Update README.md

README.md

@@ -5,6 +5,1158 @@ tags:
 - feature-extraction
 - sentence-similarity
 - transformers
+- mteb
+model-index:
+- name: mmlw-e5-small
+  results:
+  - task:
+      type: Clustering
+    dataset:
+      type: PL-MTEB/8tags-clustering
+      name: MTEB 8TagsClustering
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: v_measure
+      value: 31.772224277808153
+  - task:
+      type: Classification
+    dataset:
+      type: PL-MTEB/allegro-reviews
+      name: MTEB AllegroReviews
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 33.03180914512922
+    - type: f1
+      value: 29.800304217426167
+  - task:
+      type: Retrieval
+    dataset:
+      type: arguana-pl
+      name: MTEB ArguAna-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 28.804999999999996
+    - type: map_at_10
+      value: 45.327
+    - type: map_at_100
+      value: 46.17
+    - type: map_at_1000
+      value: 46.177
+    - type: map_at_3
+      value: 40.528999999999996
+    - type: map_at_5
+      value: 43.335
+    - type: mrr_at_1
+      value: 30.299
+    - type: mrr_at_10
+      value: 45.763
+    - type: mrr_at_100
+      value: 46.641
+    - type: mrr_at_1000
+      value: 46.648
+    - type: mrr_at_3
+      value: 41.074
+    - type: mrr_at_5
+      value: 43.836999999999996
+    - type: ndcg_at_1
+      value: 28.804999999999996
+    - type: ndcg_at_10
+      value: 54.308
+    - type: ndcg_at_100
+      value: 57.879000000000005
+    - type: ndcg_at_1000
+      value: 58.048
+    - type: ndcg_at_3
+      value: 44.502
+    - type: ndcg_at_5
+      value: 49.519000000000005
+    - type: precision_at_1
+      value: 28.804999999999996
+    - type: precision_at_10
+      value: 8.286
+    - type: precision_at_100
+      value: 0.984
+    - type: precision_at_1000
+      value: 0.1
+    - type: precision_at_3
+      value: 18.682000000000002
+    - type: precision_at_5
+      value: 13.627
+    - type: recall_at_1
+      value: 28.804999999999996
+    - type: recall_at_10
+      value: 82.85900000000001
+    - type: recall_at_100
+      value: 98.36399999999999
+    - type: recall_at_1000
+      value: 99.644
+    - type: recall_at_3
+      value: 56.04599999999999
+    - type: recall_at_5
+      value: 68.137
+  - task:
+      type: Classification
+    dataset:
+      type: PL-MTEB/cbd
+      name: MTEB CBD
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 64.24
+    - type: ap
+      value: 17.967103105024705
+    - type: f1
+      value: 52.97375416129459
+  - 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: 88.8
+    - type: cos_sim_ap
+      value: 76.68028778789487
+    - type: cos_sim_f1
+      value: 66.82352941176471
+    - type: cos_sim_precision
+      value: 60.42553191489362
+    - type: cos_sim_recall
+      value: 74.73684210526315
+    - type: dot_accuracy
+      value: 88.1
+    - type: dot_ap
+      value: 72.04910086070551
+    - type: dot_f1
+      value: 66.66666666666667
+    - type: dot_precision
+      value: 69.31818181818183
+    - type: dot_recall
+      value: 64.21052631578948
+    - type: euclidean_accuracy
+      value: 88.8
+    - type: euclidean_ap
+      value: 76.63591858340688
+    - type: euclidean_f1
+      value: 67.13286713286713
+    - type: euclidean_precision
+      value: 60.25104602510461
+    - type: euclidean_recall
+      value: 75.78947368421053
+    - type: manhattan_accuracy
+      value: 88.9
+    - type: manhattan_ap
+      value: 76.54552849815124
+    - type: manhattan_f1
+      value: 66.66666666666667
+    - type: manhattan_precision
+      value: 60.51502145922747
+    - type: manhattan_recall
+      value: 74.21052631578947
+    - type: max_accuracy
+      value: 88.9
+    - type: max_ap
+      value: 76.68028778789487
+    - type: max_f1
