README.md

metadata

base_model: baai/bge-base-en-v1.5
language:
  - en
library_name: model2vec
license: mit
model_name: brown-beetle-tiny-v1
tags:
  - embeddings
  - static-embeddings
  - sentence-transformers
  - mteb
model-index:
  - name: brown-beetle-tiny-v1
    results:
      - dataset:
          config: en-ext
          name: MTEB AmazonCounterfactualClassification (en-ext)
          revision: e8379541af4e31359cca9fbcf4b00f2671dba205
          split: test
          type: mteb/amazon_counterfactual
        metrics:
          - type: accuracy
            value: 64.09295352323838
          - type: ap
            value: 16.57841154272169
          - type: ap_weighted
            value: 16.57841154272169
          - type: f1
            value: 52.8558683644378
          - type: f1_weighted
            value: 70.99795716291565
          - type: main_score
            value: 64.09295352323838
        task:
          type: Classification
      - dataset:
          config: en
          name: MTEB AmazonCounterfactualClassification (en)
          revision: e8379541af4e31359cca9fbcf4b00f2671dba205
          split: test
          type: mteb/amazon_counterfactual
        metrics:
          - type: accuracy
            value: 66.55223880597015
          - type: ap
            value: 29.489029255823183
          - type: ap_weighted
            value: 29.489029255823183
          - type: f1
            value: 60.63546188197216
          - type: f1_weighted
            value: 69.88550022841326
          - type: main_score
            value: 66.55223880597015
        task:
          type: Classification
      - dataset:
          config: default
          name: MTEB AmazonPolarityClassification (default)
          revision: e2d317d38cd51312af73b3d32a06d1a08b442046
          split: test
          type: mteb/amazon_polarity
        metrics:
          - type: accuracy
            value: 66.96194999999999
          - type: ap
            value: 61.92605604727599
          - type: ap_weighted
            value: 61.92605604727599
          - type: f1
            value: 66.59212154571806
          - type: f1_weighted
            value: 66.59212154571806
          - type: main_score
            value: 66.96194999999999
        task:
          type: Classification
      - dataset:
          config: en
          name: MTEB AmazonReviewsClassification (en)
          revision: 1399c76144fd37290681b995c656ef9b2e06e26d
          split: test
          type: mteb/amazon_reviews_multi
        metrics:
          - type: accuracy
            value: 31.406
          - type: f1
            value: 31.105909676226467
          - type: f1_weighted
            value: 31.105909676226467
          - type: main_score
            value: 31.406
        task:
          type: Classification
      - dataset:
          config: default
          name: MTEB ArguAna (default)
          revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
          split: test
          type: mteb/arguana
        metrics:
          - type: main_score
            value: 28.839
          - type: map_at_1
            value: 14.438
          - type: map_at_10
            value: 23.541
          - type: map_at_100
            value: 24.589
          - type: map_at_1000
            value: 24.672
          - type: map_at_20
            value: 24.093999999999998
          - type: map_at_3
            value: 20.578
          - type: map_at_5
            value: 22.197
          - type: mrr_at_1
            value: 14.864864864864865
          - type: mrr_at_10
            value: 23.69953600216757
          - type: mrr_at_100
            value: 24.754046628510885
          - type: mrr_at_1000
            value: 24.837834580004223
          - type: mrr_at_20
            value: 24.2590837465165
          - type: mrr_at_3
            value: 20.70886676149834
          - type: mrr_at_5
            value: 22.38738738738736
          - type: nauc_map_at_1000_diff1
            value: 11.710523444120719
          - type: nauc_map_at_1000_max
            value: -1.41407564949768
          - type: nauc_map_at_1000_std
            value: 14.46184437776828
          - type: nauc_map_at_100_diff1
            value: 11.695316106812099
          - type: nauc_map_at_100_max
            value: -1.4188305060204984
          - type: nauc_map_at_100_std
            value: 14.490744157955113
          - type: nauc_map_at_10_diff1
            value: 11.567234339158974
          - type: nauc_map_at_10_max
            value: -1.5892321978000112
          - type: nauc_map_at_10_std
            value: 13.73387241027869
          - type: nauc_map_at_1_diff1
            value: 12.88166978338844
          - type: nauc_map_at_1_max
            value: -5.632696878755496
          - type: nauc_map_at_1_std
            value: 11.116501462763512
          - type: nauc_map_at_20_diff1
            value: 11.592369512079118
          - type: nauc_map_at_20_max
            value: -1.3187282261869946
          - type: nauc_map_at_20_std
            value: 14.304147251709228
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            value: 11.256151680396243
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            value: -3.1045816700611084
          - type: nauc_map_at_3_std
            value: 11.98559615155674
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            value: -2.827886538484471
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            value: 12.986381975293579
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            value: 10.177159281558183
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            value: -1.692409833784558
          - type: nauc_mrr_at_1000_std
            value: 14.152763593329503
          - type: nauc_mrr_at_100_diff1
            value: 10.165711735180038
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            value: 14.182158646102106
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            value: -1.900984327744186
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            value: 13.42201050782521
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          - type: nauc_mrr_at_3_std
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            value: 9.948977775457102
          - type: nauc_mrr_at_5_max
            value: -2.9364908406397463
          - type: nauc_mrr_at_5_std
            value: 12.627802226242318
          - type: nauc_ndcg_at_1000_diff1
            value: 12.191441277161175
          - type: nauc_ndcg_at_1000_max
            value: 0.8222149831662116
          - type: nauc_ndcg_at_1000_std
            value: 17.691386726273176
          - type: nauc_ndcg_at_100_diff1
            value: 12.026922096707512
          - type: nauc_ndcg_at_100_max
            value: 0.9649095671797968
          - type: nauc_ndcg_at_100_std
            value: 18.79566154822669
          - type: nauc_ndcg_at_10_diff1
            value: 11.668212582460665
          - type: nauc_ndcg_at_10_max
            value: 0.9423653801824595
          - type: nauc_ndcg_at_10_std
            value: 15.538609047969858
          - type: nauc_ndcg_at_1_diff1
            value: 12.88166978338844
          - type: nauc_ndcg_at_1_max
            value: -5.632696878755496
          - type: nauc_ndcg_at_1_std
            value: 11.116501462763512
          - type: nauc_ndcg_at_20_diff1
            value: 11.692620670468228
          - type: nauc_ndcg_at_20_max
            value: 1.8201755765222798
          - type: nauc_ndcg_at_20_std
            value: 17.560542858395902
          - type: nauc_ndcg_at_3_diff1
            value: 11.023407454967298
          - type: nauc_ndcg_at_3_max
            value: -2.2256962581095268
          - type: nauc_ndcg_at_3_std
            value: 12.147790886487178
          - type: nauc_ndcg_at_5_diff1
            value: 11.23700232185496
          - type: nauc_ndcg_at_5_max
            value: -1.8374455211691147
          - type: nauc_ndcg_at_5_std
            value: 13.822082848830622
          - type: nauc_precision_at_1000_diff1
            value: 19.5190660354492
          - type: nauc_precision_at_1000_max
            value: 18.114410701992146
          - type: nauc_precision_at_1000_std
            value: 49.7944310686017
          - type: nauc_precision_at_100_diff1
            value: 13.493960597733729
          - type: nauc_precision_at_100_max
            value: 8.568691284955749
          - type: nauc_precision_at_100_std
            value: 39.0964671762103
          - type: nauc_precision_at_10_diff1
            value: 12.149349128166126
          - type: nauc_precision_at_10_max
            value: 7.695226757131975
          - type: nauc_precision_at_10_std
            value: 20.424722092975394
          - type: nauc_precision_at_1_diff1
            value: 12.88166978338844
          - type: nauc_precision_at_1_max
            value: -5.632696878755496
          - type: nauc_precision_at_1_std
            value: 11.116501462763512
          - type: nauc_precision_at_20_diff1
            value: 12.152076579176686
          - type: nauc_precision_at_20_max
            value: 10.951422872400038
          - type: nauc_precision_at_20_std
            value: 27.762016972799575
          - type: nauc_precision_at_3_diff1
            value: 10.520705211562325
          - type: nauc_precision_at_3_max
            value: -0.08840953178400665
          - type: nauc_precision_at_3_std
            value: 12.515570437615686
          - type: nauc_precision_at_5_diff1
            value: 10.858147634309764
          - type: nauc_precision_at_5_max
            value: 0.4927084766401162
          - type: nauc_precision_at_5_std
            value: 15.900545493843174
          - type: nauc_recall_at_1000_diff1
            value: 19.51906603544921
          - type: nauc_recall_at_1000_max
            value: 18.114410701992174
          - type: nauc_recall_at_1000_std
            value: 49.79443106860158
          - type: nauc_recall_at_100_diff1
            value: 13.493960597733695
          - type: nauc_recall_at_100_max
            value: 8.568691284955717
          - type: nauc_recall_at_100_std
            value: 39.09646717621017
          - type: nauc_recall_at_10_diff1
            value: 12.14934912816615
          - type: nauc_recall_at_10_max
            value: 7.6952267571319855
          - type: nauc_recall_at_10_std
            value: 20.42472209297543
          - type: nauc_recall_at_1_diff1
            value: 12.88166978338844
          - type: nauc_recall_at_1_max
            value: -5.632696878755496
          - type: nauc_recall_at_1_std
            value: 11.116501462763512
          - type: nauc_recall_at_20_diff1
            value: 12.152076579176654
          - type: nauc_recall_at_20_max
            value: 10.951422872400016
          - type: nauc_recall_at_20_std
            value: 27.76201697279958
          - type: nauc_recall_at_3_diff1
            value: 10.52070521156232
          - type: nauc_recall_at_3_max
            value: -0.08840953178398737
          - type: nauc_recall_at_3_std
            value: 12.515570437615686
          - type: nauc_recall_at_5_diff1
            value: 10.85814763430975
          - type: nauc_recall_at_5_max
            value: 0.49270847664009765
          - type: nauc_recall_at_5_std
            value: 15.900545493843135
          - type: ndcg_at_1
            value: 14.438
          - type: ndcg_at_10
            value: 28.839
          - type: ndcg_at_100
            value: 34.428
          - type: ndcg_at_1000
            value: 36.846000000000004
          - type: ndcg_at_20
            value: 30.842000000000002
          - type: ndcg_at_3
            value: 22.683
          - type: ndcg_at_5
            value: 25.591
          - type: precision_at_1
            value: 14.438
          - type: precision_at_10
            value: 4.587
          - type: precision_at_100
            value: 0.731
          - type: precision_at_1000
            value: 0.093
          - type: precision_at_20
            value: 2.688
          - type: precision_at_3
            value: 9.602
          - type: precision_at_5
            value: 7.1690000000000005
          - type: recall_at_1
            value: 14.438
          - type: recall_at_10
            value: 45.875
          - type: recall_at_100
            value: 73.115
          - type: recall_at_1000
            value: 92.60300000000001
          - type: recall_at_20
            value: 53.769999999999996
          - type: recall_at_3
            value: 28.804999999999996
          - type: recall_at_5
            value: 35.846000000000004
        task:
          type: Retrieval
      - dataset:
          config: default
          name: MTEB ArxivClusteringP2P (default)
          revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
          split: test
          type: mteb/arxiv-clustering-p2p
        metrics:
          - type: main_score
            value: 30.721708670938618
          - type: v_measure
            value: 30.721708670938618
          - type: v_measure_std
            value: 14.59075919640026
        task:
          type: Clustering
      - dataset:
          config: default
          name: MTEB ArxivClusteringP2P (default)
          revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
          split: test
          type: mteb/arxiv-clustering-p2p
        metrics:
          - type: main_score
            value: 30.721628572270227
          - type: v_measure
            value: 30.721628572270227
          - type: v_measure_std
            value: 14.590724884146741
        task:
          type: Clustering
      - dataset:
          config: default
          name: MTEB ArxivClusteringS2S (default)
          revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
          split: test
          type: mteb/arxiv-clustering-s2s
        metrics:
          - type: main_score
            value: 20.81189338758185
          - type: v_measure
            value: 20.81189338758185
          - type: v_measure_std
            value: 15.630749849934816
        task:
          type: Clustering
      - dataset:
          config: default
          name: MTEB ArxivClusteringS2S (default)
          revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
          split: test
          type: mteb/arxiv-clustering-s2s
        metrics:
          - type: main_score
            value: 20.81189338758186
          - type: v_measure
            value: 20.81189338758186
          - type: v_measure_std
            value: 15.630749849934816
        task:
          type: Clustering
      - dataset:
          config: default
          name: MTEB AskUbuntuDupQuestions (default)
          revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
          split: test
          type: mteb/askubuntudupquestions-reranking
        metrics:
          - type: main_score
            value: 51.269563672134986
          - type: map
            value: 51.269563672134986
          - type: mrr
            value: 64.9430594028932
          - type: nAUC_map_diff1
            value: 13.234765254548417
          - type: nAUC_map_max
            value: 14.005654835382275
          - type: nAUC_map_std
            value: 4.940982887482917
          - type: nAUC_mrr_diff1
            value: 20.319406020706065
          - type: nAUC_mrr_max
            value: 20.987604228375332
          - type: nAUC_mrr_std
            value: 9.22453984185132
        task:
          type: Reranking
      - dataset:
          config: default
          name: MTEB AskUbuntuDupQuestions (default)
          revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
          split: test
          type: mteb/askubuntudupquestions-reranking
        metrics:
          - type: main_score
            value: 51.269563672134986
          - type: map
            value: 51.269563672134986
          - type: mrr
            value: 64.9430594028932
          - type: nAUC_map_diff1
            value: 13.234765254548417
          - type: nAUC_map_max
            value: 14.005654835382275
          - type: nAUC_map_std
            value: 4.940982887482917
          - type: nAUC_mrr_diff1
            value: 20.319406020706065
          - type: nAUC_mrr_max
            value: 20.987604228375332
          - type: nAUC_mrr_std
            value: 9.22453984185132
        task:
          type: Reranking
      - dataset:
          config: default
          name: MTEB BIOSSES (default)
          revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
          split: test
          type: mteb/biosses-sts
        metrics:
          - type: cosine_pearson
            value: 72.65277568567002
          - type: cosine_spearman
            value: 71.5739200169482
          - type: euclidean_pearson
            value: 54.35299652840819
          - type: euclidean_spearman
            value: 55.29644068980453
          - type: main_score
            value: 71.5739200169482
          - type: manhattan_pearson
            value: 52.58607516245499
          - type: manhattan_spearman
            value: 54.298827597067664
        task:
          type: STS
      - dataset:
          config: default
          name: MTEB Banking77Classification (default)
          revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
          split: test
          type: mteb/banking77
        metrics:
          - type: accuracy
            value: 70.06168831168831
          - type: f1
            value: 70.19892920542246
          - type: f1_weighted
            value: 70.19892920542246
          - type: main_score
            value: 70.06168831168831
        task:
          type: Classification
      - dataset:
          config: default
          name: MTEB BiorxivClusteringP2P (default)
          revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
          split: test
          type: mteb/biorxiv-clustering-p2p
        metrics:
          - type: main_score
            value: 24.8818318188809
          - type: v_measure
            value: 24.8818318188809
          - type: v_measure_std
            value: 0.7960068034300037
        task:
          type: Clustering
      - dataset:
          config: default
          name: MTEB BiorxivClusteringP2P (default)
          revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
          split: test
          type: mteb/biorxiv-clustering-p2p
        metrics:
          - type: main_score
            value: 24.880938025057198
          - type: v_measure
            value: 24.880938025057198
          - type: v_measure_std
            value: 0.7956500964619948
        task:
          type: Clustering
      - dataset:
          config: default
          name: MTEB BiorxivClusteringS2S (default)
          revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
          split: test
          type: mteb/biorxiv-clustering-s2s
        metrics:
          - type: main_score
            value: 13.286390001618445
          - type: v_measure
            value: 13.286390001618445
          - type: v_measure_std
            value: 0.9260829767505151
        task:
          type: Clustering
      - dataset:
          config: default
          name: MTEB BiorxivClusteringS2S (default)
          revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
          split: test
          type: mteb/biorxiv-clustering-s2s
        metrics:
          - type: main_score
            value: 13.286390001618448
          - type: v_measure
            value: 13.286390001618448
          - type: v_measure_std
            value: 0.9260829767505148
        task:
          type: Clustering
      - dataset:
          config: default
          name: MTEB CQADupstackAndroidRetrieval (default)
          revision: f46a197baaae43b4f621051089b82a364682dfeb
          split: test
          type: mteb/cqadupstack-android
        metrics:
          - type: main_score
            value: 25.598
          - type: map_at_1
            value: 15.296000000000001
          - type: map_at_10
            value: 21.340999999999998
          - type: map_at_100
            value: 22.299
          - type: map_at_1000
            value: 22.439999999999998
          - type: map_at_20
            value: 21.823
          - type: map_at_3
            value: 19.186
          - type: map_at_5
            value: 20.307
          - type: mrr_at_1
            value: 20.171673819742487
          - type: mrr_at_10
            value: 25.96248609124146
          - type: mrr_at_100
            value: 26.832705786570926
          - type: mrr_at_1000
            value: 26.912543796379445
          - type: mrr_at_20
            value: 26.420649989525486
          - type: mrr_at_3
            value: 23.962804005722468
          - type: mrr_at_5
            value: 25.21459227467812
          - type: nauc_map_at_1000_diff1
            value: 43.81837614044429
          - type: nauc_map_at_1000_max
            value: 29.960220786660646
          - type: nauc_map_at_1000_std
            value: -7.210785807307356
          - type: nauc_map_at_100_diff1
            value: 43.80996491314085
          - type: nauc_map_at_100_max
            value: 29.944713236108733
          - type: nauc_map_at_100_std
            value: -7.255860646858293
          - type: nauc_map_at_10_diff1
            value: 44.01155643098911
          - type: nauc_map_at_10_max
            value: 29.53988039453277
          - type: nauc_map_at_10_std
            value: -7.875507294985671
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          - type: ndcg_at_10
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          - type: ndcg_at_100
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          - type: ndcg_at_1000
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          - type: ndcg_at_3
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          - type: ndcg_at_5
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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: 32.255
          - type: recall_at_3
            value: 21.221999999999998
          - type: recall_at_5
            value: 24.355
        task:
          type: Retrieval
      - dataset:
          config: default
          name: MTEB ImdbClassification (default)
          revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
          split: test
          type: mteb/imdb
        metrics:
          - type: accuracy
            value: 65.9264
          - type: ap
            value: 60.756531398956945
          - type: ap_weighted
            value: 60.756531398956945
          - type: f1
            value: 65.51017691516725
          - type: f1_weighted
            value: 65.51017691516724
          - type: main_score
            value: 65.9264
        task:
          type: Classification
      - dataset:
          config: en
          name: MTEB MTOPDomainClassification (en)
          revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
          split: test
          type: mteb/mtop_domain
        metrics:
          - type: accuracy
            value: 80.67259461924306
          - type: f1
            value: 79.9597409844225
          - type: f1_weighted
            value: 80.8035256676638
          - type: main_score
            value: 80.67259461924306
        task:
          type: Classification
      - dataset:
          config: en
          name: MTEB MTOPIntentClassification (en)
          revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
          split: test
          type: mteb/mtop_intent
        metrics:
          - type: accuracy
            value: 56.54354765161879
          - type: f1
            value: 40.667405344171634
          - type: f1_weighted
            value: 60.9216341010469
          - type: main_score
            value: 56.54354765161879
        task:
          type: Classification
      - dataset:
          config: en
          name: MTEB MassiveIntentClassification (en)
          revision: 4672e20407010da34463acc759c162ca9734bca6
          split: test
          type: mteb/amazon_massive_intent
        metrics:
          - type: accuracy
            value: 59.0719569603228
          - type: f1
            value: 58.168886864690336
          - type: f1_weighted
            value: 59.57900662649745
          - type: main_score
            value: 59.0719569603228
        task:
          type: Classification
      - dataset:
          config: en
          name: MTEB MassiveScenarioClassification (en)
          revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
          split: test
          type: mteb/amazon_massive_scenario
        metrics:
          - type: accuracy
            value: 62.59246805648958
          - type: f1
            value: 62.08069974222518
          - type: f1_weighted
            value: 62.794653215101604
          - type: main_score
            value: 62.59246805648958
        task:
          type: Classification
      - dataset:
          config: default
          name: MTEB MedrxivClusteringP2P (default)
          revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
          split: test
          type: mteb/medrxiv-clustering-p2p
        metrics:
          - type: main_score
            value: 24.526232087760377
          - type: v_measure
            value: 24.526232087760377
          - type: v_measure_std
            value: 1.3231622419863613
        task:
          type: Clustering
      - dataset:
          config: default
          name: MTEB MedrxivClusteringS2S (default)
          revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
          split: test
          type: mteb/medrxiv-clustering-s2s
        metrics:
          - type: main_score
            value: 20.194412620609075
          - type: v_measure
            value: 20.194412620609075
          - type: v_measure_std
            value: 1.636243479295598
        task:
          type: Clustering
      - dataset:
          config: default
          name: MTEB MindSmallReranking (default)
          revision: 59042f120c80e8afa9cdbb224f67076cec0fc9a7
          split: test
          type: mteb/mind_small
        metrics:
          - type: main_score
            value: 26.59574079364091
          - type: map
            value: 26.59574079364091
          - type: mrr
            value: 26.734835405117906
          - type: nAUC_map_diff1
            value: 17.816336924527814
          - type: nAUC_map_max
            value: -32.28299945433697
          - type: nAUC_map_std
            value: -18.970361215864656
          - type: nAUC_mrr_diff1
            value: 16.909657362222404
          - type: nAUC_mrr_max
            value: -26.468833047236117
          - type: nAUC_mrr_std
            value: -16.206930004122203
        task:
          type: Reranking
      - dataset:
          config: default
          name: MTEB RedditClustering (default)
          revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
          split: test
          type: mteb/reddit-clustering
        metrics:
          - type: main_score
            value: 25.20525559369379
          - type: v_measure
            value: 25.20525559369379
          - type: v_measure_std
            value: 3.716703201672722
        task:
          type: Clustering
      - dataset:
          config: default
          name: MTEB RedditClusteringP2P (default)
          revision: 385e3cb46b4cfa89021f56c4380204149d0efe33
          split: test
          type: mteb/reddit-clustering-p2p
        metrics:
          - type: main_score
            value: 36.610660271894346
          - type: v_measure
            value: 36.610660271894346
          - type: v_measure_std
            value: 10.534090572143375
        task:
          type: Clustering
      - dataset:
          config: default
          name: MTEB SICK-R (default)
          revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
          split: test
          type: mteb/sickr-sts
        metrics:
          - type: cosine_pearson
            value: 73.88162235809878
          - type: cosine_spearman
            value: 64.19649802838084
          - type: euclidean_pearson
            value: 66.51859611378926
          - type: euclidean_spearman
            value: 59.6266264848432
          - type: main_score
            value: 64.19649802838084
          - type: manhattan_pearson
            value: 66.67285438914075
          - type: manhattan_spearman
            value: 59.87530286451058
        task:
          type: STS
      - dataset:
          config: default
          name: MTEB STS12 (default)
          revision: a0d554a64d88156834ff5ae9920b964011b16384
          split: test
          type: mteb/sts12-sts
        metrics:
          - type: cosine_pearson
            value: 67.73929220446036
          - type: cosine_spearman
            value: 60.75363314544754
          - type: euclidean_pearson
            value: 56.81702291127883
          - type: euclidean_spearman
            value: 51.923738495157814
          - type: main_score
            value: 60.75363314544754
          - type: manhattan_pearson
            value: 56.86705283582077
          - type: manhattan_spearman
            value: 51.93399158324235
        task:
          type: STS
      - dataset:
          config: default
          name: MTEB STS13 (default)
          revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
          split: test
          type: mteb/sts13-sts
        metrics:
          - type: cosine_pearson
            value: 72.42112734144125
          - type: cosine_spearman
            value: 73.59653137440841
          - type: euclidean_pearson
            value: 57.561401730473264
          - type: euclidean_spearman
            value: 58.581546191861
          - type: main_score
            value: 73.59653137440841
          - type: manhattan_pearson
            value: 57.70055341285516
          - type: manhattan_spearman
            value: 58.42777714658004
        task:
          type: STS
      - dataset:
          config: default
          name: MTEB STS14 (default)
          revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
          split: test
          type: mteb/sts14-sts
        metrics:
          - type: cosine_pearson
            value: 69.6802098874101
          - type: cosine_spearman
            value: 67.31752503036513
          - type: euclidean_pearson
            value: 57.77439148526571
          - type: euclidean_spearman
            value: 57.54518624632547
          - type: main_score
            value: 67.31752503036513
          - type: manhattan_pearson
            value: 57.826113726980225
          - type: manhattan_spearman
            value: 57.62333865582037
        task:
          type: STS
      - dataset:
          config: default
          name: MTEB STS15 (default)
          revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
          split: test
          type: mteb/sts15-sts
        metrics:
          - type: cosine_pearson
            value: 72.70416316480933
          - type: cosine_spearman
            value: 74.27113308901295
          - type: euclidean_pearson
            value: 56.71321653105237
          - type: euclidean_spearman
            value: 59.50982015715706
          - type: main_score
            value: 74.27113308901295
          - type: manhattan_pearson
            value: 56.89847334180773
          - type: manhattan_spearman
            value: 59.46793125210128
        task:
          type: STS
      - dataset:
          config: default
          name: MTEB STS16 (default)
          revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
          split: test
          type: mteb/sts16-sts
        metrics:
          - type: cosine_pearson
            value: 63.90089258497955
          - type: cosine_spearman
            value: 66.87333410406687
          - type: euclidean_pearson
            value: 51.17410118962291
          - type: euclidean_spearman
            value: 54.00446857938969
          - type: main_score
            value: 66.87333410406687
          - type: manhattan_pearson
            value: 50.957252868925785
          - type: manhattan_spearman
            value: 53.90823679117365
        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: 78.3081155365183
          - type: cosine_spearman
            value: 79.95190716648233
          - type: euclidean_pearson
            value: 65.61131056255932
          - type: euclidean_spearman
            value: 66.47265770652439
          - type: main_score
            value: 79.95190716648233
          - type: manhattan_pearson
            value: 66.45361314456927
          - type: manhattan_spearman
            value: 67.37156904121075
        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: 21.052932104990603
          - type: cosine_spearman
            value: 18.11753200383624
          - type: euclidean_pearson
            value: -13.223141516540442
          - type: euclidean_spearman
            value: -13.840197821416345
          - type: main_score
            value: 18.11753200383624
          - type: manhattan_pearson
            value: -15.780391442498672
          - type: manhattan_spearman
            value: -15.964949757477415
        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: 19.391740742905483
          - type: cosine_spearman
            value: 16.72340259240136
          - type: euclidean_pearson
            value: -11.027102023055617
          - type: euclidean_spearman
            value: -14.089671183063315
          - type: main_score
            value: 16.72340259240136
          - type: manhattan_pearson
            value: -9.630121740021742
          - type: manhattan_spearman
            value: -12.712224581945044
        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: 16.543270296306552
          - type: cosine_spearman
            value: 13.326682468836701
          - type: euclidean_pearson
            value: -16.68928390130844
          - type: euclidean_spearman
            value: -16.549540032350627
          - type: main_score
            value: 13.326682468836701
          - type: manhattan_pearson
            value: -19.00891735419843
          - type: manhattan_spearman
            value: -17.698001607994165
        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: -2.9439800614294684
          - type: cosine_spearman
            value: -5.3077802551968265
          - type: euclidean_pearson
            value: -11.370503095296403
          - type: euclidean_spearman
            value: -11.559874891543458
          - type: main_score
            value: -5.3077802551968265
          - type: manhattan_pearson
            value: -11.568850533311064
          - type: manhattan_spearman
            value: -11.33350236892719
        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: 18.65393295613954
          - type: cosine_spearman
            value: 15.24163076732163
          - type: euclidean_pearson
            value: -17.67941685499847
          - type: euclidean_spearman
            value: -18.798375175098357
          - type: main_score
            value: 15.24163076732163
          - type: manhattan_pearson
            value: -18.12153260050368
          - type: manhattan_spearman
            value: -20.005495664435774
        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: 9.521577216425623
          - type: cosine_spearman
            value: 6.843613091602483
          - type: euclidean_pearson
            value: -4.097799713874057
          - type: euclidean_spearman
            value: -11.156128457955933
          - type: main_score
            value: 6.843613091602483
          - type: manhattan_pearson
            value: -4.05688864628645
          - type: manhattan_spearman
            value: -11.89166145882455
        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: -1.4988979360452002
          - type: cosine_spearman
            value: -3.2874562266915137
          - type: euclidean_pearson
            value: -20.943851828369116
          - type: euclidean_spearman
            value: -23.783711189126038
          - type: main_score
            value: -3.2874562266915137
          - type: manhattan_pearson
            value: -21.108855435186715
          - type: manhattan_spearman
            value: -23.244298623218594
        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: 15.136123348625533
          - type: cosine_spearman
            value: 20.810954246441803
          - type: euclidean_pearson
            value: 19.516242119260312
          - type: euclidean_spearman
            value: 24.474690200239962
          - type: main_score
            value: 20.810954246441803
          - type: manhattan_pearson
            value: 20.44847818877696
          - type: manhattan_spearman
            value: 27.624281563749992
        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: 3.14950505909999
          - type: cosine_spearman
            value: 8.436389259170458
          - type: euclidean_pearson
            value: 7.7506147255123725
          - type: euclidean_spearman
            value: 7.037062440876494
          - type: main_score
            value: 8.436389259170458
          - type: manhattan_pearson
            value: 9.706026714640052
          - type: manhattan_spearman
            value: 8.00200100450235
        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: 8.59590335620229
          - type: cosine_spearman
            value: 10.778094331264766
          - type: euclidean_pearson
            value: 28.70358543656486
          - type: euclidean_spearman
            value: 20.863348379272782
          - type: main_score
            value: 10.778094331264766
          - type: manhattan_pearson
            value: 32.10263640633953
          - type: manhattan_spearman
            value: 16.555236242029686
        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: 8.00733458463991
          - type: cosine_spearman
            value: 9.118706078872984
          - type: euclidean_pearson
            value: 9.07149432617858
          - type: euclidean_spearman
            value: 11.219345362943432
          - type: main_score
            value: 9.118706078872984
          - type: manhattan_pearson
            value: 8.832718333342706
          - type: manhattan_spearman
            value: 10.263754583872384
        task:
          type: STS
      - dataset:
          config: en
          name: MTEB STS22 (en)
          revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
          split: test
          type: mteb/sts22-crosslingual-sts
        metrics:
          - type: cosine_pearson
            value: 43.55249623133272
          - type: cosine_spearman
            value: 53.697978884880406
          - type: euclidean_pearson
            value: 43.8389320084649
          - type: euclidean_spearman
            value: 52.42704777306256
          - type: main_score
            value: 53.697978884880406
          - type: manhattan_pearson
            value: 43.86629307814909
          - type: manhattan_spearman
            value: 52.0381832205353
        task:
          type: STS
      - dataset:
          config: default
          name: MTEB STSBenchmark (default)
          revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
          split: test
          type: mteb/stsbenchmark-sts
        metrics:
          - type: cosine_pearson
            value: 67.31658836868895
          - type: cosine_spearman
            value: 66.82184731765354
          - type: euclidean_pearson
            value: 57.80273593674898
          - type: euclidean_spearman
            value: 57.772446648657706
          - type: main_score
            value: 66.82184731765354
          - type: manhattan_pearson
            value: 58.234209002194795
          - type: manhattan_spearman
            value: 58.12293550703129
        task:
          type: STS
      - dataset:
          config: default
          name: MTEB SciDocsRR (default)
          revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
          split: test
          type: mteb/scidocs-reranking
        metrics:
          - type: main_score
            value: 66.86139617126783
          - type: map
            value: 66.86139617126783
          - type: mrr
            value: 87.3149943738179
          - type: nAUC_map_diff1
            value: 10.92124948908669
          - type: nAUC_map_max
            value: 55.79229386744934
          - type: nAUC_map_std
            value: 65.42609776668083
          - type: nAUC_mrr_diff1
            value: 42.06337561377432
          - type: nAUC_mrr_max
            value: 72.26477089952296
          - type: nAUC_mrr_std
            value: 68.47174098478668
        task:
          type: Reranking
      - dataset:
          config: default
          name: MTEB SprintDuplicateQuestions (default)
          revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
          split: test
          type: mteb/sprintduplicatequestions-pairclassification
        metrics:
          - type: cosine_accuracy
            value: 99.6009900990099
          - type: cosine_accuracy_threshold
            value: 78.9186954498291
          - type: cosine_ap
            value: 84.68208216332572
          - type: cosine_f1
            value: 78.88487351574601
          - type: cosine_f1_threshold
            value: 76.20431184768677
          - type: cosine_precision
            value: 81.53681963713981
          - type: cosine_recall
            value: 76.4
          - type: dot_accuracy
            value: 99.05346534653465
          - type: dot_accuracy_threshold
            value: 62070.60546875
          - type: dot_ap
            value: 30.67111560824568
          - type: dot_f1
            value: 36.43184660275114
          - type: dot_f1_threshold
            value: 38959.15222167969
          - type: dot_precision
            value: 31.236597569692638
          - type: dot_recall
            value: 43.7
          - type: euclidean_accuracy
            value: 99.42871287128713
          - type: euclidean_accuracy_threshold
            value: 1293.6470031738281
          - type: euclidean_ap
            value: 68.4948217545871
          - type: euclidean_f1
            value: 66.38161411010155
          - type: euclidean_f1_threshold
            value: 1388.7130737304688
          - type: euclidean_precision
            value: 71.29735935706086
          - type: euclidean_recall
            value: 62.1
          - type: main_score
            value: 84.68208216332572
          - type: manhattan_accuracy
            value: 99.41584158415841
          - type: manhattan_accuracy_threshold
            value: 11503.255462646484
          - type: manhattan_ap
            value: 68.54990551262247
          - type: manhattan_f1
            value: 66.26173384870238
          - type: manhattan_f1_threshold
            value: 12185.600280761719
          - type: manhattan_precision
            value: 73.98273736128237
          - type: manhattan_recall
            value: 60
          - type: max_accuracy
            value: 99.6009900990099
          - type: max_ap
            value: 84.68208216332572
          - type: max_f1
            value: 78.88487351574601
          - type: max_precision
            value: 81.53681963713981
          - type: max_recall
            value: 76.4
          - type: similarity_accuracy
            value: 99.6009900990099
          - type: similarity_accuracy_threshold
            value: 78.9186954498291
          - type: similarity_ap
            value: 84.68208080875644
          - type: similarity_f1
            value: 78.88487351574601
          - type: similarity_f1_threshold
            value: 76.20431184768677
          - type: similarity_precision
            value: 81.53681963713981
          - type: similarity_recall
            value: 76.4
        task:
          type: PairClassification
      - dataset:
          config: default
          name: MTEB StackExchangeClustering (default)
          revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
          split: test
          type: mteb/stackexchange-clustering
        metrics:
          - type: main_score
            value: 35.27926530004693
          - type: v_measure
            value: 35.27926530004693
          - type: v_measure_std
            value: 4.213594415514492
        task:
          type: Clustering
      - dataset:
          config: default
          name: MTEB StackExchangeClusteringP2P (default)
          revision: 815ca46b2622cec33ccafc3735d572c266efdb44
          split: test
          type: mteb/stackexchange-clustering-p2p
        metrics:
          - type: main_score
            value: 29.27592909966068
          - type: v_measure
            value: 29.27592909966068
          - type: v_measure_std
            value: 1.4306687739012842
        task:
          type: Clustering
      - dataset:
          config: default
          name: MTEB StackOverflowDupQuestions (default)
          revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
          split: test
          type: mteb/stackoverflowdupquestions-reranking
        metrics:
          - type: main_score
            value: 42.46430536151378
          - type: map
            value: 42.46430536151378
          - type: mrr
            value: 42.978697160682444
          - type: nAUC_map_diff1
            value: 34.16488374642183
          - type: nAUC_map_max
            value: 15.990699582552214
          - type: nAUC_map_std
            value: 7.0505058354865024
          - type: nAUC_mrr_diff1
            value: 33.67219566480288
          - type: nAUC_mrr_max
            value: 16.990618160743995
          - type: nAUC_mrr_std
            value: 7.524962858906838
        task:
          type: Reranking
      - dataset:
          config: default
          name: MTEB SummEval (default)
          revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
          split: test
          type: mteb/summeval
        metrics:
          - type: cosine_pearson
            value: 30.183315092157393
          - type: cosine_spearman
            value: 30.164573201350965
          - type: dot_pearson
            value: 15.532441039164112
          - type: dot_spearman
            value: 17.744350263113876
          - type: main_score
            value: 30.164573201350965
          - type: pearson
            value: 30.183314669218987
          - type: spearman
            value: 30.161615957372895
        task:
          type: Summarization
      - dataset:
          config: default
          name: MTEB ToxicConversationsClassification (default)
          revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
          split: test
          type: mteb/toxic_conversations_50k
        metrics:
          - type: accuracy
            value: 62.1435546875
          - type: ap
            value: 10.253828258206063
          - type: ap_weighted
            value: 10.253828258206063
          - type: f1
            value: 47.395641667877385
          - type: f1_weighted
            value: 70.68010031561886
          - type: main_score
            value: 62.1435546875
        task:
          type: Classification
      - dataset:
          config: default
          name: MTEB TweetSentimentExtractionClassification (default)
          revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
          split: test
          type: mteb/tweet_sentiment_extraction
        metrics:
          - type: accuracy
            value: 48.39841539332202
          - type: f1
            value: 48.58310905274024
          - type: f1_weighted
            value: 48.03031996995187
          - type: main_score
            value: 48.39841539332202
        task:
          type: Classification
      - dataset:
          config: default
          name: MTEB TwentyNewsgroupsClustering (default)
          revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
          split: test
          type: mteb/twentynewsgroups-clustering
        metrics:
          - type: main_score
            value: 21.965681413174785
          - type: v_measure
            value: 21.965681413174785
          - type: v_measure_std
            value: 2.2097945438628344
        task:
          type: Clustering
      - dataset:
          config: default
          name: MTEB TwitterSemEval2015 (default)
          revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
          split: test
          type: mteb/twittersemeval2015-pairclassification
        metrics:
          - type: cosine_accuracy
            value: 81.76670441676104
          - type: cosine_accuracy_threshold
            value: 77.6945948600769
          - type: cosine_ap
            value: 57.43644750160504
          - type: cosine_f1
            value: 54.339194554736245
          - type: cosine_f1_threshold
            value: 66.83574914932251
          - type: cosine_precision
            value: 47.66169154228856
          - type: cosine_recall
            value: 63.19261213720316
          - type: dot_accuracy
            value: 78.04136615604696
          - type: dot_accuracy_threshold
            value: 69279.91943359375
          - type: dot_ap
            value: 41.27462915286439
          - type: dot_f1
            value: 45.9406677206361
          - type: dot_f1_threshold
            value: 38870.428466796875
          - type: dot_precision
            value: 35.473215568002296
          - type: dot_recall
            value: 65.17150395778364
          - type: euclidean_accuracy
            value: 80.03218692257256
          - type: euclidean_accuracy_threshold
            value: 1667.4659729003906
          - type: euclidean_ap
            value: 51.44165670701795
          - type: euclidean_f1
            value: 50.63679245283019
          - type: euclidean_f1_threshold
            value: 2015.814208984375
          - type: euclidean_precision
            value: 45.778251599147126
          - type: euclidean_recall
            value: 56.6490765171504
          - type: main_score
            value: 57.43645711181132
          - type: manhattan_accuracy
            value: 80.07987125230972
          - type: manhattan_accuracy_threshold
            value: 14477.607727050781
          - type: manhattan_ap
            value: 51.609695680028544
          - type: manhattan_f1
            value: 50.732328592655485
          - type: manhattan_f1_threshold
            value: 18645.140075683594
          - type: manhattan_precision
            value: 42.43607954545455
          - type: manhattan_recall
            value: 63.06068601583114
          - type: max_accuracy
            value: 81.76670441676104
          - type: max_ap
            value: 57.43645711181132
          - type: max_f1
            value: 54.339194554736245
          - type: max_precision
            value: 47.66169154228856
          - type: max_recall
            value: 65.17150395778364
          - type: similarity_accuracy
            value: 81.76670441676104
          - type: similarity_accuracy_threshold
            value: 77.6945948600769
          - type: similarity_ap
            value: 57.43645711181132
          - type: similarity_f1
            value: 54.339194554736245
          - type: similarity_f1_threshold
            value: 66.83574914932251
          - type: similarity_precision
            value: 47.66169154228856
          - type: similarity_recall
            value: 63.19261213720316
        task:
          type: PairClassification
      - dataset:
          config: default
          name: MTEB TwitterURLCorpus (default)
          revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
          split: test
          type: mteb/twitterurlcorpus-pairclassification
        metrics:
          - type: cosine_accuracy
            value: 85.71040478130942
          - type: cosine_accuracy_threshold
            value: 69.46260929107666
          - type: cosine_ap
            value: 78.33655877180354
          - type: cosine_f1
            value: 70.4509162801308
          - type: cosine_f1_threshold
            value: 66.09716415405273
          - type: cosine_precision
            value: 69.5884031846177
          - type: cosine_recall
            value: 71.33507853403141
          - type: dot_accuracy
            value: 82.07008964955175
          - type: dot_accuracy_threshold
            value: 27785.427856445312
          - type: dot_ap
            value: 67.05507223333423
          - type: dot_f1
            value: 63.016089065717374
          - type: dot_f1_threshold
            value: 23387.98828125
          - type: dot_precision
            value: 57.63166294286626
          - type: dot_recall
            value: 69.51031721589159
          - type: euclidean_accuracy
            value: 83.10435828773237
          - type: euclidean_accuracy_threshold
            value: 1362.842082977295
          - type: euclidean_ap
            value: 70.21973250044095
          - type: euclidean_f1
            value: 62.38352870453863
          - type: euclidean_f1_threshold
            value: 1582.8761100769043
          - type: euclidean_precision
            value: 60.91869680070443
          - type: euclidean_recall
            value: 63.92054203880505
          - type: main_score
            value: 78.33656919387448
          - type: manhattan_accuracy
            value: 83.06942989094578
          - type: manhattan_accuracy_threshold
            value: 12189.000701904297
          - type: manhattan_ap
            value: 70.16377530413878
          - type: manhattan_f1
            value: 62.365993052183335
          - type: manhattan_f1_threshold
            value: 14111.676025390625
          - type: manhattan_precision
            value: 60.56736559529856
          - type: manhattan_recall
            value: 64.27471512165074
          - type: max_accuracy
            value: 85.71040478130942
          - type: max_ap
            value: 78.33656919387448
          - type: max_f1
            value: 70.4509162801308
          - type: max_precision
            value: 69.5884031846177
          - type: max_recall
            value: 71.33507853403141
          - type: similarity_accuracy
            value: 85.71040478130942
          - type: similarity_accuracy_threshold
            value: 69.46260929107666
          - type: similarity_ap
            value: 78.33656919387448
          - type: similarity_f1
            value: 70.4509162801308
          - type: similarity_f1_threshold
            value: 66.09715819358826
          - type: similarity_precision
            value: 69.5884031846177
          - type: similarity_recall
            value: 71.33507853403141
        task:
          type: PairClassification

🪲 brown-beetle-tiny-v1 Model Card

Beetles are some of the most diverse and interesting creatures on Earth. They are found in every environment, from the deepest oceans to the highest mountains. They are also known for their ability to adapt to a wide range of habitats and lifestyles. They are small, fast and powerful!

The beetle series of models are made as good starting points for Static Embedding training (via TokenLearn or Fine-tuning), as well as decent Static Embedding models. Each beetle model is made to be an improvement over the original M2V_base_output model in some way, and that's the threshold we set for each model (except the brown beetle series, which is the original model).

This model has been distilled from baai/bge-base-en-v1.5, with PCA with 128 dimensions and applying Zipf.

The brown beetle series is made for convinience in loading and using the model instead of having to run it, though it is pretty fast to reproduce anyways. If you want to use the original model by the folks from the Minish Lab, you can use the M2V_base_output model.

Version Information

• brown-beetle-base-v0: The original model, without using PCA or Zipf. The lack of PCA and Zipf also makes this a decent model for further training.
• brown-beetle-base-v0.1: The original model, with PCA but of the same size as the original model. This model is great if you want to experiment with Zipf or other weighting methods.
• brown-beetle-base-v1: The original model, with PCA and Zipf.
• brown-beetle-small-v1: A smaller version of the original model, with PCA and Zipf. Equivalent to M2V_base_output.
• brown-beetle-tiny-v1: A tiny version of the original model, with PCA and Zipf.
• brown-beetle-base-v1.1: The original model, with PCA with 768 dimensions, applying Zipf and applying SIF re-weighting, learnt from a subset of the C4 corpus. This model is significantly better than the M2V_base_output model.
• brown-beetle-small-v1.1: A smaller version of the original model, with PCA with 256 dimensions, applying Zipf and applying SIF re-weighting, learnt from a subset of the C4 corpus. This model is significantly better than the M2V_base_output model but slightly worse than the brown-beetle-base-v1.1 model.
• brown-beetle-tiny-v1.1: A tiny version of the original model, with PCA with 128 dimensions, applying Zipf and applying SIF re-weighting, learnt from a subset of the C4 corpus. This model is significantly better than the M2V_base_output model but slightly worse than the brown-beetle-small-v1.1 model.

Installation

Install model2vec using pip:

pip install model2vec

Usage

Load this model using the from_pretrained method:

from model2vec import StaticModel

# Load a pretrained Model2Vec model
model = StaticModel.from_pretrained("bhavnicksm/brown-beetle-tiny-v1")

# Compute text embeddings
embeddings = model.encode(["Example sentence"])

Read more about the Model2Vec library here.

Reproduce this model

To reproduce this model, you must install the model2vec[distill] package and use the following code:

from model2vec.distill import distill

# Distill the model
m2v_model = distill(
    model_name="bge-base-en-v1.5",
    pca_dims=128,
    apply_zipf=True,
)

# Save the model
m2v_model.save_pretrained("brown-beetle-tiny-v1")

Comparison with other models

Coming soon...

Acknowledgements

This model is made using the Model2Vec library. Credit goes to the Minish Lab team for developing this library.

Citation

Please cite the Model2Vec repository if you use this model in your work.

@software{minishlab2024model2vec,
  authors = {Stephan Tulkens, Thomas van Dongen},
  title = {Model2Vec: Turn any Sentence Transformer into a Small Fast Model},
  year = {2024},
  url = {https://github.com/MinishLab/model2vec},
}