Update README.md

README.md

@@ -5,6 +5,1158 @@ tags:
 - feature-extraction
 - sentence-similarity
 - transformers
+- mteb
+model-index:
+- name: mmlw-roberta-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: 33.08463724780795
+  - task:
+      type: Classification
+    dataset:
+      type: PL-MTEB/allegro-reviews
+      name: MTEB AllegroReviews
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 40.25844930417495
+    - type: f1
+      value: 35.59685265418916
+  - task:
+      type: Retrieval
+    dataset:
+      type: arguana-pl
+      name: MTEB ArguAna-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 33.073
+    - type: map_at_10
+      value: 50.223
+    - type: map_at_100
+      value: 50.942
+    - type: map_at_1000
+      value: 50.94499999999999
+    - type: map_at_3
+      value: 45.721000000000004
+    - type: map_at_5
+      value: 48.413000000000004
+    - type: mrr_at_1
+      value: 34.424
+    - type: mrr_at_10
+      value: 50.68899999999999
+    - type: mrr_at_100
+      value: 51.437999999999995
+    - type: mrr_at_1000
+      value: 51.441
+    - type: mrr_at_3
+      value: 46.219
+    - type: mrr_at_5
+      value: 48.921
+    - type: ndcg_at_1
+      value: 33.073
+    - type: ndcg_at_10
+      value: 59.021
+    - type: ndcg_at_100
+      value: 61.902
+    - type: ndcg_at_1000
+      value: 61.983999999999995
+    - type: ndcg_at_3
+      value: 49.818
+    - type: ndcg_at_5
+      value: 54.644999999999996
+    - type: precision_at_1
+      value: 33.073
+    - type: precision_at_10
+      value: 8.684
+    - type: precision_at_100
+      value: 0.9900000000000001
+    - type: precision_at_1000
+      value: 0.1
+    - type: precision_at_3
+      value: 20.555
+    - type: precision_at_5
+      value: 14.666
+    - type: recall_at_1
+      value: 33.073
+    - type: recall_at_10
+      value: 86.842
+    - type: recall_at_100
+      value: 99.004
+    - type: recall_at_1000
+      value: 99.644
+    - type: recall_at_3
+      value: 61.663999999999994
+    - type: recall_at_5
+      value: 73.329
+  - task:
+      type: Classification
+    dataset:
+      type: PL-MTEB/cbd
+      name: MTEB CBD
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 68.11
+    - type: ap
+      value: 20.916633959031266
+    - type: f1
+      value: 56.85804802205465
+  - 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: 89.2
+    - type: cos_sim_ap
+      value: 79.1041156765933
+    - type: cos_sim_f1
+      value: 70.0
+    - type: cos_sim_precision
+      value: 74.11764705882354
+    - type: cos_sim_recall
+      value: 66.3157894736842
+    - type: dot_accuracy
+      value: 88.2
+    - type: dot_ap
+      value: 72.57183688228149
+    - type: dot_f1
+      value: 67.16417910447761
+    - type: dot_precision
+      value: 63.67924528301887
+    - type: dot_recall
+      value: 71.05263157894737
+    - type: euclidean_accuracy
+      value: 89.3
+    - type: euclidean_ap
+      value: 79.01345533432428
+    - type: euclidean_f1
+      value: 70.19498607242339
+    - type: euclidean_precision
+      value: 74.55621301775149
+    - type: euclidean_recall
+      value: 66.3157894736842
+    - type: manhattan_accuracy
+      value: 89.3
+    - type: manhattan_ap
+      value: 79.01671381791259
+    - type: manhattan_f1
+      value: 70.0280112044818
+    - type: manhattan_precision
+      value: 74.8502994011976
+    - type: manhattan_recall
+      value: 65.78947368421053
+    - type: max_accuracy
+      value: 89.3
+    - type: max_ap
+      value: 79.1041156765933
+    - type: max_f1
+      value: 70.19498607242339
+  - 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: 91.79559442663039
+    - type: cos_sim_spearman
+      value: 92.5438168962641
