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sft-bge-small

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metadata
model-index:
  - name: sft-bge-small
    results:
      - dataset:
          config: default
          name: MTEB AFQMC
          revision: b44c3b011063adb25877c13823db83bb193913c4
          split: validation
          type: C-MTEB/AFQMC
        metrics:
          - type: cosine_pearson
            value: 33.53658849446219
          - type: cosine_spearman
            value: 33.883815205024966
          - type: euclidean_pearson
            value: 33.04627496978132
          - type: euclidean_spearman
            value: 33.88381520628932
          - type: main_score
            value: 33.883815205024966
          - type: manhattan_pearson
            value: 32.99325108822262
          - type: manhattan_spearman
            value: 33.820124806863234
        task:
          type: STS
      - dataset:
          config: default
          name: MTEB ATEC
          revision: 0f319b1142f28d00e055a6770f3f726ae9b7d865
          split: test
          type: C-MTEB/ATEC
        metrics:
          - type: cosine_pearson
            value: 42.70324773636391
          - type: cosine_spearman
            value: 43.359361990058034
          - type: euclidean_pearson
            value: 45.61531205864215
          - type: euclidean_spearman
            value: 43.3593631156173
          - type: main_score
            value: 43.359361990058034
          - type: manhattan_pearson
            value: 45.48276231419951
          - type: manhattan_spearman
            value: 43.26880728411688
        task:
          type: STS
      - dataset:
          config: zh
          name: MTEB AmazonReviewsClassification (zh)
          revision: 1399c76144fd37290681b995c656ef9b2e06e26d
          split: test
          type: mteb/amazon_reviews_multi
        metrics:
          - type: accuracy
            value: 34.548
          - type: f1
            value: 33.36701212578771
          - type: f1_weighted
            value: 33.36701212578771
          - type: main_score
            value: 34.548
        task:
          type: Classification
      - dataset:
          config: default
          name: MTEB BQ
          revision: e3dda5e115e487b39ec7e618c0c6a29137052a55
          split: test
          type: C-MTEB/BQ
        metrics:
          - type: cosine_pearson
            value: 56.21405088075221
          - type: cosine_spearman
            value: 57.140134726780204
          - type: euclidean_pearson
            value: 56.07621870553079
          - type: euclidean_spearman
            value: 57.14013126130719
          - type: main_score
            value: 57.140134726780204
          - type: manhattan_pearson
            value: 55.91315694994356
          - type: manhattan_spearman
            value: 56.97612683481512
        task:
          type: STS
      - dataset:
          config: default
          name: MTEB CLSClusteringP2P.v2 (default)
          revision: 4b6227591c6c1a73bc76b1055f3b7f3588e72476
          split: test
          type: C-MTEB/CLSClusteringP2P
        metrics:
          - type: main_score
            value: 37.19334308094345
          - type: v_measure
            value: 37.19334308094345
          - type: v_measure_std
            value: 1.7104549965585019
        task:
          type: Clustering
      - dataset:
          config: default
          name: MTEB CLSClusteringS2S.v2 (default)
          revision: e458b3f5414b62b7f9f83499ac1f5497ae2e869f
          split: test
          type: C-MTEB/CLSClusteringS2S
        metrics:
          - type: main_score
            value: 34.93861988093335
          - type: v_measure
            value: 34.93861988093335
          - type: v_measure_std
            value: 1.166767552463492
        task:
          type: Clustering
      - dataset:
          config: default
          name: MTEB CMedQAv1-reranking
          revision: 8d7f1e942507dac42dc58017c1a001c3717da7df
          split: test
          type: C-MTEB/CMedQAv1-reranking
        metrics:
          - type: main_score
            value: 77.18563215195435
          - type: map
            value: 77.18563215195435
          - type: mrr
            value: 80.31658730158729
          - type: nAUC_map_diff1
            value: 52.93848123660803
          - type: nAUC_map_max
            value: 52.72106929433276
          - type: nAUC_map_std
            value: 17.011035198804265
          - type: nAUC_mrr_diff1
            value: 55.97351297507661
          - type: nAUC_mrr_max
            value: 58.298929607461936
          - type: nAUC_mrr_std
            value: 25.591598778732767
        task:
          type: Reranking
      - dataset:
          config: default
          name: MTEB CMedQAv2-reranking
          revision: 23d186750531a14a0357ca22cd92d712fd512ea0
          split: test
          type: C-MTEB/CMedQAv2-reranking
        metrics:
          - type: main_score
            value: 79.99056812833828
          - type: map
            value: 79.99056812833828
          - type: mrr
            value: 83.06869047619048
          - type: nAUC_map_diff1
            value: 52.09035038251355
          - type: nAUC_map_max
            value: 52.26552947348612
          - type: nAUC_map_std
            value: 12.37175423724008