+      value: 67.13286713286713
+  - 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: 91.64169404461497
+    - type: cos_sim_spearman
+      value: 91.9755161377078
+    - type: euclidean_pearson
+      value: 90.87481478491249
+    - type: euclidean_spearman
+      value: 91.92362666383987
+    - type: manhattan_pearson
+      value: 90.8415510499638
+    - type: manhattan_spearman
+      value: 91.85927127194698
+  - task:
+      type: Retrieval
+    dataset:
+      type: dbpedia-pl
+      name: MTEB DBPedia-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 6.148
+    - type: map_at_10
+      value: 12.870999999999999
+    - type: map_at_100
+      value: 18.04
+    - type: map_at_1000
+      value: 19.286
+    - type: map_at_3
+      value: 9.156
+    - type: map_at_5
+      value: 10.857999999999999
+    - type: mrr_at_1
+      value: 53.25
+    - type: mrr_at_10
+      value: 61.016999999999996
+    - type: mrr_at_100
+      value: 61.48400000000001
+    - type: mrr_at_1000
+      value: 61.507999999999996
+    - type: mrr_at_3
+      value: 58.75
+    - type: mrr_at_5
+      value: 60.375
+    - type: ndcg_at_1
+      value: 41.0
+    - type: ndcg_at_10
+      value: 30.281000000000002
+    - type: ndcg_at_100
+      value: 33.955999999999996
+    - type: ndcg_at_1000
+      value: 40.77
+    - type: ndcg_at_3
+      value: 34.127
+    - type: ndcg_at_5
+      value: 32.274
+    - type: precision_at_1
+      value: 52.5
+    - type: precision_at_10
+      value: 24.525
+    - type: precision_at_100
+      value: 8.125
+    - type: precision_at_1000
+      value: 1.728
+    - type: precision_at_3
+      value: 37.083
+    - type: precision_at_5
+      value: 32.15
+    - type: recall_at_1
+      value: 6.148
+    - type: recall_at_10
+      value: 17.866
+    - type: recall_at_100
+      value: 39.213
+    - type: recall_at_1000
+      value: 61.604000000000006
+    - type: recall_at_3
+      value: 10.084
+    - type: recall_at_5
+      value: 13.333999999999998
+  - task:
+      type: Retrieval
+    dataset:
+      type: fiqa-pl
+      name: MTEB FiQA-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 14.643
+    - type: map_at_10
+      value: 23.166
+    - type: map_at_100
+      value: 24.725
+    - type: map_at_1000
+      value: 24.92
+    - type: map_at_3
+      value: 20.166
+    - type: map_at_5
+      value: 22.003
+    - type: mrr_at_1
+      value: 29.630000000000003
+    - type: mrr_at_10
+      value: 37.632
+    - type: mrr_at_100
+      value: 38.512
+    - type: mrr_at_1000
+      value: 38.578
+    - type: mrr_at_3
+      value: 35.391
+    - type: mrr_at_5
+      value: 36.857
+    - type: ndcg_at_1
+      value: 29.166999999999998
+    - type: ndcg_at_10
+      value: 29.749
+    - type: ndcg_at_100
+      value: 35.983
+    - type: ndcg_at_1000
+      value: 39.817
+    - type: ndcg_at_3
+      value: 26.739
+    - type: ndcg_at_5
+      value: 27.993000000000002
+    - type: precision_at_1
+      value: 29.166999999999998
+    - type: precision_at_10
+      value: 8.333
+    - type: precision_at_100
+      value: 1.448
+    - type: precision_at_1000
+      value: 0.213
+    - type: precision_at_3
+      value: 17.747
+    - type: precision_at_5
+      value: 13.58
+    - type: recall_at_1
+      value: 14.643
+    - type: recall_at_10
+      value: 35.247
+    - type: recall_at_100
+      value: 59.150999999999996
+    - type: recall_at_1000
+      value: 82.565
+    - type: recall_at_3
+      value: 24.006
+    - type: recall_at_5
+      value: 29.383
+  - task:
+      type: Retrieval
+    dataset:
+      type: hotpotqa-pl
+      name: MTEB HotpotQA-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 32.627
+    - type: map_at_10
+      value: 48.041
+    - type: map_at_100
+      value: 49.008