+    - type: euclidean_pearson
+      value: 92.02981265332856
+    - type: euclidean_spearman
+      value: 92.5548245733484
+    - type: manhattan_pearson
+      value: 91.95296287979178
+    - type: manhattan_spearman
+      value: 92.50279516120241
+  - task:
+      type: Retrieval
+    dataset:
+      type: dbpedia-pl
+      name: MTEB DBPedia-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 7.829999999999999
+    - type: map_at_10
+      value: 16.616
+    - type: map_at_100
+      value: 23.629
+    - type: map_at_1000
+      value: 25.235999999999997
+    - type: map_at_3
+      value: 12.485
+    - type: map_at_5
+      value: 14.077
+    - type: mrr_at_1
+      value: 61.75000000000001
+    - type: mrr_at_10
+      value: 69.852
+    - type: mrr_at_100
+      value: 70.279
+    - type: mrr_at_1000
+      value: 70.294
+    - type: mrr_at_3
+      value: 68.375
+    - type: mrr_at_5
+      value: 69.187
+    - type: ndcg_at_1
+      value: 49.75
+    - type: ndcg_at_10
+      value: 36.217
+    - type: ndcg_at_100
+      value: 41.235
+    - type: ndcg_at_1000
+      value: 48.952
+    - type: ndcg_at_3
+      value: 41.669
+    - type: ndcg_at_5
+      value: 38.285000000000004
+    - type: precision_at_1
+      value: 61.5
+    - type: precision_at_10
+      value: 28.499999999999996
+    - type: precision_at_100
+      value: 9.572
+    - type: precision_at_1000
+      value: 2.025
+    - type: precision_at_3
+      value: 44.083
+    - type: precision_at_5
+      value: 36.3
+    - type: recall_at_1
+      value: 7.829999999999999
+    - type: recall_at_10
+      value: 21.462999999999997
+    - type: recall_at_100
+      value: 47.095
+    - type: recall_at_1000
+      value: 71.883
+    - type: recall_at_3
+      value: 13.891
+    - type: recall_at_5
+      value: 16.326999999999998
+  - task:
+      type: Retrieval
+    dataset:
+      type: fiqa-pl
+      name: MTEB FiQA-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 16.950000000000003
+    - type: map_at_10
+      value: 27.422
+    - type: map_at_100
+      value: 29.146
+    - type: map_at_1000
+      value: 29.328
+    - type: map_at_3
+      value: 23.735999999999997
+    - type: map_at_5
+      value: 25.671
+    - type: mrr_at_1
+      value: 33.796
+    - type: mrr_at_10
+      value: 42.689
+    - type: mrr_at_100
+      value: 43.522
+    - type: mrr_at_1000
+      value: 43.563
+    - type: mrr_at_3
+      value: 40.226
+    - type: mrr_at_5
+      value: 41.685
+    - type: ndcg_at_1
+      value: 33.642
+    - type: ndcg_at_10
+      value: 35.008
+    - type: ndcg_at_100
+      value: 41.839
+    - type: ndcg_at_1000
+      value: 45.035
+    - type: ndcg_at_3
+      value: 31.358999999999998
+    - type: ndcg_at_5
+      value: 32.377
+    - type: precision_at_1
+      value: 33.642
+    - type: precision_at_10
+      value: 9.937999999999999
+    - type: precision_at_100
+      value: 1.685
+    - type: precision_at_1000
+      value: 0.22699999999999998
+    - type: precision_at_3
+      value: 21.142
+    - type: precision_at_5
+      value: 15.586
+    - type: recall_at_1
+      value: 16.950000000000003
+    - type: recall_at_10
+      value: 42.286
+    - type: recall_at_100
+      value: 68.51899999999999
+    - type: recall_at_1000
+      value: 87.471
+    - type: recall_at_3
+      value: 28.834
+    - type: recall_at_5
+      value: 34.274
+  - task:
+      type: Retrieval
+    dataset:
+      type: hotpotqa-pl
+      name: MTEB HotpotQA-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 37.711
+    - type: map_at_10
+      value: 57.867999999999995
+    - type: map_at_100
+      value: 58.77
+    - type: map_at_1000
+      value: 58.836999999999996
+    - type: map_at_3
+      value: 54.400999999999996