          - type: nAUC_mrr_diff1
            value: 61.14939120187718
          - type: nAUC_mrr_max
            value: 64.46388888429114
          - type: nAUC_mrr_std
            value: 19.8257853597496
        task:
          type: Reranking
      - dataset:
          config: default
          name: MTEB CmedqaRetrieval
          revision: cd540c506dae1cf9e9a59c3e06f42030d54e7301
          split: dev
          type: C-MTEB/CmedqaRetrieval
        metrics:
          - type: main_score
            value: 34.69
          - type: map_at_1
            value: 19.344
          - type: map_at_10
            value: 28.796
          - type: map_at_100
            value: 30.585
          - type: map_at_1000
            value: 30.749
          - type: map_at_20
            value: 29.706
          - type: map_at_3
            value: 25.513
          - type: map_at_5
            value: 27.178
          - type: mrr_at_1
            value: 30.407601900475118
          - type: mrr_at_10
            value: 37.5060927930395
          - type: mrr_at_100
            value: 38.57367124679012
          - type: mrr_at_1000
            value: 38.64878379455239
          - type: mrr_at_20
            value: 38.09679427251286
          - type: mrr_at_3
            value: 35.07960323414186
          - type: mrr_at_5
            value: 36.47245144619492
          - type: nauc_map_at_1000_diff1
            value: 44.51440720023725
          - type: nauc_map_at_1000_max
            value: 28.97219143148225
          - type: nauc_map_at_1000_std
            value: -8.086311202275697
          - type: nauc_map_at_100_diff1
            value: 44.48004417791743
          - type: nauc_map_at_100_max
            value: 28.943674602104245
          - type: nauc_map_at_100_std
            value: -8.117037242753526
          - type: nauc_map_at_10_diff1
            value: 44.75973064427402
          - type: nauc_map_at_10_max
            value: 28.08323798212488
          - type: nauc_map_at_10_std
            value: -9.619348483821657
          - type: nauc_map_at_1_diff1
            value: 49.6699324592167
          - type: nauc_map_at_1_max
            value: 23.459448993588776
          - type: nauc_map_at_1_std
            value: -10.743776071552071
          - type: nauc_map_at_20_diff1
            value: 44.4984776366223
          - type: nauc_map_at_20_max
            value: 28.584292621450953
          - type: nauc_map_at_20_std
            value: -8.810140926363161
          - type: nauc_map_at_3_diff1
            value: 45.99933707541341
          - type: nauc_map_at_3_max
            value: 26.894130402004972
          - type: nauc_map_at_3_std
            value: -10.933378123879866
          - type: nauc_map_at_5_diff1
            value: 45.46747106830205
          - type: nauc_map_at_5_max
            value: 27.716685754420844
          - type: nauc_map_at_5_std
            value: -10.357767749416846
          - type: nauc_mrr_at_1000_diff1
            value: 48.32510446424475
          - type: nauc_mrr_at_1000_max
            value: 33.1970315626591
          - type: nauc_mrr_at_1000_std
            value: -4.173066140057387
          - type: nauc_mrr_at_100_diff1
            value: 48.29684669904282
          - type: nauc_mrr_at_100_max
            value: 33.1987177026033
          - type: nauc_mrr_at_100_std
            value: -4.14522976270507
          - type: nauc_mrr_at_10_diff1
            value: 48.37940066077619
          - type: nauc_mrr_at_10_max
            value: 33.04364922694604
          - type: nauc_mrr_at_10_std
            value: -4.631619579133087
          - type: nauc_mrr_at_1_diff1
            value: 53.325487160335214
          - type: nauc_mrr_at_1_max
            value: 33.45510756277711
          - type: nauc_mrr_at_1_std
            value: -5.819387381295979
          - type: nauc_mrr_at_20_diff1
            value: 48.26588000840893
          - type: nauc_mrr_at_20_max
            value: 33.16675443872329
          - type: nauc_mrr_at_20_std
            value: -4.285764179231469
          - type: nauc_mrr_at_3_diff1
            value: 49.53448699043804
          - type: nauc_mrr_at_3_max
            value: 33.24069008317655
          - type: nauc_mrr_at_3_std
            value: -5.2381928595767135
          - type: nauc_mrr_at_5_diff1
            value: 48.842306548487784
          - type: nauc_mrr_at_5_max
            value: 33.28578509420531
          - type: nauc_mrr_at_5_std
            value: -4.686379267262563
          - type: nauc_ndcg_at_1000_diff1
            value: 43.52208964237314
          - type: nauc_ndcg_at_1000_max
            value: 31.413122097522926
          - type: nauc_ndcg_at_1000_std
            value: -3.5454929831424895
          - type: nauc_ndcg_at_100_diff1
            value: 42.631025867109265
          - type: nauc_ndcg_at_100_max
            value: 31.330295140981264
          - type: nauc_ndcg_at_100_std
            value: -2.7694833109497616
          - type: nauc_ndcg_at_10_diff1
            value: 43.3433130932041
          - type: nauc_ndcg_at_10_max
            value: 29.121307963920145
          - type: nauc_ndcg_at_10_std
            value: -7.657901336484528
          - type: nauc_ndcg_at_1_diff1
            value: 53.325487160335214
          - type: nauc_ndcg_at_1_max
