: 52.10526315789473
+    - type: dot_accuracy
+      value: 88.0
+    - type: dot_ap
+      value: 69.17235659054914
+    - type: dot_f1
+      value: 65.71428571428571
+    - type: dot_precision
+      value: 71.875
+    - type: dot_recall
+      value: 60.526315789473685
+    - type: euclidean_accuracy
+      value: 89.5
+    - type: euclidean_ap
+      value: 77.1905400565015
+    - type: euclidean_f1
+      value: 64.91803278688525
+    - type: euclidean_precision
+      value: 86.08695652173914
+    - type: euclidean_recall
+      value: 52.10526315789473
+    - type: manhattan_accuracy
+      value: 89.5
+    - type: manhattan_ap
+      value: 77.19531778873724
+    - type: manhattan_f1
+      value: 64.72491909385113
+    - type: manhattan_precision
+      value: 84.03361344537815
+    - type: manhattan_recall
+      value: 52.63157894736842
+    - type: max_accuracy
+      value: 89.5
+    - type: max_ap
+      value: 77.26879308078568
+    - type: max_f1
+      value: 65.71428571428571
+  - task:
+      type: STS
+    dataset:
+      type: PL-MTEB/cdscr-sts
+      name: MTEB CDSC-R
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_pearson
+      value: 93.18498922236566
+    - type: cos_sim_spearman
+      value: 93.26224500108704
+    - type: euclidean_pearson
+      value: 92.25462061070286
+    - type: euclidean_spearman
+      value: 93.18623989769242
+    - type: manhattan_pearson
+      value: 92.16291103586255
+    - type: manhattan_spearman
+      value: 93.14403078934417
+  - task:
+      type: Retrieval
+    dataset:
+      type: dbpedia-pl
+      name: MTEB DBPedia-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 8.268
+    - type: map_at_10
+      value: 17.391000000000002
+    - type: map_at_100
+      value: 24.266
+    - type: map_at_1000
+      value: 25.844
+    - type: map_at_3
+      value: 12.636
+    - type: map_at_5
+      value: 14.701
+    - type: mrr_at_1
+      value: 62.74999999999999
+    - type: mrr_at_10
+      value: 70.25200000000001
+    - type: mrr_at_100
+      value: 70.601
+    - type: mrr_at_1000
+      value: 70.613
+    - type: mrr_at_3
+      value: 68.083
+    - type: mrr_at_5
+      value: 69.37100000000001
+    - type: ndcg_at_1
+      value: 51.87500000000001
+    - type: ndcg_at_10
+      value: 37.185
+    - type: ndcg_at_100
+      value: 41.949
+    - type: ndcg_at_1000
+      value: 49.523
+    - type: ndcg_at_3
+      value: 41.556
+    - type: ndcg_at_5
+      value: 39.278
+    - type: precision_at_1
+      value: 63.24999999999999
+    - type: precision_at_10
+      value: 29.225
+    - type: precision_at_100
+      value: 9.745
+    - type: precision_at_1000
+      value: 2.046
+    - type: precision_at_3
+      value: 43.833
+    - type: precision_at_5
+      value: 37.9
+    - type: recall_at_1
+      value: 8.268
+    - type: recall_at_10
+      value: 22.542
+    - type: recall_at_100
+      value: 48.154
+    - type: recall_at_1000
+      value: 72.62100000000001
+    - type: recall_at_3
+      value: 13.818
+    - type: recall_at_5
+      value: 17.137
+  - task:
+      type: Retrieval
+    dataset:
+      type: fiqa-pl
+      name: MTEB FiQA-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 16.489
+    - type: map_at_10
+      value: 26.916
+    - type: map_at_100
+      value: 28.582
+    - type: map_at_1000
+      value: 28.774
+    - type: map_at_3
+      value: 23.048
+    - type: map_at_5
+      value: 24.977
+    - type: mrr_at_1
+      value: 33.642
+    - type: mrr_at_10
+      value: 41.987
+    - type: mrr_at_100
+      value: 42.882
+    - type: mrr_at_1000
+      value: 42.93
+    - type: mrr_at_3
+      value: 39.48
+    - type: mrr_at_5
+      value: 40.923
+    - type: ndcg_at_1
+      value: 33.488
+    - type: ndcg_at_10
+      value: 34.528
+    - type: ndcg_at_100
+      value: 41.085
+    - type: ndcg_at_1000
+      value: 44.474000000000004
+    - type: ndcg_at_3
+      value: 30.469
+    - type: ndcg_at_5
+      value: 31.618000000000002