+    - type: map_at_1000
+      value: 49.092999999999996
+    - type: map_at_3
+      value: 44.774
+    - type: map_at_5
+      value: 46.791
+    - type: mrr_at_1
+      value: 65.28
+    - type: mrr_at_10
+      value: 72.53500000000001
+    - type: mrr_at_100
+      value: 72.892
+    - type: mrr_at_1000
+      value: 72.909
+    - type: mrr_at_3
+      value: 71.083
+    - type: mrr_at_5
+      value: 71.985
+    - type: ndcg_at_1
+      value: 65.253
+    - type: ndcg_at_10
+      value: 57.13700000000001
+    - type: ndcg_at_100
+      value: 60.783
+    - type: ndcg_at_1000
+      value: 62.507000000000005
+    - type: ndcg_at_3
+      value: 52.17
+    - type: ndcg_at_5
+      value: 54.896
+    - type: precision_at_1
+      value: 65.253
+    - type: precision_at_10
+      value: 12.088000000000001
+    - type: precision_at_100
+      value: 1.496
+    - type: precision_at_1000
+      value: 0.172
+    - type: precision_at_3
+      value: 32.96
+    - type: precision_at_5
+      value: 21.931
+    - type: recall_at_1
+      value: 32.627
+    - type: recall_at_10
+      value: 60.439
+    - type: recall_at_100
+      value: 74.80799999999999
+    - type: recall_at_1000
+      value: 86.219
+    - type: recall_at_3
+      value: 49.44
+    - type: recall_at_5
+      value: 54.827999999999996
+  - task:
+      type: Retrieval
+    dataset:
+      type: msmarco-pl
+      name: MTEB MSMARCO-PL
+      config: default
+      split: validation
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 13.150999999999998
+    - type: map_at_10
+      value: 21.179000000000002
+    - type: map_at_100
+      value: 22.227
+    - type: map_at_1000
+      value: 22.308
+    - type: map_at_3
+      value: 18.473
+    - type: map_at_5
+      value: 19.942999999999998
+    - type: mrr_at_1
+      value: 13.467
+    - type: mrr_at_10
+      value: 21.471
+    - type: mrr_at_100
+      value: 22.509
+    - type: mrr_at_1000
+      value: 22.585
+    - type: mrr_at_3
+      value: 18.789
+    - type: mrr_at_5
+      value: 20.262
+    - type: ndcg_at_1
+      value: 13.539000000000001
+    - type: ndcg_at_10
+      value: 25.942999999999998
+    - type: ndcg_at_100
+      value: 31.386999999999997
+    - type: ndcg_at_1000
+      value: 33.641
+    - type: ndcg_at_3
+      value: 20.368
+    - type: ndcg_at_5
+      value: 23.003999999999998
+    - type: precision_at_1
+      value: 13.539000000000001
+    - type: precision_at_10
+      value: 4.249
+    - type: precision_at_100
+      value: 0.7040000000000001
+    - type: precision_at_1000
+      value: 0.09
+    - type: precision_at_3
+      value: 8.782
+    - type: precision_at_5
+      value: 6.6049999999999995
+    - type: recall_at_1
+      value: 13.150999999999998
+    - type: recall_at_10
+      value: 40.698
+    - type: recall_at_100
+      value: 66.71000000000001
+    - type: recall_at_1000
+      value: 84.491
+    - type: recall_at_3
+      value: 25.452
+    - type: recall_at_5
+      value: 31.791000000000004
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (pl)
+      config: pl
+      split: test
+      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
+    metrics:
+    - type: accuracy
+      value: 67.3537323470074
+    - type: f1
+      value: 64.67852047603644
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (pl)
+      config: pl
+      split: test
+      revision: 7d571f92784cd94a019292a1f45445077d0ef634
+    metrics:
+    - type: accuracy
+      value: 72.12508406186953
+    - type: f1
+      value: 71.55887309568853
+  - task:
+      type: Retrieval
+    dataset:
+      type: nfcorpus-pl
+      name: MTEB NFCorpus-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 4.18
+    - type: map_at_10
+      value: 9.524000000000001
+    - type: map_at_100
+      value: 12.272
