diff --git "a/README.md" "b/README.md"
--- "a/README.md"
+++ "b/README.md"
@@ -3,11 +3,862 @@ license: apache-2.0
 base_model: occiglot/occiglot-7b-fr-en
 tags:
 - generated_from_trainer
+- mteb
 metrics:
 - accuracy
 model-index:
 - name: llm2vec-occiglot-mntp
-  results: []
+  results:
+  - task:
+      type: Clustering
+    dataset:
+      type: lyon-nlp/alloprof
+      name: MTEB AlloProfClusteringP2P
+      config: default
+      split: test
+      revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b
+    metrics:
+    - type: v_measure
+      value: 63.99706100543374
+    - type: v_measures
+      value: [0.6309250305032879, 0.6712141669904825, 0.6368913449141772, 0.6246279406859577, 0.6418756731751959, 0.6355531442090399, 0.6161988676092909, 0.6346687792160265, 0.6312400213373579, 0.6765111319025582, 0.6309250305032879, 0.6712141669904825, 0.6368913449141772, 0.6246279406859577, 0.6418756731751959, 0.6355531442090399, 0.6161988676092909, 0.6346687792160265, 0.6312400213373579, 0.6765111319025582, 0.6309250305032879, 0.6712141669904825, 0.6368913449141772, 0.6246279406859577, 0.6418756731751959, 0.6355531442090399, 0.6161988676092909, 0.6346687792160265, 0.6312400213373579, 0.6765111319025582, 0.6309250305032879, 0.6712141669904825, 0.6368913449141772, 0.6246279406859577, 0.6418756731751959, 0.6355531442090399, 0.6161988676092909, 0.6346687792160265, 0.6312400213373579, 0.6765111319025582, 0.6309250305032879, 0.6712141669904825, 0.6368913449141772, 0.6246279406859577, 0.6418756731751959, 0.6355531442090399, 0.6161988676092909, 0.6346687792160265, 0.6312400213373579, 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+  - task:
+      type: Clustering
+    dataset:
+      type: lyon-nlp/alloprof
+      name: MTEB AlloProfClusteringS2S
+      config: default
+      split: test
+      revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b
+    metrics:
+    - type: v_measure
+      value: 29.932569372425572
+    - type: v_measures
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0.2624750092062693]
+  - task:
+      type: Reranking
+    dataset:
+      type: lyon-nlp/mteb-fr-reranking-alloprof-s2p
+      name: MTEB AlloprofReranking
+      config: default
+      split: test
+      revision: e40c8a63ce02da43200eccb5b0846fcaa888f562
+    metrics:
+    - type: map
+      value: 37.09270648443667
+    - type: mrr
+      value: 37.65235627929929
+  - task:
+      type: Retrieval
+    dataset:
+      type: lyon-nlp/alloprof
+      name: MTEB AlloprofRetrieval
+      config: default
+      split: test
+      revision: fcf295ea64c750f41fadbaa37b9b861558e1bfbd
+    metrics:
+    - type: map_at_1
+      value: 3.325
+    - type: map_at_10
+      value: 5.473999999999999
+    - type: map_at_100
+      value: 6.156
+    - type: map_at_1000
+      value: 6.319
+    - type: map_at_20
+      value: 5.756
+    - type: map_at_3
+      value: 4.662999999999999
+    - type: map_at_5
+      value: 5.101
+    - type: mrr_at_1
+      value: 3.325
+    - type: mrr_at_10
+      value: 5.473999999999999
+    - type: mrr_at_100
+      value: 6.156
+    - type: mrr_at_1000
+      value: 6.319
+    - type: mrr_at_20
+      value: 5.756
+    - type: mrr_at_3
+      value: 4.662999999999999
+    - type: mrr_at_5
+      value: 5.101
+    - type: ndcg_at_1
+      value: 3.325
+    - type: ndcg_at_10
+      value: 6.834999999999999
+    - type: ndcg_at_100
+      value: 11.023
+    - type: ndcg_at_1000
+      value: 16.580000000000002
+    - type: ndcg_at_20
+      value: 7.854
+    - type: ndcg_at_3
+      value: 5.127000000000001
+    - type: ndcg_at_5
+      value: 5.913
+    - type: precision_at_1
+      value: 3.325
+    - type: precision_at_10
+      value: 1.127
+    - type: precision_at_100
+      value: 0.329
+    - type: precision_at_1000
+      value: 0.079
+    - type: precision_at_20
+      value: 0.764
+    - type: precision_at_3
+      value: 2.1590000000000003
