---
language: en
library_name: sentence-transformers
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- sentence-similarity
- feature-extraction
- mteb
model-index:
- name: FAB-Ramy-v1
  results:
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      name: MTEB ArguAna (default)
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
      split: test
      type: mteb/arguana
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    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB AskUbuntuDupQuestions (default)
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
      split: test
      type: mteb/askubuntudupquestions-reranking
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    task:
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      name: MTEB BIOSSES (default)
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
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      type: mteb/biosses-sts
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    task:
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  - dataset:
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      revision: f46a197baaae43b4f621051089b82a364682dfeb
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  - dataset:
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  - dataset:
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      type: Retrieval
  - dataset:
      config: default
      name: MTEB SCIDOCS (default)
      revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88
      split: test
      type: mteb/scidocs
    metrics:
    - type: main_score
      value: 19.444
    - type: map_at_1
      value: 4.502
    - type: map_at_10
      value: 11.39
    - type: map_at_100
      value: 13.578000000000001
    - type: map_at_1000
      value: 13.94
    - type: map_at_20
      value: 12.406
    - type: map_at_3
      value: 8.045
    - type: map_at_5
      value: 9.618
    - type: mrr_at_1
      value: 22.1
    - type: mrr_at_10
      value: 33.15134920634915
    - type: mrr_at_100
      value: 34.311313761933675
    - type: mrr_at_1000
      value: 34.365241364096406
    - type: mrr_at_20
      value: 33.84369535607144
    - type: mrr_at_3
      value: 29.833333333333307
    - type: mrr_at_5
      value: 31.858333333333285
    - type: nauc_map_at_1000_diff1
      value: 13.717495184216915
    - type: nauc_map_at_1000_max
      value: 29.011198411487488
    - type: nauc_map_at_1000_std
      value: 26.84659672785883
    - type: nauc_map_at_100_diff1
      value: 13.679043690905408
    - type: nauc_map_at_100_max
      value: 28.9642395394068
    - type: nauc_map_at_100_std
      value: 26.605777722314194
    - type: nauc_map_at_10_diff1
      value: 13.368432894934296
    - type: nauc_map_at_10_max
      value: 27.110702917972063
    - type: nauc_map_at_10_std
      value: 22.94925796594505
    - type: nauc_map_at_1_diff1
      value: 18.759513595847864
    - type: nauc_map_at_1_max
      value: 22.187646906334894
    - type: nauc_map_at_1_std
      value: 14.187153951336118
    - type: nauc_map_at_20_diff1
      value: 13.361125473032986
    - type: nauc_map_at_20_max
      value: 28.538396642596943
    - type: nauc_map_at_20_std
      value: 25.017431011630997
    - type: nauc_map_at_3_diff1
      value: 13.603088771503444
    - type: nauc_map_at_3_max
      value: 23.440488325894666
    - type: nauc_map_at_3_std
      value: 17.568789088634574
    - type: nauc_map_at_5_diff1
      value: 12.768724297417263
    - type: nauc_map_at_5_max
      value: 25.721011116775156
    - type: nauc_map_at_5_std
      value: 20.617210938970036
    - type: nauc_mrr_at_1000_diff1
      value: 15.975239485567325
    - type: nauc_mrr_at_1000_max
      value: 23.068935178375263
    - type: nauc_mrr_at_1000_std
      value: 18.95600665491368
    - type: nauc_mrr_at_100_diff1
      value: 15.995091585658036
    - type: nauc_mrr_at_100_max
      value: 23.09377838760513
    - type: nauc_mrr_at_100_std
      value: 18.98954041920917
    - type: nauc_mrr_at_10_diff1
      value: 15.703076780120998
    - type: nauc_mrr_at_10_max
      value: 23.00082757189908
    - type: nauc_mrr_at_10_std
      value: 18.822303815995404
    - type: nauc_mrr_at_1_diff1
      value: 18.695550347655747
    - type: nauc_mrr_at_1_max
      value: 22.409410202761716
    - type: nauc_mrr_at_1_std
      value: 14.681107473163898
    - type: nauc_mrr_at_20_diff1
      value: 16.020132977247496
    - type: nauc_mrr_at_20_max
      value: 23.185061420757872
    - type: nauc_mrr_at_20_std
      value: 19.091524076258263
    - type: nauc_mrr_at_3_diff1
      value: 15.325035100345696
    - type: nauc_mrr_at_3_max
      value: 21.296388498885033
    - type: nauc_mrr_at_3_std
      value: 16.941043217669318
    - type: nauc_mrr_at_5_diff1
      value: 15.299688685606213
    - type: nauc_mrr_at_5_max
      value: 22.802086268780577
    - type: nauc_mrr_at_5_std
      value: 18.71801414862292
    - type: nauc_ndcg_at_1000_diff1
      value: 14.985183012627648
    - type: nauc_ndcg_at_1000_max
      value: 29.786848759154704
    - type: nauc_ndcg_at_1000_std
      value: 31.986231381446856
    - type: nauc_ndcg_at_100_diff1
      value: 15.043201418745348
    - type: nauc_ndcg_at_100_max
      value: 29.836151485650642
    - type: nauc_ndcg_at_100_std
      value: 31.49403639682868
    - type: nauc_ndcg_at_10_diff1
      value: 13.716366599689692
    - type: nauc_ndcg_at_10_max
      value: 26.7111463810652
    - type: nauc_ndcg_at_10_std
      value: 23.975660743984246
    - type: nauc_ndcg_at_1_diff1
      value: 18.695550347655747
    - type: nauc_ndcg_at_1_max
      value: 22.409410202761716
    - type: nauc_ndcg_at_1_std
      value: 14.681107473163898
    - type: nauc_ndcg_at_20_diff1
      value: 14.328037163111377
    - type: nauc_ndcg_at_20_max
      value: 28.735399499681684
    - type: nauc_ndcg_at_20_std
      value: 26.880344773773658
    - type: nauc_ndcg_at_3_diff1
      value: 13.269935726177302
    - type: nauc_ndcg_at_3_max
      value: 22.4350143067517
    - type: nauc_ndcg_at_3_std
      value: 18.38139918313516
    - type: nauc_ndcg_at_5_diff1
      value: 12.685257044798275
    - type: nauc_ndcg_at_5_max
      value: 25.19564166647925
    - type: nauc_ndcg_at_5_std
      value: 21.542434552277186
    - type: nauc_precision_at_1000_diff1
      value: 11.036824823724826
    - type: nauc_precision_at_1000_max
      value: 25.940844812474605
    - type: nauc_precision_at_1000_std
      value: 40.72801957013718
    - type: nauc_precision_at_100_diff1
      value: 12.787108654755427
    - type: nauc_precision_at_100_max
      value: 28.885658620100905
    - type: nauc_precision_at_100_std
      value: 39.858021500648256
    - type: nauc_precision_at_10_diff1