+    - type: map_at_1000
+      value: 13.616
+    - type: map_at_3
+      value: 6.717
+    - type: map_at_5
+      value: 8.172
+    - type: mrr_at_1
+      value: 37.152
+    - type: mrr_at_10
+      value: 45.068000000000005
+    - type: mrr_at_100
+      value: 46.026
+    - type: mrr_at_1000
+      value: 46.085
+    - type: mrr_at_3
+      value: 43.344
+    - type: mrr_at_5
+      value: 44.412
+    - type: ndcg_at_1
+      value: 34.52
+    - type: ndcg_at_10
+      value: 27.604
+    - type: ndcg_at_100
+      value: 26.012999999999998
+    - type: ndcg_at_1000
+      value: 35.272
+    - type: ndcg_at_3
+      value: 31.538
+    - type: ndcg_at_5
+      value: 30.165999999999997
+    - type: precision_at_1
+      value: 36.223
+    - type: precision_at_10
+      value: 21.053
+    - type: precision_at_100
+      value: 7.08
+    - type: precision_at_1000
+      value: 1.9929999999999999
+    - type: precision_at_3
+      value: 30.031000000000002
+    - type: precision_at_5
+      value: 26.997
+    - type: recall_at_1
+      value: 4.18
+    - type: recall_at_10
+      value: 12.901000000000002
+    - type: recall_at_100
+      value: 27.438000000000002
+    - type: recall_at_1000
+      value: 60.768
+    - type: recall_at_3
+      value: 7.492
+    - type: recall_at_5
+      value: 10.05
+  - task:
+      type: Retrieval
+    dataset:
+      type: nq-pl
+      name: MTEB NQ-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 17.965
+    - type: map_at_10
+      value: 28.04
+    - type: map_at_100
+      value: 29.217
+    - type: map_at_1000
+      value: 29.285
+    - type: map_at_3
+      value: 24.818
+    - type: map_at_5
+      value: 26.617
+    - type: mrr_at_1
+      value: 20.22
+    - type: mrr_at_10
+      value: 30.148000000000003
+    - type: mrr_at_100
+      value: 31.137999999999998
+    - type: mrr_at_1000
+      value: 31.19
+    - type: mrr_at_3
+      value: 27.201999999999998
+    - type: mrr_at_5
+      value: 28.884999999999998
+    - type: ndcg_at_1
+      value: 20.365
+    - type: ndcg_at_10
+      value: 33.832
+    - type: ndcg_at_100
+      value: 39.33
+    - type: ndcg_at_1000
+      value: 41.099999999999994
+    - type: ndcg_at_3
+      value: 27.46
+    - type: ndcg_at_5
+      value: 30.584
+    - type: precision_at_1
+      value: 20.365
+    - type: precision_at_10
+      value: 5.849
+    - type: precision_at_100
+      value: 0.8959999999999999
+    - type: precision_at_1000
+      value: 0.107
+    - type: precision_at_3
+      value: 12.64
+    - type: precision_at_5
+      value: 9.334000000000001
+    - type: recall_at_1
+      value: 17.965
+    - type: recall_at_10
+      value: 49.503
+    - type: recall_at_100
+      value: 74.351
+    - type: recall_at_1000
+      value: 87.766
+    - type: recall_at_3
+      value: 32.665
+    - type: recall_at_5
+      value: 39.974
+  - task:
+      type: Classification
+    dataset:
+      type: laugustyniak/abusive-clauses-pl
+      name: MTEB PAC
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 63.11323486823051
+    - type: ap
+      value: 74.53486257377787
+    - type: f1
+      value: 60.631005373417736
+  - task:
+      type: PairClassification
+    dataset:
+      type: PL-MTEB/ppc-pairclassification
+      name: MTEB PPC
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_accuracy
+      value: 80.10000000000001
+    - type: cos_sim_ap
+      value: 89.69526236458292
+    - type: cos_sim_f1
+      value: 83.37468982630274
+    - type: cos_sim_precision
+      value: 83.30578512396694
+    - type: cos_sim_recall
+      value: 83.44370860927152
+    - type: dot_accuracy
+      value: 77.8
+    - type: dot_ap
+      value: 87.72366051496104
+    - type: dot_f1
+      value: 82.83752860411899
+    - type: dot_precision