            value: 33.45510756277711
          - type: nauc_ndcg_at_1_std
            value: -5.819387381295979
          - type: nauc_ndcg_at_20_diff1
            value: 42.69042735273421
          - type: nauc_ndcg_at_20_max
            value: 30.135189128144113
          - type: nauc_ndcg_at_20_std
            value: -5.676679328920746
          - type: nauc_ndcg_at_3_diff1
            value: 45.4872294661908
          - type: nauc_ndcg_at_3_max
            value: 29.971944952161557
          - type: nauc_ndcg_at_3_std
            value: -7.826058866615504
          - type: nauc_ndcg_at_5_diff1
            value: 44.63791548178676
          - type: nauc_ndcg_at_5_max
            value: 29.496784393590374
          - type: nauc_ndcg_at_5_std
            value: -7.944096292023679
          - type: nauc_precision_at_1000_diff1
            value: 2.6137669501180927
          - type: nauc_precision_at_1000_max
            value: 19.926619760122094
          - type: nauc_precision_at_1000_std
            value: 18.867526538887752
          - type: nauc_precision_at_100_diff1
            value: 10.03920635386407
          - type: nauc_precision_at_100_max
            value: 27.181170898866903
          - type: nauc_precision_at_100_std
            value: 20.88605769712323
          - type: nauc_precision_at_10_diff1
            value: 25.936219722674547
          - type: nauc_precision_at_10_max
            value: 31.976548332740514
          - type: nauc_precision_at_10_std
            value: 3.6576801366468987
          - type: nauc_precision_at_1_diff1
            value: 53.325487160335214
          - type: nauc_precision_at_1_max
            value: 33.45510756277711
          - type: nauc_precision_at_1_std
            value: -5.819387381295979
          - type: nauc_precision_at_20_diff1
            value: 19.633571873524584
          - type: nauc_precision_at_20_max
            value: 30.904840563207987
          - type: nauc_precision_at_20_std
            value: 9.938896845265456
          - type: nauc_precision_at_3_diff1
            value: 37.14825198202475
          - type: nauc_precision_at_3_max
            value: 34.37632573886419
          - type: nauc_precision_at_3_std
            value: -3.0609791122986256
          - type: nauc_precision_at_5_diff1
            value: 32.78898119399301
          - type: nauc_precision_at_5_max
            value: 34.37023611560389
          - type: nauc_precision_at_5_std
            value: -0.42504548614596976
          - type: nauc_recall_at_1000_diff1
            value: 14.600972396858413
          - type: nauc_recall_at_1000_max
            value: 40.521226786378804
          - type: nauc_recall_at_1000_std
            value: 46.956959325410544
          - type: nauc_recall_at_100_diff1
            value: 23.656183428068584
          - type: nauc_recall_at_100_max
            value: 29.07683373955294
          - type: nauc_recall_at_100_std
            value: 15.637712951467797
          - type: nauc_recall_at_10_diff1
            value: 32.52919812152399
          - type: nauc_recall_at_10_max
            value: 23.552357593827423
          - type: nauc_recall_at_10_std
            value: -6.845700007396986
          - type: nauc_recall_at_1_diff1
            value: 49.6699324592167
          - type: nauc_recall_at_1_max
            value: 23.459448993588776
          - type: nauc_recall_at_1_std
            value: -10.743776071552071
          - type: nauc_recall_at_20_diff1
            value: 29.188304612884792
          - type: nauc_recall_at_20_max
            value: 25.550908369687956
          - type: nauc_recall_at_20_std
            value: -0.7990312810700567
          - type: nauc_recall_at_3_diff1
            value: 39.77533612982849
          - type: nauc_recall_at_3_max
            value: 24.588028886173564
          - type: nauc_recall_at_3_std
            value: -9.968636943964619
          - type: nauc_recall_at_5_diff1
            value: 37.068075910504966
          - type: nauc_recall_at_5_max
            value: 24.87691740154786
          - type: nauc_recall_at_5_std
            value: -8.366125373919461
          - type: ndcg_at_1
            value: 30.408
          - type: ndcg_at_10
            value: 34.69
          - type: ndcg_at_100
            value: 42.168
          - type: ndcg_at_1000
            value: 45.33
          - type: ndcg_at_20
            value: 37.316
          - type: ndcg_at_3
            value: 30.215999999999998
          - type: ndcg_at_5
            value: 31.85
          - type: precision_at_1
            value: 30.408
          - type: precision_at_10
            value: 7.882
          - type: precision_at_100
            value: 1.401
          - type: precision_at_1000
            value: 0.18
          - type: precision_at_20
            value: 4.819
          - type: precision_at_3
            value: 17.246
          - type: precision_at_5
            value: 12.503
          - type: recall_at_1
            value: 19.344
          - type: recall_at_10
            value: 43.592999999999996
          - type: recall_at_100
            value: 74.83999999999999
          - type: recall_at_1000
            value: 96.392
          - type: recall_at_20
            value: 52.455
          - type: recall_at_3
            value: 29.923