      value: 11.814983150826238
    - type: nauc_precision_at_10_max
      value: 27.255512643546137
    - type: nauc_precision_at_10_std
      value: 27.385188725103106
    - type: nauc_precision_at_1_diff1
      value: 18.695550347655747
    - type: nauc_precision_at_1_max
      value: 22.409410202761716
    - type: nauc_precision_at_1_std
      value: 14.681107473163898
    - type: nauc_precision_at_20_diff1
      value: 12.399277896733532
    - type: nauc_precision_at_20_max
      value: 29.8411274531922
    - type: nauc_precision_at_20_std
      value: 31.750340970872408
    - type: nauc_precision_at_3_diff1
      value: 10.783342570370754
    - type: nauc_precision_at_3_max
      value: 21.822145650943643
    - type: nauc_precision_at_3_std
      value: 19.88278575673906
    - type: nauc_precision_at_5_diff1
      value: 9.961029826782028
    - type: nauc_precision_at_5_max
      value: 26.109948621950217
    - type: nauc_precision_at_5_std
      value: 24.767740060380532
    - type: nauc_recall_at_1000_diff1
      value: 10.791755272965629
    - type: nauc_recall_at_1000_max
      value: 26.66377944006043
    - type: nauc_recall_at_1000_std
      value: 42.670133048407614
    - type: nauc_recall_at_100_diff1
      value: 12.731152346249097
    - type: nauc_recall_at_100_max
      value: 28.86663011256839
    - type: nauc_recall_at_100_std
      value: 39.87437580584755
    - type: nauc_recall_at_10_diff1
      value: 11.68142841889242
    - type: nauc_recall_at_10_max
      value: 27.103373590720558
    - type: nauc_recall_at_10_std
      value: 27.04385024929868
    - type: nauc_recall_at_1_diff1
      value: 18.759513595847864
    - type: nauc_recall_at_1_max
      value: 22.187646906334894
    - type: nauc_recall_at_1_std
      value: 14.187153951336118
    - type: nauc_recall_at_20_diff1
      value: 12.364424318414912
    - type: nauc_recall_at_20_max
      value: 29.80167804165616
    - type: nauc_recall_at_20_std
      value: 31.468351807134788
    - type: nauc_recall_at_3_diff1
      value: 10.93859197904096
    - type: nauc_recall_at_3_max
      value: 21.724132107323076
    - type: nauc_recall_at_3_std
      value: 19.356990775248228
    - type: nauc_recall_at_5_diff1
      value: 9.95140326972775
    - type: nauc_recall_at_5_max
      value: 25.965286128189252
    - type: nauc_recall_at_5_std
      value: 24.23016587234086
    - type: ndcg_at_1
      value: 22.1
    - type: ndcg_at_10
      value: 19.444
    - type: ndcg_at_100
      value: 28.060000000000002
    - type: ndcg_at_1000
      value: 34.078
    - type: ndcg_at_20
      value: 22.286
    - type: ndcg_at_3
      value: 18.218
    - type: ndcg_at_5
      value: 16.009999999999998
    - type: precision_at_1
      value: 22.1
    - type: precision_at_10
      value: 10.18
    - type: precision_at_100
      value: 2.268
    - type: precision_at_1000
      value: 0.371
    - type: precision_at_20
      value: 6.744999999999999
    - type: precision_at_3
      value: 17.1
    - type: precision_at_5
      value: 14.14
    - type: recall_at_1
      value: 4.502
    - type: recall_at_10
      value: 20.622
    - type: recall_at_100
      value: 46.056999999999995
    - type: recall_at_1000
      value: 75.233
    - type: recall_at_20
      value: 27.307
    - type: recall_at_3
      value: 10.412
    - type: recall_at_5
      value: 14.327000000000002
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB SICK-R (default)
      revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
      split: test
      type: mteb/sickr-sts
    metrics:
    - type: cosine_pearson
      value: 82.11817452484213
    - type: cosine_spearman
      value: 79.30791178551189
    - type: euclidean_pearson
      value: 78.97933027681707
    - type: euclidean_spearman
      value: 79.30791651031403
    - type: main_score
      value: 79.30791178551189
    - type: manhattan_pearson
      value: 78.72918056340825
    - type: manhattan_spearman
      value: 79.06604912335524
    - type: pearson
      value: 82.11817465900543
    - type: spearman
      value: 79.30791422790091
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB STS12 (default)
      revision: a0d554a64d88156834ff5ae9920b964011b16384
      split: test
      type: mteb/sts12-sts
    metrics:
    - type: cosine_pearson
      value: 79.66534565170502
    - type: cosine_spearman
      value: 68.71789951925966
    - type: euclidean_pearson
      value: 75.38034803617849
    - type: euclidean_spearman
      value: 68.71782916046409
    - type: main_score
      value: 68.71789951925966
    - type: manhattan_pearson
      value: 75.04120548057159
    - type: manhattan_spearman
      value: 68.37107097101716
    - type: pearson
      value: 79.66534548104319
    - type: spearman
      value: 68.71460093465805
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB STS13 (default)
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
      split: test
      type: mteb/sts13-sts
    metrics:
    - type: cosine_pearson
      value: 80.33061181586929
    - type: cosine_spearman
      value: 80.6334461266743
    - type: euclidean_pearson
      value: 80.08712662252661
    - type: euclidean_spearman
      value: 80.63344605500009
    - type: main_score
      value: 80.6334461266743
    - type: manhattan_pearson
      value: 79.64496714566727
    - type: manhattan_spearman
      value: 80.1367237568616
    - type: pearson
      value: 80.33061058171201
    - type: spearman
      value: 80.63344605500009
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB STS14 (default)
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
      split: test
      type: mteb/sts14-sts
    metrics:
    - type: cosine_pearson
      value: 78.02832336807212
    - type: cosine_spearman
      value: 75.26477784563788
    - type: euclidean_pearson
      value: 76.50227990354192
    - type: euclidean_spearman
      value: 75.26474419458818
    - type: main_score
      value: 75.26477784563788
    - type: manhattan_pearson
      value: 76.07476953899423
    - type: manhattan_spearman
      value: 74.86656085500788
    - type: pearson
      value: 78.02832348801336
    - type: spearman
      value: 75.26475896631564
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB STS15 (default)
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
      split: test
      type: mteb/sts15-sts
    metrics:
    - type: cosine_pearson
      value: 82.66486256825344
    - type: cosine_spearman
      value: 83.17551959894382
    - type: euclidean_pearson
      value: 82.24841235750758
    - type: euclidean_spearman
      value: 83.17552186285874
    - type: main_score
      value: 83.17551959894382
    - type: manhattan_pearson
      value: 81.9774505965764