+    - type: map_at_5
+      value: 56.564
+    - type: mrr_at_1
+      value: 75.449
+    - type: mrr_at_10
+      value: 81.575
+    - type: mrr_at_100
+      value: 81.783
+    - type: mrr_at_1000
+      value: 81.792
+    - type: mrr_at_3
+      value: 80.50399999999999
+    - type: mrr_at_5
+      value: 81.172
+    - type: ndcg_at_1
+      value: 75.422
+    - type: ndcg_at_10
+      value: 66.635
+    - type: ndcg_at_100
+      value: 69.85
+    - type: ndcg_at_1000
+      value: 71.179
+    - type: ndcg_at_3
+      value: 61.648
+    - type: ndcg_at_5
+      value: 64.412
+    - type: precision_at_1
+      value: 75.422
+    - type: precision_at_10
+      value: 13.962
+    - type: precision_at_100
+      value: 1.649
+    - type: precision_at_1000
+      value: 0.183
+    - type: precision_at_3
+      value: 39.172000000000004
+    - type: precision_at_5
+      value: 25.691000000000003
+    - type: recall_at_1
+      value: 37.711
+    - type: recall_at_10
+      value: 69.811
+    - type: recall_at_100
+      value: 82.471
+    - type: recall_at_1000
+      value: 91.29
+    - type: recall_at_3
+      value: 58.757999999999996
+    - type: recall_at_5
+      value: 64.227
+  - task:
+      type: Retrieval
+    dataset:
+      type: msmarco-pl
+      name: MTEB MSMARCO-PL
+      config: default
+      split: validation
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 17.033
+    - type: map_at_10
+      value: 27.242
+    - type: map_at_100
+      value: 28.451999999999998
+    - type: map_at_1000
+      value: 28.515
+    - type: map_at_3
+      value: 24.046
+    - type: map_at_5
+      value: 25.840999999999998
+    - type: mrr_at_1
+      value: 17.493
+    - type: mrr_at_10
+      value: 27.67
+    - type: mrr_at_100
+      value: 28.823999999999998
+    - type: mrr_at_1000
+      value: 28.881
+    - type: mrr_at_3
+      value: 24.529999999999998
+    - type: mrr_at_5
+      value: 26.27
+    - type: ndcg_at_1
+      value: 17.479
+    - type: ndcg_at_10
+      value: 33.048
+    - type: ndcg_at_100
+      value: 39.071
+    - type: ndcg_at_1000
+      value: 40.739999999999995
+    - type: ndcg_at_3
+      value: 26.493
+    - type: ndcg_at_5
+      value: 29.701
+    - type: precision_at_1
+      value: 17.479
+    - type: precision_at_10
+      value: 5.324
+    - type: precision_at_100
+      value: 0.8380000000000001
+    - type: precision_at_1000
+      value: 0.098
+    - type: precision_at_3
+      value: 11.408999999999999
+    - type: precision_at_5
+      value: 8.469999999999999
+    - type: recall_at_1
+      value: 17.033
+    - type: recall_at_10
+      value: 50.929
+    - type: recall_at_100
+      value: 79.262
+    - type: recall_at_1000
+      value: 92.239
+    - type: recall_at_3
+      value: 33.06
+    - type: recall_at_5
+      value: 40.747
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (pl)
+      config: pl
+      split: test
+      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
+    metrics:
+    - type: accuracy
+      value: 72.31002017484867
+    - type: f1
+      value: 69.61603671063031
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (pl)
+      config: pl
+      split: test
+      revision: 7d571f92784cd94a019292a1f45445077d0ef634
+    metrics:
+    - type: accuracy
+      value: 75.52790854068594
+    - type: f1
+      value: 75.4053872472259
+  - task:
+      type: Retrieval
+    dataset:
+      type: nfcorpus-pl
+      name: MTEB NFCorpus-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 5.877000000000001
+    - type: map_at_10
+      value: 12.817
+    - type: map_at_100
+      value: 16.247
+    - type: map_at_1000
+      value: 17.683
+    - type: map_at_3
+      value: 9.334000000000001
+    - type: map_at_5