          - type: recall_at_5
            value: 35.272999999999996
        task:
          type: Retrieval
      - dataset:
          config: default
          name: MTEB Cmnli
          revision: 41bc36f332156f7adc9e38f53777c959b2ae9766
          split: validation
          type: C-MTEB/CMNLI
        metrics:
          - type: cosine_accuracy
            value: 66.56644618159952
          - type: cosine_accuracy_threshold
            value: 76.13220810890198
          - type: cosine_ap
            value: 73.14617302827378
          - type: cosine_f1
            value: 70.42408665320362
          - type: cosine_f1_threshold
            value: 66.68621897697449
          - type: cosine_precision
            value: 57.97189058485719
          - type: cosine_recall
            value: 89.68903436988543
          - type: dot_accuracy
            value: 66.56644618159952
          - type: dot_accuracy_threshold
            value: 76.1322021484375
          - type: dot_ap
            value: 73.14455168745744
          - type: dot_f1
            value: 70.42408665320362
          - type: dot_f1_threshold
            value: 66.68622493743896
          - type: dot_precision
            value: 57.97189058485719
          - type: dot_recall
            value: 89.68903436988543
          - type: euclidean_accuracy
            value: 66.56644618159952
          - type: euclidean_accuracy_threshold
            value: 69.09095048904419
          - type: euclidean_ap
            value: 73.14617671721679
          - type: euclidean_f1
            value: 70.42408665320362
          - type: euclidean_f1_threshold
            value: 81.6257119178772
          - type: euclidean_precision
            value: 57.97189058485719
          - type: euclidean_recall
            value: 89.68903436988543
          - type: main_score
            value: 73.14617302827378
          - type: manhattan_accuracy
            value: 66.57847263980757
          - type: manhattan_accuracy_threshold
            value: 1258.1926345825195
          - type: manhattan_ap
            value: 73.14820845291298
          - type: manhattan_f1
            value: 70.48598130841121
          - type: manhattan_f1_threshold
            value: 1456.794548034668
          - type: manhattan_precision
            value: 58.710882765063054
          - type: manhattan_recall
            value: 88.16927753097966
          - type: max_ap
            value: 73.15794277861517
          - type: max_f1
            value: 70.48598130841121
          - type: max_precision
            value: 58.710882765063054
          - type: max_recall
            value: 89.68903436988543
          - type: similarity_accuracy
            value: 66.56644618159952
          - type: similarity_accuracy_threshold
            value: 76.1322021484375
          - type: similarity_ap
            value: 73.15794277861517
          - type: similarity_f1
            value: 70.42408665320362
          - type: similarity_f1_threshold
            value: 66.68622493743896
          - type: similarity_precision
            value: 57.97189058485719
          - type: similarity_recall
            value: 89.68903436988543
        task:
          type: PairClassification
      - dataset:
          config: default
          name: MTEB CovidRetrieval
          revision: 1271c7809071a13532e05f25fb53511ffce77117
          split: dev
          type: C-MTEB/CovidRetrieval
        metrics:
          - type: main_score
            value: 70.586
          - type: map_at_1
            value: 57.692
          - type: map_at_10
            value: 66.563
          - type: map_at_100
            value: 67.134
          - type: map_at_1000
            value: 67.15100000000001
          - type: map_at_20
            value: 66.928
          - type: map_at_3
            value: 64.752
          - type: map_at_5
            value: 65.99199999999999
          - type: mrr_at_1
            value: 57.7449947312961
          - type: mrr_at_10
            value: 66.51989562948471
          - type: mrr_at_100
            value: 67.08227337230899
          - type: mrr_at_1000
            value: 67.09996653345524
          - type: mrr_at_20
            value: 66.87876593981935
          - type: mrr_at_3
            value: 64.71724622409556
          - type: mrr_at_5
            value: 65.97119775201969
          - type: nauc_map_at_1000_diff1
            value: 72.69110060344008
          - type: nauc_map_at_1000_max
            value: 44.03869716669461
          - type: nauc_map_at_1000_std
            value: -23.946115940222256
          - type: nauc_map_at_100_diff1
            value: 72.67926034661765
          - type: nauc_map_at_100_max
            value: 44.052650160851876
          - type: nauc_map_at_100_std
            value: -23.911105541326467
          - type: nauc_map_at_10_diff1
            value: 72.53533231168593
          - type: nauc_map_at_10_max
            value: 44.15235653929674
          - type: nauc_map_at_10_std
            value: -23.900332084894313
          - type: nauc_map_at_1_diff1
            value: 77.11451883608845
          - type: nauc_map_at_1_max
            value: 42.465578617544175
          - type: nauc_map_at_1_std
            value: -26.182375444539453
          - type: nauc_map_at_20_diff1
            value: 72.61694436567365