    - type: manhattan_spearman
      value: 82.92775869917051
    - type: pearson
      value: 82.66486251397801
    - type: spearman
      value: 83.17552153015662
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB STS16 (default)
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
      split: test
      type: mteb/sts16-sts
    metrics:
    - type: cosine_pearson
      value: 78.85758004347694
    - type: cosine_spearman
      value: 79.53346527701895
    - type: euclidean_pearson
      value: 79.19288717662867
    - type: euclidean_spearman
      value: 79.53346527701895
    - type: main_score
      value: 79.53346527701895
    - type: manhattan_pearson
      value: 78.85228817502603
    - type: manhattan_spearman
      value: 79.19386225879818
    - type: pearson
      value: 78.85757994555938
    - type: spearman
      value: 79.53346470491176
    task:
      type: STS
  - dataset:
      config: en-tr
      name: MTEB STS17 (en-tr)
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
      split: test
      type: mteb/sts17-crosslingual-sts
    metrics:
    - type: cosine_pearson
      value: 1.2324984246461306
    - type: cosine_spearman
      value: -1.0887060319886745
    - type: euclidean_pearson
      value: 1.3895719685465724
    - type: euclidean_spearman
      value: -1.0887060319886745
    - type: main_score
      value: -1.0887060319886745
    - type: manhattan_pearson
      value: 1.9996696497260331
    - type: manhattan_spearman
      value: -0.10949729064179627
    - type: pearson
      value: 1.2324954103010868
    - type: spearman
      value: -1.0887060319886745
    task:
      type: STS
  - dataset:
      config: en-de
      name: MTEB STS17 (en-de)
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
      split: test
      type: mteb/sts17-crosslingual-sts
    metrics:
    - type: cosine_pearson
      value: 32.16759058328933
    - type: cosine_spearman
      value: 30.78566630137311
    - type: euclidean_pearson
      value: 32.20125625536215
    - type: euclidean_spearman
      value: 30.78566630137311
    - type: main_score
      value: 30.78566630137311
    - type: manhattan_pearson
      value: 30.50221445727974
    - type: manhattan_spearman
      value: 29.001989425079916
    - type: pearson
      value: 32.16759950381597
    - type: spearman
      value: 30.78566630137311
    task:
      type: STS
  - dataset:
      config: ar-ar
      name: MTEB STS17 (ar-ar)
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
      split: test
      type: mteb/sts17-crosslingual-sts
    metrics:
    - type: cosine_pearson
      value: 49.21561059227258
    - type: cosine_spearman
      value: 54.54683402537498
    - type: euclidean_pearson
      value: 55.10961177673182
    - type: euclidean_spearman
      value: 54.54683402537498
    - type: main_score
      value: 54.54683402537498
    - type: manhattan_pearson
      value: 54.75351371073398
    - type: manhattan_spearman
      value: 54.09299690986656
    - type: pearson
      value: 49.215620160787196
    - type: spearman
      value: 54.53831762469085
    task:
      type: STS
  - dataset:
      config: fr-en
      name: MTEB STS17 (fr-en)
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
      split: test
      type: mteb/sts17-crosslingual-sts
    metrics:
    - type: cosine_pearson
      value: 41.30563970416245
    - type: cosine_spearman
      value: 40.15540911311002
    - type: euclidean_pearson
      value: 41.39824124334786
    - type: euclidean_spearman
      value: 40.15540911311002
    - type: main_score
      value: 40.15540911311002
    - type: manhattan_pearson
      value: 40.27193928000343
    - type: manhattan_spearman
      value: 39.62417307952587
    - type: pearson
      value: 41.30563534198055
    - type: spearman
      value: 40.15540911311002
    task:
      type: STS
  - dataset:
      config: es-en
      name: MTEB STS17 (es-en)
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
      split: test
      type: mteb/sts17-crosslingual-sts
    metrics:
    - type: cosine_pearson
      value: 21.634652384973705
    - type: cosine_spearman
      value: 20.905083447883076
    - type: euclidean_pearson
      value: 21.45395108717184
    - type: euclidean_spearman
      value: 20.905083447883076
    - type: main_score
      value: 20.905083447883076
    - type: manhattan_pearson
      value: 19.536029018030728
    - type: manhattan_spearman
      value: 17.89017854049159
    - type: pearson
      value: 21.6346556425376
    - type: spearman
      value: 20.905083447883076
    task:
      type: STS
  - dataset:
      config: it-en
      name: MTEB STS17 (it-en)
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
      split: test
      type: mteb/sts17-crosslingual-sts
    metrics:
    - type: cosine_pearson
      value: 29.916756856327993
    - type: cosine_spearman
      value: 31.0628162146974
    - type: euclidean_pearson
      value: 29.440153196283557
    - type: euclidean_spearman
      value: 31.0628162146974
    - type: main_score
      value: 31.0628162146974
    - type: manhattan_pearson
      value: 28.432947464078918
    - type: manhattan_spearman
      value: 28.32518241760408
    - type: pearson
      value: 29.91674792754777
    - type: spearman
      value: 31.0628162146974
    task:
      type: STS
  - dataset:
      config: en-ar
      name: MTEB STS17 (en-ar)
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
      split: test
      type: mteb/sts17-crosslingual-sts
    metrics:
    - type: cosine_pearson
      value: 6.771893496172387
    - type: cosine_spearman
      value: 10.834475694007107
    - type: euclidean_pearson
      value: 6.5677478213162885
    - type: euclidean_spearman
      value: 10.834475694007107
    - type: main_score
      value: 10.834475694007107
    - type: manhattan_pearson
      value: 7.670696588474082
    - type: manhattan_spearman
      value: 10.71142960046072
    - type: pearson
      value: 6.771879554612134
    - type: spearman
      value: 10.834475694007107
    task:
      type: STS
  - dataset:
      config: es-es
      name: MTEB STS17 (es-es)
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
      split: test
      type: mteb/sts17-crosslingual-sts
    metrics:
    - type: cosine_pearson
      value: 74.45735169235816
    - type: cosine_spearman
      value: 74.36653700097551
    - type: euclidean_pearson
      value: 76.12322237745572
    - type: euclidean_spearman
      value: 74.36653700097551
    - type: main_score
      value: 74.36653700097551
    - type: manhattan_pearson
      value: 75.7758359581126
    - type: manhattan_spearman
      value: 74.31993284934066
    - type: pearson
      value: 74.45734889127019
    - type: spearman