+      value: 76.80339462517681
+    - type: dot_recall
+      value: 89.90066225165563
+    - type: euclidean_accuracy
+      value: 80.10000000000001
+    - type: euclidean_ap
+      value: 89.61317191870039
+    - type: euclidean_f1
+      value: 83.40214698596202
+    - type: euclidean_precision
+      value: 83.19604612850083
+    - type: euclidean_recall
+      value: 83.6092715231788
+    - type: manhattan_accuracy
+      value: 79.60000000000001
+    - type: manhattan_ap
+      value: 89.48363786968471
+    - type: manhattan_f1
+      value: 82.96296296296296
+    - type: manhattan_precision
+      value: 82.48772504091653
+    - type: manhattan_recall
+      value: 83.44370860927152
+    - type: max_accuracy
+      value: 80.10000000000001
+    - type: max_ap
+      value: 89.69526236458292
+    - type: max_f1
+      value: 83.40214698596202
+  - task:
+      type: PairClassification
+    dataset:
+      type: PL-MTEB/psc-pairclassification
+      name: MTEB PSC
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_accuracy
+      value: 96.93877551020408
+    - type: cos_sim_ap
+      value: 98.86489482248999
+    - type: cos_sim_f1
+      value: 95.11111111111113
+    - type: cos_sim_precision
+      value: 92.507204610951
+    - type: cos_sim_recall
+      value: 97.86585365853658
+    - type: dot_accuracy
+      value: 95.73283858998145
+    - type: dot_ap
+      value: 97.8261652492545
+    - type: dot_f1
+      value: 93.21533923303835
+    - type: dot_precision
+      value: 90.28571428571428
+    - type: dot_recall
+      value: 96.34146341463415
+    - type: euclidean_accuracy
+      value: 96.93877551020408
+    - type: euclidean_ap
+      value: 98.84837797066623
+    - type: euclidean_f1
+      value: 95.11111111111113
+    - type: euclidean_precision
+      value: 92.507204610951
+    - type: euclidean_recall
+      value: 97.86585365853658
+    - type: manhattan_accuracy
+      value: 96.84601113172542
+    - type: manhattan_ap
+      value: 98.78659090944161
+    - type: manhattan_f1
+      value: 94.9404761904762
+    - type: manhattan_precision
+      value: 92.73255813953489
+    - type: manhattan_recall
+      value: 97.2560975609756
+    - type: max_accuracy
+      value: 96.93877551020408
+    - type: max_ap
+      value: 98.86489482248999
+    - type: max_f1
+      value: 95.11111111111113
+  - task:
+      type: Classification
+    dataset:
+      type: PL-MTEB/polemo2_in
+      name: MTEB PolEmo2.0-IN
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 63.961218836565095
+    - type: f1
+      value: 64.3979989243291
+  - task:
+      type: Classification
+    dataset:
+      type: PL-MTEB/polemo2_out
+      name: MTEB PolEmo2.0-OUT
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 40.32388663967612
+    - type: f1
+      value: 32.339117999015755
+  - task:
+      type: Retrieval
+    dataset:
+      type: quora-pl
+      name: MTEB Quora-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 62.757
+    - type: map_at_10
+      value: 76.55999999999999
+    - type: map_at_100
+      value: 77.328
+    - type: map_at_1000
+      value: 77.35499999999999
+    - type: map_at_3
+      value: 73.288
+    - type: map_at_5
+      value: 75.25500000000001
+    - type: mrr_at_1
+      value: 72.28
+    - type: mrr_at_10
+      value: 79.879
+    - type: mrr_at_100
+      value: 80.121
+    - type: mrr_at_1000
+      value: 80.12700000000001
+    - type: mrr_at_3
+      value: 78.40700000000001
+    - type: mrr_at_5
+      value: 79.357
+    - type: ndcg_at_1
+      value: 72.33000000000001
+    - type: ndcg_at_10
+      value: 81.151
+    - type: ndcg_at_100
+      value: 83.107
+    - type: ndcg_at_1000
+      value: 83.397
+    - type: ndcg_at_3
+      value: 77.3
+    - type: ndcg_at_5
+      value: 79.307