          - type: nauc_map_at_20_max
            value: 44.02402901308803
          - type: nauc_map_at_20_std
            value: -23.971702762395797
          - type: nauc_map_at_3_diff1
            value: 72.70716523996312
          - type: nauc_map_at_3_max
            value: 43.547617926836935
          - type: nauc_map_at_3_std
            value: -24.907330594011903
          - type: nauc_map_at_5_diff1
            value: 72.73260758015672
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        task:
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        task:
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          revision: b7c64bd89eb87f8ded463478346f76731f07bf8b
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          revision: 17f9b096f80380fce5ed12a9be8be7784b337daf
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        task:
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      - dataset:
          config: default
          name: MTEB MedicalRetrieval
          revision: 2039188fb5800a9803ba5048df7b76e6fb151fc6
          split: dev
          type: C-MTEB/MedicalRetrieval
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          - type: ndcg_at_1000
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          - type: ndcg_at_20
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          - type: ndcg_at_3
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          - type: ndcg_at_5
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          - type: precision_at_1
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          - type: precision_at_10
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          - type: precision_at_100
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          - type: precision_at_1000
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          - type: precision_at_20
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          - type: precision_at_3
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          - type: precision_at_5
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          - type: recall_at_1
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          - type: recall_at_10
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          - type: recall_at_100
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          - type: recall_at_1000
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          - type: recall_at_20
            value: 60
          - type: recall_at_3
            value: 47.8
          - type: recall_at_5
            value: 51.300000000000004
        task:
          type: Retrieval
      - dataset:
          config: default
          name: MTEB MultilingualSentiment
          revision: 46958b007a63fdbf239b7672c25d0bea67b5ea1a
          split: test
          type: C-MTEB/MultilingualSentiment-classification
        metrics:
          - type: accuracy
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          - type: f1
            value: 61.413644038319504
          - type: f1_weighted
            value: 61.41364403831952
          - type: main_score
            value: 62.040000000000006
        task:
          type: Classification
      - dataset:
          config: default
          name: MTEB MultilingualSentiment
          revision: 46958b007a63fdbf239b7672c25d0bea67b5ea1a
          split: validation
          type: C-MTEB/MultilingualSentiment-classification
        metrics:
          - type: accuracy
            value: 61.083333333333336
          - type: f1
            value: 60.53964576763606
          - type: f1_weighted
            value: 60.53964576763606
          - type: main_score
            value: 61.083333333333336
        task:
          type: Classification
      - dataset:
          config: default
          name: MTEB Ocnli
          revision: 66e76a618a34d6d565d5538088562851e6daa7ec
          split: validation
          type: C-MTEB/OCNLI
        metrics:
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            value: 60.80129940443963
          - type: cosine_accuracy_threshold
            value: 74.15386438369751
          - type: cosine_ap
            value: 62.78839792290818
          - type: cosine_f1
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          - type: cosine_f1_threshold
            value: 58.69802236557007
          - type: cosine_precision
            value: 53.69813589897775
          - type: cosine_recall
            value: 94.29778247096094
          - type: dot_accuracy
            value: 60.80129940443963
          - type: dot_accuracy_threshold
            value: 74.15387630462646
          - type: dot_ap
            value: 62.7881377053932
          - type: dot_f1
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          - type: dot_f1_threshold
            value: 58.69803428649902
          - type: dot_precision
            value: 53.69813589897775
          - type: dot_recall
            value: 94.29778247096094
          - type: euclidean_accuracy
            value: 60.80129940443963
          - type: euclidean_accuracy_threshold
            value: 71.89733386039734
          - type: euclidean_ap
            value: 62.788246348811185
          - type: euclidean_f1
            value: 68.42911877394636