      value: 74.3663085426167
    task:
      type: STS
  - dataset:
      config: en-en
      name: MTEB STS17 (en-en)
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
      split: test
      type: mteb/sts17-crosslingual-sts
    metrics:
    - type: cosine_pearson
      value: 89.02346865634368
    - type: cosine_spearman
      value: 88.95770332366246
    - type: euclidean_pearson
      value: 88.4922408529274
    - type: euclidean_spearman
      value: 88.95770332366246
    - type: main_score
      value: 88.95770332366246
    - type: manhattan_pearson
      value: 88.4734951170278
    - type: manhattan_spearman
      value: 89.11588250442936
    - type: pearson
      value: 89.02346739795206
    - type: spearman
      value: 88.95770332366246
    task:
      type: STS
  - dataset:
      config: ko-ko
      name: MTEB STS17 (ko-ko)
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
      split: test
      type: mteb/sts17-crosslingual-sts
    metrics:
    - type: cosine_pearson
      value: 29.551067303498623
    - type: cosine_spearman
      value: 37.69837545026809
    - type: euclidean_pearson
      value: 35.64775987269827
    - type: euclidean_spearman
      value: 37.698190216929966
    - type: main_score
      value: 37.69837545026809
    - type: manhattan_pearson
      value: 35.620311687081326
    - type: manhattan_spearman
      value: 37.619543979504975
    - type: pearson
      value: 29.551068205501295
    - type: spearman
      value: 37.69867837380798
    task:
      type: STS
  - dataset:
      config: nl-en
      name: MTEB STS17 (nl-en)
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
      split: test
      type: mteb/sts17-crosslingual-sts
    metrics:
    - type: cosine_pearson
      value: 32.012981930508985
    - type: cosine_spearman
      value: 29.807415518545096
    - type: euclidean_pearson
      value: 32.15404597916071
    - type: euclidean_spearman
      value: 29.807415518545096
    - type: main_score
      value: 29.807415518545096
    - type: manhattan_pearson
      value: 30.24045265417985
    - type: manhattan_spearman
      value: 28.489781020773925
    - type: pearson
      value: 32.01298053872033
    - type: spearman
      value: 29.807415518545096
    task:
      type: STS
  - dataset:
      config: es
      name: MTEB STS22 (es)
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: cosine_pearson
      value: 43.54595664856279
    - type: cosine_spearman
      value: 54.10491922799427
    - type: euclidean_pearson
      value: 48.71171441794464
    - type: euclidean_spearman
      value: 54.10491922799427
    - type: main_score
      value: 54.10491922799427
    - type: manhattan_pearson
      value: 47.7554900775804
    - type: manhattan_spearman
      value: 53.56978747099107
    - type: pearson
      value: 43.545957502823356
    - type: spearman
      value: 54.10491922799427
    task:
      type: STS
  - dataset:
      config: zh
      name: MTEB STS22 (zh)
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: cosine_pearson
      value: 21.399843406874204
    - type: cosine_spearman
      value: 42.935140998882495
    - type: euclidean_pearson
      value: 31.080595708023495
    - type: euclidean_spearman
      value: 42.935140998882495
    - type: main_score
      value: 42.935140998882495
    - type: manhattan_pearson
      value: 30.59355860937394
    - type: manhattan_spearman
      value: 42.75766501508097
    - type: pearson
      value: 21.39984013579853
    - type: spearman
      value: 42.93468939388313
    task:
      type: STS
  - dataset:
      config: it
      name: MTEB STS22 (it)
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: cosine_pearson
      value: 54.87276044784988
    - type: cosine_spearman
      value: 56.66162625692095
    - type: euclidean_pearson
      value: 55.63409750483066
    - type: euclidean_spearman
      value: 56.66162625692095
    - type: main_score
      value: 56.66162625692095
    - type: manhattan_pearson
      value: 55.69743346904424
    - type: manhattan_spearman
      value: 56.83799762862467
    - type: pearson
      value: 54.87275877783328
    - type: spearman
      value: 56.66162625692095
    task:
      type: STS
  - dataset:
      config: ar
      name: MTEB STS22 (ar)
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: cosine_pearson
      value: 33.271097420210424
    - type: cosine_spearman
      value: 36.89056170474566
    - type: euclidean_pearson
      value: 35.75552665932539
    - type: euclidean_spearman
      value: 36.89056170474566
    - type: main_score
      value: 36.89056170474566
    - type: manhattan_pearson
      value: 35.23843554757213
    - type: manhattan_spearman
      value: 36.13353270766642
    - type: pearson
      value: 33.27109269640927
    - type: spearman
      value: 36.921464485571384
    task:
      type: STS
  - dataset:
      config: de-fr
      name: MTEB STS22 (de-fr)
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: cosine_pearson
      value: 35.85356656336487
    - type: cosine_spearman
      value: 28.158749195282628
    - type: euclidean_pearson
      value: 34.77644342877048
    - type: euclidean_spearman
      value: 28.158749195282628
    - type: main_score
      value: 28.158749195282628
    - type: manhattan_pearson
      value: 32.51137129119162
    - type: manhattan_spearman
      value: 25.879876063292606
    - type: pearson
      value: 35.853568724601196
    - type: spearman
      value: 28.158749195282628
    task:
      type: STS
  - dataset:
      config: pl-en
      name: MTEB STS22 (pl-en)
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: cosine_pearson
      value: 50.57237179570535
    - type: cosine_spearman
      value: 47.09751128514487
    - type: euclidean_pearson
      value: 50.446056974070686
    - type: euclidean_spearman
      value: 47.09751128514487
    - type: main_score
      value: 47.09751128514487
    - type: manhattan_pearson
      value: 50.15601221016199
    - type: manhattan_spearman
      value: 47.40486148598809
    - type: pearson
      value: 50.57235875718242
    - type: spearman
      value: 47.09751128514487
    task:
      type: STS
  - dataset:
      config: de
      name: MTEB STS22 (de)
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: cosine_pearson
      value: 24.493356312529052
    - type: cosine_spearman
      value: 29.24268427412106
    - type: euclidean_pearson
      value: 20.881166992839965
    - type: euclidean_spearman
      value: 29.24268427412106
    - type: main_score
      value: 29.24268427412106
    - type: manhattan_pearson
      value: 20.9682289948799
    - type: manhattan_spearman
      value: 29.36217779917779
    - type: pearson
      value: 24.493357428088995
    - type: spearman