+    - type: precision_at_5
+      value: 1.675
+    - type: recall_at_1
+      value: 3.325
+    - type: recall_at_10
+      value: 11.269
+    - type: recall_at_100
+      value: 32.945
+    - type: recall_at_1000
+      value: 79.318
+    - type: recall_at_20
+      value: 15.285000000000002
+    - type: recall_at_3
+      value: 6.476999999999999
+    - type: recall_at_5
+      value: 8.376999999999999
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_reviews_multi
+      name: MTEB AmazonReviewsClassification (fr)
+      config: fr
+      split: test
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+    metrics:
+    - type: accuracy
+      value: 35.071999999999996
+    - type: f1
+      value: 34.756733638269665
+    - type: scores_per_experiment
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{'accuracy': 0.3546, 'f1': 0.3516757627896389}]
+  - task:
+      type: Retrieval
+    dataset:
+      type: maastrichtlawtech/bsard
+      name: MTEB BSARDRetrieval
+      config: default
+      split: test
+      revision: 5effa1b9b5fa3b0f9e12523e6e43e5f86a6e6d59
+    metrics:
+    - type: map_at_1
+      value: 0.901
+    - type: map_at_10
+      value: 1.6150000000000002
+    - type: map_at_100
+      value: 2.046
+    - type: map_at_1000
+      value: 2.147
+    - type: map_at_20
+      value: 1.8030000000000002
+    - type: map_at_3
+      value: 1.126
+    - type: map_at_5
+      value: 1.486
+    - type: mrr_at_1
+      value: 0.901
+    - type: mrr_at_10
+      value: 1.6150000000000002
+    - type: mrr_at_100
+      value: 2.046
+    - type: mrr_at_1000
+      value: 2.147
+    - type: mrr_at_20
+      value: 1.8030000000000002
+    - type: mrr_at_3
+      value: 1.126
+    - type: mrr_at_5
+      value: 1.486
+    - type: ndcg_at_1
+      value: 0.901
+    - type: ndcg_at_10
+      value: 2.182
+    - type: ndcg_at_100
+      value: 4.926
+    - type: ndcg_at_1000
+      value: 7.825
+    - type: ndcg_at_20
+      value: 2.8649999999999998
+    - type: ndcg_at_3
+      value: 1.185
+    - type: ndcg_at_5
+      value: 1.882
+    - type: precision_at_1
+      value: 0.901
+    - type: precision_at_10
+      value: 0.40499999999999997
+    - type: precision_at_100
+      value: 0.185
+    - type: precision_at_1000
+      value: 0.042
+    - type: precision_at_20
+      value: 0.338
+    - type: precision_at_3
+      value: 0.44999999999999996
+    - type: precision_at_5
+      value: 0.631
+    - type: recall_at_1
+      value: 0.901
+    - type: recall_at_10
+      value: 4.054
+    - type: recall_at_100
+      value: 18.468
+    - type: recall_at_1000
+      value: 41.892
+    - type: recall_at_20
+      value: 6.757000000000001
+    - type: recall_at_3
+      value: 1.351
+    - type: recall_at_5
+      value: 3.1530000000000005
+  - task:
+      type: Clustering
+    dataset:
+      type: lyon-nlp/clustering-hal-s2s
+      name: MTEB HALClusteringS2S
+      config: default
+      split: test
+      revision: e06ebbbb123f8144bef1a5d18796f3dec9ae2915
+    metrics:
+    - type: v_measure
+      value: 20.821362086725557
+    - type: v_measures
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+  - task:
+      type: Clustering
+    dataset:
+      type: mlsum
+      name: MTEB MLSUMClusteringP2P (fr)
+      config: fr
+      split: test
+      revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7
+    metrics:
+    - type: v_measure
+      value: 45.2570658673633
+    - type: v_measures
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+  - task:
+      type: Clustering
+    dataset:
+      type: mlsum
+      name: MTEB MLSUMClusteringS2S (fr)
+      config: fr
+      split: test
+      revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7
+    metrics:
+    - type: v_measure
+      value: 44.94685216731792
+    - type: v_measures
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+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_domain