          - type: euclidean_f1_threshold
            value: 90.88671207427979
          - type: euclidean_precision
            value: 53.69813589897775
          - type: euclidean_recall
            value: 94.29778247096094
          - type: main_score
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          - type: manhattan_accuracy
            value: 60.42230644288035
          - type: manhattan_accuracy_threshold
            value: 1285.611915588379
          - type: manhattan_ap
            value: 62.68367089991109
          - type: manhattan_f1
            value: 68.13099041533545
          - type: manhattan_f1_threshold
            value: 1581.9337844848633
          - type: manhattan_precision
            value: 54.78484264611432
          - type: manhattan_recall
            value: 90.07391763463569
          - type: max_ap
            value: 62.78839792290818
          - type: max_f1
            value: 68.42911877394636
          - type: max_precision
            value: 54.78484264611432
          - type: max_recall
            value: 94.29778247096094
          - type: similarity_accuracy
            value: 60.80129940443963
          - type: similarity_accuracy_threshold
            value: 74.15388226509094
          - type: similarity_ap
            value: 62.7881377053932
          - type: similarity_f1
            value: 68.42911877394636
          - type: similarity_f1_threshold
            value: 58.698028326034546
          - type: similarity_precision
            value: 53.69813589897775
          - type: similarity_recall
            value: 94.29778247096094
        task:
          type: PairClassification
      - dataset:
          config: default
          name: MTEB OnlineShopping (default)
          revision: e610f2ebd179a8fda30ae534c3878750a96db120
          split: test
          type: C-MTEB/OnlineShopping-classification
        metrics:
          - type: accuracy
            value: 83.22999999999998
          - type: ap
            value: 80.04405977529461
          - type: ap_weighted
            value: 80.04405977529461
          - type: f1
            value: 83.20270595475907
          - type: f1_weighted
            value: 83.21171008766063
          - type: main_score
            value: 83.22999999999998
        task:
          type: Classification
      - dataset:
          config: default
          name: MTEB PAWSX
          revision: 9c6a90e430ac22b5779fb019a23e820b11a8b5e1
          split: test
          type: C-MTEB/PAWSX
        metrics:
          - type: cosine_pearson
            value: 9.874694562979904
          - type: cosine_spearman
            value: 9.309911313205925
          - type: euclidean_pearson
            value: 11.741278538778094
          - type: euclidean_spearman
            value: 9.328433551419229
          - type: main_score
            value: 9.309911313205925
          - type: manhattan_pearson
            value: 11.72560906113808
          - type: manhattan_spearman
            value: 9.316414394414991
        task:
          type: STS
      - dataset:
          config: zh
          name: MTEB PawsXPairClassification (zh)
          revision: 8a04d940a42cd40658986fdd8e3da561533a3646
          split: test
          type: google-research-datasets/paws-x
        metrics:
          - type: cosine_accuracy
            value: 58.650000000000006
          - type: cosine_accuracy_threshold
            value: 100
          - type: cosine_ap
            value: 53.75275143522933
          - type: cosine_f1
            value: 62.34309623430961
          - type: cosine_f1_threshold
            value: 68.03557872772217
          - type: cosine_precision
            value: 45.2887537993921
          - type: cosine_recall
            value: 100
          - type: dot_accuracy
            value: 58.599999999999994
          - type: dot_accuracy_threshold
            value: 99.99727010726929
          - type: dot_ap
            value: 53.998635904072565
          - type: dot_f1
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          - type: dot_f1_threshold
            value: 68.03557872772217
          - type: dot_precision
            value: 45.2887537993921
          - type: dot_recall
            value: 100
          - type: euclidean_accuracy
            value: 58.650000000000006
          - type: euclidean_accuracy_threshold
            value: 0
          - type: euclidean_ap
            value: 53.75275143522933
          - type: euclidean_f1
            value: 62.34309623430961
          - type: euclidean_f1_threshold
            value: 79.954993724823
          - type: euclidean_precision
            value: 45.2887537993921
          - type: euclidean_recall
            value: 100
          - type: main_score
            value: 53.998635904072565
          - type: manhattan_accuracy
            value: 58.650000000000006
          - type: manhattan_accuracy_threshold
            value: 0
          - type: manhattan_ap
            value: 53.74246831220305
          - type: manhattan_f1
            value: 62.32136632973162
          - type: manhattan_f1_threshold
            value: 1499.9944686889648
          - type: manhattan_precision
            value: 45.265822784810126
          - type: manhattan_recall
            value: 100
          - type: max_ap