      value: 29.240453915641474
    task:
      type: STS
  - dataset:
      config: es-en
      name: MTEB STS22 (es-en)
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: cosine_pearson
      value: 50.540080748188366
    - type: cosine_spearman
      value: 53.63232170702014
    - type: euclidean_pearson
      value: 51.39140780759759
    - type: euclidean_spearman
      value: 53.63232170702014
    - type: main_score
      value: 53.63232170702014
    - type: manhattan_pearson
      value: 50.888462301553986
    - type: manhattan_spearman
      value: 52.92654373219885
    - type: pearson
      value: 50.540083584395546
    - type: spearman
      value: 53.63232170702014
    task:
      type: STS
  - dataset:
      config: en
      name: MTEB STS22 (en)
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: cosine_pearson
      value: 64.06971948645636
    - type: cosine_spearman
      value: 64.99352563680702
    - type: euclidean_pearson
      value: 65.99555717049346
    - type: euclidean_spearman
      value: 64.99352563680702
    - type: main_score
      value: 64.99352563680702
    - type: manhattan_pearson
      value: 66.01772320227963
    - type: manhattan_spearman
      value: 65.0434155427717
    - type: pearson
      value: 64.06971819415902
    - type: spearman
      value: 64.99352563680702
    task:
      type: STS
  - dataset:
      config: de-en
      name: MTEB STS22 (de-en)
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: cosine_pearson
      value: 46.67900817265241
    - type: cosine_spearman
      value: 47.60915415510522
    - type: euclidean_pearson
      value: 48.24278643260973
    - type: euclidean_spearman
      value: 47.60915415510522
    - type: main_score
      value: 47.60915415510522
    - type: manhattan_pearson
      value: 46.539452359996034
    - type: manhattan_spearman
      value: 45.953269584219825
    - type: pearson
      value: 46.679005336283716
    - type: spearman
      value: 47.60915415510522
    task:
      type: STS
  - dataset:
      config: fr
      name: MTEB STS22 (fr)
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: cosine_pearson
      value: 71.1088049428891
    - type: cosine_spearman
      value: 74.1159908229773
    - type: euclidean_pearson
      value: 71.0248954697202
    - type: euclidean_spearman
      value: 74.1159908229773
    - type: main_score
      value: 74.1159908229773
    - type: manhattan_pearson
      value: 70.94990095845533
    - type: manhattan_spearman
      value: 74.29375622854518
    - type: pearson
      value: 71.1088076476087
    - type: spearman
      value: 74.1159908229773
    task:
      type: STS
  - dataset:
      config: zh-en
      name: MTEB STS22 (zh-en)
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: cosine_pearson
      value: 37.29760592795572
    - type: cosine_spearman
      value: 42.67757119479072
    - type: euclidean_pearson
      value: 37.237174929314264
    - type: euclidean_spearman
      value: 42.67757119479072
    - type: main_score
      value: 42.67757119479072
    - type: manhattan_pearson
      value: 37.76235419307985
    - type: manhattan_spearman
      value: 43.0581339245249
    - type: pearson
      value: 37.297595548851184
    - type: spearman
      value: 42.67757119479072
    task:
      type: STS
  - dataset:
      config: fr-pl
      name: MTEB STS22 (fr-pl)
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: cosine_pearson
      value: 66.86734921862265
    - type: cosine_spearman
      value: 61.97797868009122
    - type: euclidean_pearson
      value: 67.64152372054912
    - type: euclidean_spearman
      value: 61.97797868009122
    - type: main_score
      value: 61.97797868009122
    - type: manhattan_pearson
      value: 70.26598896462248
    - type: manhattan_spearman
      value: 73.24670207647144
    - type: pearson
      value: 66.86735424516324
    - type: spearman
      value: 61.97797868009122
    task:
      type: STS
  - dataset:
      config: pl
      name: MTEB STS22 (pl)
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: cosine_pearson
      value: 6.143701012309495
    - type: cosine_spearman
      value: 22.737567808497587
    - type: euclidean_pearson
      value: 2.563373511580513
    - type: euclidean_spearman
      value: 22.737567808497587
    - type: main_score
      value: 22.737567808497587
    - type: manhattan_pearson
      value: 2.3621365037778994
    - type: manhattan_spearman
      value: 22.627864826862513
    - type: pearson
      value: 6.143704340747378
    - type: spearman
      value: 22.744576484058022
    task:
      type: STS
  - dataset:
      config: tr
      name: MTEB STS22 (tr)
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: cosine_pearson
      value: 19.996779769879897
    - type: cosine_spearman
      value: 32.22266809564839
    - type: euclidean_pearson
      value: 26.533663870748843
    - type: euclidean_spearman
      value: 32.22266809564839
    - type: main_score
      value: 32.22266809564839
    - type: manhattan_pearson
      value: 26.269646880757673
    - type: manhattan_spearman
      value: 31.97874465934443
    - type: pearson
      value: 19.996777822595202
    - type: spearman
      value: 32.22266809564839
    task:
      type: STS
  - dataset:
      config: es-it
      name: MTEB STS22 (es-it)
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: cosine_pearson
      value: 42.83982490662272
    - type: cosine_spearman
      value: 40.818956422486934
    - type: euclidean_pearson
      value: 43.84293087261557
    - type: euclidean_spearman
      value: 40.818956422486934
    - type: main_score
      value: 40.818956422486934
    - type: manhattan_pearson
      value: 43.20416589305718
    - type: manhattan_spearman
      value: 40.12018234883322
    - type: pearson
      value: 42.83982477515114
    - type: spearman
      value: 40.818956422486934
    task:
      type: STS
  - dataset:
      config: ru
      name: MTEB STS22 (ru)
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: cosine_pearson
      value: 9.999127578863702
    - type: cosine_spearman
      value: 21.929995958781735
    - type: euclidean_pearson
      value: 13.169854246371976
    - type: euclidean_spearman
      value: 21.929995958781735
    - type: main_score
      value: 21.929995958781735
    - type: manhattan_pearson
      value: 12.80638513095583
    - type: manhattan_spearman
      value: 21.732217172696913
    - type: pearson
      value: 9.999129789458081
    - type: spearman
      value: 21.924422337209982
    task:
      type: STS
  - dataset:
      config: de-pl
      name: MTEB STS22 (de-pl)
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: cosine_pearson
      value: 14.906897707741331
