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Mihaiii
/
Squirtle

Sentence Similarity
sentence-transformers
ONNX
Safetensors
bert
feature-extraction
bge
mteb
Eval Results
Inference Endpoints
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Squirtle

Squirtle is a distill of bge-base-en-v1.5.

Intended purpose

This model is designed for use in semantic-autocomplete (click here for demo). Make sure you also pass pipelineParams={{ pooling: "cls", normalize: true }} since the default pooling in the component is mean.

Usage

Other than within semantic-autocomplete, you can use this model same as bge-base-en-v1.5.

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Model size
15.6M params
Tensor type
F32
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Dataset used to train Mihaiii/Squirtle

Collection including Mihaiii/Squirtle

Evaluation results

  • accuracy on MTEB AmazonCounterfactualClassification (en)
    test set self-reported
    69.597
  • ap on MTEB AmazonCounterfactualClassification (en)
    test set self-reported
    31.808
  • f1 on MTEB AmazonCounterfactualClassification (en)
    test set self-reported
    63.432
  • accuracy on MTEB AmazonPolarityClassification
    test set self-reported
    82.090
  • ap on MTEB AmazonPolarityClassification
    test set self-reported
    76.950
  • f1 on MTEB AmazonPolarityClassification
    test set self-reported
    82.045
  • accuracy on MTEB AmazonReviewsClassification (en)
    test set self-reported
    41.944
  • f1 on MTEB AmazonReviewsClassification (en)
    test set self-reported
    40.410
  • map_at_1 on MTEB ArguAna
    test set self-reported
    13.869
  • map_at_10 on MTEB ArguAna
    test set self-reported
    24.631
  • map_at_100 on MTEB ArguAna
    test set self-reported
    25.965
  • map_at_1000 on MTEB ArguAna
    test set self-reported
    26.023
  • map_at_20 on MTEB ArguAna
    test set self-reported
    25.443
  • map_at_3 on MTEB ArguAna
    test set self-reported
    20.827
  • map_at_5 on MTEB ArguAna
    test set self-reported
    22.776
  • mrr_at_1 on MTEB ArguAna
    test set self-reported
    14.580
  • mrr_at_10 on MTEB ArguAna
    test set self-reported
    24.910
  • mrr_at_100 on MTEB ArguAna
    test set self-reported
    26.230
  • mrr_at_1000 on MTEB ArguAna
    test set self-reported
    26.288
  • mrr_at_20 on MTEB ArguAna
    test set self-reported
    25.708
  • mrr_at_3 on MTEB ArguAna
    test set self-reported
    21.136
  • mrr_at_5 on MTEB ArguAna
    test set self-reported
    23.020
  • ndcg_at_1 on MTEB ArguAna
    test set self-reported
    13.869
  • ndcg_at_10 on MTEB ArguAna
    test set self-reported
    31.140
  • ndcg_at_100 on MTEB ArguAna
    test set self-reported
    37.886
  • ndcg_at_1000 on MTEB ArguAna
    test set self-reported
    39.497
  • ndcg_at_20 on MTEB ArguAna
    test set self-reported
    34.068
  • ndcg_at_3 on MTEB ArguAna
    test set self-reported
    23.163
  • ndcg_at_5 on MTEB ArguAna
    test set self-reported
    26.677
  • precision_at_1 on MTEB ArguAna
    test set self-reported
    13.869
  • precision_at_10 on MTEB ArguAna
    test set self-reported
    5.220
  • precision_at_100 on MTEB ArguAna
    test set self-reported
    0.844
  • precision_at_1000 on MTEB ArguAna
    test set self-reported
    0.097
  • precision_at_20 on MTEB ArguAna
    test set self-reported
    3.186
  • precision_at_3 on MTEB ArguAna
    test set self-reported
    9.981
  • precision_at_5 on MTEB ArguAna
    test set self-reported
    7.696
  • recall_at_1 on MTEB ArguAna
    test set self-reported
    13.869
  • recall_at_10 on MTEB ArguAna
    test set self-reported
    52.205
  • recall_at_100 on MTEB ArguAna
    test set self-reported
    84.424
  • recall_at_1000 on MTEB ArguAna
    test set self-reported
    97.297
  • recall_at_20 on MTEB ArguAna
    test set self-reported
    63.727
  • recall_at_3 on MTEB ArguAna
    test set self-reported
    29.943
  • recall_at_5 on MTEB ArguAna
    test set self-reported
    38.478
  • v_measure on MTEB ArxivClusteringP2P
    test set self-reported
    33.043
  • v_measures on MTEB ArxivClusteringP2P
    test set self-reported
    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  • v_measure on MTEB ArxivClusteringS2S
    test set self-reported
    24.681
  • v_measures on MTEB ArxivClusteringS2S
    test set self-reported
    0.2005976632299017,0.208968006943616,0.20946008190179435,0.20539809799180958,0.21463587994609631,0.20913407901977635,0.20908020832330956,0.1944493063711425,0.20181175619582953,0.2249901827151246,0.29132293951181787,0.29570222215271086,0.2796075942678196,0.28871411057617774,0.29302758518431116,0.29227253592096986,0.2856462545898644,0.28687743467743254,0.2900793948371436,0.28627385826697854,0.27308659940457203,0.14117319401377473,0.1761477350541332,0.24048342650129406,0.19387054212465876,0.14470023981605995,0.16704070762984086,0.07547453139959907,0.127993495025131,1,0.14319476311235024,0.2005976632299017,0.208968006943616,0.20946008190179435,0.20539809799180958,0.21463587994609631,0.20913407901977635,0.20908020832330956,0.1944493063711425,0.20181175619582953,0.2249901827151246,0.29132293951181787,0.29570222215271086,0.2796075942678196,0.28871411057617774,0.29302758518431116,0.29227253592096986,0.2856462545898644,0.28687743467743254,0.2900793948371436,0.28627385826697854,0.27308659940457203,0.14117319401377473,0.1761477350541332,0.24048342650129406,0.19387054212465876,0.14470023981605995,0.16704070762984086,0.07547453139959907,0.127993495025131,1,0.14319476311235024,0.2005976632299017,0.208968006943616,0.20946008190179435,0.20539809799180958,0.21463587994609631,0.20913407901977635,0.20908020832330956,0.1944493063711425,0.20181175619582953,0.2249901827151246,0.29132293951181787,0.29570222215271086,0.2796075942678196,0.28871411057617774,0.29302758518431116,0.29227253592096986,0.2856462545898644,0.28687743467743254,0.2900793948371436,0.28627385826697854,0.27308659940457203,0.14117319401377473,0.1761477350541332,0.24048342650129406,0.19387054212465876,0.14470023981605995,0.16704070762984086,0.07547453139959907,0.127993495025131,1,0.14319476311235024,0.2005976632299017,0.208968006943616,0.20946008190179435,0.20539809799180958,0.21463587994609631,0.20913407901977635,0.20908020832330956,0.1944493063711425,0.20181175619582953,0.2249901827151246,0.29132293951181787,0.29570222215271086,0.2796075942678196,0.28871411057617774,0.29302758518431116,0.29227253592096986,0.2856462545898644,0.28687743467743254,0.2900793948371436,0.28627385826697854,0.27308659940457203,0.14117319401377473,0.1761477350541332,0.24048342650129406,0.19387054212465876,0.14470023981605995,0.16704070762984086,0.07547453139959907,0.127993495025131,1,0.14319476311235024,0.2005976632299017,0.208968006943616,0.20946008190179435,0.20539809799180958,0.21463587994609631,0.20913407901977635,0.20908020832330956,0.1944493063711425,0.20181175619582953,0.2249901827151246,0.29132293951181787,0.29570222215271086,0.2796075942678196,0.28871411057617774,0.29302758518431116,0.29227253592096986,0.2856462545898644,0.28687743467743254,0.2900793948371436,0.28627385826697854,0.27308659940457203,0.14117319401377473,0.1761477350541332,0.24048342650129406,0.19387054212465876,0.14470023981605995,0.16704070762984086,0.07547453139959907,0.127993495025131,1,0.14319476311235024,0.2005976632299017,0.208968006943616,0.20946008190179435,0.20539809799180958,0.21463587994609631,0.20913407901977635,0.20908020832330956,0.1944493063711425,0.20181175619582953,0.2249901827151246,0.29132293951181787,0.29570222215271086,0.2796075942678196,0.28871411057617774,0.29302758518431116,0.29227253592096986,0.2856462545898644,0.28687743467743254,0.2900793948371436,0.28627385826697854,0.27308659940457203,0.14117319401377473,0.1761477350541332,0.24048342650129406,0.19387054212465876,0.14470023981605995,0.16704070762984086,0.07547453139959907,0.127993495025131,1,0.14319476311235024,0.2005976632299017,0.208968006943616,0.20946008190179435,0.20539809799180958,0.21463587994609631,0.20913407901977635,0.20908020832330956,0.1944493063711425,0.20181175619582953,0.2249901827151246,0.29132293951181787,0.29570222215271086,0.2796075942678196,0.28871411057617774,0.29302758518431116,0.29227253592096986,0.2856462545898644,0.28687743467743254,0.2900793948371436,0.28627385826697854,0.27308659940457203,0.14117319401377473,0.1761477350541332,0.24048342650129406,0.19387054212465876,0.14470023981605995,0.16704070762984086,0.07547453139959907,0.127993495025131,1,0.14319476311235024,0.2005976632299017,0.208968006943616,0.20946008190179435,0.20539809799180958,0.21463587994609631,0.20913407901977635,0.20908020832330956,0.1944493063711425,0.20181175619582953,0.2249901827151246,0.29132293951181787,0.29570222215271086,0.2796075942678196,0.28871411057617774,0.29302758518431116,0.29227253592096986,0.2856462545898644,0.28687743467743254,0.2900793948371436,0.28627385826697854,0.27308659940457203,0.14117319401377473,0.1761477350541332,0.24048342650129406,0.19387054212465876,0.14470023981605995,0.16704070762984086,0.07547453139959907,0.127993495025131,1,0.14319476311235024,0.2005976632299017,0.208968006943616,0.20946008190179435,0.20539809799180958,0.21463587994609631,0.20913407901977635,0.20908020832330956,0.1944493063711425,0.20181175619582953,0.2249901827151246,0.29132293951181787,0.29570222215271086,0.2796075942678196,0.2887141105761777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  • map on MTEB AskUbuntuDupQuestions
    test set self-reported
    52.344
  • mrr on MTEB AskUbuntuDupQuestions
    test set self-reported
    65.326
  • cos_sim_pearson on MTEB BIOSSES
    test set self-reported
    69.441
  • cos_sim_spearman on MTEB BIOSSES
    test set self-reported
    71.778
  • euclidean_pearson on MTEB BIOSSES
    test set self-reported
    70.594
  • euclidean_spearman on MTEB BIOSSES
    test set self-reported
    71.778
  • manhattan_pearson on MTEB BIOSSES
    test set self-reported
    70.993
  • manhattan_spearman on MTEB BIOSSES
    test set self-reported
    72.077
  • accuracy on MTEB Banking77Classification
    test set self-reported
    67.130
  • f1 on MTEB Banking77Classification
    test set self-reported
    66.000
  • v_measure on MTEB BiorxivClusteringP2P
    test set self-reported
    30.862
  • v_measures on MTEB BiorxivClusteringP2P
    test set self-reported
    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