            value: 53.998635904072565
          - type: max_f1
            value: 62.34309623430961
          - type: max_precision
            value: 45.2887537993921
          - type: max_recall
            value: 100
          - type: similarity_accuracy
            value: 58.599999999999994
          - type: similarity_accuracy_threshold
            value: 99.99727010726929
          - type: similarity_ap
            value: 53.493550734464115
          - type: similarity_f1
            value: 62.34309623430961
          - type: similarity_f1_threshold
            value: 68.03557872772217
          - type: similarity_precision
            value: 45.2887537993921
          - type: similarity_recall
            value: 100
        task:
          type: PairClassification
      - dataset:
          config: zh
          name: MTEB PawsXPairClassification (zh)
          revision: 8a04d940a42cd40658986fdd8e3da561533a3646
          split: validation
          type: google-research-datasets/paws-x
        metrics:
          - type: cosine_accuracy
            value: 60.3
          - type: cosine_accuracy_threshold
            value: 99.86656904220581
          - type: cosine_ap
            value: 49.321768758993265
          - type: cosine_f1
            value: 60.13394430736694
          - type: cosine_f1_threshold
            value: 56.31052255630493
          - type: cosine_precision
            value: 42.993951612903224
          - type: cosine_recall
            value: 100
          - type: dot_accuracy
            value: 60.3
          - type: dot_accuracy_threshold
            value: 99.86656904220581
          - type: dot_ap
            value: 49.035857424446434
          - type: dot_f1
            value: 60.13394430736694
          - type: dot_f1_threshold
            value: 56.310516595840454
          - type: dot_precision
            value: 42.993951612903224
          - type: dot_recall
            value: 100
          - type: euclidean_accuracy
            value: 60.3
          - type: euclidean_accuracy_threshold
            value: 5.164862424135208
          - type: euclidean_ap
            value: 49.321768758993265
          - type: euclidean_f1
            value: 60.13394430736694
          - type: euclidean_f1_threshold
            value: 93.14978122711182
          - type: euclidean_precision
            value: 42.993951612903224
          - type: euclidean_recall
            value: 100
          - type: main_score
            value: 49.321768758993265
          - type: manhattan_accuracy
            value: 60.3
          - type: manhattan_accuracy_threshold
            value: 93.18596124649048
          - type: manhattan_ap
            value: 49.313849813317425
          - type: manhattan_f1
            value: 60.13394430736694
          - type: manhattan_f1_threshold
            value: 1691.009521484375
          - type: manhattan_precision
            value: 42.993951612903224
          - type: manhattan_recall
            value: 100
          - type: max_ap
            value: 49.321768758993265
          - type: max_f1
            value: 60.13394430736694
          - type: max_precision
            value: 42.993951612903224
          - type: max_recall
            value: 100
          - type: similarity_accuracy
            value: 60.3
          - type: similarity_accuracy_threshold
            value: 99.86656904220581
          - type: similarity_ap
            value: 49.142597419562264
          - type: similarity_f1
            value: 60.13394430736694
          - type: similarity_f1_threshold
            value: 56.31052255630493
          - type: similarity_precision
            value: 42.993951612903224
          - type: similarity_recall
            value: 100
        task:
          type: PairClassification
      - dataset:
          config: default
          name: MTEB QBQTC
          revision: 790b0510dc52b1553e8c49f3d2afb48c0e5c48b7
          split: test
          type: C-MTEB/QBQTC
        metrics:
          - type: cosine_pearson
            value: 32.89823952962557
          - type: cosine_spearman
            value: 35.508635844641425
          - type: euclidean_pearson
            value: 33.54904181023721
          - type: euclidean_spearman
            value: 35.50900960008307
          - type: main_score
            value: 35.508635844641425
          - type: manhattan_pearson
            value: 33.46879849723637
          - type: manhattan_spearman
            value: 35.443594309440684
        task:
          type: STS
      - dataset:
          config: zh
          name: MTEB STS22.v2 (zh)
          revision: d31f33a128469b20e357535c39b82fb3c3f6f2bd
          split: test
          type: mteb/sts22-crosslingual-sts
        metrics:
          - type: cosine_pearson
            value: 73.70326766919368
          - type: cosine_spearman
            value: 73.00749391119922
          - type: euclidean_pearson
            value: 71.8060850925119
          - type: euclidean_spearman
            value: 73.00749391119922
          - type: main_score
            value: 73.00749391119922
          - type: manhattan_pearson
            value: 71.74411017438445
          - type: manhattan_spearman
            value: 72.94623233913951
        task:
          type: STS
      - dataset:
          config: zh-en
          name: MTEB STS22.v2 (zh-en)
          revision: d31f33a128469b20e357535c39b82fb3c3f6f2bd
          split: test
          type: mteb/sts22-crosslingual-sts
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          config: default
          name: MTEB STSB
          revision: 0cde68302b3541bb8b3c340dc0644b0b745b3dc0
          split: test
          type: C-MTEB/STSB
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          config: default
          name: MTEB STSB
          revision: 0cde68302b3541bb8b3c340dc0644b0b745b3dc0
          split: validation
          type: C-MTEB/STSB
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          config: zh
          name: MTEB STSBenchmarkMultilingualSTS (zh)
          revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
          split: dev
          type: mteb/stsb_multi_mt
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      - dataset:
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          name: MTEB STSBenchmarkMultilingualSTS (zh)
          revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
          split: test
          type: mteb/stsb_multi_mt
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          config: default
          name: MTEB T2Reranking
          revision: 76631901a18387f85eaa53e5450019b87ad58ef9
          split: dev
          type: C-MTEB/T2Reranking
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      - dataset:
          config: default
          name: MTEB T2Retrieval
          revision: 8731a845f1bf500a4f111cf1070785c793d10e64
          split: dev
          type: C-MTEB/T2Retrieval
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          - type: recall_at_1
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        task:
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      - dataset:
          config: default
          name: MTEB TNews
          revision: 317f262bf1e6126357bbe89e875451e4b0938fe4
          split: validation
          type: C-MTEB/TNews-classification
        metrics:
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          - type: f1
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          - type: f1_weighted
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          - type: main_score
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        task:
          type: Classification
      - dataset:
          config: default
          name: MTEB ThuNewsClusteringP2P.v2
          revision: 5798586b105c0434e4f0fe5e767abe619442cf93
          split: test
          type: C-MTEB/ThuNewsClusteringP2P
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          - type: v_measure
            value: 55.83158187491721
          - type: v_measure_std
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        task:
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      - dataset:
          config: default
          name: MTEB ThuNewsClusteringS2S.v2
          revision: 8a8b2caeda43f39e13c4bc5bea0f8a667896e10d
          split: test
          type: C-MTEB/ThuNewsClusteringS2S
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          - type: v_measure
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        task:
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      - dataset:
          config: default
          name: MTEB VideoRetrieval
          revision: 58c2597a5943a2ba48f4668c3b90d796283c5639
          split: dev
          type: C-MTEB/VideoRetrieval
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          - type: recall_at_20
            value: 81.6
          - type: recall_at_3
            value: 61.1
          - type: recall_at_5
            value: 68.5
        task:
          type: Retrieval
      - dataset:
          config: default
          name: MTEB Waimai
          revision: 339287def212450dcaa9df8c22bf93e9980c7023
          split: test
          type: C-MTEB/waimai-classification
        metrics:
          - type: accuracy
            value: 82.23999999999998
          - type: ap
            value: 62.36539084249044
          - type: ap_weighted
            value: 62.36539084249044
          - type: f1
            value: 80.34948411543205
          - type: f1_weighted
            value: 82.47078823543444
          - type: main_score
            value: 82.23999999999998
        task:
          type: Classification
tags:
  - mteb

SentenceTransformer

This is a sentence-transformers model trained. It maps sentences & paragraphs to a 512-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: 512 tokens
  • Output Dimensionality: 512 tokens
  • Similarity Function: Cosine Similarity

Model Sources

Full Model Architecture 

SentenceTransformer(
  (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel 
  (1): Pooling({'word_embedding_dimension': 512, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, '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("dumyy/sft-bge-small")
# 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, 512]

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

Training Details

Framework Versions

  • Python: 3.8.19
  • Sentence Transformers: 3.0.0
  • Transformers: 4.37.2
  • PyTorch: 1.13.1+cu117
  • Accelerate: 0.21.0
  • Datasets: 2.19.2
  • Tokenizers: 0.15.1

Citation

BibTeX