    - type: cosine_spearman
      value: 20.69363755174973
    - type: euclidean_pearson
      value: 15.746287887109824
    - type: euclidean_spearman
      value: 20.69363755174973
    - type: main_score
      value: 20.69363755174973
    - type: manhattan_pearson
      value: 17.97937212472529
    - type: manhattan_spearman
      value: 24.173371247207655
    - type: pearson
      value: 14.906893927073536
    - type: spearman
      value: 20.69363755174973
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB STSBenchmark (default)
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
      split: test
      type: mteb/stsbenchmark-sts
    metrics:
    - type: cosine_pearson
      value: 82.05268559824307
    - type: cosine_spearman
      value: 81.80129334727255
    - type: euclidean_pearson
      value: 82.00241759197277
    - type: euclidean_spearman
      value: 81.80129334727255
    - type: main_score
      value: 81.80129334727255
    - type: manhattan_pearson
      value: 81.64460953652511
    - type: manhattan_spearman
      value: 81.40232791050113
    - type: pearson
      value: 82.0526854006677
    - type: spearman
      value: 81.80129334727255
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB SciDocsRR (default)
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
      split: test
      type: mteb/scidocs-reranking
    metrics:
    - type: main_score
      value: 84.75515355697092
    - type: map
      value: 84.75515355697092
    - type: mrr
      value: 95.76542012816523
    - type: nAUC_map_diff1
      value: 2.6218598327022473
    - type: nAUC_map_max
      value: 55.31490226938186
    - type: nAUC_map_std
      value: 67.2466107017137
    - type: nAUC_mrr_diff1
      value: 45.837481251148
    - type: nAUC_mrr_max
      value: 83.85025655931555
    - type: nAUC_mrr_std
      value: 77.76943534722102
    task:
      type: Reranking
  - dataset:
      config: default
      name: MTEB SciFact (default)
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
      split: test
      type: mteb/scifact
    metrics:
    - type: main_score
      value: 51.376
    - type: map_at_1
      value: 37.556
    - type: map_at_10
      value: 46.534
    - type: map_at_100
      value: 47.277
    - type: map_at_1000
      value: 47.355999999999995
    - type: map_at_20
      value: 46.938
    - type: map_at_3
      value: 43.699
    - type: map_at_5
      value: 45.232
    - type: mrr_at_1
      value: 39.33333333333333
    - type: mrr_at_10
      value: 47.959920634920636
    - type: mrr_at_100
      value: 48.55831503603312
    - type: mrr_at_1000
      value: 48.62970983390715
    - type: mrr_at_20
      value: 48.24184842934844
    - type: mrr_at_3
      value: 45.6111111111111
    - type: mrr_at_5
      value: 47.07777777777776
    - type: nauc_map_at_1000_diff1
      value: 60.80948849351721
    - type: nauc_map_at_1000_max
      value: 47.99322551458462
    - type: nauc_map_at_1000_std
      value: 19.918623385279272
    - type: nauc_map_at_100_diff1
      value: 60.76773046819619
    - type: nauc_map_at_100_max
      value: 47.99194267747547
    - type: nauc_map_at_100_std
      value: 19.959121044456012
    - type: nauc_map_at_10_diff1
      value: 61.06017127580966
    - type: nauc_map_at_10_max
      value: 47.894995779178
    - type: nauc_map_at_10_std
      value: 19.61864315768623
    - type: nauc_map_at_1_diff1
      value: 63.87693438642291
    - type: nauc_map_at_1_max
      value: 41.7046766785424
    - type: nauc_map_at_1_std
      value: 12.461182034191653
    - type: nauc_map_at_20_diff1
      value: 60.87942740680037
    - type: nauc_map_at_20_max
      value: 48.03016625166588
    - type: nauc_map_at_20_std
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    task:
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  - dataset:
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      type: mteb/scifact
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    task:
      type: Retrieval
  - dataset:
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      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
      split: test
      type: mteb/sprintduplicatequestions-pairclassification
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      type: PairClassification
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      name: MTEB SprintDuplicateQuestions (default)
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
      split: validation
      type: mteb/sprintduplicatequestions-pairclassification
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    task:
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  - dataset:
      config: default
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      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
      split: test
      type: mteb/stackoverflowdupquestions-reranking
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    task:
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  - dataset:
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      value: 25.504388212194424
    - type: nauc_precision_at_20_diff1
      value: -4.2292835364864025
    - type: nauc_precision_at_20_max
      value: -2.301326609383918
    - type: nauc_precision_at_20_std
      value: 22.45274295709375
    - type: nauc_precision_at_3_diff1
      value: -16.354942735170056
    - type: nauc_precision_at_3_max
      value: -14.65811822200764
    - type: nauc_precision_at_3_std
      value: -5.371738642025328
    - type: nauc_precision_at_5_diff1
      value: -2.0865932304893398
    - type: nauc_precision_at_5_max
      value: -12.43800645118826
    - type: nauc_precision_at_5_std
      value: -0.785456924227922
    - type: nauc_recall_at_1000_diff1
      value: -27.067929512859383
    - type: nauc_recall_at_1000_max
      value: 8.27637512746264
    - type: nauc_recall_at_1000_std
      value: 70.20170699074127
    - type: nauc_recall_at_100_diff1
      value: -10.801744199612111
    - type: nauc_recall_at_100_max
      value: -1.521858730697413
    - type: nauc_recall_at_100_std
      value: 29.502087932404887
    - type: nauc_recall_at_10_diff1
      value: 6.620428505686945
    - type: nauc_recall_at_10_max
      value: 2.6967847665823417
    - type: nauc_recall_at_10_std
      value: -10.613005362584216
    - type: nauc_recall_at_1_diff1
      value: -17.54953791146995
    - type: nauc_recall_at_1_max
      value: -15.41277104639262
    - type: nauc_recall_at_1_std
      value: 8.141372141846212
    - type: nauc_recall_at_20_diff1
      value: 2.855400368822548
    - type: nauc_recall_at_20_max
      value: 3.6677496555985525
    - type: nauc_recall_at_20_std
      value: 5.424655779537322
    - type: nauc_recall_at_3_diff1