+    - type: precision_at_1
+      value: 33.488
+    - type: precision_at_10
+      value: 9.783999999999999
+    - type: precision_at_100
+      value: 1.6389999999999998
+    - type: precision_at_1000
+      value: 0.22699999999999998
+    - type: precision_at_3
+      value: 20.525
+    - type: precision_at_5
+      value: 15.093
+    - type: recall_at_1
+      value: 16.489
+    - type: recall_at_10
+      value: 42.370000000000005
+    - type: recall_at_100
+      value: 67.183
+    - type: recall_at_1000
+      value: 87.211
+    - type: recall_at_3
+      value: 27.689999999999998
+    - type: recall_at_5
+      value: 33.408
+  - task:
+      type: Retrieval
+    dataset:
+      type: hotpotqa-pl
+      name: MTEB HotpotQA-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 37.373
+    - type: map_at_10
+      value: 57.509
+    - type: map_at_100
+      value: 58.451
+    - type: map_at_1000
+      value: 58.524
+    - type: map_at_3
+      value: 54.064
+    - type: map_at_5
+      value: 56.257999999999996
+    - type: mrr_at_1
+      value: 74.895
+    - type: mrr_at_10
+      value: 81.233
+    - type: mrr_at_100
+      value: 81.461
+    - type: mrr_at_1000
+      value: 81.47
+    - type: mrr_at_3
+      value: 80.124
+    - type: mrr_at_5
+      value: 80.862
+    - type: ndcg_at_1
+      value: 74.747
+    - type: ndcg_at_10
+      value: 66.249
+    - type: ndcg_at_100
+      value: 69.513
+    - type: ndcg_at_1000
+      value: 70.896
+    - type: ndcg_at_3
+      value: 61.312
+    - type: ndcg_at_5
+      value: 64.132
+    - type: precision_at_1
+      value: 74.747
+    - type: precision_at_10
+      value: 13.873
+    - type: precision_at_100
+      value: 1.641
+    - type: precision_at_1000
+      value: 0.182
+    - type: precision_at_3
+      value: 38.987
+    - type: precision_at_5
+      value: 25.621
+    - type: recall_at_1
+      value: 37.373
+    - type: recall_at_10
+      value: 69.365
+    - type: recall_at_100
+      value: 82.039
+    - type: recall_at_1000
+      value: 91.148
+    - type: recall_at_3
+      value: 58.48100000000001
+    - type: recall_at_5
+      value: 64.051
+  - task:
+      type: Retrieval
+    dataset:
+      type: msmarco-pl
+      name: MTEB MSMARCO-PL
+      config: default
+      split: validation
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 16.753999999999998
+    - type: map_at_10
+      value: 26.764
+    - type: map_at_100
+      value: 27.929
+    - type: map_at_1000
+      value: 27.994999999999997
+    - type: map_at_3
+      value: 23.527
+    - type: map_at_5
+      value: 25.343
+    - type: mrr_at_1
+      value: 17.192
+    - type: mrr_at_10
+      value: 27.141
+    - type: mrr_at_100
+      value: 28.269
+    - type: mrr_at_1000
+      value: 28.327999999999996
+    - type: mrr_at_3
+      value: 23.906
+    - type: mrr_at_5
+      value: 25.759999999999998
+    - type: ndcg_at_1
+      value: 17.177999999999997
+    - type: ndcg_at_10
+      value: 32.539
+    - type: ndcg_at_100
+      value: 38.383
+    - type: ndcg_at_1000
+      value: 40.132
+    - type: ndcg_at_3
+      value: 25.884
+    - type: ndcg_at_5
+      value: 29.15
+    - type: precision_at_1
+      value: 17.177999999999997
+    - type: precision_at_10
+      value: 5.268
+    - type: precision_at_100
+      value: 0.823
+    - type: precision_at_1000
+      value: 0.097
+    - type: precision_at_3
+      value: 11.122
+    - type: precision_at_5
+      value: 8.338
+    - type: recall_at_1
+      value: 16.753999999999998
+    - type: recall_at_10
+      value: 50.388
+    - type: recall_at_100
+      value: 77.86999999999999
+    - type: recall_at_1000
+      value: 91.55
+    - type: recall_at_3
+      value: 32.186
+    - type: recall_at_5
+      value: 40.048
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (pl)
+      config: pl
+      split: test
+      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
+    metrics:
+    - type: accuracy
+      value: 70.9280430396772
+    - type: f1
+      value: 68.7099581466286
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (pl)
+      config: pl
+      split: test
+      revision: 7d571f92784cd94a019292a1f45445077d0ef634
+    metrics:
+    - type: accuracy
+      value: 74.76126429051783
+    - type: f1
+      value: 74.72274307018111
+  - task:
+      type: Retrieval
+    dataset:
+      type: nfcorpus-pl
+      name: MTEB NFCorpus-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 5.348
+    - type: map_at_10
+      value: 12.277000000000001
+    - type: map_at_100
+      value: 15.804000000000002
+    - type: map_at_1000
+      value: 17.277
+    - type: map_at_3
+      value: 8.783000000000001
+    - type: map_at_5
+      value: 10.314
+    - type: mrr_at_1
+      value: 43.963
+    - type: mrr_at_10
+      value: 52.459999999999994
+    - type: mrr_at_100
+      value: 53.233
+    - type: mrr_at_1000
+      value: 53.26499999999999
+    - type: mrr_at_3
+      value: 50.464
+    - type: mrr_at_5
+      value: 51.548
+    - type: ndcg_at_1
+      value: 40.711999999999996
+    - type: ndcg_at_10
+      value: 33.709
+    - type: ndcg_at_100
+      value: 31.398
+    - type: ndcg_at_1000
+      value: 40.042
+    - type: ndcg_at_3
+      value: 37.85
+    - type: ndcg_at_5
+      value: 36.260999999999996
+    - type: precision_at_1
+      value: 43.344
+    - type: precision_at_10
+      value: 25.851000000000003
+    - type: precision_at_100
+      value: 8.279
+    - type: precision_at_1000
+      value: 2.085
+    - type: precision_at_3
+      value: 36.326
+    - type: precision_at_5
+      value: 32.074000000000005
+    - type: recall_at_1
+      value: 5.348
+    - type: recall_at_10
+      value: 16.441
+    - type: recall_at_100
+      value: 32.975
+    - type: recall_at_1000
+      value: 64.357
+    - type: recall_at_3
+      value: 9.841999999999999
+    - type: recall_at_5
+      value: 12.463000000000001
+  - task:
+      type: Retrieval
+    dataset:
+      type: nq-pl
+      name: MTEB NQ-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 24.674
+    - type: map_at_10
+      value: 37.672
+    - type: map_at_100
+      value: 38.767
+    - type: map_at_1000
+      value: 38.82
+    - type: map_at_3
+      value: 33.823
+    - type: map_at_5
+      value: 36.063
+    - type: mrr_at_1
+      value: 27.839000000000002
+    - type: mrr_at_10
+      value: 40.129
+    - type: mrr_at_100
+      value: 41.008
+    - type: mrr_at_1000
+      value: 41.048
+    - type: mrr_at_3
+      value: 36.718
+    - type: mrr_at_5
+      value: 38.841
+    - type: ndcg_at_1
+      value: 27.839000000000002
+    - type: ndcg_at_10
+      value: 44.604
+    - type: ndcg_at_100
+      value: 49.51
+    - type: ndcg_at_1000
+      value: 50.841
+    - type: ndcg_at_3
+      value: 37.223
+    - type: ndcg_at_5
+      value: 41.073
+    - type: precision_at_1
+      value: 27.839000000000002
+    - type: precision_at_10
+      value: 7.5
+    - type: precision_at_100
+      value: 1.03
+    - type: precision_at_1000
+      value: 0.116
+    - type: precision_at_3
+      value: 17.005
+    - type: precision_at_5
+      value: 12.399000000000001
+    - type: recall_at_1
+      value: 24.674
+    - type: recall_at_10
+      value: 63.32299999999999
+    - type: recall_at_100
+      value: 85.088
+    - type: recall_at_1000
+      value: 95.143
+    - type: recall_at_3
+      value: 44.157999999999994
+    - type: recall_at_5
+      value: 53.054
+  - task:
+      type: Classification
+    dataset:
+      type: laugustyniak/abusive-clauses-pl
+      name: MTEB PAC
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 64.5033304373009
+    - type: ap
+      value: 75.81507275237081
+    - type: f1
+      value: 62.24617820785985
+  - task:
+      type: PairClassification
+    dataset:
+      type: PL-MTEB/ppc-pairclassification
+      name: MTEB PPC
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_accuracy
+      value: 85.39999999999999
+    - type: cos_sim_ap
+      value: 91.75881977787009
+    - type: cos_sim_f1
+      value: 87.79264214046823
+    - type: cos_sim_precision
+      value: 88.68243243243244
+    - type: cos_sim_recall
+      value: 86.9205298013245
+    - type: dot_accuracy
+      value: 71.0
+    - type: dot_ap
+      value: 82.97829049033108
+    - type: dot_f1
+      value: 78.77055039313797
+    - type: dot_precision
+      value: 69.30817610062893
+    - type: dot_recall
+      value: 91.22516556291392
+    - type: euclidean_accuracy
+      value: 85.2
+    - type: euclidean_ap
+      value: 91.85245521151309
+    - type: euclidean_f1
+      value: 87.64607679465777
+    - type: euclidean_precision
+      value: 88.38383838383838
+    - type: euclidean_recall
+      value: 86.9205298013245
+    - type: manhattan_accuracy
+      value: 85.39999999999999
+    - type: manhattan_ap
+      value: 91.85497100160649
+    - type: manhattan_f1
+      value: 87.77219430485762
+    - type: manhattan_precision
+      value: 88.8135593220339
+    - type: manhattan_recall
+      value: 86.75496688741721
+    - type: max_accuracy
+      value: 85.39999999999999
+    - type: max_ap
+      value: 91.85497100160649
+    - type: max_f1
+      value: 87.79264214046823
+  - task:
+      type: PairClassification
+    dataset:
+      type: PL-MTEB/psc-pairclassification
+      name: MTEB PSC
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_accuracy
+      value: 97.58812615955473
+    - type: cos_sim_ap
+      value: 99.14945370088302
+    - type: cos_sim_f1
+      value: 96.06060606060606
+    - type: cos_sim_precision
+      value: 95.48192771084338
+    - type: cos_sim_recall
+      value: 96.64634146341463
+    - type: dot_accuracy
+      value: 95.17625231910947
+    - type: dot_ap
+      value: 97.05592933601112
+    - type: dot_f1
+      value: 92.14501510574019
+    - type: dot_precision
+      value: 91.31736526946108
+    - type: dot_recall
+      value: 92.98780487804879
+    - type: euclidean_accuracy
+      value: 97.6808905380334
+    - type: euclidean_ap
+      value: 99.18538119402824
+    - type: euclidean_f1
+      value: 96.20637329286798
+    - type: euclidean_precision
+      value: 95.77039274924472
+    - type: euclidean_recall
+      value: 96.64634146341463
+    - type: manhattan_accuracy
+      value: 97.58812615955473
+    - type: manhattan_ap
+      value: 99.17870990853292
+    - type: manhattan_f1
+      value: 96.02446483180427
+    - type: manhattan_precision
+      value: 96.31901840490798
+    - type: manhattan_recall
+      value: 95.73170731707317
+    - type: max_accuracy
+      value: 97.6808905380334
+    - type: max_ap
+      value: 99.18538119402824
+    - type: max_f1
+      value: 96.20637329286798
+  - task:
+      type: Classification
+    dataset:
+      type: PL-MTEB/polemo2_in
+      name: MTEB PolEmo2.0-IN
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 68.69806094182825
+    - type: f1
+      value: 68.0619984307764
+  - task:
+      type: Classification
+    dataset:
+      type: PL-MTEB/polemo2_out
+      name: MTEB PolEmo2.0-OUT
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 35.80971659919028
+    - type: f1
+      value: 31.13081621324864
+  - task:
+      type: Retrieval
+    dataset:
+      type: quora-pl
+      name: MTEB Quora-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 66.149
+    - type: map_at_10
+      value: 80.133
+    - type: map_at_100
+      value: 80.845
+    - type: map_at_1000
+      value: 80.866
+    - type: map_at_3
+      value: 76.983
+    - type: map_at_5
+      value: 78.938
+    - type: mrr_at_1
+      value: 76.09
+    - type: mrr_at_10
+      value: 83.25099999999999
+    - type: mrr_at_100
+      value: 83.422
+    - type: mrr_at_1000
+      value: 83.42500000000001
+    - type: mrr_at_3
+      value: 82.02199999999999
+    - type: mrr_at_5
+      value: 82.831
+    - type: ndcg_at_1
+      value: 76.14999999999999
+    - type: ndcg_at_10
+      value: 84.438
