Update README.md
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README.md
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@@ -1,11 +1,687 @@
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---
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pipeline_tag: sentence-similarity
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tags:
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---
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# Solon Embeddings — large 0.1
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---
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tags:
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- mteb
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model-index:
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- name: Solon-embeddings-large-0.1
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results:
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- task:
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type: Clustering
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dataset:
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type: lyon-nlp/alloprof
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name: MTEB AlloProfClusteringP2P
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config: default
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split: test
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revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b
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metrics:
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- type: v_measure
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value: 64.16942168287153
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- task:
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type: Clustering
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dataset:
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type: lyon-nlp/alloprof
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name: MTEB AlloProfClusteringS2S
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config: default
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split: test
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revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b
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metrics:
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- type: v_measure
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value: 38.17076313383054
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- task:
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type: Reranking
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dataset:
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type: lyon-nlp/mteb-fr-reranking-alloprof-s2p
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name: MTEB AlloprofReranking
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config: default
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split: test
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revision: 666fdacebe0291776e86f29345663dfaf80a0db9
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metrics:
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- type: map
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value: 64.8770878097632
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- type: mrr
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value: 66.39132423169396
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- task:
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type: Retrieval
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dataset:
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type: lyon-nlp/alloprof
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name: MTEB AlloprofRetrieval
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config: default
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split: test
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revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b
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metrics:
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- type: map_at_1
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value: 29.62
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- type: map_at_10
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value: 40.963
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- type: map_at_100
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value: 41.894
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- type: map_at_1000
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value: 41.939
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- type: map_at_3
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value: 37.708999999999996
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- type: map_at_5
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value: 39.696999999999996
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- type: mrr_at_1
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value: 29.62
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- type: mrr_at_10
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value: 40.963
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- type: mrr_at_100
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value: 41.894
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- type: mrr_at_1000
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value: 41.939
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- type: mrr_at_3
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value: 37.708999999999996
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- type: mrr_at_5
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value: 39.696999999999996
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- type: ndcg_at_1
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value: 29.62
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- type: ndcg_at_10
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value: 46.942
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- type: ndcg_at_100
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value: 51.629999999999995
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- type: ndcg_at_1000
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value: 52.927
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- type: ndcg_at_3
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value: 40.333999999999996
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- type: ndcg_at_5
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value: 43.922
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- type: precision_at_1
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value: 29.62
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- type: precision_at_10
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value: 6.589
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- type: precision_at_100
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value: 0.882
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- type: precision_at_1000
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value: 0.099
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- type: precision_at_3
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value: 15.976
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- type: precision_at_5
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value: 11.33
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- type: recall_at_1
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value: 29.62
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- type: recall_at_10
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value: 65.889
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- type: recall_at_100
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value: 88.212
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- type: recall_at_1000
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value: 98.575
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- type: recall_at_3
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value: 47.927
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- type: recall_at_5
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value: 56.64900000000001
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- task:
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type: Classification
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dataset:
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type: mteb/amazon_reviews_multi
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name: MTEB AmazonReviewsClassification (fr)
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config: fr
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split: test
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revision: 1399c76144fd37290681b995c656ef9b2e06e26d
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metrics:
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- type: accuracy
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value: 42.077999999999996
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- type: f1
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value: 40.64511241732637
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- task:
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type: Retrieval
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dataset:
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type: maastrichtlawtech/bsard
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name: MTEB BSARDRetrieval
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config: default
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split: test
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revision: 5effa1b9b5fa3b0f9e12523e6e43e5f86a6e6d59
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metrics:
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- type: map_at_1
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value: 0.901
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- type: map_at_10
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value: 1.524
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- type: map_at_100
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value: 1.833
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- type: map_at_1000
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value: 1.916
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- type: map_at_3
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value: 1.276
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- type: map_at_5
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value: 1.276
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- type: mrr_at_1
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value: 0.901
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- type: mrr_at_10
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value: 1.524
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- type: mrr_at_100
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value: 1.833
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- type: mrr_at_1000
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value: 1.916
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- type: mrr_at_3
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value: 1.276
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- type: mrr_at_5
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value: 1.276
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- type: ndcg_at_1
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value: 0.901
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- type: ndcg_at_10
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value: 2.085
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- type: ndcg_at_100
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value: 3.805
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- type: ndcg_at_1000
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value: 6.704000000000001
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- type: ndcg_at_3
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value: 1.41
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- type: ndcg_at_5
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value: 1.41
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- type: precision_at_1
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value: 0.901
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- type: precision_at_10
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value: 0.40499999999999997
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- type: precision_at_100
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value: 0.126
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- type: precision_at_1000
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value: 0.037
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- type: precision_at_3
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value: 0.601
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- type: precision_at_5
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value: 0.36
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- type: recall_at_1
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value: 0.901
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- type: recall_at_10
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value: 4.054
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- type: recall_at_100
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value: 12.613
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- type: recall_at_1000
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value: 36.937
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- type: recall_at_3
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value: 1.802
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- type: recall_at_5
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value: 1.802
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- task:
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type: BitextMining
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dataset:
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type: rbawden/DiaBLa
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name: MTEB DiaBLaBitextMining (fr-en)
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config: fr-en
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split: test
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revision: 5345895c56a601afe1a98519ce3199be60a27dba
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metrics:
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- type: accuracy
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value: 88.90048712595686
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- type: f1
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205 |
+
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210 |
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|
211 |
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type: Clustering
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212 |
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dataset:
|
213 |
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type: lyon-nlp/clustering-hal-s2s
|
214 |
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name: MTEB HALClusteringS2S
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config: default
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216 |
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metrics:
|
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- type: v_measure
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220 |
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value: 24.087988843991155
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|
222 |
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type: Clustering
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223 |
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dataset:
|
224 |
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type: mlsum
|
225 |
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name: MTEB MLSUMClusteringP2P
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226 |
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config: default
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227 |
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split: test
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228 |
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metrics:
|
230 |
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- type: v_measure
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231 |
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value: 43.79603865728535
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232 |
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- task:
|
233 |
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type: Clustering
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234 |
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dataset:
|
235 |
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type: mlsum
|
236 |
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name: MTEB MLSUMClusteringS2S
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config: default
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metrics:
|
241 |
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- type: v_measure
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242 |
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value: 37.746550373003
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243 |
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- task:
|
244 |
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type: Classification
|
245 |
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dataset:
|
246 |
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type: mteb/mtop_domain
|
247 |
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name: MTEB MTOPDomainClassification (fr)
|
248 |
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config: fr
|
249 |
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split: test
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revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
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metrics:
|
252 |
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- type: accuracy
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253 |
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value: 89.26088318196052
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- type: f1
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255 |
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256 |
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- task:
|
257 |
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type: Classification
|
258 |
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dataset:
|
259 |
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type: mteb/mtop_intent
|
260 |
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name: MTEB MTOPIntentClassification (fr)
|
261 |
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config: fr
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262 |
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split: test
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revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
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265 |
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266 |
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value: 68.55308487316003
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268 |
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269 |
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|
270 |
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type: Classification
|
271 |
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dataset:
|
272 |
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type: masakhane/masakhanews
|
273 |
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name: MTEB MasakhaNEWSClassification (fra)
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274 |
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config: fra
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275 |
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revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
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281 |
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282 |
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|
283 |
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type: Clustering
|
284 |
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dataset:
|
285 |
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type: masakhane/masakhanews
|
286 |
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name: MTEB MasakhaNEWSClusteringP2P (fra)
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config: fra
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288 |
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292 |
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value: 40.80377094681114
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293 |
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- task:
|
294 |
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type: Clustering
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295 |
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dataset:
|
296 |
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type: masakhane/masakhanews
|
297 |
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name: MTEB MasakhaNEWSClusteringS2S (fra)
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298 |
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config: fra
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299 |
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metrics:
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302 |
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303 |
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value: 28.79703837416241
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304 |
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- task:
|
305 |
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type: Classification
|
306 |
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dataset:
|
307 |
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type: mteb/amazon_massive_intent
|
308 |
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name: MTEB MassiveIntentClassification (fr)
|
309 |
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config: fr
|
310 |
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split: test
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311 |
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revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
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312 |
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metrics:
|
313 |
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314 |
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value: 67.40080699394755
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316 |
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317 |
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|
318 |
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type: Classification
|
319 |
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dataset:
|
320 |
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type: mteb/amazon_massive_scenario
|
321 |
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name: MTEB MassiveScenarioClassification (fr)
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322 |
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config: fr
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metrics:
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326 |
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329 |
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330 |
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- task:
|
331 |
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type: Retrieval
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332 |
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dataset:
|
333 |
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type: jinaai/mintakaqa
|
334 |
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name: MTEB MintakaRetrieval (fr)
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335 |
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config: fr
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336 |
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metrics:
|
339 |
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340 |
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value: 16.625999999999998
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341 |
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365 |
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366 |
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value: 30.074
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367 |
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368 |
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value: 35.683
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369 |
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- type: ndcg_at_1000
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373 |
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value: 27.124
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375 |
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376 |
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value: 16.625999999999998
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377 |
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378 |
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value: 4.566
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379 |
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380 |
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value: 0.729
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381 |
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- type: precision_at_1000
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382 |
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value: 0.097
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383 |
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|
384 |
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value: 9.801
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385 |
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- type: precision_at_5
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386 |
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value: 7.305000000000001
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387 |
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- type: recall_at_1
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388 |
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value: 16.625999999999998
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389 |
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- type: recall_at_10
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390 |
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value: 45.659
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391 |
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- type: recall_at_100
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value: 72.85000000000001
|
393 |
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- type: recall_at_1000
|
394 |
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value: 97.42
|
395 |
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- type: recall_at_3
|
396 |
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value: 29.402
|
397 |
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- type: recall_at_5
|
398 |
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value: 36.527
|
399 |
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- task:
|
400 |
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type: PairClassification
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401 |
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dataset:
|
402 |
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type: paws-x
|
403 |
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name: MTEB PawsX (fr)
|
404 |
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config: fr
|
405 |
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split: test
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406 |
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407 |
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metrics:
|
408 |
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- type: cos_sim_accuracy
|
409 |
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value: 60.6
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410 |
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- type: cos_sim_ap
|
411 |
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value: 60.18915797975459
|
412 |
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|
413 |
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414 |
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- type: cos_sim_precision
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415 |
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416 |
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- type: cos_sim_recall
|
417 |
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value: 100.0
|
418 |
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- type: dot_accuracy
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419 |
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value: 60.6
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420 |
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- type: dot_ap
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421 |
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value: 60.091135216056024
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422 |
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424 |
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|
425 |
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value: 45.44539506794162
|
426 |
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- type: dot_recall
|
427 |
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value: 100.0
|
428 |
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- type: euclidean_accuracy
|
429 |
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value: 60.6
|
430 |
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- type: euclidean_ap
|
431 |
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|
432 |
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- type: euclidean_f1
|
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|
434 |
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- type: euclidean_precision
|
435 |
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value: 45.44539506794162
|
436 |
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|
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value: 100.0
|
438 |
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- type: manhattan_accuracy
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439 |
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440 |
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446 |
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|
448 |
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value: 60.650000000000006
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450 |
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451 |
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|
452 |
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- type: max_f1
|
453 |
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454 |
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- task:
|
455 |
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type: STS
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456 |
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dataset:
|
457 |
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type: Lajavaness/SICK-fr
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458 |
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name: MTEB SICKFr
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459 |
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460 |
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split: test
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461 |
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462 |
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metrics:
|
463 |
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value: 79.77067200230256
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465 |
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466 |
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|
467 |
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468 |
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value: 76.34017074673956
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469 |
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- type: euclidean_spearman
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470 |
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471 |
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- type: manhattan_pearson
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473 |
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- type: manhattan_spearman
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475 |
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- task:
|
476 |
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|
477 |
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dataset:
|
478 |
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type: mteb/sts22-crosslingual-sts
|
479 |
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name: MTEB STS22 (fr)
|
480 |
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config: fr
|
481 |
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split: test
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482 |
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483 |
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metrics:
|
484 |
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|
485 |
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|
486 |
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|
487 |
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|
488 |
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- type: euclidean_pearson
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489 |
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|
490 |
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- type: euclidean_spearman
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491 |
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492 |
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- type: manhattan_pearson
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494 |
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- type: manhattan_spearman
|
495 |
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|
496 |
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- task:
|
497 |
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type: STS
|
498 |
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dataset:
|
499 |
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type: stsb_multi_mt
|
500 |
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name: MTEB STSBenchmarkMultilingualSTS (fr)
|
501 |
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config: fr
|
502 |
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split: test
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503 |
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504 |
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metrics:
|
505 |
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507 |
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508 |
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509 |
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511 |
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513 |
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- type: manhattan_pearson
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515 |
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- type: manhattan_spearman
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516 |
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517 |
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- task:
|
518 |
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type: Summarization
|
519 |
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dataset:
|
520 |
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type: lyon-nlp/summarization-summeval-fr-p2p
|
521 |
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name: MTEB SummEvalFr
|
522 |
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config: default
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523 |
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split: test
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524 |
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525 |
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metrics:
|
526 |
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|
527 |
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value: 30.476001473421586
|
528 |
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529 |
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|
530 |
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- type: dot_pearson
|
531 |
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532 |
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533 |
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|
534 |
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- task:
|
535 |
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type: Reranking
|
536 |
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dataset:
|
537 |
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type: lyon-nlp/mteb-fr-reranking-syntec-s2p
|
538 |
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name: MTEB SyntecReranking
|
539 |
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config: default
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540 |
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split: test
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541 |
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542 |
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543 |
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|
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545 |
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- type: mrr
|
546 |
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|
547 |
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- task:
|
548 |
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type: Retrieval
|
549 |
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dataset:
|
550 |
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type: lyon-nlp/mteb-fr-retrieval-syntec-s2p
|
551 |
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name: MTEB SyntecRetrieval
|
552 |
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config: default
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553 |
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split: test
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554 |
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555 |
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metrics:
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558 |
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|
559 |
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566 |
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582 |
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602 |
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604 |
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|
605 |
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606 |
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|
607 |
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608 |
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609 |
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610 |
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612 |
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|
613 |
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|
614 |
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- type: recall_at_5
|
615 |
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value: 96.0
|
616 |
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- task:
|
617 |
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type: Retrieval
|
618 |
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dataset:
|
619 |
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type: jinaai/xpqa
|
620 |
+
name: MTEB XPQARetrieval (fr)
|
621 |
+
config: fr
|
622 |
+
split: test
|
623 |
+
revision: c99d599f0a6ab9b85b065da6f9d94f9cf731679f
|
624 |
+
metrics:
|
625 |
+
- type: map_at_1
|
626 |
+
value: 42.027
|
627 |
+
- type: map_at_10
|
628 |
+
value: 64.331
|
629 |
+
- type: map_at_100
|
630 |
+
value: 65.657
|
631 |
+
- type: map_at_1000
|
632 |
+
value: 65.7
|
633 |
+
- type: map_at_3
|
634 |
+
value: 57.967999999999996
|
635 |
+
- type: map_at_5
|
636 |
+
value: 62.33800000000001
|
637 |
+
- type: mrr_at_1
|
638 |
+
value: 65.688
|
639 |
+
- type: mrr_at_10
|
640 |
+
value: 72.263
|
641 |
+
- type: mrr_at_100
|
642 |
+
value: 72.679
|
643 |
+
- type: mrr_at_1000
|
644 |
+
value: 72.69099999999999
|
645 |
+
- type: mrr_at_3
|
646 |
+
value: 70.405
|
647 |
+
- type: mrr_at_5
|
648 |
+
value: 71.587
|
649 |
+
- type: ndcg_at_1
|
650 |
+
value: 65.688
|
651 |
+
- type: ndcg_at_10
|
652 |
+
value: 70.221
|
653 |
+
- type: ndcg_at_100
|
654 |
+
value: 74.457
|
655 |
+
- type: ndcg_at_1000
|
656 |
+
value: 75.178
|
657 |
+
- type: ndcg_at_3
|
658 |
+
value: 65.423
|
659 |
+
- type: ndcg_at_5
|
660 |
+
value: 67.05499999999999
|
661 |
+
- type: precision_at_1
|
662 |
+
value: 65.688
|
663 |
+
- type: precision_at_10
|
664 |
+
value: 16.208
|
665 |
+
- type: precision_at_100
|
666 |
+
value: 1.975
|
667 |
+
- type: precision_at_1000
|
668 |
+
value: 0.207
|
669 |
+
- type: precision_at_3
|
670 |
+
value: 39.831
|
671 |
+
- type: precision_at_5
|
672 |
+
value: 28.652
|
673 |
+
- type: recall_at_1
|
674 |
+
value: 42.027
|
675 |
+
- type: recall_at_10
|
676 |
+
value: 78.803
|
677 |
+
- type: recall_at_100
|
678 |
+
value: 95.051
|
679 |
+
- type: recall_at_1000
|
680 |
+
value: 99.75500000000001
|
681 |
+
- type: recall_at_3
|
682 |
+
value: 62.62799999999999
|
683 |
+
- type: recall_at_5
|
684 |
+
value: 70.975
|
685 |
---
|
686 |
|
687 |
# Solon Embeddings — large 0.1
|