      value: -6.347995630633211
    - type: nauc_recall_at_3_max
      value: -7.202472967368409
    - type: nauc_recall_at_3_std
      value: -19.60457697668874
    - type: nauc_recall_at_5_diff1
      value: 4.71874396631723
    - type: nauc_recall_at_5_max
      value: -5.187633322645269
    - type: nauc_recall_at_5_std
      value: -14.486281013374851
    - type: ndcg_at_1
      value: 13.264999999999999
    - type: ndcg_at_10
      value: 13.841000000000001
    - type: ndcg_at_100
      value: 21.303
    - type: ndcg_at_1000
      value: 31.628
    - type: ndcg_at_20
      value: 14.768999999999998
    - type: ndcg_at_3
      value: 13.286000000000001
    - type: ndcg_at_5
      value: 15.301
    - type: precision_at_1
      value: 16.326999999999998
    - type: precision_at_10
      value: 12.857
    - type: precision_at_100
      value: 4.531000000000001
    - type: precision_at_1000
      value: 1.11
    - type: precision_at_20
      value: 9.898
    - type: precision_at_3
      value: 14.966
    - type: precision_at_5
      value: 17.143
    - type: recall_at_1
      value: 1.05
    - type: recall_at_10
      value: 9.76
    - type: recall_at_100
      value: 27.98
    - type: recall_at_1000
      value: 59.78
    - type: recall_at_20
      value: 14.426
    - type: recall_at_3
      value: 3.6609999999999996
    - type: recall_at_5
      value: 6.525
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB TwitterSemEval2015 (default)
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
      split: test
      type: mteb/twittersemeval2015-pairclassification
    metrics:
    - type: cosine_accuracy
      value: 86.46361089586935
    - type: cosine_accuracy_threshold
      value: 68.602854013443
    - type: cosine_ap
      value: 76.19134872998976
    - type: cosine_f1
      value: 70.0497512437811
    - type: cosine_f1_threshold
      value: 63.82530331611633
    - type: cosine_precision
      value: 66.25882352941177
    - type: cosine_recall
      value: 74.30079155672823
    - type: dot_accuracy
      value: 86.46361089586935
    - type: dot_accuracy_threshold
      value: 68.60285997390747
    - type: dot_ap
      value: 76.19134090974376
    - type: dot_f1
      value: 70.0497512437811
    - type: dot_f1_threshold
      value: 63.82530927658081
    - type: dot_precision
      value: 66.25882352941177
    - type: dot_recall
      value: 74.30079155672823
    - type: euclidean_accuracy
      value: 86.46361089586935
    - type: euclidean_accuracy_threshold
      value: 79.24284934997559
    - type: euclidean_ap
      value: 76.19134954237678
    - type: euclidean_f1
      value: 70.0497512437811
    - type: euclidean_f1_threshold
      value: 85.05843877792358
    - type: euclidean_precision
      value: 66.25882352941177
    - type: euclidean_recall
      value: 74.30079155672823
    - type: main_score
      value: 76.191355296053
    - type: manhattan_accuracy
      value: 86.35632115396078
    - type: manhattan_accuracy_threshold
      value: 1689.6617889404297
    - type: manhattan_ap
      value: 76.04793395742094
    - type: manhattan_f1
      value: 69.95183401259726
    - type: manhattan_f1_threshold
      value: 1861.5121841430664
    - type: manhattan_precision
      value: 65.75342465753424
    - type: manhattan_recall
      value: 74.72295514511873
    - type: max_accuracy
      value: 86.46361089586935
    - type: max_ap
      value: 76.191355296053
    - type: max_f1
      value: 70.0497512437811
    - type: max_precision
      value: 66.25882352941177
    - type: max_recall
      value: 74.72295514511873
    - type: similarity_accuracy
      value: 86.46361089586935
    - type: similarity_accuracy_threshold
      value: 68.60285997390747
    - type: similarity_ap
      value: 76.191355296053
    - type: similarity_f1
      value: 70.0497512437811
    - type: similarity_f1_threshold
      value: 63.82531523704529
    - type: similarity_precision
      value: 66.25882352941177
    - type: similarity_recall
      value: 74.30079155672823
    task:
      type: PairClassification
  - dataset:
      config: default
      name: MTEB TwitterURLCorpus (default)
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
      split: test
      type: mteb/twitterurlcorpus-pairclassification
    metrics:
    - type: cosine_accuracy
      value: 88.00209570380719
    - type: cosine_accuracy_threshold
      value: 66.62089228630066
    - type: cosine_ap
      value: 83.732187827528
    - type: cosine_f1
      value: 75.75757575757575
    - type: cosine_f1_threshold
      value: 62.46500015258789
    - type: cosine_precision
      value: 73.8520035097982
    - type: cosine_recall
      value: 77.76408992916538
    - type: dot_accuracy
      value: 88.00209570380719
    - type: dot_accuracy_threshold
      value: 66.62088632583618
    - type: dot_ap
      value: 83.73218146671233
    - type: dot_f1
      value: 75.75757575757575
    - type: dot_f1_threshold
      value: 62.46500015258789
    - type: dot_precision
      value: 73.8520035097982
    - type: dot_recall
      value: 77.76408992916538
    - type: euclidean_accuracy
      value: 88.00209570380719
    - type: euclidean_accuracy_threshold
      value: 81.70570135116577
    - type: euclidean_ap
      value: 83.7321851505459
    - type: euclidean_f1
      value: 75.75757575757575
    - type: euclidean_f1_threshold
      value: 86.64293885231018
    - type: euclidean_precision
      value: 73.8520035097982
    - type: euclidean_recall
      value: 77.76408992916538
    - type: main_score
      value: 83.732187827528
    - type: manhattan_accuracy
      value: 87.9846315054139
    - type: manhattan_accuracy_threshold
      value: 1792.7431106567383
    - type: manhattan_ap
      value: 83.6902817311313
    - type: manhattan_f1
      value: 75.7556651707896
    - type: manhattan_f1_threshold
      value: 1904.5093536376953
    - type: manhattan_precision
      value: 73.08050089445437
    - type: manhattan_recall
      value: 78.6341238065907
    - type: max_accuracy
      value: 88.00209570380719
    - type: max_ap
      value: 83.732187827528
    - type: max_f1
      value: 75.75757575757575
    - type: max_precision
      value: 73.8520035097982
    - type: max_recall
      value: 78.6341238065907
    - type: similarity_accuracy
      value: 88.00209570380719
    - type: similarity_accuracy_threshold
      value: 66.62089824676514
    - type: similarity_ap
      value: 83.73218773533418
    - type: similarity_f1
      value: 75.75757575757575
    - type: similarity_f1_threshold
      value: 62.46500015258789
    - type: similarity_precision
      value: 73.8520035097982
    - type: similarity_recall
      value: 77.76408992916538
    task:
      type: PairClassification
---