+    - type: precision_at_1
+      value: 72.33000000000001
+    - type: precision_at_10
+      value: 12.587000000000002
+    - type: precision_at_100
+      value: 1.488
+    - type: precision_at_1000
+      value: 0.155
+    - type: precision_at_3
+      value: 33.943
+    - type: precision_at_5
+      value: 22.61
+    - type: recall_at_1
+      value: 62.757
+    - type: recall_at_10
+      value: 90.616
+    - type: recall_at_100
+      value: 97.905
+    - type: recall_at_1000
+      value: 99.618
+    - type: recall_at_3
+      value: 79.928
+    - type: recall_at_5
+      value: 85.30499999999999
+  - task:
+      type: Retrieval
+    dataset:
+      type: scidocs-pl
+      name: MTEB SCIDOCS-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 3.313
+    - type: map_at_10
+      value: 8.559999999999999
+    - type: map_at_100
+      value: 10.177999999999999
+    - type: map_at_1000
+      value: 10.459999999999999
+    - type: map_at_3
+      value: 6.094
+    - type: map_at_5
+      value: 7.323
+    - type: mrr_at_1
+      value: 16.3
+    - type: mrr_at_10
+      value: 25.579
+    - type: mrr_at_100
+      value: 26.717000000000002
+    - type: mrr_at_1000
+      value: 26.799
+    - type: mrr_at_3
+      value: 22.583000000000002
+    - type: mrr_at_5
+      value: 24.298000000000002
+    - type: ndcg_at_1
+      value: 16.3
+    - type: ndcg_at_10
+      value: 14.789
+    - type: ndcg_at_100
+      value: 21.731
+    - type: ndcg_at_1000
+      value: 27.261999999999997
+    - type: ndcg_at_3
+      value: 13.74
+    - type: ndcg_at_5
+      value: 12.199
+    - type: precision_at_1
+      value: 16.3
+    - type: precision_at_10
+      value: 7.779999999999999
+    - type: precision_at_100
+      value: 1.79
+    - type: precision_at_1000
+      value: 0.313
+    - type: precision_at_3
+      value: 12.933
+    - type: precision_at_5
+      value: 10.86
+    - type: recall_at_1
+      value: 3.313
+    - type: recall_at_10
+      value: 15.772
+    - type: recall_at_100
+      value: 36.392
+    - type: recall_at_1000
+      value: 63.525
+    - type: recall_at_3
+      value: 7.863
+    - type: recall_at_5
+      value: 11.003
+  - 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: 81.7977986139421
+    - type: cos_sim_ap
+      value: 73.21294750778902
+    - type: cos_sim_f1
+      value: 66.57391304347826
+    - type: cos_sim_precision
+      value: 65.05778382053025
+    - type: cos_sim_recall
+      value: 68.16239316239316
+    - type: dot_accuracy
+      value: 78.67916836526702
+    - type: dot_ap
+      value: 63.61943815978181
+    - type: dot_f1
+      value: 62.45014245014245
+    - type: dot_precision
+      value: 52.04178537511871
+    - type: dot_recall
+      value: 78.06267806267806
+    - type: euclidean_accuracy
+      value: 81.7774154097024
+    - type: euclidean_ap
+      value: 73.25053778387148
+    - type: euclidean_f1
+      value: 66.55064392620953
+    - type: euclidean_precision
+      value: 65.0782845473111
+    - type: euclidean_recall
+      value: 68.09116809116809
+    - type: manhattan_accuracy
+      value: 81.63473298002447
+    - type: manhattan_ap
+      value: 72.99781945530033
+    - type: manhattan_f1
+      value: 66.3623595505618
+    - type: manhattan_precision
+      value: 65.4432132963989
+    - type: manhattan_recall
+      value: 67.3076923076923
+    - type: max_accuracy
+      value: 81.7977986139421
+    - type: max_ap
+      value: 73.25053778387148
+    - type: max_f1
+      value: 66.57391304347826
+  - 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: 79.62332929388755
+    - type: cos_sim_spearman
+      value: 73.70598290849304
+    - type: euclidean_pearson
+      value: 77.3603286710006
+    - type: euclidean_spearman
+      value: 73.74420279933932