+      value: 10.886999999999999
+    - type: mrr_at_1
+      value: 45.201
+    - type: mrr_at_10
+      value: 52.7
+    - type: mrr_at_100
+      value: 53.425999999999995
+    - type: mrr_at_1000
+      value: 53.461000000000006
+    - type: mrr_at_3
+      value: 50.464
+    - type: mrr_at_5
+      value: 51.827
+    - type: ndcg_at_1
+      value: 41.949999999999996
+    - type: ndcg_at_10
+      value: 34.144999999999996
+    - type: ndcg_at_100
+      value: 31.556
+    - type: ndcg_at_1000
+      value: 40.265
+    - type: ndcg_at_3
+      value: 38.07
+    - type: ndcg_at_5
+      value: 36.571
+    - type: precision_at_1
+      value: 44.272
+    - type: precision_at_10
+      value: 25.697
+    - type: precision_at_100
+      value: 8.077
+    - type: precision_at_1000
+      value: 2.084
+    - type: precision_at_3
+      value: 36.016999999999996
+    - type: precision_at_5
+      value: 31.703
+    - type: recall_at_1
+      value: 5.877000000000001
+    - type: recall_at_10
+      value: 16.986
+    - type: recall_at_100
+      value: 32.719
+    - type: recall_at_1000
+      value: 63.763000000000005
+    - type: recall_at_3
+      value: 10.292
+    - type: recall_at_5
+      value: 12.886000000000001
+  - task:
+      type: Retrieval
+    dataset:
+      type: nq-pl
+      name: MTEB NQ-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 25.476
+    - type: map_at_10
+      value: 38.67
+    - type: map_at_100
+      value: 39.784000000000006
+    - type: map_at_1000
+      value: 39.831
+    - type: map_at_3
+      value: 34.829
+    - type: map_at_5
+      value: 37.025000000000006
+    - type: mrr_at_1
+      value: 28.621000000000002
+    - type: mrr_at_10
+      value: 41.13
+    - type: mrr_at_100
+      value: 42.028
+    - type: mrr_at_1000
+      value: 42.059999999999995
+    - type: mrr_at_3
+      value: 37.877
+    - type: mrr_at_5
+      value: 39.763999999999996
+    - type: ndcg_at_1
+      value: 28.563
+    - type: ndcg_at_10
+      value: 45.654
+    - type: ndcg_at_100
+      value: 50.695
+    - type: ndcg_at_1000
+      value: 51.873999999999995
+    - type: ndcg_at_3
+      value: 38.359
+    - type: ndcg_at_5
+      value: 42.045
+    - type: precision_at_1
+      value: 28.563
+    - type: precision_at_10
+      value: 7.6450000000000005
+    - type: precision_at_100
+      value: 1.052
+    - type: precision_at_1000
+      value: 0.117
+    - type: precision_at_3
+      value: 17.458000000000002
+    - type: precision_at_5
+      value: 12.613
+    - type: recall_at_1
+      value: 25.476
+    - type: recall_at_10
+      value: 64.484
+    - type: recall_at_100
+      value: 86.96199999999999
+    - type: recall_at_1000
+      value: 95.872
+    - type: recall_at_3
+      value: 45.527
+    - type: recall_at_5
+      value: 54.029
+  - task:
+      type: Classification
+    dataset:
+      type: laugustyniak/abusive-clauses-pl
+      name: MTEB PAC
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 65.87315377932232
+    - type: ap
+      value: 76.41966964416534
+    - type: f1
+      value: 63.64417488639012
+  - task:
+      type: PairClassification
+    dataset:
+      type: PL-MTEB/ppc-pairclassification
+      name: MTEB PPC
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_accuracy
+      value: 87.7
+    - type: cos_sim_ap
+      value: 92.81319372631636
+    - type: cos_sim_f1
+      value: 90.04048582995952
+    - type: cos_sim_precision
+      value: 88.11410459587957
+    - type: cos_sim_recall
+      value: 92.05298013245033
+    - type: dot_accuracy
+      value: 75.0
+    - type: dot_ap
+      value: 83.63089957943261
+    - type: dot_f1
+      value: 80.76923076923077
+    - type: dot_precision
+      value: 75.43103448275862