# SentenceTransformer

This is a [sentence-transformers](https://www.SBERT.net) model trained. It maps sentences & paragraphs to a 768-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more.

## Model Details

### Model Description
- **Model Type:** Sentence Transformer
<!-- - **Base model:** [Unknown](https://huggingface.co/unknown) -->
- **Maximum Sequence Length:** 384 tokens
- **Output Dimensionality:** 768 tokens
- **Similarity Function:** Cosine Similarity
<!-- - **Training Dataset:** Unknown -->
<!-- - **Language:** Unknown -->
<!-- - **License:** Unknown -->

### Model Sources

- **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
- **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers)
- **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers)

### Full Model Architecture

```
SentenceTransformer(
  (0): Transformer({'max_seq_length': 384, 'do_lower_case': False}) with Transformer model: MPNetModel 
  (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
  (2): Normalize()
)
```

## Usage

### Direct Usage (Sentence Transformers)

First install the Sentence Transformers library:

```bash
pip install -U sentence-transformers
```

Then you can load this model and run inference.
```python
from sentence_transformers import SentenceTransformer

# Download from the 🤗 Hub
model = SentenceTransformer("qinxianliu/FAB-Ramy-v1")
# Run inference
sentences = [
    'The weather is lovely today.',
    "It's so sunny outside!",
    'He drove to the stadium.',
]
embeddings = model.encode(sentences)
print(embeddings.shape)
# [3, 768]

# Get the similarity scores for the embeddings
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [3, 3]
```

<!--
### Direct Usage (Transformers)

<details><summary>Click to see the direct usage in Transformers</summary>

</details>
-->

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### Downstream Usage (Sentence Transformers)

You can finetune this model on your own dataset.

<details><summary>Click to expand</summary>

</details>
-->

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### Out-of-Scope Use

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## Bias, Risks and Limitations

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### Recommendations

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## Training Details

### Framework Versions
- Python: 3.10.14
- Sentence Transformers: 3.0.1
- Transformers: 4.41.2
- PyTorch: 2.3.1+cu121
- Accelerate: 0.31.0
- Datasets: 2.19.1
- Tokenizers: 0.19.1

## Citation

### BibTeX

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