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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: windberta |
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results: |
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- task: |
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type: STS |
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dataset: |
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type: C-MTEB/AFQMC |
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name: MTEB AFQMC |
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config: default |
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split: validation |
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revision: None |
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metrics: |
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- type: cos_sim_pearson |
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value: 42.33337754104733 |
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- type: cos_sim_spearman |
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value: 46.77492896615997 |
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- type: euclidean_pearson |
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value: 45.485443713440205 |
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- type: euclidean_spearman |
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value: 46.77492896615997 |
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- type: manhattan_pearson |
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value: 45.47908853063357 |
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- type: manhattan_spearman |
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value: 46.78349339487035 |
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- task: |
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type: STS |
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dataset: |
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type: C-MTEB/ATEC |
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name: MTEB ATEC |
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config: default |
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split: test |
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revision: None |
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metrics: |
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- type: cos_sim_pearson |
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value: 42.4857636418899 |
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- type: cos_sim_spearman |
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value: 50.1796711684779 |
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- type: euclidean_pearson |
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value: 50.19857844860528 |
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- type: euclidean_spearman |
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value: 50.17966891674149 |
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- type: manhattan_pearson |
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value: 50.189134647291425 |
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- type: manhattan_spearman |
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value: 50.186194448855524 |
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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 (zh) |
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config: zh |
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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: 43.32 |
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- type: f1 |
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value: 41.656310147227025 |
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- task: |
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type: STS |
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dataset: |
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type: C-MTEB/BQ |
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name: MTEB BQ |
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config: default |
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split: test |
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revision: None |
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metrics: |
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- type: cos_sim_pearson |
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value: 53.71954834756843 |
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- type: cos_sim_spearman |
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value: 55.24915785430301 |
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- type: euclidean_pearson |
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value: 54.51293350057512 |
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- type: euclidean_spearman |
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value: 55.249150926099745 |
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- type: manhattan_pearson |
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value: 54.47449996486367 |
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- type: manhattan_spearman |
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value: 55.2105677621172 |
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- task: |
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type: Clustering |
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dataset: |
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type: C-MTEB/CLSClusteringP2P |
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name: MTEB CLSClusteringP2P |
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config: default |
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split: test |
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revision: None |
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metrics: |
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- type: v_measure |
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value: 42.45793696381908 |
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- task: |
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type: Clustering |
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dataset: |
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type: C-MTEB/CLSClusteringS2S |
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name: MTEB CLSClusteringS2S |
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config: default |
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split: test |
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revision: None |
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metrics: |
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- type: v_measure |
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value: 40.378561138339656 |
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- task: |
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type: Reranking |
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dataset: |
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type: C-MTEB/CMedQAv1-reranking |
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name: MTEB CMedQAv1 |
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config: default |
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split: test |
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revision: None |
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metrics: |
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- type: map |
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value: 77.41779986882574 |
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- type: mrr |
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value: 81.09345238095239 |
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- task: |
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type: Reranking |
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dataset: |
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type: C-MTEB/CMedQAv2-reranking |
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name: MTEB CMedQAv2 |
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config: default |
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split: test |
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revision: None |
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metrics: |
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- type: map |
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value: 77.84113571204598 |
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- type: mrr |
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value: 81.18206349206349 |
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- task: |
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type: Retrieval |
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dataset: |
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type: C-MTEB/CmedqaRetrieval |
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name: MTEB CmedqaRetrieval |
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config: default |
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split: dev |
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revision: None |
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metrics: |
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- type: map_at_1 |
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value: 18.706 |
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- type: map_at_10 |
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value: 27.782 |
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- type: map_at_100 |
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value: 29.482000000000003 |
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- type: map_at_1000 |
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value: 29.64 |
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- type: map_at_3 |
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value: 24.606 |
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- type: map_at_5 |
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value: 26.32 |
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- type: mrr_at_1 |
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value: 29.307 |
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- type: mrr_at_10 |
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value: 36.226 |
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- type: mrr_at_100 |
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value: 37.262 |
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- type: mrr_at_1000 |
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value: 37.335 |
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- type: mrr_at_3 |
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value: 33.928999999999995 |
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- type: mrr_at_5 |
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value: 35.181000000000004 |
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- type: ndcg_at_1 |
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value: 29.307 |
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- type: ndcg_at_10 |
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value: 33.452 |
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- type: ndcg_at_100 |
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value: 40.747 |
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- type: ndcg_at_1000 |
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value: 43.881 |
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- type: ndcg_at_3 |
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value: 29.186 |
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- type: ndcg_at_5 |
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value: 30.866 |
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- type: precision_at_1 |
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value: 29.307 |
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- type: precision_at_10 |
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value: 7.632 |
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- type: precision_at_100 |
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value: 1.357 |
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- type: precision_at_1000 |
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value: 0.17600000000000002 |
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- type: precision_at_3 |
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value: 16.688 |
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- type: precision_at_5 |
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value: 12.173 |
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- type: recall_at_1 |
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value: 18.706 |
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- type: recall_at_10 |
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value: 41.925000000000004 |
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- type: recall_at_100 |
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value: 72.817 |
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- type: recall_at_1000 |
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value: 94.33500000000001 |
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- type: recall_at_3 |
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value: 28.968 |
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- type: recall_at_5 |
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value: 34.29 |
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- task: |
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type: PairClassification |
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dataset: |
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type: C-MTEB/CMNLI |
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name: MTEB Cmnli |
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config: default |
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split: validation |
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revision: None |
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metrics: |
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- type: cos_sim_accuracy |
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value: 79.84365604329525 |
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- type: cos_sim_ap |
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value: 87.54800685674849 |
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- type: cos_sim_f1 |
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value: 81.0654184776552 |
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- type: cos_sim_precision |
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value: 77.4488926746167 |
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- type: cos_sim_recall |
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value: 85.0362403553893 |
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- type: dot_accuracy |
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value: 79.84365604329525 |
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- type: dot_ap |
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value: 87.55923139984687 |
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- type: dot_f1 |
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value: 81.0654184776552 |
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- type: dot_precision |
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value: 77.4488926746167 |
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- type: dot_recall |
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value: 85.0362403553893 |
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- type: euclidean_accuracy |
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value: 79.84365604329525 |
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- type: euclidean_ap |
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value: 87.54800685674849 |
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- type: euclidean_f1 |
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value: 81.0654184776552 |
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- type: euclidean_precision |
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value: 77.4488926746167 |
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- type: euclidean_recall |
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value: 85.0362403553893 |
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- type: manhattan_accuracy |
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value: 79.7714972940469 |
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- type: manhattan_ap |
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value: 87.55523320840679 |
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- type: manhattan_f1 |
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value: 80.99598034836983 |
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- type: manhattan_precision |
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value: 77.51656336824108 |
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- type: manhattan_recall |
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value: 84.80243161094225 |
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- type: max_accuracy |
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value: 79.84365604329525 |
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- type: max_ap |
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value: 87.55923139984687 |
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- type: max_f1 |
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value: 81.0654184776552 |
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- task: |
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type: Retrieval |
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dataset: |
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type: C-MTEB/CovidRetrieval |
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name: MTEB CovidRetrieval |
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config: default |
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split: dev |
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revision: None |
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metrics: |
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- type: map_at_1 |
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value: 60.589999999999996 |
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- type: map_at_10 |
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value: 69.27600000000001 |
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- type: map_at_100 |
|
|
value: 69.812 |
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- type: map_at_1000 |
|
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value: 69.82300000000001 |
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- type: map_at_3 |
|
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value: 67.448 |
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- type: map_at_5 |
|
|
value: 68.537 |
|
|
- type: mrr_at_1 |
|
|
value: 60.695 |
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- type: mrr_at_10 |
|
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value: 69.32300000000001 |
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- type: mrr_at_100 |
|
|
value: 69.854 |
|
|
- type: mrr_at_1000 |
|
|
value: 69.865 |
|
|
- type: mrr_at_3 |
|
|
value: 67.545 |
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- type: mrr_at_5 |
|
|
value: 68.625 |
|
|
- type: ndcg_at_1 |
|
|
value: 60.695 |
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|
- type: ndcg_at_10 |
|
|
value: 73.36 |
|
|
- type: ndcg_at_100 |
|
|
value: 75.78200000000001 |
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|
- type: ndcg_at_1000 |
|
|
value: 76.077 |
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|
- type: ndcg_at_3 |
|
|
value: 69.639 |
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|
- type: ndcg_at_5 |
|
|
value: 71.59400000000001 |
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- type: precision_at_1 |
|
|
value: 60.695 |
|
|
- type: precision_at_10 |
|
|
value: 8.704 |
|
|
- type: precision_at_100 |
|
|
value: 0.98 |
|
|
- type: precision_at_1000 |
|
|
value: 0.1 |
|
|
- type: precision_at_3 |
|
|
value: 25.430000000000003 |
|
|
- type: precision_at_5 |
|
|
value: 16.27 |
|
|
- type: recall_at_1 |
|
|
value: 60.589999999999996 |
|
|
- type: recall_at_10 |
|
|
value: 86.038 |
|
|
- type: recall_at_100 |
|
|
value: 96.944 |
|
|
- type: recall_at_1000 |
|
|
value: 99.262 |
|
|
- type: recall_at_3 |
|
|
value: 75.869 |
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- type: recall_at_5 |
|
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value: 80.55799999999999 |
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- task: |
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type: Retrieval |
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dataset: |
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type: C-MTEB/DuRetrieval |
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name: MTEB DuRetrieval |
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config: default |
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split: dev |
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revision: None |
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metrics: |
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- type: map_at_1 |
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|
value: 23.294999999999998 |
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- type: map_at_10 |
|
|
value: 70.99499999999999 |
|
|
- type: map_at_100 |
|
|
value: 74.126 |
|
|
- type: map_at_1000 |
|
|
value: 74.205 |
|
|
- type: map_at_3 |
|
|
value: 48.845 |
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|
- type: map_at_5 |
|
|
value: 61.551 |
|
|
- type: mrr_at_1 |
|
|
value: 83.3 |
|
|
- type: mrr_at_10 |
|
|
value: 88.446 |
|
|
- type: mrr_at_100 |
|
|
value: 88.564 |
|
|
- type: mrr_at_1000 |
|
|
value: 88.57000000000001 |
|
|
- type: mrr_at_3 |
|
|
value: 88.0 |
|
|
- type: mrr_at_5 |
|
|
value: 88.25 |
|
|
- type: ndcg_at_1 |
|
|
value: 83.3 |
|
|
- type: ndcg_at_10 |
|
|
value: 80.128 |
|
|
- type: ndcg_at_100 |
|
|
value: 84.009 |
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|
- type: ndcg_at_1000 |
|
|
value: 84.798 |
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|
- type: ndcg_at_3 |
|
|
value: 78.79 |
|
|
- type: ndcg_at_5 |
|
|
value: 77.405 |
|
|
- type: precision_at_1 |
|
|
value: 83.3 |
|
|
- type: precision_at_10 |
|
|
value: 38.82 |
|
|
- type: precision_at_100 |
|
|
value: 4.657 |
|
|
- type: precision_at_1000 |
|
|
value: 0.484 |
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|
- type: precision_at_3 |
|
|
value: 70.89999999999999 |
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|
- type: precision_at_5 |
|
|
value: 59.550000000000004 |
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|
- type: recall_at_1 |
|
|
value: 23.294999999999998 |
|
|
- type: recall_at_10 |
|
|
value: 82.12 |
|
|
- type: recall_at_100 |
|
|
value: 94.223 |
|
|
- type: recall_at_1000 |
|
|
value: 98.264 |
|
|
- type: recall_at_3 |
|
|
value: 51.946000000000005 |
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- type: recall_at_5 |
|
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value: 67.54299999999999 |
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- task: |
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type: Retrieval |
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dataset: |
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type: C-MTEB/EcomRetrieval |
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name: MTEB EcomRetrieval |
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config: default |
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split: dev |
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revision: None |
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metrics: |
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|
- type: map_at_1 |
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|
value: 42.0 |
|
|
- type: map_at_10 |
|
|
value: 51.207 |
|
|
- type: map_at_100 |
|
|
value: 51.964 |
|
|
- type: map_at_1000 |
|
|
value: 51.993 |
|
|
- type: map_at_3 |
|
|
value: 48.9 |
|
|
- type: map_at_5 |
|
|
value: 50.239999999999995 |
|
|
- type: mrr_at_1 |
|
|
value: 42.0 |
|
|
- type: mrr_at_10 |
|
|
value: 51.207 |
|
|
- type: mrr_at_100 |
|
|
value: 51.964 |
|
|
- type: mrr_at_1000 |
|
|
value: 51.993 |
|
|
- type: mrr_at_3 |
|
|
value: 48.9 |
|
|
- type: mrr_at_5 |
|
|
value: 50.239999999999995 |
|
|
- type: ndcg_at_1 |
|
|
value: 42.0 |
|
|
- type: ndcg_at_10 |
|
|
value: 55.886 |
|
|
- type: ndcg_at_100 |
|
|
value: 59.622 |
|
|
- type: ndcg_at_1000 |
|
|
value: 60.480999999999995 |
|
|
- type: ndcg_at_3 |
|
|
value: 51.112 |
|
|
- type: ndcg_at_5 |
|
|
value: 53.513 |
|
|
- type: precision_at_1 |
|
|
value: 42.0 |
|
|
- type: precision_at_10 |
|
|
value: 7.07 |
|
|
- type: precision_at_100 |
|
|
value: 0.8829999999999999 |
|
|
- type: precision_at_1000 |
|
|
value: 0.095 |
|
|
- type: precision_at_3 |
|
|
value: 19.167 |
|
|
- type: precision_at_5 |
|
|
value: 12.659999999999998 |
|
|
- type: recall_at_1 |
|
|
value: 42.0 |
|
|
- type: recall_at_10 |
|
|
value: 70.7 |
|
|
- type: recall_at_100 |
|
|
value: 88.3 |
|
|
- type: recall_at_1000 |
|
|
value: 95.19999999999999 |
|
|
- type: recall_at_3 |
|
|
value: 57.49999999999999 |
|
|
- type: recall_at_5 |
|
|
value: 63.3 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: C-MTEB/IFlyTek-classification |
|
|
name: MTEB IFlyTek |
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config: default |
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|
split: validation |
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revision: None |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 47.07964601769912 |
|
|
- type: f1 |
|
|
value: 35.71948030119852 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: C-MTEB/JDReview-classification |
|
|
name: MTEB JDReview |
|
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config: default |
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|
split: test |
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revision: None |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 84.48405253283303 |
|
|
- type: ap |
|
|
value: 51.641044322555516 |
|
|
- type: f1 |
|
|
value: 79.09258868144057 |
|
|
- task: |
|
|
type: STS |
|
|
dataset: |
|
|
type: C-MTEB/LCQMC |
|
|
name: MTEB LCQMC |
|
|
config: default |
|
|
split: test |
|
|
revision: None |
|
|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 68.02458550340191 |
|
|
- type: cos_sim_spearman |
|
|
value: 74.28734803466209 |
|
|
- type: euclidean_pearson |
|
|
value: 73.34335009219284 |
|
|
- type: euclidean_spearman |
|
|
value: 74.28734803466209 |
|
|
- type: manhattan_pearson |
|
|
value: 73.34314353425192 |
|
|
- type: manhattan_spearman |
|
|
value: 74.28417768884727 |
|
|
- task: |
|
|
type: Reranking |
|
|
dataset: |
|
|
type: C-MTEB/Mmarco-reranking |
|
|
name: MTEB MMarcoReranking |
|
|
config: default |
|
|
split: dev |
|
|
revision: None |
|
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metrics: |
|
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- type: map |
|
|
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|
|
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|
|
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|
|
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|
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|
|
name: MTEB MMarcoRetrieval |
|
|
config: default |
|
|
split: dev |
|
|
revision: None |
|
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metrics: |
|
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|
|
value: 61.039 |
|
|
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|
|
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|
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|
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|
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|
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|
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|
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|
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|
|
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|
|
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|
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|
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|
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|
|
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|
|
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|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
- type: precision_at_1000 |
|
|
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|
|
- type: precision_at_3 |
|
|
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|
|
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|
|
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|
|
- type: recall_at_1 |
|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
config: af |
|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
config: am |
|
|
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|
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|
|
metrics: |
|
|
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|
|
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|
|
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|
|
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|
|
- task: |
|
|
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|
|
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|
|
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|
|
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|
|
config: ar |
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|
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|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
- task: |
|
|
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|
|
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|
|
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|
|
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|
|
config: az |
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|
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|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
- task: |
|
|
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|
|
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|
|
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|
|
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|
|
config: bn |
|
|
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|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
- task: |
|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
- task: |
|
|
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|
|
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|
|
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|
|
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|
|
config: da |
|
|
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|
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|
|
metrics: |
|
|
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|
|
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|
|
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|
|
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|
|
- task: |
|
|
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|
|
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|
|
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|
|
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|
|
config: de |
|
|
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|
|
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|
|
metrics: |
|
|
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|
|
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|
|
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|
|
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|
|
- task: |
|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
metrics: |
|
|
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|
|
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|
|
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|
|
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|
|
- task: |
|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
metrics: |
|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
metrics: |
|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
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|
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|
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|
|
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|
|
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|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
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|
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|
|
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|
|
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|
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|
|
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|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
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|
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|
|
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|
|
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|
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|
|
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|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
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|
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|
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|
|
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|
|
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|
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|
|
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|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
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|
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|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
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|
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|
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|
|
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|
|
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|
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|
|
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|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
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|
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|
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|
|
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|
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|
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|
|
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|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
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|
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|
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|
|
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|
|
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|
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|
|
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|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
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|
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|
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|
|
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|
|
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|
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|
|
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|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
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|
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|
|
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|
|
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|
|
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|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
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|
|
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|
|
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|
|
type: mteb/amazon_massive_intent |
|
|
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|
|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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config: is |
|
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split: test |
|
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revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
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metrics: |
|
|
- type: accuracy |
|
|
value: 37.804303967720244 |
|
|
- type: f1 |
|
|
value: 33.702687457766196 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: mteb/amazon_massive_scenario |
|
|
name: MTEB MassiveScenarioClassification (it) |
|
|
config: it |
|
|
split: test |
|
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
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metrics: |
|
|
- type: accuracy |
|
|
value: 41.684599865501006 |
|
|
- type: f1 |
|
|
value: 37.827678631817356 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: mteb/amazon_massive_scenario |
|
|
name: MTEB MassiveScenarioClassification (ja) |
|
|
config: ja |
|
|
split: test |
|
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 48.379287155346326 |
|
|
- type: f1 |
|
|
value: 47.42916530771652 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: mteb/amazon_massive_scenario |
|
|
name: MTEB MassiveScenarioClassification (jv) |
|
|
config: jv |
|
|
split: test |
|
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 35.19502353732348 |
|
|
- type: f1 |
|
|
value: 32.346531581560086 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: mteb/amazon_massive_scenario |
|
|
name: MTEB MassiveScenarioClassification (ka) |
|
|
config: ka |
|
|
split: test |
|
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 9.902488231338264 |
|
|
- type: f1 |
|
|
value: 6.949726319598101 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: mteb/amazon_massive_scenario |
|
|
name: MTEB MassiveScenarioClassification (km) |
|
|
config: km |
|
|
split: test |
|
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 12.750504371217216 |
|
|
- type: f1 |
|
|
value: 6.484683676180122 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: mteb/amazon_massive_scenario |
|
|
name: MTEB MassiveScenarioClassification (kn) |
|
|
config: kn |
|
|
split: test |
|
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 10.309347679892403 |
|
|
- type: f1 |
|
|
value: 6.303469804836742 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: mteb/amazon_massive_scenario |
|
|
name: MTEB MassiveScenarioClassification (ko) |
|
|
config: ko |
|
|
split: test |
|
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 14.515803631472762 |
|
|
- type: f1 |
|
|
value: 11.448228509062176 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: mteb/amazon_massive_scenario |
|
|
name: MTEB MassiveScenarioClassification (lv) |
|
|
config: lv |
|
|
split: test |
|
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 33.076664425016816 |
|
|
- type: f1 |
|
|
value: 29.62119483929902 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: mteb/amazon_massive_scenario |
|
|
name: MTEB MassiveScenarioClassification (ml) |
|
|
config: ml |
|
|
split: test |
|
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 7.4411566913248155 |
|
|
- type: f1 |
|
|
value: 3.9500853520943777 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: mteb/amazon_massive_scenario |
|
|
name: MTEB MassiveScenarioClassification (mn) |
|
|
config: mn |
|
|
split: test |
|
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 17.982515131136516 |
|
|
- type: f1 |
|
|
value: 16.21370873212602 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: mteb/amazon_massive_scenario |
|
|
name: MTEB MassiveScenarioClassification (ms) |
|
|
config: ms |
|
|
split: test |
|
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 37.92871553463349 |
|
|
- type: f1 |
|
|
value: 33.45105376049966 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: mteb/amazon_massive_scenario |
|
|
name: MTEB MassiveScenarioClassification (my) |
|
|
config: my |
|
|
split: test |
|
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 11.72831203765972 |
|
|
- type: f1 |
|
|
value: 8.44884960923806 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: mteb/amazon_massive_scenario |
|
|
name: MTEB MassiveScenarioClassification (nb) |
|
|
config: nb |
|
|
split: test |
|
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 38.02286482851379 |
|
|
- type: f1 |
|
|
value: 34.67204151455546 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: mteb/amazon_massive_scenario |
|
|
name: MTEB MassiveScenarioClassification (nl) |
|
|
config: nl |
|
|
split: test |
|
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 40.373234700739744 |
|
|
- type: f1 |
|
|
value: 35.65457711900268 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: mteb/amazon_massive_scenario |
|
|
name: MTEB MassiveScenarioClassification (pl) |
|
|
config: pl |
|
|
split: test |
|
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 36.344989912575656 |
|
|
- type: f1 |
|
|
value: 32.79620374350878 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: mteb/amazon_massive_scenario |
|
|
name: MTEB MassiveScenarioClassification (pt) |
|
|
config: pt |
|
|
split: test |
|
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 41.82918628110289 |
|
|
- type: f1 |
|
|
value: 38.67744252721392 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: mteb/amazon_massive_scenario |
|
|
name: MTEB MassiveScenarioClassification (ro) |
|
|
config: ro |
|
|
split: test |
|
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 40.62542030934767 |
|
|
- type: f1 |
|
|
value: 36.98261635854706 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: mteb/amazon_massive_scenario |
|
|
name: MTEB MassiveScenarioClassification (ru) |
|
|
config: ru |
|
|
split: test |
|
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 18.95763281775387 |
|
|
- type: f1 |
|
|
value: 16.30423107207311 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: mteb/amazon_massive_scenario |
|
|
name: MTEB MassiveScenarioClassification (sl) |
|
|
config: sl |
|
|
split: test |
|
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 35.299260255548084 |
|
|
- type: f1 |
|
|
value: 31.765574086767216 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: mteb/amazon_massive_scenario |
|
|
name: MTEB MassiveScenarioClassification (sq) |
|
|
config: sq |
|
|
split: test |
|
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 41.956960322797585 |
|
|
- type: f1 |
|
|
value: 38.574130779247525 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: mteb/amazon_massive_scenario |
|
|
name: MTEB MassiveScenarioClassification (sv) |
|
|
config: sv |
|
|
split: test |
|
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 37.19233355749832 |
|
|
- type: f1 |
|
|
value: 33.81282301018017 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: mteb/amazon_massive_scenario |
|
|
name: MTEB MassiveScenarioClassification (sw) |
|
|
config: sw |
|
|
split: test |
|
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 38.87693342299933 |
|
|
- type: f1 |
|
|
value: 36.374284150293924 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: mteb/amazon_massive_scenario |
|
|
name: MTEB MassiveScenarioClassification (ta) |
|
|
config: ta |
|
|
split: test |
|
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 8.5137861466039 |
|
|
- type: f1 |
|
|
value: 3.77604514028691 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: mteb/amazon_massive_scenario |
|
|
name: MTEB MassiveScenarioClassification (te) |
|
|
config: te |
|
|
split: test |
|
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 7.347007397444519 |
|
|
- type: f1 |
|
|
value: 4.316679614648472 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: mteb/amazon_massive_scenario |
|
|
name: MTEB MassiveScenarioClassification (th) |
|
|
config: th |
|
|
split: test |
|
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 10.104236718224612 |
|
|
- type: f1 |
|
|
value: 7.587154404252399 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: mteb/amazon_massive_scenario |
|
|
name: MTEB MassiveScenarioClassification (tl) |
|
|
config: tl |
|
|
split: test |
|
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 35.907868190988566 |
|
|
- type: f1 |
|
|
value: 32.42532534803655 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: mteb/amazon_massive_scenario |
|
|
name: MTEB MassiveScenarioClassification (tr) |
|
|
config: tr |
|
|
split: test |
|
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 32.07800941492939 |
|
|
- type: f1 |
|
|
value: 31.072741162550983 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: mteb/amazon_massive_scenario |
|
|
name: MTEB MassiveScenarioClassification (ur) |
|
|
config: ur |
|
|
split: test |
|
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 10.373234700739745 |
|
|
- type: f1 |
|
|
value: 7.124408430261137 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: mteb/amazon_massive_scenario |
|
|
name: MTEB MassiveScenarioClassification (vi) |
|
|
config: vi |
|
|
split: test |
|
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 33.91055817081373 |
|
|
- type: f1 |
|
|
value: 31.82496122405504 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: mteb/amazon_massive_scenario |
|
|
name: MTEB MassiveScenarioClassification (zh-CN) |
|
|
config: zh-CN |
|
|
split: test |
|
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 74.94283792871552 |
|
|
- type: f1 |
|
|
value: 74.29520816825985 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: mteb/amazon_massive_scenario |
|
|
name: MTEB MassiveScenarioClassification (zh-TW) |
|
|
config: zh-TW |
|
|
split: test |
|
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 70.99529253530599 |
|
|
- type: f1 |
|
|
value: 70.48943927686703 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: C-MTEB/MedicalRetrieval |
|
|
name: MTEB MedicalRetrieval |
|
|
config: default |
|
|
split: dev |
|
|
revision: None |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 42.199999999999996 |
|
|
- type: map_at_10 |
|
|
value: 47.774 |
|
|
- type: map_at_100 |
|
|
value: 48.324 |
|
|
- type: map_at_1000 |
|
|
value: 48.392 |
|
|
- type: map_at_3 |
|
|
value: 46.317 |
|
|
- type: map_at_5 |
|
|
value: 47.072 |
|
|
- type: mrr_at_1 |
|
|
value: 42.3 |
|
|
- type: mrr_at_10 |
|
|
value: 47.827 |
|
|
- type: mrr_at_100 |
|
|
value: 48.378 |
|
|
- type: mrr_at_1000 |
|
|
value: 48.446 |
|
|
- type: mrr_at_3 |
|
|
value: 46.367000000000004 |
|
|
- type: mrr_at_5 |
|
|
value: 47.142 |
|
|
- type: ndcg_at_1 |
|
|
value: 42.199999999999996 |
|
|
- type: ndcg_at_10 |
|
|
value: 50.671 |
|
|
- type: ndcg_at_100 |
|
|
value: 53.724000000000004 |
|
|
- type: ndcg_at_1000 |
|
|
value: 55.694 |
|
|
- type: ndcg_at_3 |
|
|
value: 47.625 |
|
|
- type: ndcg_at_5 |
|
|
value: 48.964 |
|
|
- type: precision_at_1 |
|
|
value: 42.199999999999996 |
|
|
- type: precision_at_10 |
|
|
value: 5.99 |
|
|
- type: precision_at_100 |
|
|
value: 0.751 |
|
|
- type: precision_at_1000 |
|
|
value: 0.091 |
|
|
- type: precision_at_3 |
|
|
value: 17.133000000000003 |
|
|
- type: precision_at_5 |
|
|
value: 10.92 |
|
|
- type: recall_at_1 |
|
|
value: 42.199999999999996 |
|
|
- type: recall_at_10 |
|
|
value: 59.9 |
|
|
- type: recall_at_100 |
|
|
value: 75.1 |
|
|
- type: recall_at_1000 |
|
|
value: 91.0 |
|
|
- type: recall_at_3 |
|
|
value: 51.4 |
|
|
- type: recall_at_5 |
|
|
value: 54.6 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: C-MTEB/MultilingualSentiment-classification |
|
|
name: MTEB MultilingualSentiment |
|
|
config: default |
|
|
split: validation |
|
|
revision: None |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 72.68333333333334 |
|
|
- type: f1 |
|
|
value: 72.53084383657173 |
|
|
- task: |
|
|
type: PairClassification |
|
|
dataset: |
|
|
type: C-MTEB/OCNLI |
|
|
name: MTEB Ocnli |
|
|
config: default |
|
|
split: validation |
|
|
revision: None |
|
|
metrics: |
|
|
- type: cos_sim_accuracy |
|
|
value: 72.92907417433676 |
|
|
- type: cos_sim_ap |
|
|
value: 77.2067217322648 |
|
|
- type: cos_sim_f1 |
|
|
value: 76.53631284916202 |
|
|
- type: cos_sim_precision |
|
|
value: 68.44296419650291 |
|
|
- type: cos_sim_recall |
|
|
value: 86.80042238648363 |
|
|
- type: dot_accuracy |
|
|
value: 72.92907417433676 |
|
|
- type: dot_ap |
|
|
value: 77.2067217322648 |
|
|
- type: dot_f1 |
|
|
value: 76.53631284916202 |
|
|
- type: dot_precision |
|
|
value: 68.44296419650291 |
|
|
- type: dot_recall |
|
|
value: 86.80042238648363 |
|
|
- type: euclidean_accuracy |
|
|
value: 72.92907417433676 |
|
|
- type: euclidean_ap |
|
|
value: 77.2067217322648 |
|
|
- type: euclidean_f1 |
|
|
value: 76.53631284916202 |
|
|
- type: euclidean_precision |
|
|
value: 68.44296419650291 |
|
|
- type: euclidean_recall |
|
|
value: 86.80042238648363 |
|
|
- type: manhattan_accuracy |
|
|
value: 72.98321602598809 |
|
|
- type: manhattan_ap |
|
|
value: 77.10385348859928 |
|
|
- type: manhattan_f1 |
|
|
value: 76.67134174848059 |
|
|
- type: manhattan_precision |
|
|
value: 68.79194630872483 |
|
|
- type: manhattan_recall |
|
|
value: 86.58922914466737 |
|
|
- type: max_accuracy |
|
|
value: 72.98321602598809 |
|
|
- type: max_ap |
|
|
value: 77.2067217322648 |
|
|
- type: max_f1 |
|
|
value: 76.67134174848059 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: C-MTEB/OnlineShopping-classification |
|
|
name: MTEB OnlineShopping |
|
|
config: default |
|
|
split: test |
|
|
revision: None |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 92.11000000000003 |
|
|
- type: ap |
|
|
value: 90.49414877664759 |
|
|
- type: f1 |
|
|
value: 92.10539417755511 |
|
|
- task: |
|
|
type: STS |
|
|
dataset: |
|
|
type: C-MTEB/PAWSX |
|
|
name: MTEB PAWSX |
|
|
config: default |
|
|
split: test |
|
|
revision: None |
|
|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 29.106919865870793 |
|
|
- type: cos_sim_spearman |
|
|
value: 33.23892524348652 |
|
|
- type: euclidean_pearson |
|
|
value: 33.62483348491917 |
|
|
- type: euclidean_spearman |
|
|
value: 33.23892524348652 |
|
|
- type: manhattan_pearson |
|
|
value: 33.63464275000747 |
|
|
- type: manhattan_spearman |
|
|
value: 33.250596030941196 |
|
|
- task: |
|
|
type: STS |
|
|
dataset: |
|
|
type: C-MTEB/QBQTC |
|
|
name: MTEB QBQTC |
|
|
config: default |
|
|
split: test |
|
|
revision: None |
|
|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 28.83792748309052 |
|
|
- type: cos_sim_spearman |
|
|
value: 30.92395949947476 |
|
|
- type: euclidean_pearson |
|
|
value: 29.296076928835973 |
|
|
- type: euclidean_spearman |
|
|
value: 30.92395949947476 |
|
|
- type: manhattan_pearson |
|
|
value: 29.220578930008596 |
|
|
- type: manhattan_spearman |
|
|
value: 30.848850181684227 |
|
|
- task: |
|
|
type: STS |
|
|
dataset: |
|
|
type: mteb/sts22-crosslingual-sts |
|
|
name: MTEB STS22 (zh) |
|
|
config: zh |
|
|
split: test |
|
|
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 |
|
|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 62.485183619582465 |
|
|
- type: cos_sim_spearman |
|
|
value: 64.41414883218417 |
|
|
- type: euclidean_pearson |
|
|
value: 63.53854165422046 |
|
|
- type: euclidean_spearman |
|
|
value: 64.41414883218417 |
|
|
- type: manhattan_pearson |
|
|
value: 63.57621522539751 |
|
|
- type: manhattan_spearman |
|
|
value: 64.49062238421523 |
|
|
- task: |
|
|
type: STS |
|
|
dataset: |
|
|
type: C-MTEB/STSB |
|
|
name: MTEB STSB |
|
|
config: default |
|
|
split: test |
|
|
revision: None |
|
|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 78.96466421469466 |
|
|
- type: cos_sim_spearman |
|
|
value: 79.74344126074892 |
|
|
- type: euclidean_pearson |
|
|
value: 79.57588420768205 |
|
|
- type: euclidean_spearman |
|
|
value: 79.74344126074892 |
|
|
- type: manhattan_pearson |
|
|
value: 79.50301779470537 |
|
|
- type: manhattan_spearman |
|
|
value: 79.67817007436709 |
|
|
- task: |
|
|
type: Reranking |
|
|
dataset: |
|
|
type: C-MTEB/T2Reranking |
|
|
name: MTEB T2Reranking |
|
|
config: default |
|
|
split: dev |
|
|
revision: None |
|
|
metrics: |
|
|
- type: map |
|
|
value: 65.85321176285859 |
|
|
- type: mrr |
|
|
value: 75.72496534158688 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: C-MTEB/T2Retrieval |
|
|
name: MTEB T2Retrieval |
|
|
config: default |
|
|
split: dev |
|
|
revision: None |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 24.437 |
|
|
- type: map_at_10 |
|
|
value: 67.85799999999999 |
|
|
- type: map_at_100 |
|
|
value: 71.65599999999999 |
|
|
- type: map_at_1000 |
|
|
value: 71.771 |
|
|
- type: map_at_3 |
|
|
value: 47.752 |
|
|
- type: map_at_5 |
|
|
value: 58.620000000000005 |
|
|
- type: mrr_at_1 |
|
|
value: 83.776 |
|
|
- type: mrr_at_10 |
|
|
value: 87.36699999999999 |
|
|
- type: mrr_at_100 |
|
|
value: 87.529 |
|
|
- type: mrr_at_1000 |
|
|
value: 87.535 |
|
|
- type: mrr_at_3 |
|
|
value: 86.669 |
|
|
- type: mrr_at_5 |
|
|
value: 87.126 |
|
|
- type: ndcg_at_1 |
|
|
value: 83.776 |
|
|
- type: ndcg_at_10 |
|
|
value: 76.839 |
|
|
- type: ndcg_at_100 |
|
|
value: 81.547 |
|
|
- type: ndcg_at_1000 |
|
|
value: 82.723 |
|
|
- type: ndcg_at_3 |
|
|
value: 78.731 |
|
|
- type: ndcg_at_5 |
|
|
value: 76.982 |
|
|
- type: precision_at_1 |
|
|
value: 83.776 |
|
|
- type: precision_at_10 |
|
|
value: 38.507999999999996 |
|
|
- type: precision_at_100 |
|
|
value: 4.809 |
|
|
- type: precision_at_1000 |
|
|
value: 0.509 |
|
|
- type: precision_at_3 |
|
|
value: 69.151 |
|
|
- type: precision_at_5 |
|
|
value: 57.74399999999999 |
|
|
- type: recall_at_1 |
|
|
value: 24.437 |
|
|
- type: recall_at_10 |
|
|
value: 75.887 |
|
|
- type: recall_at_100 |
|
|
value: 91.104 |
|
|
- type: recall_at_1000 |
|
|
value: 97.024 |
|
|
- type: recall_at_3 |
|
|
value: 49.835 |
|
|
- type: recall_at_5 |
|
|
value: 62.854 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: C-MTEB/TNews-classification |
|
|
name: MTEB TNews |
|
|
config: default |
|
|
split: validation |
|
|
revision: None |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 49.851 |
|
|
- type: f1 |
|
|
value: 48.115308719873006 |
|
|
- task: |
|
|
type: Clustering |
|
|
dataset: |
|
|
type: C-MTEB/ThuNewsClusteringP2P |
|
|
name: MTEB ThuNewsClusteringP2P |
|
|
config: default |
|
|
split: test |
|
|
revision: None |
|
|
metrics: |
|
|
- type: v_measure |
|
|
value: 58.53624772949936 |
|
|
- task: |
|
|
type: Clustering |
|
|
dataset: |
|
|
type: C-MTEB/ThuNewsClusteringS2S |
|
|
name: MTEB ThuNewsClusteringS2S |
|
|
config: default |
|
|
split: test |
|
|
revision: None |
|
|
metrics: |
|
|
- type: v_measure |
|
|
value: 54.145039782849956 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: C-MTEB/VideoRetrieval |
|
|
name: MTEB VideoRetrieval |
|
|
config: default |
|
|
split: dev |
|
|
revision: None |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 49.0 |
|
|
- type: map_at_10 |
|
|
value: 58.888 |
|
|
- type: map_at_100 |
|
|
value: 59.512 |
|
|
- type: map_at_1000 |
|
|
value: 59.532 |
|
|
- type: map_at_3 |
|
|
value: 56.65 |
|
|
- type: map_at_5 |
|
|
value: 57.91 |
|
|
- type: mrr_at_1 |
|
|
value: 49.0 |
|
|
- type: mrr_at_10 |
|
|
value: 58.888 |
|
|
- type: mrr_at_100 |
|
|
value: 59.512 |
|
|
- type: mrr_at_1000 |
|
|
value: 59.532 |
|
|
- type: mrr_at_3 |
|
|
value: 56.65 |
|
|
- type: mrr_at_5 |
|
|
value: 57.91 |
|
|
- type: ndcg_at_1 |
|
|
value: 49.0 |
|
|
- type: ndcg_at_10 |
|
|
value: 63.656 |
|
|
- type: ndcg_at_100 |
|
|
value: 66.666 |
|
|
- type: ndcg_at_1000 |
|
|
value: 67.269 |
|
|
- type: ndcg_at_3 |
|
|
value: 59.082 |
|
|
- type: ndcg_at_5 |
|
|
value: 61.35 |
|
|
- type: precision_at_1 |
|
|
value: 49.0 |
|
|
- type: precision_at_10 |
|
|
value: 7.86 |
|
|
- type: precision_at_100 |
|
|
value: 0.9259999999999999 |
|
|
- type: precision_at_1000 |
|
|
value: 0.098 |
|
|
- type: precision_at_3 |
|
|
value: 22.033 |
|
|
- type: precision_at_5 |
|
|
value: 14.32 |
|
|
- type: recall_at_1 |
|
|
value: 49.0 |
|
|
- type: recall_at_10 |
|
|
value: 78.60000000000001 |
|
|
- type: recall_at_100 |
|
|
value: 92.60000000000001 |
|
|
- type: recall_at_1000 |
|
|
value: 97.5 |
|
|
- type: recall_at_3 |
|
|
value: 66.10000000000001 |
|
|
- type: recall_at_5 |
|
|
value: 71.6 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: C-MTEB/waimai-classification |
|
|
name: MTEB Waimai |
|
|
config: default |
|
|
split: test |
|
|
revision: None |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 86.44000000000001 |
|
|
- type: ap |
|
|
value: 69.51298270778649 |
|
|
- type: f1 |
|
|
value: 84.72728998827236 |
|
|
--- |
|
|
license: mit |
|
|
--- |
|
|
|