+      name: MTEB MTOPDomainClassification (fr)
+      config: fr
+      split: test
+      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
+    metrics:
+    - type: accuracy
+      value: 75.69996868149076
+    - type: f1
+      value: 75.40911375049545
+    - type: scores_per_experiment
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+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_intent
+      name: MTEB MTOPIntentClassification (fr)
+      config: fr
+      split: test
+      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
+    metrics:
+    - type: accuracy
+      value: 63.75822110867524
+    - type: f1
+      value: 42.22367596410695
+    - type: scores_per_experiment
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+  - task:
+      type: Classification
+    dataset:
+      type: masakhane/masakhanews
+      name: MTEB MasakhaNEWSClassification (eng)
+      config: eng
+      split: test
+      revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
+    metrics:
+    - type: accuracy
+      value: 77.91139240506328
+    - type: f1
+      value: 77.05013060581847
+    - type: scores_per_experiment
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+  - task:
+      type: Classification
+    dataset:
+      type: masakhane/masakhanews
+      name: MTEB MasakhaNEWSClassification (fra)
+      config: fra
+      split: test
+      revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
+    metrics:
+    - type: accuracy
+      value: 75.9952606635071
+    - type: f1
+      value: 72.14436891647776
+    - type: scores_per_experiment
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+  - task:
+      type: Clustering
+    dataset:
+      type: masakhane/masakhanews
+      name: MTEB MasakhaNEWSClusteringP2P (eng)
+      config: eng
+      split: test
+      revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
+    metrics:
+    - type: v_measure
+      value: 58.30018967761718
+    - type: v_measures
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+  - task:
+      type: Clustering
+    dataset:
+      type: masakhane/masakhanews
+      name: MTEB MasakhaNEWSClusteringP2P (fra)
+      config: fra
+      split: test
+      revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
+    metrics:
+    - type: v_measure
+      value: 51.33788486523143
+    - type: v_measures
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+  - task:
+      type: Clustering
+    dataset:
+      type: masakhane/masakhanews
+      name: MTEB MasakhaNEWSClusteringS2S (eng)
+      config: eng
+      split: test
+      revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
+    metrics:
+    - type: v_measure
+      value: 35.12771102662738
+    - type: v_measures
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+  - task:
+      type: Clustering
+    dataset:
+      type: masakhane/masakhanews
+      name: MTEB MasakhaNEWSClusteringS2S (fra)
+      config: fra
+      split: test
+      revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
+    metrics:
+    - type: v_measure
+      value: 32.200350451108655
+    - type: v_measures
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+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (fr)
+      config: fr
+      split: test
+      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
+    metrics:
+    - type: accuracy
+      value: 56.028917283120386
+    - type: f1
+      value: 52.65339345173721
+    - type: scores_per_experiment
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+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (fr)
+      config: fr
+      split: test
+      revision: 7d571f92784cd94a019292a1f45445077d0ef634
+    metrics:
+    - type: accuracy
+      value: 59.297242770679226
+    - type: f1
+      value: 57.613317912056885
+    - type: scores_per_experiment
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+  - task:
+      type: Retrieval
+    dataset:
+      type: jinaai/mintakaqa
+      name: MTEB MintakaRetrieval (fr)
+      config: fr
+      split: test
+      revision: efa78cc2f74bbcd21eff2261f9e13aebe40b814e
+    metrics:
+    - type: map_at_1
+      value: 0.737
+    - type: map_at_10
+      value: 1.248
+    - type: map_at_100
+      value: 1.5350000000000001
+    - type: map_at_1000
+      value: 1.727
+    - type: map_at_20
+      value: 1.3259999999999998
+    - type: map_at_3
+      value: 0.9690000000000001
+    - type: map_at_5
+      value: 1.1119999999999999
+    - type: mrr_at_1
+      value: 0.737
+    - type: mrr_at_10
+      value: 1.248
+    - type: mrr_at_100
+      value: 1.5350000000000001
+    - type: mrr_at_1000
+      value: 1.727
+    - type: mrr_at_20
+      value: 1.3259999999999998
+    - type: mrr_at_3
+      value: 0.9690000000000001
+    - type: mrr_at_5
+      value: 1.1119999999999999
+    - type: ndcg_at_1
+      value: 0.737
+    - type: ndcg_at_10
+      value: 1.66
+    - type: ndcg_at_100
+      value: 3.581
+    - type: ndcg_at_1000
+      value: 11.177
+    - type: ndcg_at_20
+      value: 1.941
+    - type: ndcg_at_3
+      value: 1.0659999999999998
+    - type: ndcg_at_5
+      value: 1.3299999999999998
+    - type: precision_at_1
+      value: 0.737
+    - type: precision_at_10
+      value: 0.303
+    - type: precision_at_100
+      value: 0.132
+    - type: precision_at_1000
+      value: 0.079
+    - type: precision_at_20
+      value: 0.207
+    - type: precision_at_3
+      value: 0.44999999999999996
+    - type: precision_at_5
+      value: 0.40099999999999997
+    - type: recall_at_1
+      value: 0.737
+    - type: recall_at_10
+      value: 3.0300000000000002
+    - type: recall_at_100
+      value: 13.227
+    - type: recall_at_1000
+      value: 78.501
+    - type: recall_at_20
+      value: 4.136
+    - type: recall_at_3
+      value: 1.351
+    - type: recall_at_5
+      value: 2.007
+  - task:
+      type: Classification
+    dataset:
+      type: allocine
+      name: MTEB MovieReviewSentimentClassification
+      config: default
+      split: test
+      revision: a4654f4896408912913a62ace89614879a549287
+    metrics:
+    - type: accuracy
+      value: 81.71875
+    - type: ap
+      value: 75.47842425736047
+    - type: f1
+      value: 81.5713940370767
+    - type: scores_per_experiment
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+  - task:
+      type: PairClassification
+    dataset:
+      type: GEM/opusparcus
+      name: MTEB OpusparcusPC (fr)
+      config: fr
+      split: test
+      revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
+    metrics:
+    - type: cos_sim_accuracy
+      value: 99.90069513406156
+    - type: cos_sim_ap
+      value: 100.0
+    - type: cos_sim_f1
+      value: 99.95032290114257
+    - type: cos_sim_precision
+      value: 100.0
+    - type: cos_sim_recall
+      value: 99.90069513406156
+    - type: dot_accuracy
+      value: 99.90069513406156
+    - type: dot_ap
+      value: 100.0
+    - type: dot_f1
+      value: 99.95032290114257
+    - type: dot_precision
+      value: 100.0
+    - type: dot_recall
+      value: 99.90069513406156
+    - type: euclidean_accuracy
+      value: 99.90069513406156
+    - type: euclidean_ap
+      value: 100.0
+    - type: euclidean_f1
+      value: 99.95032290114257
+    - type: euclidean_precision
+      value: 100.0
+    - type: euclidean_recall
+      value: 99.90069513406156
+    - type: manhattan_accuracy
+      value: 99.90069513406156
+    - type: manhattan_ap
+      value: 100.0
+    - type: manhattan_f1
+      value: 99.95032290114257
+    - type: manhattan_precision
+      value: 100.0
+    - type: manhattan_recall
+      value: 99.90069513406156
+    - type: max_accuracy
+      value: 99.90069513406156
+    - type: max_ap
+      value: 100.0
+    - type: max_f1
+      value: 99.95032290114257
+  - task:
+      type: PairClassification
+    dataset:
+      type: paws-x
+      name: MTEB PawsX (fr)
+      config: fr
+      split: test
+      revision: 8a04d940a42cd40658986fdd8e3da561533a3646
+    metrics:
+    - type: cos_sim_accuracy
+      value: 62.2
+    - type: cos_sim_ap
+      value: 61.06853292904232
+    - type: cos_sim_f1
+      value: 62.77423920736024
+    - type: cos_sim_precision
+      value: 46.125845033801355
+    - type: cos_sim_recall
+      value: 98.2281284606866
+    - type: dot_accuracy
+      value: 56.599999999999994
+    - type: dot_ap
+      value: 49.196383003432366
+    - type: dot_f1
+      value: 62.491349480968864
+    - type: dot_precision
+      value: 45.44539506794162
+    - type: dot_recall
+      value: 100.0
+    - type: euclidean_accuracy
+      value: 62.050000000000004
+    - type: euclidean_ap
+      value: 60.800193112023656
+    - type: euclidean_f1
+      value: 62.800565770862804
+    - type: euclidean_precision
+      value: 46.129870129870135
+    - type: euclidean_recall
+      value: 98.33887043189368
+    - type: manhattan_accuracy
+      value: 62.35000000000001
+    - type: manhattan_ap
+      value: 61.058370414376824
+    - type: manhattan_f1
+      value: 62.82685512367492
+    - type: manhattan_precision
+      value: 46.133886870783606
+    - type: manhattan_recall
+      value: 98.44961240310077
+    - type: max_accuracy
+      value: 62.35000000000001
+    - type: max_ap
+      value: 61.06853292904232
+    - type: max_f1
+      value: 62.82685512367492
+  - task:
+      type: STS
+    dataset:
+      type: Lajavaness/SICK-fr
+      name: MTEB SICKFr
+      config: default
+      split: test
+      revision: e077ab4cf4774a1e36d86d593b150422fafd8e8a
+    metrics:
+    - type: cos_sim_pearson
+      value: 60.96413420799593
+    - type: cos_sim_spearman
+      value: 58.18262720076686
+    - type: euclidean_pearson
+      value: 58.78305606004982
+    - type: euclidean_spearman
+      value: 57.51277670943302
+    - type: manhattan_pearson
+      value: 60.23979598152332
+    - type: manhattan_spearman
+      value: 59.03365066514682
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (fr)
+      config: fr
+      split: test
+      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
+    metrics:
+    - type: cos_sim_pearson
+      value: 42.79213665745784
+    - type: cos_sim_spearman
+      value: 67.82830105719044
+    - type: euclidean_pearson
+      value: 51.49974160914888
+    - type: euclidean_spearman
+      value: 68.39759338405578
+    - type: manhattan_pearson
+      value: 53.397979271640054
+    - type: manhattan_spearman
+      value: 69.75326227137708
+  - task:
+      type: STS
+    dataset:
+      type: PhilipMay/stsb_multi_mt
+      name: MTEB STSBenchmarkMultilingualSTS (fr)
+      config: fr
+      split: test
+      revision: 93d57ef91790589e3ce9c365164337a8a78b7632
+    metrics:
+    - type: cos_sim_pearson
+      value: 52.24207237860239
+    - type: cos_sim_spearman
+      value: 51.982655539567965
+    - type: euclidean_pearson
+      value: 55.70873380936832
+    - type: euclidean_spearman
+      value: 54.56293527619584
+    - type: manhattan_pearson
+      value: 57.94419279659701
+    - type: manhattan_spearman
+      value: 56.577458741875944
+  - task:
+      type: Summarization
+    dataset:
+      type: lyon-nlp/summarization-summeval-fr-p2p
+      name: MTEB SummEvalFr
+      config: default
+      split: test
+      revision: b385812de6a9577b6f4d0f88c6a6e35395a94054
+    metrics:
+    - type: cos_sim_pearson
+      value: 28.170707514130306
+    - type: cos_sim_spearman
+      value: 28.718143797860808
+    - type: dot_pearson
+      value: 18.331802861285077
+    - type: dot_spearman
+      value: 18.173321127745957
+  - task:
+      type: Reranking
+    dataset:
+      type: lyon-nlp/mteb-fr-reranking-syntec-s2p
+      name: MTEB SyntecReranking
+      config: default
+      split: test
+      revision: b205c5084a0934ce8af14338bf03feb19499c84d
+    metrics:
+    - type: map
+      value: 62.866666666666674
+    - type: mrr
+      value: 62.866666666666674
+  - task:
+      type: Retrieval
+    dataset:
+      type: lyon-nlp/mteb-fr-retrieval-syntec-s2p
+      name: MTEB SyntecRetrieval
+      config: default
+      split: test
+      revision: 19661ccdca4dfc2d15122d776b61685f48c68ca9
+    metrics:
+    - type: map_at_1
+      value: 12.0
+    - type: map_at_10
+      value: 21.644
+    - type: map_at_100
+      value: 24.02
+    - type: map_at_1000
+      value: 24.02
+    - type: map_at_20
+      value: 23.088
+    - type: map_at_3
+      value: 18.167
+    - type: map_at_5
+      value: 19.967
+    - type: mrr_at_1
+      value: 12.0
+    - type: mrr_at_10
+      value: 21.644
+    - type: mrr_at_100
+      value: 24.02
+    - type: mrr_at_1000
+      value: 24.02
+    - type: mrr_at_20
+      value: 23.088
+    - type: mrr_at_3
+      value: 18.167
+    - type: mrr_at_5
+      value: 19.967
+    - type: ndcg_at_1
+      value: 12.0
+    - type: ndcg_at_10
+      value: 27.644999999999996
+    - type: ndcg_at_100
+      value: 39.085
+    - type: ndcg_at_1000
+      value: 39.085
+    - type: ndcg_at_20
+      value: 32.940999999999995
+    - type: ndcg_at_3
+      value: 20.416999999999998
+    - type: ndcg_at_5
+      value: 23.687
+    - type: precision_at_1
+      value: 12.0
+    - type: precision_at_10
+      value: 4.7
+    - type: precision_at_100
+      value: 1.0
+    - type: precision_at_1000
+      value: 0.1
+    - type: precision_at_20
+      value: 3.4000000000000004
+    - type: precision_at_3
+      value: 9.0
+    - type: precision_at_5
+      value: 7.000000000000001
+    - type: recall_at_1
+      value: 12.0
+    - type: recall_at_10
+      value: 47.0
+    - type: recall_at_100
+      value: 100.0
+    - type: recall_at_1000
+      value: 100.0
+    - type: recall_at_20
+      value: 68.0
+    - type: recall_at_3
+      value: 27.0
+    - type: recall_at_5
+      value: 35.0
+  - task:
+      type: Retrieval
+    dataset:
+      type: jinaai/xpqa
+      name: MTEB XPQARetrieval (fr)
+      config: fr
+      split: test
+      revision: c99d599f0a6ab9b85b065da6f9d94f9cf731679f
+    metrics:
+    - type: map_at_1
+      value: 14.168
+    - type: map_at_10
+      value: 21.8
+    - type: map_at_100
+      value: 23.066
+    - type: map_at_1000
+      value: 23.265
+    - type: map_at_20
+      value: 22.427
+    - type: map_at_3
+      value: 19.277
+    - type: map_at_5
+      value: 20.693
+    - type: mrr_at_1
+      value: 24.032
+    - type: mrr_at_10
+      value: 29.848000000000003
+    - type: mrr_at_100
+      value: 30.648999999999997
+    - type: mrr_at_1000
+      value: 30.737
+    - type: mrr_at_20
+      value: 30.213
+    - type: mrr_at_3
+      value: 28.126
+    - type: mrr_at_5
+      value: 29.000999999999998
+    - type: ndcg_at_1
+      value: 24.032
+    - type: ndcg_at_10
+      value: 26.39
+    - type: ndcg_at_100
+      value: 31.978
+    - type: ndcg_at_1000
+      value: 36.57
+    - type: ndcg_at_20
+      value: 28.109
+    - type: ndcg_at_3
+      value: 23.46
+    - type: ndcg_at_5
+      value: 24.201
+    - type: precision_at_1
+      value: 24.032
+    - type: precision_at_10
+      value: 6.648999999999999
+    - type: precision_at_100
+      value: 1.172
+    - type: precision_at_1000
+      value: 0.182
+    - type: precision_at_20
+      value: 3.959
+    - type: precision_at_3
+      value: 14.642
+    - type: precision_at_5
+      value: 10.681000000000001
+    - type: recall_at_1
+      value: 14.168
+    - type: recall_at_10
+      value: 31.613000000000003
+    - type: recall_at_100
+      value: 53.996
+    - type: recall_at_1000
+      value: 85.705
+    - type: recall_at_20
+      value: 36.925000000000004
+    - type: recall_at_3
+      value: 22.528000000000002
+    - type: recall_at_5
+      value: 26.344
 language:
 - fr
 ---