+    - type: manhattan_pearson
+      value: 77.12735032552482
+    - type: manhattan_spearman
+      value: 73.53014836690127
+  - 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: 37.696942928686724
+    - type: cos_sim_spearman
+      value: 40.6271445245692
+    - type: euclidean_pearson
+      value: 30.212734461370832
+    - type: euclidean_spearman
+      value: 40.66643376699638
+    - type: manhattan_pearson
+      value: 29.90223716230108
+    - type: manhattan_spearman
+      value: 40.35576319091178
+  - task:
+      type: Retrieval
+    dataset:
+      type: scifact-pl
+      name: MTEB SciFact-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 43.528
+    - type: map_at_10
+      value: 53.290000000000006
+    - type: map_at_100
+      value: 54.342
+    - type: map_at_1000
+      value: 54.376999999999995
+    - type: map_at_3
+      value: 50.651999999999994
+    - type: map_at_5
+      value: 52.248000000000005
+    - type: mrr_at_1
+      value: 46.666999999999994
+    - type: mrr_at_10
+      value: 55.286
+    - type: mrr_at_100
+      value: 56.094
+    - type: mrr_at_1000
+      value: 56.125
+    - type: mrr_at_3
+      value: 53.222
+    - type: mrr_at_5
+      value: 54.339000000000006
+    - type: ndcg_at_1
+      value: 46.0
+    - type: ndcg_at_10
+      value: 58.142
+    - type: ndcg_at_100
+      value: 62.426
+    - type: ndcg_at_1000
+      value: 63.395999999999994
+    - type: ndcg_at_3
+      value: 53.53
+    - type: ndcg_at_5
+      value: 55.842000000000006
+    - type: precision_at_1
+      value: 46.0
+    - type: precision_at_10
+      value: 7.9670000000000005
+    - type: precision_at_100
+      value: 1.023
+    - type: precision_at_1000
+      value: 0.11100000000000002
+    - type: precision_at_3
+      value: 21.444
+    - type: precision_at_5
+      value: 14.333000000000002
+    - type: recall_at_1
+      value: 43.528
+    - type: recall_at_10
+      value: 71.511
+    - type: recall_at_100
+      value: 89.93299999999999
+    - type: recall_at_1000
+      value: 97.667
+    - type: recall_at_3
+      value: 59.067
+    - type: recall_at_5
+      value: 64.789
+  - task:
+      type: Retrieval
+    dataset:
+      type: trec-covid-pl
+      name: MTEB TRECCOVID-PL
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 0.22699999999999998
+    - type: map_at_10
+      value: 1.3379999999999999
+    - type: map_at_100
+      value: 6.965000000000001
+    - type: map_at_1000
+      value: 17.135
+    - type: map_at_3
+      value: 0.53
+    - type: map_at_5
+      value: 0.799
+    - type: mrr_at_1
+      value: 84.0
+    - type: mrr_at_10
+      value: 88.083
+    - type: mrr_at_100
+      value: 88.432
+    - type: mrr_at_1000
+      value: 88.432
+    - type: mrr_at_3
+      value: 87.333
+    - type: mrr_at_5
+      value: 87.833
+    - type: ndcg_at_1
+      value: 76.0
+    - type: ndcg_at_10
+      value: 58.199
+    - type: ndcg_at_100
+      value: 43.230000000000004
+    - type: ndcg_at_1000
+      value: 39.751
+    - type: ndcg_at_3
+      value: 63.743
+    - type: ndcg_at_5
+      value: 60.42999999999999
+    - type: precision_at_1
+      value: 84.0
+    - type: precision_at_10
+      value: 62.0
+    - type: precision_at_100
+      value: 44.519999999999996
+    - type: precision_at_1000
+      value: 17.746000000000002
+    - type: precision_at_3
+      value: 67.333
+    - type: precision_at_5
+      value: 63.2
+    - type: recall_at_1
+      value: 0.22699999999999998
+    - type: recall_at_10
+      value: 1.627
+    - type: recall_at_100
+      value: 10.600999999999999
+    - type: recall_at_1000
+      value: 37.532
+    - type: recall_at_3
+      value: 0.547
+    - type: recall_at_5
+      value: 0.864
 language: pl
 license: apache-2.0
 widget: