Update README.md

README.md

@@ -5,6 +5,1158 @@ tags:
 - feature-extraction
 - sentence-similarity
 - transformers
+- mteb
+model-index:
+- name: mmlw-e5-large
+  results:
+  - task:
+      type: Clustering
+    dataset:
+      type: PL-MTEB/8tags-clustering
+      name: MTEB 8TagsClustering
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: v_measure
+      value: 30.623921415441725
+  - task:
+      type: Classification
+    dataset:
+      type: PL-MTEB/allegro-reviews
+      name: MTEB AllegroReviews
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 37.683896620278325
+    - type: f1
+      value: 34.19193027014284
+  - task:
+      type: Retrieval
+    dataset:
+      type: arguana-pl
+      name: MTEB ArguAna-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 38.407000000000004
+    - type: map_at_10
+      value: 55.147
+    - type: map_at_100
+      value: 55.757
+    - type: map_at_1000
+      value: 55.761
+    - type: map_at_3
+      value: 51.268
+    - type: map_at_5
+      value: 53.696999999999996
+    - type: mrr_at_1
+      value: 40.043
+    - type: mrr_at_10
+      value: 55.840999999999994
+    - type: mrr_at_100
+      value: 56.459
+    - type: mrr_at_1000
+      value: 56.462999999999994
+    - type: mrr_at_3
+      value: 52.074
+    - type: mrr_at_5
+      value: 54.364999999999995
+    - type: ndcg_at_1
+      value: 38.407000000000004
+    - type: ndcg_at_10
+      value: 63.248000000000005
+    - type: ndcg_at_100
+      value: 65.717
+    - type: ndcg_at_1000
+      value: 65.79
+    - type: ndcg_at_3
+      value: 55.403999999999996
+    - type: ndcg_at_5
+      value: 59.760000000000005
+    - type: precision_at_1
+      value: 38.407000000000004
+    - type: precision_at_10
+      value: 8.862
+    - type: precision_at_100
+      value: 0.991
+    - type: precision_at_1000
+      value: 0.1
+    - type: precision_at_3
+      value: 22.451
+    - type: precision_at_5
+      value: 15.576
+    - type: recall_at_1
+      value: 38.407000000000004
+    - type: recall_at_10
+      value: 88.62
+    - type: recall_at_100
+      value: 99.075
+    - type: recall_at_1000
+      value: 99.57300000000001
+    - type: recall_at_3
+      value: 67.354
+    - type: recall_at_5
+      value: 77.881
+  - task:
+      type: Classification
+    dataset:
+      type: PL-MTEB/cbd
+      name: MTEB CBD
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 66.14999999999999
+    - type: ap
+      value: 21.69513674684204
+    - type: f1
+      value: 56.48142830893528
+  - 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: 89.4
+    - type: cos_sim_ap
+      value: 76.83228768203222
+    - type: cos_sim_f1
+      value: 65.3658536585366
+    - type: cos_sim_precision
+      value: 60.909090909090914
+    - type: cos_sim_recall
+      value: 70.52631578947368
+    - type: dot_accuracy
+      value: 84.1
+    - type: dot_ap
+      value: 57.26072201751864
+    - type: dot_f1
+      value: 62.75395033860045
+    - type: dot_precision
+      value: 54.9407114624506
+    - type: dot_recall
+      value: 73.15789473684211
+    - type: euclidean_accuracy
+      value: 89.4
+    - type: euclidean_ap
+      value: 76.59095263388942
+    - type: euclidean_f1
+      value: 65.21739130434783
+    - type: euclidean_precision
+      value: 60.26785714285714
+    - type: euclidean_recall
+      value: 71.05263157894737
+    - type: manhattan_accuracy
+      value: 89.4
+    - type: manhattan_ap
+      value: 76.58825999753456
+    - type: manhattan_f1
+      value: 64.72019464720195
+    - type: manhattan_precision
+      value: 60.18099547511312
+    - type: manhattan_recall
+      value: 70.0
+    - type: max_accuracy
+      value: 89.4
+    - type: max_ap
+      value: 76.83228768203222
+    - type: max_f1
+      value: 65.3658536585366
+  - 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: 93.73949495291659
+    - type: cos_sim_spearman
+      value: 93.50397366192922
+    - type: euclidean_pearson
+      value: 92.47498888987636
+    - type: euclidean_spearman
+      value: 93.39315936230747
+    - type: manhattan_pearson
+      value: 92.47250250777654
+    - type: manhattan_spearman
+      value: 93.36739690549109
+  - task:
+      type: Retrieval
+    dataset:
+      type: dbpedia-pl
+      name: MTEB DBPedia-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 8.434
+    - type: map_at_10
+      value: 18.424
+    - type: map_at_100
+      value: 26.428
+    - type: map_at_1000
+      value: 28.002
+    - type: map_at_3
+      value: 13.502
+    - type: map_at_5
+      value: 15.577
+    - type: mrr_at_1
+      value: 63.0
+    - type: mrr_at_10
+      value: 72.714
+    - type: mrr_at_100
+      value: 73.021
+    - type: mrr_at_1000
+      value: 73.028
+    - type: mrr_at_3
+      value: 70.75
+    - type: mrr_at_5
+      value: 72.3
+    - type: ndcg_at_1
+      value: 52.75
+    - type: ndcg_at_10
+      value: 39.839999999999996
+    - type: ndcg_at_100
+      value: 44.989000000000004
+    - type: ndcg_at_1000
+      value: 52.532999999999994
+    - type: ndcg_at_3
+      value: 45.198
+    - type: ndcg_at_5
+      value: 42.015
+    - type: precision_at_1
+      value: 63.0
+    - type: precision_at_10
+      value: 31.05
+    - type: precision_at_100
+      value: 10.26
+    - type: precision_at_1000
+      value: 1.9879999999999998
+    - type: precision_at_3
+      value: 48.25
+    - type: precision_at_5
+      value: 40.45
+    - type: recall_at_1
+      value: 8.434
+    - type: recall_at_10
+      value: 24.004
+    - type: recall_at_100
+      value: 51.428
+    - type: recall_at_1000
+      value: 75.712
+    - type: recall_at_3
+      value: 15.015
+    - type: recall_at_5
+      value: 18.282999999999998
+  - task:
+      type: Retrieval
+    dataset:
+      type: fiqa-pl
+      name: MTEB FiQA-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 19.088
+    - type: map_at_10
+      value: 31.818
+    - type: map_at_100
+      value: 33.689
+    - type: map_at_1000
+      value: 33.86
+    - type: map_at_3
+      value: 27.399
+    - type: map_at_5
+      value: 29.945
+    - type: mrr_at_1
+      value: 38.117000000000004
+    - type: mrr_at_10
+      value: 47.668
+    - type: mrr_at_100
+      value: 48.428
+    - type: mrr_at_1000
+      value: 48.475
+    - type: mrr_at_3
+      value: 45.242
+    - type: mrr_at_5
+      value: 46.716
+    - type: ndcg_at_1
+      value: 38.272
+    - type: ndcg_at_10
+      value: 39.903
+    - type: ndcg_at_100
+      value: 46.661
+    - type: ndcg_at_1000
+      value: 49.625
+    - type: ndcg_at_3
+      value: 35.921
+    - type: ndcg_at_5
+      value: 37.558
+    - type: precision_at_1
+      value: 38.272
+    - type: precision_at_10
+      value: 11.358
+    - type: precision_at_100
+      value: 1.8190000000000002
+    - type: precision_at_1000
+      value: 0.23500000000000001
+    - type: precision_at_3
+      value: 24.434
+    - type: precision_at_5
+      value: 18.395
+    - type: recall_at_1
+      value: 19.088
+    - type: recall_at_10
+      value: 47.355999999999995
+    - type: recall_at_100
+      value: 72.451
+    - type: recall_at_1000
+      value: 90.257
+    - type: recall_at_3
+      value: 32.931
+    - type: recall_at_5
+      value: 39.878
+  - task:
+      type: Retrieval
+    dataset:
+      type: hotpotqa-pl
+      name: MTEB HotpotQA-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 39.095
+    - type: map_at_10
+      value: 62.529
+    - type: map_at_100
+      value: 63.425
+    - type: map_at_1000
+      value: 63.483000000000004
+    - type: map_at_3
+      value: 58.887
+    - type: map_at_5
+      value: 61.18599999999999
+    - type: mrr_at_1
+      value: 78.123
+    - type: mrr_at_10
+      value: 84.231
+    - type: mrr_at_100
+      value: 84.408
+    - type: mrr_at_1000
+      value: 84.414
+    - type: mrr_at_3
+      value: 83.286
+    - type: mrr_at_5
+      value: 83.94
+    - type: ndcg_at_1
+      value: 78.19
+    - type: ndcg_at_10
+      value: 70.938
+    - type: ndcg_at_100
+      value: 73.992
+    - type: ndcg_at_1000
+      value: 75.1
+    - type: ndcg_at_3
+      value: 65.863
+    - type: ndcg_at_5
+      value: 68.755
+    - type: precision_at_1
+      value: 78.19
+    - type: precision_at_10
+      value: 14.949000000000002
+    - type: precision_at_100
+      value: 1.733
+    - type: precision_at_1000
+      value: 0.188
+    - type: precision_at_3
+      value: 42.381
+    - type: precision_at_5
+      value: 27.711000000000002
+    - type: recall_at_1
+      value: 39.095
+    - type: recall_at_10
+      value: 74.747
+    - type: recall_at_100
+      value: 86.631
+    - type: recall_at_1000
+      value: 93.923
+    - type: recall_at_3
+      value: 63.571999999999996
+    - type: recall_at_5
+      value: 69.27799999999999
+  - task:
+      type: Retrieval
+    dataset:
+      type: msmarco-pl
+      name: MTEB MSMARCO-PL
+      config: default
+      split: validation
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 19.439999999999998
+    - type: map_at_10
+      value: 30.264000000000003
+    - type: map_at_100
+      value: 31.438
+    - type: map_at_1000
+      value: 31.495
+    - type: map_at_3
+      value: 26.735
+    - type: map_at_5
+      value: 28.716
+    - type: mrr_at_1
+      value: 19.914
+    - type: mrr_at_10
+      value: 30.753999999999998
+    - type: mrr_at_100
+      value: 31.877
+    - type: mrr_at_1000
+      value: 31.929000000000002
+    - type: mrr_at_3
+      value: 27.299
+    - type: mrr_at_5
+      value: 29.254
+    - type: ndcg_at_1
+      value: 20.014000000000003
+    - type: ndcg_at_10
+      value: 36.472
+    - type: ndcg_at_100
+      value: 42.231
+    - type: ndcg_at_1000
+      value: 43.744
+    - type: ndcg_at_3
+      value: 29.268
+    - type: ndcg_at_5
+      value: 32.79
+    - type: precision_at_1
+      value: 20.014000000000003
+    - type: precision_at_10
+      value: 5.814
+    - type: precision_at_100
+      value: 0.8710000000000001
+    - type: precision_at_1000
+      value: 0.1
+    - type: precision_at_3
+      value: 12.426
+    - type: precision_at_5
+      value: 9.238
+    - type: recall_at_1
+      value: 19.439999999999998
+    - type: recall_at_10
+      value: 55.535000000000004
+    - type: recall_at_100
+      value: 82.44399999999999
+    - type: recall_at_1000
+      value: 94.217
+    - type: recall_at_3
+      value: 35.963
+    - type: recall_at_5
+      value: 44.367000000000004
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (pl)
+      config: pl
+      split: test
+      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
+    metrics:
+    - type: accuracy
+      value: 72.01412239408205
+    - type: f1
+      value: 70.04544187503352
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (pl)
+      config: pl
+      split: test
+      revision: 7d571f92784cd94a019292a1f45445077d0ef634
+    metrics:
+    - type: accuracy
+      value: 75.26899798251513
+    - type: f1
+      value: 75.55876166863844
+  - task:
+      type: Retrieval
+    dataset:
+      type: nfcorpus-pl
+      name: MTEB NFCorpus-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 5.772
+    - type: map_at_10
+      value: 12.708
+    - type: map_at_100
+      value: 16.194
+    - type: map_at_1000
+      value: 17.630000000000003
+    - type: map_at_3
+      value: 9.34
+    - type: map_at_5
+      value: 10.741
+    - type: mrr_at_1
+      value: 43.344
+    - type: mrr_at_10
+      value: 53.429
+    - type: mrr_at_100
+      value: 53.88699999999999
+    - type: mrr_at_1000
+      value: 53.925
+    - type: mrr_at_3
+      value: 51.342
+    - type: mrr_at_5
+      value: 52.456
+    - type: ndcg_at_1
+      value: 41.641
+    - type: ndcg_at_10
+      value: 34.028000000000006
+    - type: ndcg_at_100
+      value: 31.613000000000003
+    - type: ndcg_at_1000
+      value: 40.428
+    - type: ndcg_at_3
+      value: 38.991
+    - type: ndcg_at_5
+      value: 36.704
+    - type: precision_at_1
+      value: 43.034
+    - type: precision_at_10
+      value: 25.324999999999996
+    - type: precision_at_100
+      value: 7.889
+    - type: precision_at_1000
+      value: 2.069
+    - type: precision_at_3
+      value: 36.739
+    - type: precision_at_5
+      value: 32.074000000000005
+    - type: recall_at_1
+      value: 5.772
+    - type: recall_at_10
+      value: 16.827
+    - type: recall_at_100
+      value: 32.346000000000004
+    - type: recall_at_1000
+      value: 62.739
+    - type: recall_at_3
+      value: 10.56
+    - type: recall_at_5
+      value: 12.655
+  - task:
+      type: Retrieval
+    dataset:
+      type: nq-pl
+      name: MTEB NQ-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 26.101000000000003
+    - type: map_at_10
+      value: 39.912
+    - type: map_at_100
+      value: 41.037
+    - type: map_at_1000
+      value: 41.077000000000005
+    - type: map_at_3
+      value: 35.691
+    - type: map_at_5
+      value: 38.155
+    - type: mrr_at_1
+      value: 29.403000000000002
+    - type: mrr_at_10
+      value: 42.376999999999995
+    - type: mrr_at_100
+      value: 43.248999999999995
+    - type: mrr_at_1000
+      value: 43.277
+    - type: mrr_at_3
+      value: 38.794000000000004
+    - type: mrr_at_5
+      value: 40.933
+    - type: ndcg_at_1
+      value: 29.519000000000002
+    - type: ndcg_at_10
+      value: 47.33
+    - type: ndcg_at_100
+      value: 52.171
+    - type: ndcg_at_1000
+      value: 53.125
+    - type: ndcg_at_3
+      value: 39.316
+    - type: ndcg_at_5
+      value: 43.457
+    - type: precision_at_1
+      value: 29.519000000000002
+    - type: precision_at_10
+      value: 8.03
+    - type: precision_at_100
+      value: 1.075
+    - type: precision_at_1000
+      value: 0.117
+    - type: precision_at_3
+      value: 18.009
+    - type: precision_at_5
+      value: 13.221
+    - type: recall_at_1
+      value: 26.101000000000003
+    - type: recall_at_10
+      value: 67.50399999999999
+    - type: recall_at_100
+      value: 88.64699999999999
+    - type: recall_at_1000
+      value: 95.771
+    - type: recall_at_3
+      value: 46.669
+    - type: recall_at_5
+      value: 56.24
+  - task:
+      type: Classification
+    dataset:
+      type: laugustyniak/abusive-clauses-pl
+      name: MTEB PAC
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 63.76773819866782
+    - type: ap
+      value: 74.87896817642536
+    - type: f1
+      value: 61.420506092721425
+  - task:
+      type: PairClassification
+    dataset:
+      type: PL-MTEB/ppc-pairclassification
+      name: MTEB PPC
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_accuracy
+      value: 82.1
+    - type: cos_sim_ap
+      value: 91.09417013497443
+    - type: cos_sim_f1
+      value: 84.78437754271766
+    - type: cos_sim_precision
+      value: 83.36
+    - type: cos_sim_recall
+      value: 86.25827814569537
+    - type: dot_accuracy
+      value: 75.9
+    - type: dot_ap
+      value: 86.82680649789796
+    - type: dot_f1
+      value: 80.5379746835443
+    - type: dot_precision
+      value: 77.12121212121212
+    - type: dot_recall
+      value: 84.27152317880795
+    - type: euclidean_accuracy
+      value: 81.6
+    - type: euclidean_ap
+      value: 90.81248760600693
+    - type: euclidean_f1
+      value: 84.35374149659863
+    - type: euclidean_precision
+      value: 86.7132867132867
+    - type: euclidean_recall
+      value: 82.11920529801324
+    - type: manhattan_accuracy
+      value: 81.6
+    - type: manhattan_ap
+      value: 90.81272803548767
+    - type: manhattan_f1
+      value: 84.33530906011855
+    - type: manhattan_precision
+      value: 86.30849220103987
+    - type: manhattan_recall
+      value: 82.45033112582782
+    - type: max_accuracy
+      value: 82.1
+    - type: max_ap
+      value: 91.09417013497443
+    - type: max_f1
+      value: 84.78437754271766
+  - task:
+      type: PairClassification
+    dataset:
+      type: PL-MTEB/psc-pairclassification
+      name: MTEB PSC
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_accuracy
+      value: 98.05194805194806
+    - type: cos_sim_ap
+      value: 99.52709687103496
+    - type: cos_sim_f1
+      value: 96.83257918552036
+    - type: cos_sim_precision
+      value: 95.82089552238806
+    - type: cos_sim_recall
+      value: 97.86585365853658
+    - type: dot_accuracy
+      value: 92.30055658627087
+    - type: dot_ap
+      value: 94.12759311032353
+    - type: dot_f1
+      value: 87.00906344410878
+    - type: dot_precision
+      value: 86.22754491017965
+    - type: dot_recall
+      value: 87.8048780487805
+    - type: euclidean_accuracy
+      value: 98.05194805194806
+    - type: euclidean_ap
+      value: 99.49402675624125
+    - type: euclidean_f1
+      value: 96.8133535660091
+    - type: euclidean_precision
+      value: 96.37462235649546
+    - type: euclidean_recall
+      value: 97.2560975609756
+    - type: manhattan_accuracy
+      value: 98.05194805194806
+    - type: manhattan_ap
+      value: 99.50120505935962
+    - type: manhattan_f1
+      value: 96.8133535660091
+    - type: manhattan_precision
+      value: 96.37462235649546
+    - type: manhattan_recall
+      value: 97.2560975609756
+    - type: max_accuracy
+      value: 98.05194805194806
+    - type: max_ap
+      value: 99.52709687103496
+    - type: max_f1
+      value: 96.83257918552036
+  - task:
+      type: Classification
+    dataset:
+      type: PL-MTEB/polemo2_in
+      name: MTEB PolEmo2.0-IN
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 69.45983379501385
+    - type: f1
+      value: 68.60917948426784
+  - task:
+      type: Classification
+    dataset:
+      type: PL-MTEB/polemo2_out
+      name: MTEB PolEmo2.0-OUT
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 43.13765182186235
+    - type: f1
+      value: 36.15557441785656
+  - task:
+      type: Retrieval
+    dataset:
+      type: quora-pl
+      name: MTEB Quora-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 67.448
+    - type: map_at_10
+      value: 81.566
+    - type: map_at_100
+      value: 82.284
+    - type: map_at_1000
+      value: 82.301
+    - type: map_at_3
+      value: 78.425
+    - type: map_at_5
+      value: 80.43400000000001
+    - type: mrr_at_1
+      value: 77.61
+    - type: mrr_at_10
+      value: 84.467
+    - type: mrr_at_100
+      value: 84.63199999999999
+    - type: mrr_at_1000
+      value: 84.634
+    - type: mrr_at_3
+      value: 83.288
+    - type: mrr_at_5
+      value: 84.095
+    - type: ndcg_at_1
+      value: 77.66
+    - type: ndcg_at_10
+      value: 85.63199999999999
+    - type: ndcg_at_100
+      value: 87.166
+    - type: ndcg_at_1000
+      value: 87.306
+    - type: ndcg_at_3
+      value: 82.32300000000001
+    - type: ndcg_at_5
+      value: 84.22
+    - type: precision_at_1
+      value: 77.66
+    - type: precision_at_10
+      value: 13.136000000000001
+    - type: precision_at_100
+      value: 1.522
+    - type: precision_at_1000
+      value: 0.156
+    - type: precision_at_3
+      value: 36.153
+    - type: precision_at_5
+      value: 23.982
+    - type: recall_at_1
+      value: 67.448
+    - type: recall_at_10
+      value: 93.83200000000001
+    - type: recall_at_100
+      value: 99.212
+    - type: recall_at_1000
+      value: 99.94
+    - type: recall_at_3
+      value: 84.539
+    - type: recall_at_5
+      value: 89.71000000000001
+  - task:
+      type: Retrieval
+    dataset:
+      type: scidocs-pl
+      name: MTEB SCIDOCS-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 4.393
+    - type: map_at_10
+      value: 11.472
+    - type: map_at_100
+      value: 13.584999999999999
+    - type: map_at_1000
+      value: 13.918
+    - type: map_at_3
+      value: 8.212
+    - type: map_at_5
+      value: 9.864
+    - type: mrr_at_1
+      value: 21.7
+    - type: mrr_at_10
+      value: 32.268
+    - type: mrr_at_100
+      value: 33.495000000000005
+    - type: mrr_at_1000
+      value: 33.548
+    - type: mrr_at_3
+      value: 29.15
+    - type: mrr_at_5
+      value: 30.91
+    - type: ndcg_at_1
+      value: 21.6
+    - type: ndcg_at_10
+      value: 19.126
+    - type: ndcg_at_100
+      value: 27.496
+    - type: ndcg_at_1000
+      value: 33.274
+    - type: ndcg_at_3
+      value: 18.196
+    - type: ndcg_at_5
+      value: 15.945
+    - type: precision_at_1
+      value: 21.6
+    - type: precision_at_10
+      value: 9.94
+    - type: precision_at_100
+      value: 2.1999999999999997
+    - type: precision_at_1000
+      value: 0.359
+    - type: precision_at_3
+      value: 17.2
+    - type: precision_at_5
+      value: 14.12
+    - type: recall_at_1
+      value: 4.393
+    - type: recall_at_10
+      value: 20.166999999999998
+    - type: recall_at_100
+      value: 44.678000000000004
+    - type: recall_at_1000
+      value: 72.868
+    - type: recall_at_3
+      value: 10.473
+    - type: recall_at_5
+      value: 14.313
+  - 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: 82.65389319200979
+    - type: cos_sim_ap
+      value: 76.13749398520014
+    - type: cos_sim_f1
+      value: 66.64355062413314
+    - type: cos_sim_precision
+      value: 64.93243243243244
+    - type: cos_sim_recall
+      value: 68.44729344729345
+    - type: dot_accuracy
+      value: 76.0905014268243
+    - type: dot_ap
+      value: 58.058968583382494
+    - type: dot_f1
+      value: 61.181080324657145
+    - type: dot_precision
+      value: 50.391885661595204
+    - type: dot_recall
+      value: 77.84900284900284
+    - type: euclidean_accuracy
+      value: 82.61312678353036
+    - type: euclidean_ap
+      value: 76.10290283033221
+    - type: euclidean_f1
+      value: 66.50782845473111
+    - type: euclidean_precision
+      value: 63.6897001303781
+    - type: euclidean_recall
+      value: 69.58689458689459
+    - type: manhattan_accuracy
+      value: 82.6742763962495
+    - type: manhattan_ap
+      value: 76.12712309700966
+    - type: manhattan_f1
+      value: 66.59700452803902
+    - type: manhattan_precision
+      value: 65.16700749829583
+    - type: manhattan_recall
+      value: 68.09116809116809
+    - type: max_accuracy
+      value: 82.6742763962495
+    - type: max_ap
+      value: 76.13749398520014
+    - type: max_f1
+      value: 66.64355062413314
+  - 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: 81.23898481255246
+    - type: cos_sim_spearman
+      value: 76.0416957474899
+    - type: euclidean_pearson
+      value: 78.96475496102107
+    - type: euclidean_spearman
+      value: 76.07208683063504
+    - type: manhattan_pearson
+      value: 78.92666424673251
+    - type: manhattan_spearman
+      value: 76.04968227583831
+  - 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: 39.13987124398541
+    - type: cos_sim_spearman
+      value: 40.40194528288759
+    - type: euclidean_pearson
+      value: 29.14566247168167
+    - type: euclidean_spearman
+      value: 39.97389932591777
+    - type: manhattan_pearson
+      value: 29.172993134388935
+    - type: manhattan_spearman
+      value: 39.85681935287037
+  - task:
+      type: Retrieval
+    dataset:
+      type: scifact-pl
+      name: MTEB SciFact-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 57.260999999999996
+    - type: map_at_10
+      value: 66.92399999999999
+    - type: map_at_100
+      value: 67.443
+    - type: map_at_1000
+      value: 67.47800000000001
+    - type: map_at_3
+      value: 64.859
+    - type: map_at_5
+      value: 65.71900000000001
+    - type: mrr_at_1
+      value: 60.333000000000006
+    - type: mrr_at_10
+      value: 67.95400000000001
+    - type: mrr_at_100
+      value: 68.42
+    - type: mrr_at_1000
+      value: 68.45
+    - type: mrr_at_3
+      value: 66.444
+    - type: mrr_at_5
+      value: 67.128
+    - type: ndcg_at_1
+      value: 60.333000000000006
+    - type: ndcg_at_10
+      value: 71.209
+    - type: ndcg_at_100
+      value: 73.37
+    - type: ndcg_at_1000
+      value: 74.287
+    - type: ndcg_at_3
+      value: 67.66799999999999
+    - type: ndcg_at_5
+      value: 68.644
+    - type: precision_at_1
+      value: 60.333000000000006
+    - type: precision_at_10
+      value: 9.467
+    - type: precision_at_100
+      value: 1.053
+    - type: precision_at_1000
+      value: 0.11299999999999999
+    - type: precision_at_3
+      value: 26.778000000000002
+    - type: precision_at_5
+      value: 16.933
+    - type: recall_at_1
+      value: 57.260999999999996
+    - type: recall_at_10
+      value: 83.256
+    - type: recall_at_100
+      value: 92.767
+    - type: recall_at_1000
+      value: 100.0
+    - type: recall_at_3
+      value: 72.933
+    - type: recall_at_5
+      value: 75.744
+  - task:
+      type: Retrieval
+    dataset:
+      type: trec-covid-pl
+      name: MTEB TRECCOVID-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 0.22
+    - type: map_at_10
+      value: 1.693
+    - type: map_at_100
+      value: 9.281
+    - type: map_at_1000
+      value: 21.462999999999997
+    - type: map_at_3
+      value: 0.609
+    - type: map_at_5
+      value: 0.9570000000000001
+    - type: mrr_at_1
+      value: 80.0
+    - type: mrr_at_10
+      value: 88.73299999999999
+    - type: mrr_at_100
+      value: 88.73299999999999
+    - type: mrr_at_1000
+      value: 88.73299999999999
+    - type: mrr_at_3
+      value: 88.333
+    - type: mrr_at_5
+      value: 88.73299999999999
+    - type: ndcg_at_1
+      value: 79.0
+    - type: ndcg_at_10
+      value: 71.177
+    - type: ndcg_at_100
+      value: 52.479
+    - type: ndcg_at_1000
+      value: 45.333
+    - type: ndcg_at_3
+      value: 77.48
+    - type: ndcg_at_5
+      value: 76.137
+    - type: precision_at_1
+      value: 82.0
+    - type: precision_at_10
+      value: 74.0
+    - type: precision_at_100
+      value: 53.68000000000001
+    - type: precision_at_1000
+      value: 19.954
+    - type: precision_at_3
+      value: 80.667
+    - type: precision_at_5
+      value: 80.80000000000001
+    - type: recall_at_1
+      value: 0.22
+    - type: recall_at_10
+      value: 1.934
+    - type: recall_at_100
+      value: 12.728
+    - type: recall_at_1000
+      value: 41.869
+    - type: recall_at_3
+      value: 0.637
+    - type: recall_at_5
+      value: 1.042
 language: pl
 license: apache-2.0
 widget: