README.md

metadata

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
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          config: default
          name: MTEB AskUbuntuDupQuestions (default)
          revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
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          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
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            value: 13.679043690905408
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            value: 28.9642395394068
          - type: nauc_map_at_100_std
            value: 26.605777722314194
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            value: 13.368432894934296
          - type: nauc_map_at_10_max
            value: 27.110702917972063
          - type: nauc_map_at_10_std
            value: 22.94925796594505
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            value: 18.759513595847864
          - type: nauc_map_at_1_max
            value: 22.187646906334894
          - type: nauc_map_at_1_std
            value: 14.187153951336118
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            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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            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 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
• Maximum Sequence Length: 384 tokens
• Output Dimensionality: 768 tokens
• Similarity Function: Cosine Similarity

Model Sources

• Documentation: Sentence Transformers Documentation
• Repository: Sentence Transformers on GitHub
• Hugging Face: Sentence Transformers on Hugging Face

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:

pip install -U sentence-transformers

Then you can load this model and run inference.

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]

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