+    - type: ndcg_at_100
+      value: 86.048
+    - type: ndcg_at_1000
+      value: 86.226
+    - type: ndcg_at_3
+      value: 80.97999999999999
+    - type: ndcg_at_5
+      value: 82.856
+    - type: precision_at_1
+      value: 76.14999999999999
+    - type: precision_at_10
+      value: 12.985
+    - type: precision_at_100
+      value: 1.513
+    - type: precision_at_1000
+      value: 0.156
+    - type: precision_at_3
+      value: 35.563
+    - type: precision_at_5
+      value: 23.586
+    - type: recall_at_1
+      value: 66.149
+    - type: recall_at_10
+      value: 93.195
+    - type: recall_at_100
+      value: 98.924
+    - type: recall_at_1000
+      value: 99.885
+    - type: recall_at_3
+      value: 83.439
+    - type: recall_at_5
+      value: 88.575
+  - task:
+      type: Retrieval
+    dataset:
+      type: scidocs-pl
+      name: MTEB SCIDOCS-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 3.688
+    - type: map_at_10
+      value: 10.23
+    - type: map_at_100
+      value: 12.077
+    - type: map_at_1000
+      value: 12.382
+    - type: map_at_3
+      value: 7.149
+    - type: map_at_5
+      value: 8.689
+    - type: mrr_at_1
+      value: 18.2
+    - type: mrr_at_10
+      value: 28.816999999999997
+    - type: mrr_at_100
+      value: 29.982
+    - type: mrr_at_1000
+      value: 30.058
+    - type: mrr_at_3
+      value: 25.983
+    - type: mrr_at_5
+      value: 27.418
+    - type: ndcg_at_1
+      value: 18.2
+    - type: ndcg_at_10
+      value: 17.352999999999998
+    - type: ndcg_at_100
+      value: 24.859
+    - type: ndcg_at_1000
+      value: 30.535
+    - type: ndcg_at_3
+      value: 16.17
+    - type: ndcg_at_5
+      value: 14.235000000000001
+    - type: precision_at_1
+      value: 18.2
+    - type: precision_at_10
+      value: 9.19
+    - type: precision_at_100
+      value: 2.01
+    - type: precision_at_1000
+      value: 0.338
+    - type: precision_at_3
+      value: 15.5
+    - type: precision_at_5
+      value: 12.78
+    - type: recall_at_1
+      value: 3.688
+    - type: recall_at_10
+      value: 18.632
+    - type: recall_at_100
+      value: 40.822
+    - type: recall_at_1000
+      value: 68.552
+    - type: recall_at_3
+      value: 9.423
+    - type: recall_at_5
+      value: 12.943
+  - task:
+      type: PairClassification
+    dataset:
+      type: PL-MTEB/sicke-pl-pairclassification
+      name: MTEB SICK-E-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_accuracy
+      value: 83.12270688952303
+    - type: cos_sim_ap
+      value: 76.4528312253856
+    - type: cos_sim_f1
+      value: 68.69627507163324
+    - type: cos_sim_precision
+      value: 69.0922190201729
+    - type: cos_sim_recall
+      value: 68.30484330484332
+    - type: dot_accuracy
+      value: 79.20913167549939
+    - type: dot_ap
+      value: 65.03147071986633
+    - type: dot_f1
+      value: 62.812160694896846
+    - type: dot_precision
+      value: 50.74561403508772
+    - type: dot_recall
+      value: 82.4074074074074
+    - type: euclidean_accuracy
+      value: 83.16347329800244
+    - type: euclidean_ap
+      value: 76.49405838298205
+    - type: euclidean_f1
+      value: 68.66738120757414
+    - type: euclidean_precision
+      value: 68.88888888888889
+    - type: euclidean_recall
+      value: 68.44729344729345
+    - type: manhattan_accuracy
+      value: 83.16347329800244
+    - type: manhattan_ap
+      value: 76.5080551733795
+    - type: manhattan_f1
+      value: 68.73883529832084
+    - type: manhattan_precision
+      value: 68.9605734767025
+    - type: manhattan_recall
+      value: 68.51851851851852
+    - type: max_accuracy
+      value: 83.16347329800244
+    - type: max_ap
+      value: 76.5080551733795
+    - type: max_f1
+      value: 68.73883529832084
+  - task:
+      type: STS
+    dataset:
+      type: PL-MTEB/sickr-pl-sts
+      name: MTEB SICK-R-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_pearson
+      value: 82.60225159739653
+    - type: cos_sim_spearman
+      value: 76.76667220288542
+    - type: euclidean_pearson
+      value: 80.16302518898615
+    - type: euclidean_spearman
+      value: 76.76131897866455
+    - type: manhattan_pearson
+      value: 80.11881021613914
+    - type: manhattan_spearman
+      value: 76.74246419368048
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (pl)
+      config: pl
+      split: test
+      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
+    metrics:
+    - type: cos_sim_pearson
+      value: 38.2744776092718
+    - type: cos_sim_spearman
+      value: 40.35664941442517
+    - type: euclidean_pearson
+      value: 29.148502128336585
+    - type: euclidean_spearman
+      value: 40.45531563224982
+    - type: manhattan_pearson
+      value: 29.124177399433098
+    - type: manhattan_spearman
+      value: 40.2801387844354
+  - task:
+      type: Retrieval
+    dataset:
+      type: scifact-pl
+      name: MTEB SciFact-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 52.994
+    - type: map_at_10
+      value: 63.612
+    - type: map_at_100
+      value: 64.294
+    - type: map_at_1000
+      value: 64.325
+    - type: map_at_3
+      value: 61.341
+    - type: map_at_5
+      value: 62.366
+    - type: mrr_at_1
+      value: 56.667
+    - type: mrr_at_10
+      value: 65.333
+    - type: mrr_at_100
+      value: 65.89399999999999
+    - type: mrr_at_1000
+      value: 65.91900000000001
+    - type: mrr_at_3
+      value: 63.666999999999994
+    - type: mrr_at_5
+      value: 64.36699999999999
+    - type: ndcg_at_1
+      value: 56.333
+    - type: ndcg_at_10
+      value: 68.292
+    - type: ndcg_at_100
+      value: 71.136
+    - type: ndcg_at_1000
+      value: 71.90100000000001
+    - type: ndcg_at_3
+      value: 64.387
+    - type: ndcg_at_5
+      value: 65.546
+    - type: precision_at_1
+      value: 56.333
+    - type: precision_at_10
+      value: 9.133
+    - type: precision_at_100
+      value: 1.0630000000000002
+    - type: precision_at_1000
+      value: 0.11299999999999999
+    - type: precision_at_3
+      value: 25.556
+    - type: precision_at_5
+      value: 16.267
+    - type: recall_at_1
+      value: 52.994
+    - type: recall_at_10
+      value: 81.178
+    - type: recall_at_100
+      value: 93.767
+    - type: recall_at_1000
+      value: 99.667
+    - type: recall_at_3
+      value: 69.906
+    - type: recall_at_5
+      value: 73.18299999999999
+  - task:
+      type: Retrieval
+    dataset:
+      type: trec-covid-pl
+      name: MTEB TRECCOVID-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 0.231
+    - type: map_at_10
+      value: 1.822
+    - type: map_at_100
+      value: 10.134
+    - type: map_at_1000
+      value: 24.859
+    - type: map_at_3
+      value: 0.615
+    - type: map_at_5
+      value: 0.9939999999999999
+    - type: mrr_at_1
+      value: 84.0
+    - type: mrr_at_10
+      value: 90.4
+    - type: mrr_at_100
+      value: 90.4
+    - type: mrr_at_1000
+      value: 90.4
+    - type: mrr_at_3
+      value: 89.0
+    - type: mrr_at_5
+      value: 90.4
+    - type: ndcg_at_1
+      value: 81.0
+    - type: ndcg_at_10
+      value: 73.333
+    - type: ndcg_at_100
+      value: 55.35099999999999
+    - type: ndcg_at_1000
+      value: 49.875
+    - type: ndcg_at_3
+      value: 76.866
+    - type: ndcg_at_5
+      value: 75.472
+    - type: precision_at_1
+      value: 86.0
+    - type: precision_at_10
+      value: 78.2
+    - type: precision_at_100
+      value: 57.18
+    - type: precision_at_1000
+      value: 22.332
+    - type: precision_at_3
+      value: 82.0
+    - type: precision_at_5
+      value: 81.2
+    - type: recall_at_1
+      value: 0.231
+    - type: recall_at_10
+      value: 2.056
+    - type: recall_at_100
+      value: 13.468
+    - type: recall_at_1000
+      value: 47.038999999999994
+    - type: recall_at_3
+      value: 0.6479999999999999
+    - type: recall_at_5
+      value: 1.088
 language: pl
 license: apache-2.0
 widget: