transformers gguf language granite embeddings multilingual mteb llama-cpp gguf-my-repo sentence-similarity en ar cs de es fr it ja ko nl pt zh base_model:ibm-granite/granite-embedding-278m-multilingual base_model:quantized:ibm-granite/granite-embedding-278m-multilingual license:apache-2.0 model-index endpoints_compatible region:us feature-extraction
---
base_model: ibm-granite/granite-embedding-278m-multilingual
language:
- en
- ar
- cs
- de
- es
- fr
- it
- ja
- ko
- nl
- pt
- zh
library_name: transformers
license: apache-2.0
pipeline_tag: sentence-similarity
tags:
- language
- granite
- embeddings
- multilingual
- mteb
- llama-cpp
- gguf-my-repo
model-index:
- name: ibm-granite/granite-embedding-278m-multilingual
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en-ext)
      type: mteb/amazon_counterfactual
      config: en-ext
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 73.4333
    - type: f1
      value: 61.2301
    - type: f1_weighted
      value: 78.40899999999999
    - type: ap
      value: 23.347
    - type: ap_weighted
      value: 23.347
    - type: main_score
      value: 73.4333
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: mteb/amazon_counterfactual
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 71.806
    - type: f1
      value: 65.6467
    - type: f1_weighted
      value: 74.4815
    - type: ap
      value: 34.045700000000004
    - type: ap_weighted
      value: 34.045700000000004
    - type: main_score
      value: 71.806
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification (default)
      type: mteb/amazon_polarity
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 67.5907
    - type: f1
      value: 67.36370000000001
    - type: f1_weighted
      value: 67.36370000000001
    - type: ap
      value: 62.0368
    - type: ap_weighted
      value: 62.0368
    - type: main_score
      value: 67.5907
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: mteb/amazon_reviews_multi
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 37.278
    - type: f1
      value: 36.4099
    - type: f1_weighted
      value: 36.4099
    - type: main_score
      value: 37.278
  - task:
      type: Retrieval
    dataset:
      name: MTEB AppsRetrieval (default)
      type: CoIR-Retrieval/apps
      config: default
      split: test
      revision: f22508f96b7a36c2415181ed8bb76f76e04ae2d5
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      value: 3.453
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      value: 4.882000000000001
    - type: ndcg_at_5
      value: 5.564
    - type: ndcg_at_10
      value: 6.214
    - type: ndcg_at_20
      value: 6.814000000000001
    - type: ndcg_at_100
      value: 8.581
    - type: ndcg_at_1000
      value: 12.215
    - type: map_at_1
      value: 3.453
    - type: map_at_3
      value: 4.515000000000001
    - type: map_at_5
      value: 4.89
    - type: map_at_10
      value: 5.151
    - type: map_at_20
      value: 5.313
    - type: map_at_100
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    - type: map_at_1000
      value: 5.638
    - type: recall_at_1
      value: 3.453
    - type: recall_at_3
      value: 5.949999999999999
    - type: recall_at_5
      value: 7.623
    - type: recall_at_10
      value: 9.668000000000001
    - type: recall_at_20
      value: 12.058
    - type: recall_at_100
      value: 21.859
    - type: recall_at_1000
      value: 52.722
    - type: precision_at_1
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    - type: precision_at_3
      value: 1.983
    - type: precision_at_5
      value: 1.525
    - type: precision_at_10
      value: 0.967
    - type: precision_at_20
      value: 0.603
    - type: precision_at_100
      value: 0.219
    - type: precision_at_1000
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    - type: mrr_at_1
      value: 3.4528999999999996
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      value: 4.5153
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    - type: mrr_at_10
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  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna (default)
      type: mteb/arguana
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
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      value: 45.050000000000004
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      value: 50.458999999999996
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      value: 57.918000000000006
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    - type: recall_at_10
      value: 83.001
    - type: recall_at_20
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    - type: recall_at_1000
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    - type: precision_at_1
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      value: 10.6379
    - type: nauc_mrr_at_1000_max
      value: -5.9887999999999995
    - type: nauc_mrr_at_1000_std
      value: -3.4465000000000003
    - type: nauc_mrr_at_1000_diff1
      value: 10.641399999999999
    - type: main_score
      value: 55.24400000000001
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P (default)
      type: mteb/arxiv-clustering-p2p
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 43.1321
    - type: v_measure_std
      value: 13.594000000000001
    - type: main_score
      value: 43.1321
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S (default)
      type: mteb/arxiv-clustering-s2s
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 32.9343
    - type: v_measure_std
      value: 14.2478
    - type: main_score
      value: 32.9343
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions (default)
      type: mteb/askubuntudupquestions-reranking
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 62.3443
    - type: mrr
      value: 76.3882
    - type: nAUC_map_max
      value: 28.3073
    - type: nAUC_map_std
      value: 15.5307
    - type: nAUC_map_diff1
      value: 12.6855
    - type: nAUC_mrr_max
      value: 36.409200000000006
    - type: nAUC_mrr_std
      value: 22.6271
    - type: nAUC_mrr_diff1
      value: 19.1211
    - type: main_score
      value: 62.3443
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES (default)
      type: mteb/biosses-sts
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: pearson
      value: 84.3253
    - type: spearman
      value: 81.6362
    - type: cosine_pearson
      value: 84.3253
    - type: cosine_spearman
      value: 81.6362
    - type: manhattan_pearson
      value: 82.70960000000001
    - type: manhattan_spearman
      value: 81.3037
    - type: euclidean_pearson
      value: 82.6906
    - type: euclidean_spearman
      value: 81.6362
    - type: main_score
      value: 81.6362
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification (default)
      type: mteb/banking77
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 78.0617
    - type: f1
      value: 77.2085
    - type: f1_weighted
      value: 77.2085
    - type: main_score
      value: 78.0617
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P (default)
      type: mteb/biorxiv-clustering-p2p
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 35.8271
    - type: v_measure_std
      value: 0.7191000000000001
    - type: main_score
      value: 35.8271
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S (default)
      type: mteb/biorxiv-clustering-s2s
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 30.3905
    - type: v_measure_std
      value: 0.7136
    - type: main_score
      value: 30.3905
  - task:
      type: Retrieval
    dataset:
      name: MTEB COIRCodeSearchNetRetrieval (python)
      type: CoIR-Retrieval/CodeSearchNet
      config: python
      split: test
      revision: 4adc7bc41202b5c13543c9c886a25f340634dab3
    metrics:
    - type: ndcg_at_1
      value: 83.22800000000001
    - type: ndcg_at_3
      value: 87.41799999999999
    - type: ndcg_at_5
      value: 88.089
    - type: ndcg_at_10
      value: 88.789
    - type: ndcg_at_20
      value: 89.156
    - type: ndcg_at_100
      value: 89.60900000000001
    - type: ndcg_at_1000
      value: 89.79
    - type: map_at_1
      value: 83.22800000000001
    - type: map_at_3
      value: 86.431
    - type: map_at_5
      value: 86.80499999999999
    - type: map_at_10
      value: 87.09599999999999
    - type: map_at_20
      value: 87.198
    - type: map_at_100
      value: 87.263
    - type: map_at_1000
      value: 87.27000000000001
    - type: recall_at_1
      value: 83.22800000000001
    - type: recall_at_3
      value: 90.253
    - type: recall_at_5
      value: 91.876
    - type: recall_at_10
      value: 94.03399999999999
    - type: recall_at_20
      value: 95.475
    - type: recall_at_100
      value: 97.882
    - type: recall_at_1000
      value: 99.316
    - type: precision_at_1
      value: 83.22800000000001
    - type: precision_at_3
      value: 30.084
    - type: precision_at_5
      value: 18.375
    - type: precision_at_10
      value: 9.403
    - type: precision_at_20
      value: 4.774
    - type: precision_at_100
      value: 0.979
    - type: precision_at_1000
      value: 0.099
    - type: mrr_at_1
      value: 83.235
    - type: mrr_at_3
      value: 86.4336
    - type: mrr_at_5
      value: 86.8077
    - type: mrr_at_10
      value: 87.0979
    - type: mrr_at_20
      value: 87.2001
    - type: mrr_at_100
      value: 87.26509999999999
    - type: mrr_at_1000
      value: 87.2718
    - type: nauc_ndcg_at_1_max
      value: 82.2462
    - type: nauc_ndcg_at_1_std
      value: 11.4635
    - type: nauc_ndcg_at_1_diff1
      value: 90.5106
    - type: nauc_ndcg_at_3_max
      value: 83.9742
    - type: nauc_ndcg_at_3_std
      value: 12.7085
    - type: nauc_ndcg_at_3_diff1
      value: 88.2182
    - type: nauc_ndcg_at_5_max
      value: 84.18870000000001
    - type: nauc_ndcg_at_5_std
      value: 13.167499999999999
    - type: nauc_ndcg_at_5_diff1
      value: 88.44999999999999
    - type: nauc_ndcg_at_10_max
      value: 84.2219
    - type: nauc_ndcg_at_10_std
      value: 13.5219
    - type: nauc_ndcg_at_10_diff1
      value: 88.6386
    - type: nauc_ndcg_at_20_max
      value: 84.2289
    - type: nauc_ndcg_at_20_std
      value: 14.0686
    - type: nauc_ndcg_at_20_diff1
      value: 88.7516
    - type: nauc_ndcg_at_100_max
      value: 84.12049999999999
    - type: nauc_ndcg_at_100_std
      value: 14.1778
    - type: nauc_ndcg_at_100_diff1
      value: 88.8592
    - type: nauc_ndcg_at_1000_max
      value: 84.0367
    - type: nauc_ndcg_at_1000_std
      value: 13.9125
    - type: nauc_ndcg_at_1000_diff1
      value: 88.9054
    - type: nauc_map_at_1_max
      value: 82.2462
    - type: nauc_map_at_1_std
      value: 11.4635
    - type: nauc_map_at_1_diff1
      value: 90.5106
    - type: nauc_map_at_3_max
      value: 83.5638
    - type: nauc_map_at_3_std
      value: 12.3576
    - type: nauc_map_at_3_diff1
      value: 88.8502
    - type: nauc_map_at_5_max
      value: 83.6625
    - type: nauc_map_at_5_std
      value: 12.582099999999999
    - type: nauc_map_at_5_diff1
      value: 88.9876
    - type: nauc_map_at_10_max
      value: 83.6605
    - type: nauc_map_at_10_std
      value: 12.6859
    - type: nauc_map_at_10_diff1
      value: 89.07119999999999
    - type: nauc_map_at_20_max
      value: 83.65629999999999
    - type: nauc_map_at_20_std
      value: 12.8105
    - type: nauc_map_at_20_diff1
      value: 89.1036
    - type: nauc_map_at_100_max
      value: 83.6413
    - type: nauc_map_at_100_std
      value: 12.823699999999999
    - type: nauc_map_at_100_diff1
      value: 89.1193
    - type: nauc_map_at_1000_max
      value: 83.6386
    - type: nauc_map_at_1000_std
      value: 12.815999999999999
    - type: nauc_map_at_1000_diff1
      value: 89.1209
    - type: nauc_recall_at_1_max
      value: 82.2462
    - type: nauc_recall_at_1_std
      value: 11.4635
    - type: nauc_recall_at_1_diff1
      value: 90.5106
    - type: nauc_recall_at_3_max
      value: 85.512
    - type: nauc_recall_at_3_std
      value: 14.061399999999999
    - type: nauc_recall_at_3_diff1
      value: 85.7898
    - type: nauc_recall_at_5_max
      value: 86.5434
    - type: nauc_recall_at_5_std
      value: 15.894400000000001
    - type: nauc_recall_at_5_diff1
      value: 86.0934
    - type: nauc_recall_at_10_max
      value: 87.59909999999999
    - type: nauc_recall_at_10_std
      value: 18.9872
    - type: nauc_recall_at_10_diff1
      value: 86.26740000000001
    - type: nauc_recall_at_20_max
      value: 88.76190000000001
    - type: nauc_recall_at_20_std
      value: 25.6618
    - type: nauc_recall_at_20_diff1
      value: 86.5002
    - type: nauc_recall_at_100_max
      value: 91.0976
    - type: nauc_recall_at_100_std
      value: 40.9161
    - type: nauc_recall_at_100_diff1
      value: 86.5441
    - type: nauc_recall_at_1000_max
      value: 96.018
    - type: nauc_recall_at_1000_std
      value: 65.6217
    - type: nauc_recall_at_1000_diff1
      value: 86.8456
    - type: nauc_precision_at_1_max
      value: 82.2462
    - type: nauc_precision_at_1_std
      value: 11.4635
    - type: nauc_precision_at_1_diff1
      value: 90.5106
    - type: nauc_precision_at_3_max
      value: 85.512
    - type: nauc_precision_at_3_std
      value: 14.061399999999999
    - type: nauc_precision_at_3_diff1
      value: 85.7898
    - type: nauc_precision_at_5_max
      value: 86.5434
    - type: nauc_precision_at_5_std
      value: 15.894400000000001
    - type: nauc_precision_at_5_diff1
      value: 86.0934
    - type: nauc_precision_at_10_max
      value: 87.59909999999999
    - type: nauc_precision_at_10_std
      value: 18.9872
    - type: nauc_precision_at_10_diff1
      value: 86.26740000000001
    - type: nauc_precision_at_20_max
      value: 88.76190000000001
    - type: nauc_precision_at_20_std
      value: 25.6618
    - type: nauc_precision_at_20_diff1
      value: 86.5002
    - type: nauc_precision_at_100_max
      value: 91.0976
    - type: nauc_precision_at_100_std
      value: 40.9161
    - type: nauc_precision_at_100_diff1
      value: 86.5441
    - type: nauc_precision_at_1000_max
      value: 96.018
    - type: nauc_precision_at_1000_std
      value: 65.6217
    - type: nauc_precision_at_1000_diff1
      value: 86.8456
    - type: nauc_mrr_at_1_max
      value: 82.2393
    - type: nauc_mrr_at_1_std
      value: 11.5163
    - type: nauc_mrr_at_1_diff1
      value: 90.50160000000001
    - type: nauc_mrr_at_3_max
      value: 83.5623
    - type: nauc_mrr_at_3_std
      value: 12.395
    - type: nauc_mrr_at_3_diff1
      value: 88.8463
    - type: nauc_mrr_at_5_max
      value: 83.6609
    - type: nauc_mrr_at_5_std
      value: 12.620700000000001
    - type: nauc_mrr_at_5_diff1
      value: 88.9836
    - type: nauc_mrr_at_10_max
      value: 83.6589
    - type: nauc_mrr_at_10_std
      value: 12.7255
    - type: nauc_mrr_at_10_diff1
      value: 89.0672
    - type: nauc_mrr_at_20_max
      value: 83.6546
    - type: nauc_mrr_at_20_std
      value: 12.8504
    - type: nauc_mrr_at_20_diff1
      value: 89.09949999999999
    - type: nauc_mrr_at_100_max
      value: 83.6396
    - type: nauc_mrr_at_100_std
      value: 12.8638
    - type: nauc_mrr_at_100_diff1
      value: 89.1152
    - type: nauc_mrr_at_1000_max
      value: 83.6369
    - type: nauc_mrr_at_1000_std
      value: 12.856100000000001
    - type: nauc_mrr_at_1000_diff1
      value: 89.1168
    - type: main_score
      value: 88.789
  - task:
      type: Retrieval
    dataset:
      name: MTEB COIRCodeSearchNetRetrieval (javascript)
      type: CoIR-Retrieval/CodeSearchNet
      config: javascript
      split: test
      revision: 4adc7bc41202b5c13543c9c886a25f340634dab3
    metrics:
    - type: ndcg_at_1
      value: 29.14
    - type: ndcg_at_3
      value: 35.185
    - type: ndcg_at_5
      value: 37.013
    - type: ndcg_at_10
      value: 38.778
    - type: ndcg_at_20
      value: 40.184999999999995
    - type: ndcg_at_100
      value: 42.394999999999996
    - type: ndcg_at_1000
      value: 44.243
    - type: map_at_1
      value: 29.14
    - type: map_at_3
      value: 33.703
    - type: map_at_5
      value: 34.717999999999996
    - type: map_at_10
      value: 35.443999999999996
    - type: map_at_20
      value: 35.831
    - type: map_at_100
      value: 36.132999999999996
    - type: map_at_1000
      value: 36.193999999999996
    - type: recall_at_1
      value: 29.14
    - type: recall_at_3
      value: 39.471000000000004
    - type: recall_at_5
      value: 43.908
    - type: recall_at_10
      value: 49.376999999999995
    - type: recall_at_20
      value: 54.937999999999995
    - type: recall_at_100
      value: 66.91
    - type: recall_at_1000
      value: 81.98100000000001
    - type: precision_at_1
      value: 29.14
    - type: precision_at_3
      value: 13.157
    - type: precision_at_5
      value: 8.782
    - type: precision_at_10
      value: 4.938
    - type: precision_at_20
      value: 2.7470000000000003
    - type: precision_at_100
      value: 0.6689999999999999
    - type: precision_at_1000
      value: 0.082
    - type: mrr_at_1
      value: 29.140100000000004
    - type: mrr_at_3
      value: 33.703
    - type: mrr_at_5
      value: 34.7179
    - type: mrr_at_10
      value: 35.4443
    - type: mrr_at_20
      value: 35.830600000000004
    - type: mrr_at_100
      value: 36.1332
    - type: mrr_at_1000
      value: 36.1935
    - type: nauc_ndcg_at_1_max
      value: 46.9222
    - type: nauc_ndcg_at_1_std
      value: 3.3564999999999996
    - type: nauc_ndcg_at_1_diff1
      value: 60.583
    - type: nauc_ndcg_at_3_max
      value: 49.205799999999996
    - type: nauc_ndcg_at_3_std
      value: 5.976299999999999
    - type: nauc_ndcg_at_3_diff1
      value: 55.09610000000001
    - type: nauc_ndcg_at_5_max
      value: 49.0533
    - type: nauc_ndcg_at_5_std
      value: 6.5834
    - type: nauc_ndcg_at_5_diff1
      value: 54.430800000000005
    - type: nauc_ndcg_at_10_max
      value: 48.626799999999996
    - type: nauc_ndcg_at_10_std
      value: 7.4441
    - type: nauc_ndcg_at_10_diff1
      value: 53.1986
    - type: nauc_ndcg_at_20_max
      value: 48.7498
    - type: nauc_ndcg_at_20_std
      value: 8.3344
    - type: nauc_ndcg_at_20_diff1
      value: 52.844
    - type: nauc_ndcg_at_100_max
      value: 48.7164
    - type: nauc_ndcg_at_100_std
      value: 9.1646
    - type: nauc_ndcg_at_100_diff1
      value: 52.6307
    - type: nauc_ndcg_at_1000_max
      value: 48.634699999999995
    - type: nauc_ndcg_at_1000_std
      value: 9.3865
    - type: nauc_ndcg_at_1000_diff1
      value: 53.100899999999996
    - type: nauc_map_at_1_max
      value: 46.9222
    - type: nauc_map_at_1_std
      value: 3.3564999999999996
    - type: nauc_map_at_1_diff1
      value: 60.583
    - type: nauc_map_at_3_max
      value: 48.7099
    - type: nauc_map_at_3_std
      value: 5.2638
    - type: nauc_map_at_3_diff1
      value: 56.370200000000004
    - type: nauc_map_at_5_max
      value: 48.6303
    - type: nauc_map_at_5_std
      value: 5.5931
    - type: nauc_map_at_5_diff1
      value: 55.9968
    - type: nauc_map_at_10_max
      value: 48.4549
    - type: nauc_map_at_10_std
      value: 5.949800000000001
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      value: 55.4941
    - type: nauc_map_at_20_max
      value: 48.4854
    - type: nauc_map_at_20_std
      value: 6.1861
    - type: nauc_map_at_20_diff1
      value: 55.4072
    - type: nauc_map_at_100_max
      value: 48.4835
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      value: 6.2885
    - type: nauc_map_at_100_diff1
      value: 55.3743
    - type: nauc_map_at_1000_max
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    - type: nauc_map_at_1000_std
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    - type: nauc_map_at_1000_diff1
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    - type: nauc_recall_at_1_max
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    - type: nauc_recall_at_1_std
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    - type: nauc_recall_at_1_diff1
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    - type: nauc_recall_at_3_max
      value: 50.5754
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    - type: nauc_recall_at_5_max
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    - type: nauc_recall_at_10_max
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    - type: nauc_recall_at_10_std
      value: 12.2017
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      value: 46.042
    - type: nauc_recall_at_20_max
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    - type: nauc_recall_at_20_std
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    - type: nauc_recall_at_100_max
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      value: 41.2386
    - type: nauc_recall_at_1000_max
      value: 48.7068
    - type: nauc_recall_at_1000_std
      value: 34.4874
    - type: nauc_recall_at_1000_diff1
      value: 42.088
    - type: nauc_precision_at_1_max
      value: 46.9222
    - type: nauc_precision_at_1_std
      value: 3.3564999999999996
    - type: nauc_precision_at_1_diff1
      value: 60.583
    - type: nauc_precision_at_3_max
      value: 50.5754
    - type: nauc_precision_at_3_std
      value: 8.005700000000001
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      value: 51.542100000000005
    - type: nauc_precision_at_5_max
      value: 50.199000000000005
    - type: nauc_precision_at_5_std
      value: 9.5088
    - type: nauc_precision_at_5_diff1
      value: 49.9358
    - type: nauc_precision_at_10_max
      value: 48.899100000000004
    - type: nauc_precision_at_10_std
      value: 12.2017
    - type: nauc_precision_at_10_diff1
      value: 46.042
    - type: nauc_precision_at_20_max
      value: 49.433899999999994
    - type: nauc_precision_at_20_std
      value: 16.1228
    - type: nauc_precision_at_20_diff1
      value: 44.1762
    - type: nauc_precision_at_100_max
      value: 49.2626
    - type: nauc_precision_at_100_std
      value: 23.1356
    - type: nauc_precision_at_100_diff1
      value: 41.2386
    - type: nauc_precision_at_1000_max
      value: 48.7068
    - type: nauc_precision_at_1000_std
      value: 34.4874
    - type: nauc_precision_at_1000_diff1
      value: 42.088
    - type: nauc_mrr_at_1_max
      value: 46.9222
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  - task:
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  - task:
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      revision: 4adc7bc41202b5c13543c9c886a25f340634dab3
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  - task:
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      type: CoIR-Retrieval/CodeSearchNet
      config: java
      split: test
      revision: 4adc7bc41202b5c13543c9c886a25f340634dab3
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      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
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  - task:
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      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
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  - task:
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      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
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      type: CoIR-Retrieval/CodeSearchNet-ccr
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      revision: 6e1effa2c03723c5fde48ee912b5ee08d4f211e8
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  - task:
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      type: CoIR-Retrieval/CodeSearchNet-ccr
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      revision: 6e1effa2c03723c5fde48ee912b5ee08d4f211e8
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  - task:
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  - task:
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  - task:
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      type: code-search-net/code_search_net
      config: ruby
      split: test
      revision: fdc6a9e39575768c27eb8a2a5f702bf846eb4759
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  - task:
      type: Retrieval
    dataset:
      name: MTEB CodeSearchNetRetrieval (java)
      type: code-search-net/code_search_net
      config: java
      split: test
      revision: fdc6a9e39575768c27eb8a2a5f702bf846eb4759
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    - type: recall_at_10
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    - type: recall_at_20
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    - type: recall_at_100
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    - type: recall_at_1000
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    - type: precision_at_1
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    - type: precision_at_10
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    - type: precision_at_20
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    - type: precision_at_100
      value: 0.958
    - type: precision_at_1000
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    - type: mrr_at_1
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    - type: mrr_at_3
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    - type: mrr_at_5
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    - type: mrr_at_10
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    - type: mrr_at_20
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  - task:
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      type: code-search-net/code_search_net
      config: php
      split: test
      revision: fdc6a9e39575768c27eb8a2a5f702bf846eb4759
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    - type: recall_at_1000
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  - task:
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  - task:
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      type: mteb/imdb
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      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
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      config: ar
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  - task:
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      type: miracl/mmteb-miracl
      config: bn
      split: dev
      revision: main
    metrics:
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    - type: recall_at_1000
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    - type: precision_at_1
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  - task:
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  - task:
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  - task:
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      type: mteb/msmarco
      config: default
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  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: mteb/mtop_domain
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
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  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: mteb/mtop_intent
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
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  - task:
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    dataset:
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      type: mteb/amazon_massive_intent
      config: en
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    metrics:
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  - task:
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    dataset:
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      type: mteb/amazon_massive_scenario
      config: en
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    metrics:
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      value: 70.928
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    - type: main_score
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  - task:
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    dataset:
      name: MTEB MedrxivClusteringP2P (default)
      type: mteb/medrxiv-clustering-p2p
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
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    - type: v_measure_std
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    - type: main_score
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  - task:
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    dataset:
      name: MTEB MedrxivClusteringS2S (default)
      type: mteb/medrxiv-clustering-s2s
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
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  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking (default)
      type: mteb/mind_small
      config: default
      split: test
      revision: 59042f120c80e8afa9cdbb224f67076cec0fc9a7
    metrics:
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    - type: mrr
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    - type: nAUC_map_max
      value: -19.592000000000002
    - type: nAUC_map_std
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      value: -0.8847
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    - type: main_score
      value: 30.5381
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus (default)
      type: mteb/nfcorpus
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
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  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering (default)
      type: mteb/reddit-clustering
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
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    - type: main_score
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  - task:
      type: Clustering
    dataset:
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      type: mteb/reddit-clustering-p2p
      config: default
      split: test
      revision: 385e3cb46b4cfa89021f56c4380204149d0efe33
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    - type: main_score
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  - task:
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    dataset:
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      type: mteb/scidocs
      config: default
      split: test
      revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88
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  - task:
      type: STS
    dataset:
      name: MTEB SICK-R (default)
      type: mteb/sickr-sts
      config: default
      split: test
      revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
    metrics:
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    - type: cosine_pearson
      value: 75.5378
    - type: cosine_spearman
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    - type: manhattan_pearson
      value: 72.905
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      value: 68.9036
    - type: euclidean_pearson
      value: 72.7586
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      value: 68.7448
    - type: main_score
      value: 68.7448
  - task:
      type: STS
    dataset:
      name: MTEB STS12 (default)
      type: mteb/sts12-sts
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
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    - type: spearman
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    - type: cosine_pearson
      value: 81.6341
    - type: cosine_spearman
      value: 75.1911
    - type: manhattan_pearson
      value: 78.4046
    - type: manhattan_spearman
      value: 75.1706
    - type: euclidean_pearson
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    - type: main_score
      value: 75.1911
  - task:
      type: STS
    dataset:
      name: MTEB STS13 (default)
      type: mteb/sts13-sts
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
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    - type: spearman
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    - type: cosine_pearson
      value: 76.4378
    - type: cosine_spearman
      value: 77.3053
    - type: manhattan_pearson
      value: 77.1958
    - type: manhattan_spearman
      value: 77.2543
    - type: euclidean_pearson
      value: 77.2317
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      value: 77.3053
    - type: main_score
      value: 77.3053
  - task:
      type: STS
    dataset:
      name: MTEB STS14 (default)
      type: mteb/sts14-sts
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
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    - type: spearman
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    - type: cosine_pearson
      value: 78.4342
    - type: cosine_spearman
      value: 74.9479
    - type: manhattan_pearson
      value: 77.12219999999999
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      value: 74.924
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      value: 77.14800000000001
    - type: euclidean_spearman
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    - type: main_score
      value: 74.9479
  - task:
      type: STS
    dataset:
      name: MTEB STS15 (default)
      type: mteb/sts15-sts
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
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    - type: spearman
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    - type: cosine_pearson
      value: 85.1908
    - type: cosine_spearman
      value: 86.0174
    - type: manhattan_pearson
      value: 85.4436
    - type: manhattan_spearman
      value: 86.0332
    - type: euclidean_pearson
      value: 85.4339
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      value: 86.0174
    - type: main_score
      value: 86.0174
  - task:
      type: STS
    dataset:
      name: MTEB STS16 (default)
      type: mteb/sts16-sts
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
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      value: 80.5421
    - type: spearman
      value: 81.9568
    - type: cosine_pearson
      value: 80.5421
    - type: cosine_spearman
      value: 81.9568
    - type: manhattan_pearson
      value: 81.1013
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      value: 81.8165
    - type: euclidean_pearson
      value: 81.24510000000001
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      value: 81.9568
    - type: main_score
      value: 81.9568
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-tr)
      type: mteb/sts17-crosslingual-sts
      config: en-tr
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
    - type: pearson
      value: 48.2717
    - type: spearman
      value: 44.642900000000004
    - type: cosine_pearson
      value: 48.2717
    - type: cosine_spearman
      value: 44.642900000000004
    - type: manhattan_pearson
      value: 50.314400000000006
    - type: manhattan_spearman
      value: 44.982299999999995
    - type: euclidean_pearson
      value: 50.1685
    - type: euclidean_spearman
      value: 44.642900000000004
    - type: main_score
      value: 44.642900000000004
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (it-en)
      type: mteb/sts17-crosslingual-sts
      config: it-en
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
    - type: pearson
      value: 67.8601
    - type: spearman
      value: 68.2763
    - type: cosine_pearson
      value: 67.8601
    - type: cosine_spearman
      value: 68.2763
    - type: manhattan_pearson
      value: 68.1563
    - type: manhattan_spearman
      value: 68.4724
    - type: euclidean_pearson
      value: 68.1026
    - type: euclidean_spearman
      value: 68.2763
    - type: main_score
      value: 68.2763
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: mteb/sts17-crosslingual-sts
      config: en-en
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
    - type: pearson
      value: 78.05539999999999
    - type: spearman
      value: 78.5929
    - type: cosine_pearson
      value: 78.05539999999999
    - type: cosine_spearman
      value: 78.5929
    - type: manhattan_pearson
      value: 78.408
    - type: manhattan_spearman
      value: 78.8622
    - type: euclidean_pearson
      value: 78.1413
    - type: euclidean_spearman
      value: 78.5929
    - type: main_score
      value: 78.5929
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-ar)
      type: mteb/sts17-crosslingual-sts
      config: en-ar
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
    - type: pearson
      value: 59.4349
    - type: spearman
      value: 59.838800000000006
    - type: cosine_pearson
      value: 59.4349
    - type: cosine_spearman
      value: 59.838800000000006
    - type: manhattan_pearson
      value: 60.7565
    - type: manhattan_spearman
      value: 60.5824
    - type: euclidean_pearson
      value: 60.247099999999996
    - type: euclidean_spearman
      value: 59.838800000000006
    - type: main_score
      value: 59.838800000000006
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (fr-en)
      type: mteb/sts17-crosslingual-sts
      config: fr-en
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
    - type: pearson
      value: 73.84039999999999
    - type: spearman
      value: 74.2498
    - type: cosine_pearson
      value: 73.84039999999999
    - type: cosine_spearman
      value: 74.2498
    - type: manhattan_pearson
      value: 74.6784
    - type: manhattan_spearman
      value: 74.4608
    - type: euclidean_pearson
      value: 74.5596
    - type: euclidean_spearman
      value: 74.2498
    - type: main_score
      value: 74.2498
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (nl-en)
      type: mteb/sts17-crosslingual-sts
      config: nl-en
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
    - type: pearson
      value: 67.9218
    - type: spearman
      value: 68.0418
    - type: cosine_pearson
      value: 67.9218
    - type: cosine_spearman
      value: 68.0418
    - type: manhattan_pearson
      value: 68.51
    - type: manhattan_spearman
      value: 68.1968
    - type: euclidean_pearson
      value: 68.343
    - type: euclidean_spearman
      value: 68.0418
    - type: main_score
      value: 68.0418
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (es-en)
      type: mteb/sts17-crosslingual-sts
      config: es-en
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
    - type: pearson
      value: 70.381
    - type: spearman
      value: 69.5729
    - type: cosine_pearson
      value: 70.381
    - type: cosine_spearman
      value: 69.5729
    - type: manhattan_pearson
      value: 70.8688
    - type: manhattan_spearman
      value: 69.4406
    - type: euclidean_pearson
      value: 71.0267
    - type: euclidean_spearman
      value: 69.5729
    - type: main_score
      value: 69.5729
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-de)
      type: mteb/sts17-crosslingual-sts
      config: en-de
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
    - type: pearson
      value: 70.0196
    - type: spearman
      value: 69.7175
    - type: cosine_pearson
      value: 70.0196
    - type: cosine_spearman
      value: 69.7175
    - type: manhattan_pearson
      value: 71.40990000000001
    - type: manhattan_spearman
      value: 70.1461
    - type: euclidean_pearson
      value: 70.88799999999999
    - type: euclidean_spearman
      value: 69.7175
    - type: main_score
      value: 69.7175
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (de-en)
      type: mteb/sts22-crosslingual-sts
      config: de-en
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: pearson
      value: 65.7536
    - type: spearman
      value: 60.04429999999999
    - type: cosine_pearson
      value: 65.7536
    - type: cosine_spearman
      value: 60.04429999999999
    - type: manhattan_pearson
      value: 68.58579999999999
    - type: manhattan_spearman
      value: 60.3699
    - type: euclidean_pearson
      value: 68.3761
    - type: euclidean_spearman
      value: 60.04429999999999
    - type: main_score
      value: 60.04429999999999
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: mteb/sts22-crosslingual-sts
      config: en
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: pearson
      value: 68.997
    - type: spearman
      value: 68.1508
    - type: cosine_pearson
      value: 68.997
    - type: cosine_spearman
      value: 68.1508
    - type: manhattan_pearson
      value: 68.9229
    - type: manhattan_spearman
      value: 68.0124
    - type: euclidean_pearson
      value: 69.0519
    - type: euclidean_spearman
      value: 68.1508
    - type: main_score
      value: 68.1508
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (es-en)
      type: mteb/sts22-crosslingual-sts
      config: es-en
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: pearson
      value: 80.2006
    - type: spearman
      value: 80.4702
    - type: cosine_pearson
      value: 80.2006
    - type: cosine_spearman
      value: 80.4702
    - type: manhattan_pearson
      value: 80.81009999999999
    - type: manhattan_spearman
      value: 80.6037
    - type: euclidean_pearson
      value: 80.66290000000001
    - type: euclidean_spearman
      value: 80.4702
    - type: main_score
      value: 80.4702
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (zh-en)
      type: mteb/sts22-crosslingual-sts
      config: zh-en
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: pearson
      value: 74.0885
    - type: spearman
      value: 72.4574
    - type: cosine_pearson
      value: 74.0885
    - type: cosine_spearman
      value: 72.4574
    - type: manhattan_pearson
      value: 75.25659999999999
    - type: manhattan_spearman
      value: 71.9695
    - type: euclidean_pearson
      value: 75.4999
    - type: euclidean_spearman
      value: 72.4574
    - type: main_score
      value: 72.4574
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (pl-en)
      type: mteb/sts22-crosslingual-sts
      config: pl-en
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: pearson
      value: 74.1794
    - type: spearman
      value: 70.6749
    - type: cosine_pearson
      value: 74.1794
    - type: cosine_spearman
      value: 70.6749
    - type: manhattan_pearson
      value: 74.3245
    - type: manhattan_spearman
      value: 71.2375
    - type: euclidean_pearson
      value: 73.221
    - type: euclidean_spearman
      value: 70.6749
    - type: main_score
      value: 70.6749
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark (default)
      type: mteb/stsbenchmark-sts
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: pearson
      value: 76.7328
    - type: spearman
      value: 78.4076
    - type: cosine_pearson
      value: 76.7328
    - type: cosine_spearman
      value: 78.4076
    - type: manhattan_pearson
      value: 78.24950000000001
    - type: manhattan_spearman
      value: 78.23400000000001
    - type: euclidean_pearson
      value: 78.3628
    - type: euclidean_spearman
      value: 78.4076
    - type: main_score
      value: 78.4076
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR (default)
      type: mteb/scidocs-reranking
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 79.6097
    - type: mrr
      value: 94.12939999999999
    - type: nAUC_map_max
      value: 58.7937
    - type: nAUC_map_std
      value: 69.6785
    - type: nAUC_map_diff1
      value: 7.4891
    - type: nAUC_mrr_max
      value: 84.7821
    - type: nAUC_mrr_std
      value: 77.6636
    - type: nAUC_mrr_diff1
      value: 49.763600000000004
    - type: main_score
      value: 79.6097
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact (default)
      type: mteb/scifact
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: ndcg_at_1
      value: 54.0
    - type: ndcg_at_3
      value: 60.851
    - type: ndcg_at_5
      value: 63.410999999999994
    - type: ndcg_at_10
      value: 65.847
    - type: ndcg_at_20
      value: 66.937
    - type: ndcg_at_100
      value: 68.262
    - type: ndcg_at_1000
      value: 69.341
    - type: map_at_1
      value: 51.093999999999994
    - type: map_at_3
      value: 58.044
    - type: map_at_5
      value: 59.702999999999996
    - type: map_at_10
      value: 60.885999999999996
    - type: map_at_20
      value: 61.266
    - type: map_at_100
      value: 61.482000000000006
    - type: map_at_1000
      value: 61.519
    - type: recall_at_1
      value: 51.093999999999994
    - type: recall_at_3
      value: 66.128
    - type: recall_at_5
      value: 72.456
    - type: recall_at_10
      value: 79.3
    - type: recall_at_20
      value: 83.2
    - type: recall_at_100
      value: 90.0
    - type: recall_at_1000
      value: 98.667
    - type: precision_at_1
      value: 54.0
    - type: precision_at_3
      value: 23.778
    - type: precision_at_5
      value: 15.933
    - type: precision_at_10
      value: 8.967
    - type: precision_at_20
      value: 4.75
    - type: precision_at_100
      value: 1.03
    - type: precision_at_1000
      value: 0.11199999999999999
    - type: mrr_at_1
      value: 54.0
    - type: mrr_at_3
      value: 60.3889
    - type: mrr_at_5
      value: 61.7556
    - type: mrr_at_10
      value: 62.5984
    - type: mrr_at_20
      value: 62.85039999999999
    - type: mrr_at_100
      value: 63.0155
    - type: mrr_at_1000
      value: 63.052699999999994
    - type: nauc_ndcg_at_1_max
      value: 56.6373
    - type: nauc_ndcg_at_1_std
      value: 2.1765
    - type: nauc_ndcg_at_1_diff1
      value: 71.14829999999999
    - type: nauc_ndcg_at_3_max
      value: 53.7965
    - type: nauc_ndcg_at_3_std
      value: -3.4057999999999997
    - type: nauc_ndcg_at_3_diff1
      value: 63.712199999999996
    - type: nauc_ndcg_at_5_max
      value: 56.96059999999999
    - type: nauc_ndcg_at_5_std
      value: 1.4794
    - type: nauc_ndcg_at_5_diff1
      value: 64.65419999999999
    - type: nauc_ndcg_at_10_max
      value: 59.4154
    - type: nauc_ndcg_at_10_std
      value: 5.2752
    - type: nauc_ndcg_at_10_diff1
      value: 64.3098
    - type: nauc_ndcg_at_20_max
      value: 59.7717
    - type: nauc_ndcg_at_20_std
      value: 6.2032
    - type: nauc_ndcg_at_20_diff1
      value: 64.18599999999999
    - type: nauc_ndcg_at_100_max
      value: 59.2146
    - type: nauc_ndcg_at_100_std
      value: 6.0138
    - type: nauc_ndcg_at_100_diff1
      value: 64.0895
    - type: nauc_ndcg_at_1000_max
      value: 58.5714
    - type: nauc_ndcg_at_1000_std
      value: 4.8872
    - type: nauc_ndcg_at_1000_diff1
      value: 64.66969999999999
    - type: nauc_map_at_1_max
      value: 51.2417
    - type: nauc_map_at_1_std
      value: -5.42
    - type: nauc_map_at_1_diff1
      value: 70.0616
    - type: nauc_map_at_3_max
      value: 51.9587
    - type: nauc_map_at_3_std
      value: -5.3035
    - type: nauc_map_at_3_diff1
      value: 65.282
    - type: nauc_map_at_5_max
      value: 54.1516
    - type: nauc_map_at_5_std
      value: -2.2858
    - type: nauc_map_at_5_diff1
      value: 65.86659999999999
    - type: nauc_map_at_10_max
      value: 55.5412
    - type: nauc_map_at_10_std
      value: -0.34299999999999997
    - type: nauc_map_at_10_diff1
      value: 65.89620000000001
    - type: nauc_map_at_20_max
      value: 55.7967
    - type: nauc_map_at_20_std
      value: 0.13799999999999998
    - type: nauc_map_at_20_diff1
      value: 65.8685
    - type: nauc_map_at_100_max
      value: 55.74550000000001
    - type: nauc_map_at_100_std
      value: 0.211
    - type: nauc_map_at_100_diff1
      value: 65.8557
    - type: nauc_map_at_1000_max
      value: 55.728
    - type: nauc_map_at_1000_std
      value: 0.1875
    - type: nauc_map_at_1000_diff1
      value: 65.8748
    - type: nauc_recall_at_1_max
      value: 51.2417
    - type: nauc_recall_at_1_std
      value: -5.42
    - type: nauc_recall_at_1_diff1
      value: 70.0616
    - type: nauc_recall_at_3_max
      value: 52.4327
    - type: nauc_recall_at_3_std
      value: -6.7153
    - type: nauc_recall_at_3_diff1
      value: 57.111999999999995
    - type: nauc_recall_at_5_max
      value: 60.5827
    - type: nauc_recall_at_5_std
      value: 7.1365
    - type: nauc_recall_at_5_diff1
      value: 58.3449
    - type: nauc_recall_at_10_max
      value: 70.24770000000001
    - type: nauc_recall_at_10_std
      value: 22.0896
    - type: nauc_recall_at_10_diff1
      value: 55.7264
    - type: nauc_recall_at_20_max
      value: 73.483
    - type: nauc_recall_at_20_std
      value: 29.653299999999998
    - type: nauc_recall_at_20_diff1
      value: 53.54750000000001
    - type: nauc_recall_at_100_max
      value: 74.0321
    - type: nauc_recall_at_100_std
      value: 37.491400000000006
    - type: nauc_recall_at_100_diff1
      value: 47.3918
    - type: nauc_recall_at_1000_max
      value: 69.5378
    - type: nauc_recall_at_1000_std
      value: 60.5042
    - type: nauc_recall_at_1000_diff1
      value: 19.5028
    - type: nauc_precision_at_1_max
      value: 56.6373
    - type: nauc_precision_at_1_std
      value: 2.1765
    - type: nauc_precision_at_1_diff1
      value: 71.14829999999999
    - type: nauc_precision_at_3_max
      value: 51.811099999999996
    - type: nauc_precision_at_3_std
      value: 8.4319
    - type: nauc_precision_at_3_diff1
      value: 48.545500000000004
    - type: nauc_precision_at_5_max
      value: 55.4685
    - type: nauc_precision_at_5_std
      value: 26.387
    - type: nauc_precision_at_5_diff1
      value: 39.6201
    - type: nauc_precision_at_10_max
      value: 53.2436
    - type: nauc_precision_at_10_std
      value: 41.6957
    - type: nauc_precision_at_10_diff1
      value: 24.6115
    - type: nauc_precision_at_20_max
      value: 48.353699999999996
    - type: nauc_precision_at_20_std
      value: 47.253
    - type: nauc_precision_at_20_diff1
      value: 15.687599999999998
    - type: nauc_precision_at_100_max
      value: 36.771100000000004
    - type: nauc_precision_at_100_std
      value: 48.1335
    - type: nauc_precision_at_100_diff1
      value: 2.6454
    - type: nauc_precision_at_1000_max
      value: 23.0391
    - type: nauc_precision_at_1000_std
      value: 53.26499999999999
    - type: nauc_precision_at_1000_diff1
      value: -15.0974
    - type: nauc_mrr_at_1_max
      value: 56.6373
    - type: nauc_mrr_at_1_std
      value: 2.1765
    - type: nauc_mrr_at_1_diff1
      value: 71.14829999999999
    - type: nauc_mrr_at_3_max
      value: 57.6843
    - type: nauc_mrr_at_3_std
      value: 2.4692
    - type: nauc_mrr_at_3_diff1
      value: 66.10340000000001
    - type: nauc_mrr_at_5_max
      value: 59.2453
    - type: nauc_mrr_at_5_std
      value: 5.1308
    - type: nauc_mrr_at_5_diff1
      value: 66.7377
    - type: nauc_mrr_at_10_max
      value: 59.5575
    - type: nauc_mrr_at_10_std
      value: 5.7778
    - type: nauc_mrr_at_10_diff1
      value: 66.36149999999999
    - type: nauc_mrr_at_20_max
      value: 59.466300000000004
    - type: nauc_mrr_at_20_std
      value: 5.6867
    - type: nauc_mrr_at_20_diff1
      value: 66.37100000000001
    - type: nauc_mrr_at_100_max
      value: 59.404999999999994
    - type: nauc_mrr_at_100_std
      value: 5.6528
    - type: nauc_mrr_at_100_diff1
      value: 66.41040000000001
    - type: nauc_mrr_at_1000_max
      value: 59.3919
    - type: nauc_mrr_at_1000_std
      value: 5.6358
    - type: nauc_mrr_at_1000_diff1
      value: 66.43050000000001
    - type: main_score
      value: 65.847
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions (default)
      type: mteb/sprintduplicatequestions-pairclassification
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: similarity_accuracy
      value: 99.7386
    - type: similarity_accuracy_threshold
      value: 84.1442
    - type: similarity_f1
      value: 86.41980000000001
    - type: similarity_f1_threshold
      value: 84.1442
    - type: similarity_precision
      value: 88.98310000000001
    - type: similarity_recall
      value: 84.0
    - type: similarity_ap
      value: 93.50309999999999
    - type: cosine_accuracy
      value: 99.7386
    - type: cosine_accuracy_threshold
      value: 84.1442
    - type: cosine_f1
      value: 86.41980000000001
    - type: cosine_f1_threshold
      value: 84.1442
    - type: cosine_precision
      value: 88.98310000000001
    - type: cosine_recall
      value: 84.0
    - type: cosine_ap
      value: 93.50309999999999
    - type: manhattan_accuracy
      value: 99.7406
    - type: manhattan_accuracy_threshold
      value: 1243.0971
    - type: manhattan_f1
      value: 86.5641
    - type: manhattan_f1_threshold
      value: 1243.0971
    - type: manhattan_precision
      value: 88.8421
    - type: manhattan_recall
      value: 84.39999999999999
    - type: manhattan_ap
      value: 93.50840000000001
    - type: euclidean_accuracy
      value: 99.7386
    - type: euclidean_accuracy_threshold
      value: 56.313
    - type: euclidean_f1
      value: 86.41980000000001
    - type: euclidean_f1_threshold
      value: 56.313
    - type: euclidean_precision
      value: 88.98310000000001
    - type: euclidean_recall
      value: 84.0
    - type: euclidean_ap
      value: 93.50309999999999
    - type: dot_accuracy
      value: 99.7386
    - type: dot_accuracy_threshold
      value: 84.1442
    - type: dot_f1
      value: 86.41980000000001
    - type: dot_f1_threshold
      value: 84.1442
    - type: dot_precision
      value: 88.98310000000001
    - type: dot_recall
      value: 84.0
    - type: dot_ap
      value: 93.50309999999999
    - type: max_accuracy
      value: 99.7406
    - type: max_f1
      value: 86.5641
    - type: max_precision
      value: 88.98310000000001
    - type: max_recall
      value: 84.39999999999999
    - type: max_ap
      value: 93.50840000000001
    - type: main_score
      value: 93.50840000000001
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering (default)
      type: mteb/stackexchange-clustering
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 55.9311
    - type: v_measure_std
      value: 5.0881
    - type: main_score
      value: 55.9311
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P (default)
      type: mteb/stackexchange-clustering-p2p
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 32.9298
    - type: v_measure_std
      value: 1.7169
    - type: main_score
      value: 32.9298
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions (default)
      type: mteb/stackoverflowdupquestions-reranking
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 51.7759
    - type: mrr
      value: 52.7456
    - type: nAUC_map_max
      value: 15.138499999999999
    - type: nAUC_map_std
      value: 9.876999999999999
    - type: nAUC_map_diff1
      value: 37.8337
    - type: nAUC_mrr_max
      value: 16.128600000000002
    - type: nAUC_mrr_std
      value: 10.4175
    - type: nAUC_mrr_diff1
      value: 37.3753
    - type: main_score
      value: 51.7759
  - task:
      type: Retrieval
    dataset:
      name: MTEB StackOverflowQA (default)
      type: CoIR-Retrieval/stackoverflow-qa
      config: default
      split: test
      revision: db8f169f3894c14a00251061f957b2063eef2bd5
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      value: 75.473
    - type: ndcg_at_5
      value: 77.118
    - type: ndcg_at_10
      value: 78.45
    - type: ndcg_at_20
      value: 79.181
    - type: ndcg_at_100
      value: 80.259
    - type: ndcg_at_1000
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    - type: map_at_1
      value: 68.205
    - type: map_at_3
      value: 73.763
    - type: map_at_5
      value: 74.68299999999999
    - type: map_at_10
      value: 75.234
    - type: map_at_20
      value: 75.43900000000001
    - type: map_at_100
      value: 75.59
    - type: map_at_1000
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    - type: recall_at_1
      value: 68.205
    - type: recall_at_3
      value: 80.391
    - type: recall_at_5
      value: 84.353
    - type: recall_at_10
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    - type: recall_at_20
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    - type: recall_at_100
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    - type: recall_at_1000
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    - type: precision_at_5
      value: 16.871
    - 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: mrr_at_3
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    - type: mrr_at_5
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    - type: mrr_at_20
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    - type: nauc_ndcg_at_1_max
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      value: 80.8018
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      value: -5.6573
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      value: 80.8018
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      value: 77.837
    - type: nauc_recall_at_1_max
      value: 70.0997
    - type: nauc_recall_at_1_std
      value: -6.6174
    - type: nauc_recall_at_1_diff1
      value: 80.8018
    - type: nauc_recall_at_3_max
      value: 73.3015
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    - type: nauc_recall_at_5_diff1
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    - type: nauc_recall_at_10_max
      value: 71.8002
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      value: 72.9934
    - type: nauc_recall_at_20_std
      value: 2.0923000000000003
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    - type: nauc_recall_at_100_max
      value: 76.0971
    - type: nauc_recall_at_100_std
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    - type: nauc_recall_at_1000_max
      value: 76.7462
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      value: 69.8675
    - type: nauc_precision_at_1_max
      value: 70.0997
    - type: nauc_precision_at_1_std
      value: -6.6174
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      value: 80.8018
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      value: 73.3015
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      value: -4.9247
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      value: 72.6201
    - type: nauc_precision_at_5_max
      value: 73.3818
    - type: nauc_precision_at_5_std
      value: -4.196
    - type: nauc_precision_at_5_diff1
      value: 71.8984
    - type: nauc_precision_at_10_max
      value: 71.8002
    - type: nauc_precision_at_10_std
      value: 1.0328
    - type: nauc_precision_at_10_diff1
      value: 69.0552
    - type: nauc_precision_at_20_max
      value: 72.9934
    - type: nauc_precision_at_20_std
      value: 2.0923000000000003
    - type: nauc_precision_at_20_diff1
      value: 67.3481
    - type: nauc_precision_at_100_max
      value: 76.0971
    - type: nauc_precision_at_100_std
      value: 12.4217
    - type: nauc_precision_at_100_diff1
      value: 66.6112
    - type: nauc_precision_at_1000_max
      value: 76.7462
    - type: nauc_precision_at_1000_std
      value: 50.754200000000004
    - type: nauc_precision_at_1000_diff1
      value: 69.8675
    - type: nauc_mrr_at_1_max
      value: 70.0997
    - type: nauc_mrr_at_1_std
      value: -6.6174
    - type: nauc_mrr_at_1_diff1
      value: 80.8018
    - type: nauc_mrr_at_3_max
      value: 71.46329999999999
    - type: nauc_mrr_at_3_std
      value: -5.9901
    - type: nauc_mrr_at_3_diff1
      value: 77.7281
    - type: nauc_mrr_at_5_max
      value: 71.4046
    - type: nauc_mrr_at_5_std
      value: -5.9794
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      value: 77.8163
    - type: nauc_mrr_at_10_max
      value: 71.2618
    - type: nauc_mrr_at_10_std
      value: -5.702999999999999
    - type: nauc_mrr_at_10_diff1
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    - type: nauc_mrr_at_20_max
      value: 71.30330000000001
    - type: nauc_mrr_at_20_std
      value: -5.691
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      value: 77.7683
    - type: nauc_mrr_at_100_max
      value: 71.3035
    - type: nauc_mrr_at_100_std
      value: -5.680000000000001
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      value: 77.8324
    - type: nauc_mrr_at_1000_max
      value: 71.3013
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      value: -5.6772
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    - type: main_score
      value: 78.45
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval (default)
      type: mteb/summeval
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
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      value: 31.7097
    - type: spearman
      value: 32.0256
    - type: cosine_spearman
      value: 32.0256
    - type: cosine_pearson
      value: 31.7097
    - type: dot_spearman
      value: 32.0256
    - type: dot_pearson
      value: 31.7097
    - type: main_score
      value: 32.0256
  - task:
      type: Retrieval
    dataset:
      name: MTEB SyntheticText2SQL (default)
      type: CoIR-Retrieval/synthetic-text2sql
      config: default
      split: test
      revision: 686b87296c3a0191b5d9415a00526c62db9fce09
    metrics:
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      value: 3.5549999999999997
    - type: ndcg_at_3
      value: 41.534
    - type: ndcg_at_5
      value: 44.847
    - type: ndcg_at_10
      value: 47.344
    - type: ndcg_at_20
      value: 48.826
    - type: ndcg_at_100
      value: 50.442
    - type: ndcg_at_1000
      value: 50.937
    - type: map_at_1
      value: 3.5549999999999997
    - type: map_at_3
      value: 33.083
    - type: map_at_5
      value: 34.928
    - type: map_at_10
      value: 35.964
    - type: map_at_20
      value: 36.376
    - type: map_at_100
      value: 36.61
    - type: map_at_1000
      value: 36.63
    - type: recall_at_1
      value: 3.5549999999999997
    - type: recall_at_3
      value: 65.63
    - type: recall_at_5
      value: 73.646
    - type: recall_at_10
      value: 81.337
    - type: recall_at_20
      value: 87.165
    - type: recall_at_100
      value: 95.71
    - type: recall_at_1000
      value: 99.556
    - type: precision_at_1
      value: 3.5549999999999997
    - type: precision_at_3
      value: 21.877
    - type: precision_at_5
      value: 14.729000000000001
    - type: precision_at_10
      value: 8.134
    - type: precision_at_20
      value: 4.358
    - type: precision_at_100
      value: 0.9570000000000001
    - type: precision_at_1000
      value: 0.1
    - type: mrr_at_1
      value: 31.721100000000003
    - type: mrr_at_3
      value: 48.6754
    - type: mrr_at_5
      value: 50.3093
    - type: mrr_at_10
      value: 51.2454
    - type: mrr_at_20
      value: 51.629999999999995
    - type: mrr_at_100
      value: 51.8552
    - type: mrr_at_1000
      value: 51.8747
    - type: nauc_ndcg_at_1_max
      value: 6.543
    - type: nauc_ndcg_at_1_std
      value: -11.0614
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      value: 77.4191
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  - task:
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      type: mteb/toxic_conversations_50k
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  - task:
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      type: mteb/tweet_sentiment_extraction
      config: default
      split: test
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  - task:
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      split: test
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    metrics:
    - type: v_measure
      value: 38.6199
    - type: v_measure_std
      value: 2.3855999999999997
    - type: main_score
      value: 38.6199
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015 (default)
      type: mteb/twittersemeval2015-pairclassification
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: similarity_accuracy
      value: 82.9886
    - type: similarity_accuracy_threshold
      value: 86.3901
    - type: similarity_f1
      value: 60.866200000000006
    - type: similarity_f1_threshold
      value: 83.9821
    - type: similarity_precision
      value: 59.333499999999994
    - type: similarity_recall
      value: 62.480199999999996
    - type: similarity_ap
      value: 64.413
    - type: cosine_accuracy
      value: 82.9886
    - type: cosine_accuracy_threshold
      value: 86.3901
    - type: cosine_f1
      value: 60.866200000000006
    - type: cosine_f1_threshold
      value: 83.9821
    - type: cosine_precision
      value: 59.333499999999994
    - type: cosine_recall
      value: 62.480199999999996
    - type: cosine_ap
      value: 64.413
    - type: manhattan_accuracy
      value: 82.9409
    - type: manhattan_accuracy_threshold
      value: 1144.7468000000001
    - type: manhattan_f1
      value: 60.760400000000004
    - type: manhattan_f1_threshold
      value: 1291.7232999999999
    - type: manhattan_precision
      value: 54.7126
    - type: manhattan_recall
      value: 68.3113
    - type: manhattan_ap
      value: 64.3592
    - type: euclidean_accuracy
      value: 82.9886
    - type: euclidean_accuracy_threshold
      value: 52.1726
    - type: euclidean_f1
      value: 60.866200000000006
    - type: euclidean_f1_threshold
      value: 56.6001
    - type: euclidean_precision
      value: 59.333499999999994
    - type: euclidean_recall
      value: 62.480199999999996
    - type: euclidean_ap
      value: 64.4131
    - type: dot_accuracy
      value: 82.9886
    - type: dot_accuracy_threshold
      value: 86.3901
    - type: dot_f1
      value: 60.866200000000006
    - type: dot_f1_threshold
      value: 83.9821
    - type: dot_precision
      value: 59.333499999999994
    - type: dot_recall
      value: 62.480199999999996
    - type: dot_ap
      value: 64.413
    - type: max_accuracy
      value: 82.9886
    - type: max_f1
      value: 60.866200000000006
    - type: max_precision
      value: 59.333499999999994
    - type: max_recall
      value: 68.3113
    - type: max_ap
      value: 64.4131
    - type: main_score
      value: 64.4131
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus (default)
      type: mteb/twitterurlcorpus-pairclassification
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: similarity_accuracy
      value: 88.95100000000001
    - type: similarity_accuracy_threshold
      value: 82.18520000000001
    - type: similarity_f1
      value: 77.9051
    - type: similarity_f1_threshold
      value: 80.3369
    - type: similarity_precision
      value: 76.07310000000001
    - type: similarity_recall
      value: 79.8275
    - type: similarity_ap
      value: 86.1545
    - type: cosine_accuracy
      value: 88.95100000000001
    - type: cosine_accuracy_threshold
      value: 82.18520000000001
    - type: cosine_f1
      value: 77.9051
    - type: cosine_f1_threshold
      value: 80.3369
    - type: cosine_precision
      value: 76.07310000000001
    - type: cosine_recall
      value: 79.8275
    - type: cosine_ap
      value: 86.1545
    - type: manhattan_accuracy
      value: 88.9277
    - type: manhattan_accuracy_threshold
      value: 1338.2836
    - type: manhattan_f1
      value: 77.8186
    - type: manhattan_f1_threshold
      value: 1372.5978
    - type: manhattan_precision
      value: 76.5745
    - type: manhattan_recall
      value: 79.1038
    - type: manhattan_ap
      value: 86.114
    - type: euclidean_accuracy
      value: 88.95100000000001
    - type: euclidean_accuracy_threshold
      value: 59.6905
    - type: euclidean_f1
      value: 77.9051
    - type: euclidean_f1_threshold
      value: 62.71060000000001
    - type: euclidean_precision
      value: 76.07310000000001
    - type: euclidean_recall
      value: 79.8275
    - type: euclidean_ap
      value: 86.1544
    - type: dot_accuracy
      value: 88.95100000000001
    - type: dot_accuracy_threshold
      value: 82.18520000000001
    - type: dot_f1
      value: 77.9051
    - type: dot_f1_threshold
      value: 80.3369
    - type: dot_precision
      value: 76.07310000000001
    - type: dot_recall
      value: 79.8275
    - type: dot_ap
      value: 86.1544
    - type: max_accuracy
      value: 88.95100000000001
    - type: max_f1
      value: 77.9051
    - type: max_precision
      value: 76.5745
    - type: max_recall
      value: 79.8275
    - type: max_ap
      value: 86.1545
    - type: main_score
      value: 86.1545
---

# hongkeon/granite-embedding-278m-multilingual-Q4_K_M-GGUF
This model was converted to GGUF format from [`ibm-granite/granite-embedding-278m-multilingual`](https://huggingface.co/ibm-granite/granite-embedding-278m-multilingual) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original model card](https://huggingface.co/ibm-granite/granite-embedding-278m-multilingual) for more details on the model.

## Use with llama.cpp
Install llama.cpp through brew (works on Mac and Linux)

```bash
brew install llama.cpp

```
Invoke the llama.cpp server or the CLI.

### CLI:
```bash
llama-cli --hf-repo hongkeon/granite-embedding-278m-multilingual-Q4_K_M-GGUF --hf-file granite-embedding-278m-multilingual-q4_k_m.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo hongkeon/granite-embedding-278m-multilingual-Q4_K_M-GGUF --hf-file granite-embedding-278m-multilingual-q4_k_m.gguf -c 2048
```

Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.

Step 1: Clone llama.cpp from GitHub.
```
git clone https://github.com/ggerganov/llama.cpp
```

Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
```
cd llama.cpp && LLAMA_CURL=1 make
```

Step 3: Run inference through the main binary.
```
./llama-cli --hf-repo hongkeon/granite-embedding-278m-multilingual-Q4_K_M-GGUF --hf-file granite-embedding-278m-multilingual-q4_k_m.gguf -p "The meaning to life and the universe is"
```
or 
```
./llama-server --hf-repo hongkeon/granite-embedding-278m-multilingual-Q4_K_M-GGUF --hf-file granite-embedding-278m-multilingual-q4_k_m.gguf -c 2048
```