+    - type: dot_recall
+      value: 86.9205298013245
+    - type: euclidean_accuracy
+      value: 87.7
+    - type: euclidean_ap
+      value: 92.94772245932825
+    - type: euclidean_f1
+      value: 90.10458567980692
+    - type: euclidean_precision
+      value: 87.63693270735524
+    - type: euclidean_recall
+      value: 92.71523178807946
+    - type: manhattan_accuracy
+      value: 87.8
+    - type: manhattan_ap
+      value: 92.95330512127123
+    - type: manhattan_f1
+      value: 90.08130081300813
+    - type: manhattan_precision
+      value: 88.49840255591054
+    - type: manhattan_recall
+      value: 91.72185430463577
+    - type: max_accuracy
+      value: 87.8
+    - type: max_ap
+      value: 92.95330512127123
+    - type: max_f1
+      value: 90.10458567980692
+  - task:
+      type: PairClassification
+    dataset:
+      type: PL-MTEB/psc-pairclassification
+      name: MTEB PSC
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_accuracy
+      value: 96.19666048237477
+    - type: cos_sim_ap
+      value: 98.61237969571302
+    - type: cos_sim_f1
+      value: 93.77845220030349
+    - type: cos_sim_precision
+      value: 93.35347432024169
+    - type: cos_sim_recall
+      value: 94.20731707317073
+    - type: dot_accuracy
+      value: 94.89795918367348
+    - type: dot_ap
+      value: 97.02853491357943
+    - type: dot_f1
+      value: 91.85185185185186
+    - type: dot_precision
+      value: 89.33717579250721
+    - type: dot_recall
+      value: 94.51219512195121
+    - type: euclidean_accuracy
+      value: 96.38218923933209
+    - type: euclidean_ap
+      value: 98.58145584134218
+    - type: euclidean_f1
+      value: 94.04580152671755
+    - type: euclidean_precision
+      value: 94.18960244648318
+    - type: euclidean_recall
+      value: 93.90243902439023
+    - type: manhattan_accuracy
+      value: 96.47495361781077
+    - type: manhattan_ap
+      value: 98.6108221024781
+    - type: manhattan_f1
+      value: 94.18960244648318
+    - type: manhattan_precision
+      value: 94.47852760736197
+    - type: manhattan_recall
+      value: 93.90243902439023
+    - type: max_accuracy
+      value: 96.47495361781077
+    - type: max_ap
+      value: 98.61237969571302
+    - type: max_f1
+      value: 94.18960244648318
+  - task:
+      type: Classification
+    dataset:
+      type: PL-MTEB/polemo2_in
+      name: MTEB PolEmo2.0-IN
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 71.73130193905818
+    - type: f1
+      value: 71.17731918813324
+  - task:
+      type: Classification
+    dataset:
+      type: PL-MTEB/polemo2_out
+      name: MTEB PolEmo2.0-OUT
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 46.59919028340081
+    - type: f1
+      value: 37.216392949948954
+  - task:
+      type: Retrieval
+    dataset:
+      type: quora-pl
+      name: MTEB Quora-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 66.134
+    - type: map_at_10
+      value: 80.19
+    - type: map_at_100
+      value: 80.937
+    - type: map_at_1000
+      value: 80.95599999999999
+    - type: map_at_3
+      value: 77.074
+    - type: map_at_5
+      value: 79.054
+    - type: mrr_at_1
+      value: 75.88000000000001
+    - type: mrr_at_10
+      value: 83.226
+    - type: mrr_at_100
+      value: 83.403
+    - type: mrr_at_1000
+      value: 83.406
+    - type: mrr_at_3
+      value: 82.03200000000001
+    - type: mrr_at_5
+      value: 82.843
+    - type: ndcg_at_1
+      value: 75.94
+    - type: ndcg_at_10
+      value: 84.437
+    - type: ndcg_at_100
+      value: 86.13
+    - type: ndcg_at_1000
+      value: 86.29299999999999
+    - type: ndcg_at_3
+      value: 81.07799999999999
+    - type: ndcg_at_5
+      value: 83.0
+    - type: precision_at_1
+      value: 75.94
+    - type: precision_at_10
+      value: 12.953999999999999
+    - type: precision_at_100
+      value: 1.514
+    - type: precision_at_1000
+      value: 0.156
+    - type: precision_at_3
+      value: 35.61
+    - type: precision_at_5
+      value: 23.652
+    - type: recall_at_1
+      value: 66.134
+    - type: recall_at_10
+      value: 92.991
+    - type: recall_at_100
+      value: 99.003
+    - type: recall_at_1000
+      value: 99.86
+    - type: recall_at_3
+      value: 83.643
+    - type: recall_at_5
+      value: 88.81099999999999
+  - task:
+      type: Retrieval
+    dataset:
+      type: scidocs-pl
+      name: MTEB SCIDOCS-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 4.183
+    - type: map_at_10
+      value: 10.626
+    - type: map_at_100
+      value: 12.485
+    - type: map_at_1000
+      value: 12.793
+    - type: map_at_3
+      value: 7.531000000000001
+    - type: map_at_5
+      value: 9.037
+    - type: mrr_at_1
+      value: 20.5
+    - type: mrr_at_10
+      value: 30.175
+    - type: mrr_at_100
+      value: 31.356
+    - type: mrr_at_1000
+      value: 31.421
+    - type: mrr_at_3
+      value: 26.900000000000002
+    - type: mrr_at_5
+      value: 28.689999999999998
+    - type: ndcg_at_1
+      value: 20.599999999999998
+    - type: ndcg_at_10
+      value: 17.84
+    - type: ndcg_at_100
+      value: 25.518
+    - type: ndcg_at_1000
+      value: 31.137999999999998
+    - type: ndcg_at_3
+      value: 16.677
+    - type: ndcg_at_5
+      value: 14.641000000000002
+    - type: precision_at_1
+      value: 20.599999999999998
+    - type: precision_at_10
+      value: 9.3
+    - type: precision_at_100
+      value: 2.048
+    - type: precision_at_1000
+      value: 0.33999999999999997
+    - type: precision_at_3
+      value: 15.533
+    - type: precision_at_5
+      value: 12.839999999999998
+    - type: recall_at_1
+      value: 4.183
+    - type: recall_at_10
+      value: 18.862000000000002
+    - type: recall_at_100
+      value: 41.592
+    - type: recall_at_1000
+      value: 69.037
+    - type: recall_at_3
+      value: 9.443
+    - type: recall_at_5
+      value: 13.028
+  - 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: 86.32286995515696
+    - type: cos_sim_ap
+      value: 82.04302619416443
+    - type: cos_sim_f1
+      value: 74.95572086432874
+    - type: cos_sim_precision
+      value: 74.55954897815363
+    - type: cos_sim_recall
+      value: 75.35612535612536
+    - type: dot_accuracy
+      value: 83.9176518548716
+    - type: dot_ap
+      value: 76.8608733580272
+    - type: dot_f1
+      value: 72.31936654569449
+    - type: dot_precision
+      value: 67.36324523663184
+    - type: dot_recall
+      value: 78.06267806267806
+    - type: euclidean_accuracy
+      value: 86.32286995515696
+    - type: euclidean_ap
+      value: 81.9648986659308
+    - type: euclidean_f1
+      value: 74.93796526054591
+    - type: euclidean_precision
+      value: 74.59421312632321
+    - type: euclidean_recall
+      value: 75.28490028490027
+    - type: manhattan_accuracy
+      value: 86.30248675091724
+    - type: manhattan_ap
+      value: 81.92853980116878
+    - type: manhattan_f1
+      value: 74.80968858131489
+    - type: manhattan_precision
+      value: 72.74562584118439
+    - type: manhattan_recall
+      value: 76.99430199430199
+    - type: max_accuracy
+      value: 86.32286995515696
+    - type: max_ap
+      value: 82.04302619416443
+    - type: max_f1
+      value: 74.95572086432874
+  - 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: 83.07566183637853
+    - type: cos_sim_spearman
+      value: 79.20198022242548
+    - type: euclidean_pearson
+      value: 81.27875473517936
+    - type: euclidean_spearman
+      value: 79.21560102311153
+    - type: manhattan_pearson
+      value: 81.21559474880459
+    - type: manhattan_spearman
+      value: 79.1537846814979
+  - 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: 36.39657573900194
+    - type: cos_sim_spearman
+      value: 40.36403461037013
+    - type: euclidean_pearson
+      value: 29.143416004776316
+    - type: euclidean_spearman
+      value: 40.43197841306375
+    - type: manhattan_pearson
+      value: 29.18632337290767
+    - type: manhattan_spearman
+      value: 40.50563343395481
+  - task:
+      type: Retrieval
+    dataset:
+      type: scifact-pl
+      name: MTEB SciFact-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 49.428
+    - type: map_at_10
+      value: 60.423
+    - type: map_at_100
+      value: 61.037
+    - type: map_at_1000
+      value: 61.065999999999995
+    - type: map_at_3
+      value: 56.989000000000004
+    - type: map_at_5
+      value: 59.041999999999994
+    - type: mrr_at_1
+      value: 52.666999999999994
+    - type: mrr_at_10
+      value: 61.746
+    - type: mrr_at_100
+      value: 62.273
+    - type: mrr_at_1000
+      value: 62.300999999999995
+    - type: mrr_at_3
+      value: 59.278
+    - type: mrr_at_5
+      value: 60.611000000000004
+    - type: ndcg_at_1
+      value: 52.333
+    - type: ndcg_at_10
+      value: 65.75
+    - type: ndcg_at_100
+      value: 68.566
+    - type: ndcg_at_1000
+      value: 69.314
+    - type: ndcg_at_3
+      value: 59.768
+    - type: ndcg_at_5
+      value: 62.808
+    - type: precision_at_1
+      value: 52.333
+    - type: precision_at_10
+      value: 9.167
+    - type: precision_at_100
+      value: 1.0630000000000002
+    - type: precision_at_1000
+      value: 0.11299999999999999
+    - type: precision_at_3
+      value: 23.778
+    - type: precision_at_5
+      value: 16.2
+    - type: recall_at_1
+      value: 49.428
+    - type: recall_at_10
+      value: 81.07799999999999
+    - type: recall_at_100
+      value: 93.93299999999999
+    - type: recall_at_1000
+      value: 99.667
+    - type: recall_at_3
+      value: 65.061
+    - type: recall_at_5
+      value: 72.667
+  - task:
+      type: Retrieval
+    dataset:
+      type: trec-covid-pl
+      name: MTEB TRECCOVID-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 0.22100000000000003
+    - type: map_at_10
+      value: 1.788
+    - type: map_at_100
+      value: 9.937
+    - type: map_at_1000
+      value: 24.762999999999998
+    - type: map_at_3
+      value: 0.579
+    - type: map_at_5
+      value: 0.947
+    - type: mrr_at_1
+      value: 78.0
+    - type: mrr_at_10
+      value: 88.067
+    - type: mrr_at_100
+      value: 88.067
+    - type: mrr_at_1000
+      value: 88.067
+    - type: mrr_at_3
+      value: 87.667
+    - type: mrr_at_5
+      value: 88.067
+    - type: ndcg_at_1
+      value: 76.0
+    - type: ndcg_at_10
+      value: 71.332
+    - type: ndcg_at_100
+      value: 54.80500000000001
+    - type: ndcg_at_1000
+      value: 49.504999999999995
+    - type: ndcg_at_3
+      value: 73.693
+    - type: ndcg_at_5
+      value: 73.733
+    - type: precision_at_1
+      value: 82.0
+    - type: precision_at_10
+      value: 76.8
+    - type: precision_at_100
+      value: 56.68
+    - type: precision_at_1000
+      value: 22.236
+    - type: precision_at_3
+      value: 78.667
+    - type: precision_at_5
+      value: 79.2
+    - type: recall_at_1
+      value: 0.22100000000000003
+    - type: recall_at_10
+      value: 2.033
+    - type: recall_at_100
+      value: 13.431999999999999
+    - type: recall_at_1000
+      value: 46.913
+    - type: recall_at_3
+      value: 0.625
+    - type: recall_at_5
+      value: 1.052
 language: pl
 license: apache-2.0
 widget: