Upload README.md
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README.md
CHANGED
@@ -14,17 +14,17 @@ model-index:
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revision: None
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metrics:
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- type: cos_sim_pearson
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-
value: 44.
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- type: cos_sim_spearman
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-
value: 46.
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- type: euclidean_pearson
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-
value: 45.
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- type: euclidean_spearman
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-
value: 46.
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- type: manhattan_pearson
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-
value: 45.
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- type: manhattan_spearman
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-
value: 46.
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- task:
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type: STS
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dataset:
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@@ -35,17 +35,17 @@ model-index:
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revision: None
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metrics:
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- type: cos_sim_pearson
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-
value: 49.
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- type: cos_sim_spearman
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-
value: 51.
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- type: euclidean_pearson
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-
value: 53.
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- type: euclidean_spearman
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-
value: 51.
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- type: manhattan_pearson
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-
value: 53.
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- type: manhattan_spearman
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-
value: 51.
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- task:
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type: Classification
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dataset:
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@@ -56,9 +56,9 @@ model-index:
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revision: 1399c76144fd37290681b995c656ef9b2e06e26d
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metrics:
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- type: accuracy
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-
value:
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- type: f1
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-
value:
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- task:
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type: STS
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dataset:
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@@ -69,17 +69,17 @@ model-index:
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revision: None
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metrics:
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- type: cos_sim_pearson
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-
value:
|
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- type: cos_sim_spearman
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-
value:
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- type: euclidean_pearson
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-
value: 63.
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- type: euclidean_spearman
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-
value:
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- type: manhattan_pearson
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-
value: 63.
|
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- type: manhattan_spearman
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-
value:
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- task:
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type: Clustering
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dataset:
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@@ -90,7 +90,7 @@ model-index:
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revision: None
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metrics:
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- type: v_measure
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-
value:
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- task:
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type: Clustering
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dataset:
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@@ -101,7 +101,7 @@ model-index:
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revision: None
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metrics:
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- type: v_measure
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-
value: 37.
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- task:
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type: Reranking
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dataset:
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@@ -112,9 +112,9 @@ model-index:
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revision: None
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metrics:
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- type: map
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-
value: 84.
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- type: mrr
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-
value: 86.
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- task:
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type: Reranking
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dataset:
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@@ -125,9 +125,9 @@ model-index:
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revision: None
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metrics:
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- type: map
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-
value: 85.
|
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- type: mrr
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-
value: 87.
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- task:
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type: Retrieval
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dataset:
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@@ -138,65 +138,65 @@ model-index:
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revision: None
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metrics:
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- type: map_at_1
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-
value:
|
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- type: map_at_10
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-
value: 35.
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- type: map_at_100
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-
value: 37.
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- type: map_at_1000
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-
value: 37.
|
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- type: map_at_3
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-
value: 31.
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- type: map_at_5
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-
value: 33.
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- type: mrr_at_1
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-
value: 36.
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- type: mrr_at_10
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-
value: 44.
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- type: mrr_at_100
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-
value: 45.
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- type: mrr_at_1000
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-
value: 45.
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- type: mrr_at_3
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-
value:
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- type: mrr_at_5
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-
value: 43.
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- type: ndcg_at_1
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-
value: 36.
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- type: ndcg_at_10
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-
value: 41.
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- type: ndcg_at_100
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-
value:
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- type: ndcg_at_1000
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-
value: 51.
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- type: ndcg_at_3
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-
value: 36.
|
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- type: ndcg_at_5
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-
value: 38.
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- type: precision_at_1
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-
value: 36.
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- type: precision_at_10
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-
value: 9.
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- type: precision_at_100
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-
value: 1.
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- type: precision_at_1000
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value: 0.183
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- type: precision_at_3
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-
value: 20.
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- type: precision_at_5
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-
value: 15.
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- type: recall_at_1
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-
value:
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- type: recall_at_10
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-
value: 51.
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- type: recall_at_100
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-
value: 81.
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- type: recall_at_1000
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-
value: 98.
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- type: recall_at_3
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-
value: 36.
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- type: recall_at_5
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-
value: 42.
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- task:
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type: PairClassification
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dataset:
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@@ -207,51 +207,51 @@ model-index:
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revision: None
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metrics:
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- type: cos_sim_accuracy
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-
value:
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- type: cos_sim_ap
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-
value: 84.
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- type: cos_sim_f1
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-
value: 77.
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- type: cos_sim_precision
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-
value: 72.
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- type: cos_sim_recall
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-
value:
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- type: dot_accuracy
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-
value:
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- type: dot_ap
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-
value: 84.
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- type: dot_f1
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-
value: 77.
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- type: dot_precision
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-
value: 72.
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- type: dot_recall
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-
value:
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- type: euclidean_accuracy
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-
value:
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- type: euclidean_ap
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-
value: 84.
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- type: euclidean_f1
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-
value: 77.
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- type: euclidean_precision
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-
value: 72.
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- type: euclidean_recall
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-
value:
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- type: manhattan_accuracy
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-
value:
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- type: manhattan_ap
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-
value: 84.
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- type: manhattan_f1
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-
value: 77.
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- type: manhattan_precision
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-
value:
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- type: manhattan_recall
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-
value:
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- type: max_accuracy
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-
value:
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- type: max_ap
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-
value: 84.
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- type: max_f1
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-
value: 77.
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- task:
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type: Retrieval
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dataset:
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@@ -262,65 +262,65 @@ model-index:
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revision: None
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metrics:
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- type: map_at_1
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-
value:
|
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- type: map_at_10
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-
value: 75.
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- type: map_at_100
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-
value:
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- type: map_at_1000
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-
value:
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- type: map_at_3
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-
value: 73.
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- type: map_at_5
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-
value: 74.
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- type: mrr_at_1
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-
value:
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- type: mrr_at_10
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-
value: 75.
|
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- type: mrr_at_100
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-
value: 75.
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- type: mrr_at_1000
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-
value: 75.
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- type: mrr_at_3
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-
value: 73.
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- type: mrr_at_5
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-
value: 74.
|
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- type: ndcg_at_1
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-
value:
|
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- type: ndcg_at_10
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-
value: 79.
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- type: ndcg_at_100
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-
value:
|
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- type: ndcg_at_1000
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-
value:
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- type: ndcg_at_3
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-
value: 75.
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- type: ndcg_at_5
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-
value: 77.
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- type: precision_at_1
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-
value:
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- type: precision_at_10
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-
value: 9.
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- type: precision_at_100
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-
value: 0.
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- type: precision_at_1000
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value: 0.101
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- type: precision_at_3
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-
value: 27.
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- type: precision_at_5
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-
value: 17.
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- type: recall_at_1
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-
value:
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- type: recall_at_10
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-
value:
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- type: recall_at_100
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-
value: 98.
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- type: recall_at_1000
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value: 99.684
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- type: recall_at_3
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-
value: 81.
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- type: recall_at_5
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-
value:
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- task:
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type: Retrieval
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dataset:
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@@ -331,65 +331,65 @@ model-index:
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revision: None
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metrics:
|
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- type: map_at_1
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334 |
-
value: 25.
|
335 |
- type: map_at_10
|
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-
value:
|
337 |
- type: map_at_100
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-
value: 81.
|
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- type: map_at_1000
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-
value:
|
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- type: map_at_3
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-
value: 54.
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- type: map_at_5
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-
value: 68.
|
345 |
- type: mrr_at_1
|
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-
value:
|
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- type: mrr_at_10
|
348 |
-
value: 92.
|
349 |
- type: mrr_at_100
|
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-
value: 92.
|
351 |
- type: mrr_at_1000
|
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-
value: 92.
|
353 |
- type: mrr_at_3
|
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-
value:
|
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- type: mrr_at_5
|
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-
value: 92.
|
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- type: ndcg_at_1
|
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-
value:
|
359 |
- type: ndcg_at_10
|
360 |
-
value: 86.
|
361 |
- type: ndcg_at_100
|
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-
value: 89.
|
363 |
- type: ndcg_at_1000
|
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-
value: 89.
|
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- type: ndcg_at_3
|
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-
value:
|
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- type: ndcg_at_5
|
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-
value: 84.
|
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- type: precision_at_1
|
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-
value:
|
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- type: precision_at_10
|
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-
value: 41.
|
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- type: precision_at_100
|
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-
value: 4.
|
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- type: precision_at_1000
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value: 0.48900000000000005
|
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- type: precision_at_3
|
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-
value: 76.
|
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- type: precision_at_5
|
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-
value: 64.
|
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- type: recall_at_1
|
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-
value: 25.
|
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- type: recall_at_10
|
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-
value: 88.
|
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- type: recall_at_100
|
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-
value: 97.
|
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- type: recall_at_1000
|
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-
value: 99.
|
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- type: recall_at_3
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-
value: 56.
|
391 |
- type: recall_at_5
|
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-
value: 74.
|
393 |
- task:
|
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type: Retrieval
|
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dataset:
|
@@ -400,65 +400,65 @@ model-index:
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revision: None
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metrics:
|
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- type: map_at_1
|
403 |
-
value:
|
404 |
- type: map_at_10
|
405 |
-
value: 57.
|
406 |
- type: map_at_100
|
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-
value:
|
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- type: map_at_1000
|
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-
value:
|
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- type: map_at_3
|
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-
value: 54.
|
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- type: map_at_5
|
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-
value: 56.
|
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- type: mrr_at_1
|
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-
value:
|
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- type: mrr_at_10
|
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-
value: 57.
|
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- type: mrr_at_100
|
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-
value:
|
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- type: mrr_at_1000
|
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-
value:
|
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- type: mrr_at_3
|
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-
value: 54.
|
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- type: mrr_at_5
|
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-
value: 56.
|
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- type: ndcg_at_1
|
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-
value:
|
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- type: ndcg_at_10
|
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-
value: 62.
|
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- type: ndcg_at_100
|
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-
value: 65.
|
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- type: ndcg_at_1000
|
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-
value:
|
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- type: ndcg_at_3
|
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-
value:
|
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- type: ndcg_at_5
|
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-
value:
|
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- type: precision_at_1
|
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-
value:
|
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- type: precision_at_10
|
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-
value: 7.
|
442 |
- type: precision_at_100
|
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-
value: 0.
|
444 |
- type: precision_at_1000
|
445 |
value: 0.097
|
446 |
- type: precision_at_3
|
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value: 21.133
|
448 |
- type: precision_at_5
|
449 |
-
value: 14.
|
450 |
- type: recall_at_1
|
451 |
-
value:
|
452 |
- type: recall_at_10
|
453 |
-
value: 78.
|
454 |
- type: recall_at_100
|
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-
value: 92.
|
456 |
- type: recall_at_1000
|
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value: 96.6
|
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- type: recall_at_3
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459 |
value: 63.4
|
460 |
- type: recall_at_5
|
461 |
-
value:
|
462 |
- task:
|
463 |
type: Classification
|
464 |
dataset:
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@@ -469,9 +469,9 @@ model-index:
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|
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revision: None
|
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metrics:
|
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- type: accuracy
|
472 |
-
value:
|
473 |
- type: f1
|
474 |
-
value: 35.
|
475 |
- task:
|
476 |
type: Classification
|
477 |
dataset:
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@@ -482,11 +482,11 @@ model-index:
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|
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revision: None
|
483 |
metrics:
|
484 |
- type: accuracy
|
485 |
-
value: 84.
|
486 |
- type: ap
|
487 |
-
value: 52.
|
488 |
- type: f1
|
489 |
-
value: 79.
|
490 |
- task:
|
491 |
type: STS
|
492 |
dataset:
|
@@ -497,17 +497,17 @@ model-index:
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|
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revision: None
|
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metrics:
|
499 |
- type: cos_sim_pearson
|
500 |
-
value:
|
501 |
- type: cos_sim_spearman
|
502 |
-
value:
|
503 |
- type: euclidean_pearson
|
504 |
-
value: 75.
|
505 |
- type: euclidean_spearman
|
506 |
-
value:
|
507 |
- type: manhattan_pearson
|
508 |
-
value: 75.
|
509 |
- type: manhattan_spearman
|
510 |
-
value:
|
511 |
- task:
|
512 |
type: Retrieval
|
513 |
dataset:
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@@ -518,65 +518,65 @@ model-index:
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|
518 |
revision: None
|
519 |
metrics:
|
520 |
- type: map_at_1
|
521 |
-
value: 65.
|
522 |
- type: map_at_10
|
523 |
-
value: 74.
|
524 |
- type: map_at_100
|
525 |
-
value: 74.
|
526 |
- type: map_at_1000
|
527 |
-
value: 74.
|
528 |
- type: map_at_3
|
529 |
-
value: 72.
|
530 |
- type: map_at_5
|
531 |
-
value: 73.
|
532 |
- type: mrr_at_1
|
533 |
-
value: 67.
|
534 |
- type: mrr_at_10
|
535 |
-
value:
|
536 |
- type: mrr_at_100
|
537 |
-
value: 75.
|
538 |
- type: mrr_at_1000
|
539 |
-
value: 75.
|
540 |
- type: mrr_at_3
|
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-
value: 73.
|
542 |
- type: mrr_at_5
|
543 |
-
value: 74.
|
544 |
- type: ndcg_at_1
|
545 |
-
value: 67.
|
546 |
- type: ndcg_at_10
|
547 |
-
value:
|
548 |
- type: ndcg_at_100
|
549 |
-
value: 79.
|
550 |
- type: ndcg_at_1000
|
551 |
-
value:
|
552 |
- type: ndcg_at_3
|
553 |
-
value: 74.
|
554 |
- type: ndcg_at_5
|
555 |
-
value: 76.
|
556 |
- type: precision_at_1
|
557 |
-
value: 67.
|
558 |
- type: precision_at_10
|
559 |
-
value: 9.
|
560 |
- type: precision_at_100
|
561 |
-
value: 1.
|
562 |
- type: precision_at_1000
|
563 |
value: 0.105
|
564 |
- type: precision_at_3
|
565 |
-
value:
|
566 |
- type: precision_at_5
|
567 |
-
value: 17.
|
568 |
- type: recall_at_1
|
569 |
-
value: 65.
|
570 |
- type: recall_at_10
|
571 |
-
value: 88.
|
572 |
- type: recall_at_100
|
573 |
-
value: 95.
|
574 |
- type: recall_at_1000
|
575 |
-
value: 98.
|
576 |
- type: recall_at_3
|
577 |
-
value: 79.
|
578 |
- type: recall_at_5
|
579 |
-
value: 84.
|
580 |
- task:
|
581 |
type: Classification
|
582 |
dataset:
|
@@ -587,9 +587,9 @@ model-index:
|
|
587 |
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
|
588 |
metrics:
|
589 |
- type: accuracy
|
590 |
-
value: 67.
|
591 |
- type: f1
|
592 |
-
value:
|
593 |
- task:
|
594 |
type: Classification
|
595 |
dataset:
|
@@ -600,9 +600,9 @@ model-index:
|
|
600 |
revision: 7d571f92784cd94a019292a1f45445077d0ef634
|
601 |
metrics:
|
602 |
- type: accuracy
|
603 |
-
value:
|
604 |
- type: f1
|
605 |
-
value: 72.
|
606 |
- task:
|
607 |
type: Retrieval
|
608 |
dataset:
|
@@ -613,65 +613,65 @@ model-index:
|
|
613 |
revision: None
|
614 |
metrics:
|
615 |
- type: map_at_1
|
616 |
-
value: 48.
|
617 |
- type: map_at_10
|
618 |
-
value:
|
619 |
- type: map_at_100
|
620 |
-
value: 55.
|
621 |
- type: map_at_1000
|
622 |
-
value: 55.
|
623 |
- type: map_at_3
|
624 |
-
value: 53.
|
625 |
- type: map_at_5
|
626 |
-
value: 54.
|
627 |
- type: mrr_at_1
|
628 |
-
value:
|
629 |
- type: mrr_at_10
|
630 |
-
value:
|
631 |
- type: mrr_at_100
|
632 |
-
value: 55.
|
633 |
- type: mrr_at_1000
|
634 |
-
value: 55.
|
635 |
- type: mrr_at_3
|
636 |
-
value: 53.
|
637 |
- type: mrr_at_5
|
638 |
-
value: 54.
|
639 |
- type: ndcg_at_1
|
640 |
-
value: 48.
|
641 |
- type: ndcg_at_10
|
642 |
-
value:
|
643 |
- type: ndcg_at_100
|
644 |
-
value: 60.
|
645 |
- type: ndcg_at_1000
|
646 |
-
value: 62.
|
647 |
- type: ndcg_at_3
|
648 |
-
value:
|
649 |
- type: ndcg_at_5
|
650 |
-
value: 56.
|
651 |
- type: precision_at_1
|
652 |
-
value: 48.
|
653 |
- type: precision_at_10
|
654 |
-
value: 6.
|
655 |
- type: precision_at_100
|
656 |
-
value: 0.
|
657 |
- type: precision_at_1000
|
658 |
value: 0.095
|
659 |
- type: precision_at_3
|
660 |
-
value: 19.
|
661 |
- type: precision_at_5
|
662 |
-
value: 12.
|
663 |
- type: recall_at_1
|
664 |
-
value: 48.
|
665 |
- type: recall_at_10
|
666 |
-
value:
|
667 |
- type: recall_at_100
|
668 |
-
value: 81.
|
669 |
- type: recall_at_1000
|
670 |
-
value:
|
671 |
- type: recall_at_3
|
672 |
-
value: 59.
|
673 |
- type: recall_at_5
|
674 |
-
value: 63.
|
675 |
- task:
|
676 |
type: Classification
|
677 |
dataset:
|
@@ -682,9 +682,9 @@ model-index:
|
|
682 |
revision: None
|
683 |
metrics:
|
684 |
- type: accuracy
|
685 |
-
value: 71.
|
686 |
- type: f1
|
687 |
-
value: 70.
|
688 |
- task:
|
689 |
type: PairClassification
|
690 |
dataset:
|
@@ -695,51 +695,51 @@ model-index:
|
|
695 |
revision: None
|
696 |
metrics:
|
697 |
- type: cos_sim_accuracy
|
698 |
-
value:
|
699 |
- type: cos_sim_ap
|
700 |
-
value:
|
701 |
- type: cos_sim_f1
|
702 |
-
value: 73.
|
703 |
- type: cos_sim_precision
|
704 |
-
value: 62.
|
705 |
- type: cos_sim_recall
|
706 |
-
value:
|
707 |
- type: dot_accuracy
|
708 |
-
value:
|
709 |
- type: dot_ap
|
710 |
-
value:
|
711 |
- type: dot_f1
|
712 |
-
value: 73.
|
713 |
- type: dot_precision
|
714 |
-
value: 62.
|
715 |
- type: dot_recall
|
716 |
-
value:
|
717 |
- type: euclidean_accuracy
|
718 |
-
value:
|
719 |
- type: euclidean_ap
|
720 |
-
value:
|
721 |
- type: euclidean_f1
|
722 |
-
value: 73.
|
723 |
- type: euclidean_precision
|
724 |
-
value: 62.
|
725 |
- type: euclidean_recall
|
726 |
-
value:
|
727 |
- type: manhattan_accuracy
|
728 |
-
value:
|
729 |
- type: manhattan_ap
|
730 |
-
value:
|
731 |
- type: manhattan_f1
|
732 |
-
value:
|
733 |
- type: manhattan_precision
|
734 |
-
value:
|
735 |
- type: manhattan_recall
|
736 |
-
value:
|
737 |
- type: max_accuracy
|
738 |
-
value:
|
739 |
- type: max_ap
|
740 |
-
value:
|
741 |
- type: max_f1
|
742 |
-
value: 73.
|
743 |
- task:
|
744 |
type: Classification
|
745 |
dataset:
|
@@ -750,11 +750,11 @@ model-index:
|
|
750 |
revision: None
|
751 |
metrics:
|
752 |
- type: accuracy
|
753 |
-
value: 91.
|
754 |
- type: ap
|
755 |
-
value: 89.
|
756 |
- type: f1
|
757 |
-
value: 91.
|
758 |
- task:
|
759 |
type: STS
|
760 |
dataset:
|
@@ -765,17 +765,17 @@ model-index:
|
|
765 |
revision: None
|
766 |
metrics:
|
767 |
- type: cos_sim_pearson
|
768 |
-
value:
|
769 |
- type: cos_sim_spearman
|
770 |
-
value:
|
771 |
- type: euclidean_pearson
|
772 |
-
value:
|
773 |
- type: euclidean_spearman
|
774 |
-
value:
|
775 |
- type: manhattan_pearson
|
776 |
-
value:
|
777 |
- type: manhattan_spearman
|
778 |
-
value: 29.
|
779 |
- task:
|
780 |
type: STS
|
781 |
dataset:
|
@@ -786,17 +786,17 @@ model-index:
|
|
786 |
revision: None
|
787 |
metrics:
|
788 |
- type: cos_sim_pearson
|
789 |
-
value:
|
790 |
- type: cos_sim_spearman
|
791 |
-
value: 37.
|
792 |
- type: euclidean_pearson
|
793 |
-
value: 35.
|
794 |
- type: euclidean_spearman
|
795 |
-
value: 37.
|
796 |
- type: manhattan_pearson
|
797 |
-
value: 35.
|
798 |
- type: manhattan_spearman
|
799 |
-
value: 37.
|
800 |
- task:
|
801 |
type: STS
|
802 |
dataset:
|
@@ -807,17 +807,17 @@ model-index:
|
|
807 |
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
|
808 |
metrics:
|
809 |
- type: cos_sim_pearson
|
810 |
-
value: 68.
|
811 |
- type: cos_sim_spearman
|
812 |
-
value: 69.
|
813 |
- type: euclidean_pearson
|
814 |
-
value:
|
815 |
- type: euclidean_spearman
|
816 |
-
value: 69.
|
817 |
- type: manhattan_pearson
|
818 |
-
value: 70.
|
819 |
- type: manhattan_spearman
|
820 |
-
value: 70.
|
821 |
- task:
|
822 |
type: STS
|
823 |
dataset:
|
@@ -828,17 +828,17 @@ model-index:
|
|
828 |
revision: None
|
829 |
metrics:
|
830 |
- type: cos_sim_pearson
|
831 |
-
value:
|
832 |
- type: cos_sim_spearman
|
833 |
-
value: 79.
|
834 |
- type: euclidean_pearson
|
835 |
-
value: 79.
|
836 |
- type: euclidean_spearman
|
837 |
-
value: 79.
|
838 |
- type: manhattan_pearson
|
839 |
-
value: 79.
|
840 |
- type: manhattan_spearman
|
841 |
-
value: 79.
|
842 |
- task:
|
843 |
type: Reranking
|
844 |
dataset:
|
@@ -849,9 +849,9 @@ model-index:
|
|
849 |
revision: None
|
850 |
metrics:
|
851 |
- type: map
|
852 |
-
value:
|
853 |
- type: mrr
|
854 |
-
value:
|
855 |
- task:
|
856 |
type: Retrieval
|
857 |
dataset:
|
@@ -862,65 +862,65 @@ model-index:
|
|
862 |
revision: None
|
863 |
metrics:
|
864 |
- type: map_at_1
|
865 |
-
value: 26.
|
866 |
- type: map_at_10
|
867 |
-
value:
|
868 |
- type: map_at_100
|
869 |
-
value:
|
870 |
- type: map_at_1000
|
871 |
-
value:
|
872 |
- type: map_at_3
|
873 |
-
value:
|
874 |
- type: map_at_5
|
875 |
-
value:
|
876 |
- type: mrr_at_1
|
877 |
-
value:
|
878 |
- type: mrr_at_10
|
879 |
-
value:
|
880 |
- type: mrr_at_100
|
881 |
-
value:
|
882 |
- type: mrr_at_1000
|
883 |
-
value:
|
884 |
- type: mrr_at_3
|
885 |
-
value: 90.
|
886 |
- type: mrr_at_5
|
887 |
-
value:
|
888 |
- type: ndcg_at_1
|
889 |
-
value:
|
890 |
- type: ndcg_at_10
|
891 |
-
value:
|
892 |
- type: ndcg_at_100
|
893 |
-
value: 86.
|
894 |
- type: ndcg_at_1000
|
895 |
-
value:
|
896 |
- type: ndcg_at_3
|
897 |
-
value:
|
898 |
- type: ndcg_at_5
|
899 |
-
value:
|
900 |
- type: precision_at_1
|
901 |
-
value:
|
902 |
- type: precision_at_10
|
903 |
-
value: 41.
|
904 |
- type: precision_at_100
|
905 |
-
value: 4.
|
906 |
- type: precision_at_1000
|
907 |
value: 0.515
|
908 |
- type: precision_at_3
|
909 |
-
value:
|
910 |
- type: precision_at_5
|
911 |
-
value:
|
912 |
- type: recall_at_1
|
913 |
-
value: 26.
|
914 |
- type: recall_at_10
|
915 |
-
value:
|
916 |
- type: recall_at_100
|
917 |
-
value: 94.
|
918 |
- type: recall_at_1000
|
919 |
-
value: 98.
|
920 |
- type: recall_at_3
|
921 |
-
value:
|
922 |
- type: recall_at_5
|
923 |
-
value:
|
924 |
- task:
|
925 |
type: Classification
|
926 |
dataset:
|
@@ -931,9 +931,9 @@ model-index:
|
|
931 |
revision: None
|
932 |
metrics:
|
933 |
- type: accuracy
|
934 |
-
value: 51.
|
935 |
- type: f1
|
936 |
-
value: 49.
|
937 |
- task:
|
938 |
type: Clustering
|
939 |
dataset:
|
@@ -944,7 +944,7 @@ model-index:
|
|
944 |
revision: None
|
945 |
metrics:
|
946 |
- type: v_measure
|
947 |
-
value: 62.
|
948 |
- task:
|
949 |
type: Clustering
|
950 |
dataset:
|
@@ -955,7 +955,7 @@ model-index:
|
|
955 |
revision: None
|
956 |
metrics:
|
957 |
- type: v_measure
|
958 |
-
value:
|
959 |
- task:
|
960 |
type: Retrieval
|
961 |
dataset:
|
@@ -966,65 +966,65 @@ model-index:
|
|
966 |
revision: None
|
967 |
metrics:
|
968 |
- type: map_at_1
|
969 |
-
value: 52.
|
970 |
- type: map_at_10
|
971 |
-
value: 62.
|
972 |
- type: map_at_100
|
973 |
-
value: 63.
|
974 |
- type: map_at_1000
|
975 |
-
value: 63.
|
976 |
- type: map_at_3
|
977 |
-
value: 60.
|
978 |
- type: map_at_5
|
979 |
-
value:
|
980 |
- type: mrr_at_1
|
981 |
-
value: 52.
|
982 |
- type: mrr_at_10
|
983 |
-
value: 62.
|
984 |
- type: mrr_at_100
|
985 |
-
value: 63.
|
986 |
- type: mrr_at_1000
|
987 |
-
value: 63.
|
988 |
- type: mrr_at_3
|
989 |
-
value: 60.
|
990 |
- type: mrr_at_5
|
991 |
-
value:
|
992 |
- type: ndcg_at_1
|
993 |
-
value: 52.
|
994 |
- type: ndcg_at_10
|
995 |
-
value: 67.
|
996 |
- type: ndcg_at_100
|
997 |
-
value: 70.
|
998 |
- type: ndcg_at_1000
|
999 |
-
value: 70.
|
1000 |
- type: ndcg_at_3
|
1001 |
-
value:
|
1002 |
- type: ndcg_at_5
|
1003 |
-
value: 65.
|
1004 |
- type: precision_at_1
|
1005 |
-
value: 52.
|
1006 |
- type: precision_at_10
|
1007 |
-
value: 8.
|
1008 |
- type: precision_at_100
|
1009 |
-
value: 0.
|
1010 |
- type: precision_at_1000
|
1011 |
value: 0.098
|
1012 |
- type: precision_at_3
|
1013 |
-
value: 23.
|
1014 |
- type: precision_at_5
|
1015 |
-
value: 15.
|
1016 |
- type: recall_at_1
|
1017 |
-
value: 52.
|
1018 |
- type: recall_at_10
|
1019 |
-
value:
|
1020 |
- type: recall_at_100
|
1021 |
-
value: 95.
|
1022 |
- type: recall_at_1000
|
1023 |
value: 98.2
|
1024 |
- type: recall_at_3
|
1025 |
-
value: 70.
|
1026 |
- type: recall_at_5
|
1027 |
-
value:
|
1028 |
- task:
|
1029 |
type: Classification
|
1030 |
dataset:
|
@@ -1035,11 +1035,11 @@ model-index:
|
|
1035 |
revision: None
|
1036 |
metrics:
|
1037 |
- type: accuracy
|
1038 |
-
value: 86.
|
1039 |
- type: ap
|
1040 |
-
value: 69.
|
1041 |
- type: f1
|
1042 |
-
value: 84.
|
1043 |
- task:
|
1044 |
type: Reranking
|
1045 |
dataset:
|
@@ -1050,7 +1050,7 @@ model-index:
|
|
1050 |
revision: None
|
1051 |
metrics:
|
1052 |
- type: map
|
1053 |
-
value:
|
1054 |
- type: mrr
|
1055 |
-
value: 26.
|
1056 |
---
|
|
|
14 |
revision: None
|
15 |
metrics:
|
16 |
- type: cos_sim_pearson
|
17 |
+
value: 44.80910972039708
|
18 |
- type: cos_sim_spearman
|
19 |
+
value: 46.97947004057185
|
20 |
- type: euclidean_pearson
|
21 |
+
value: 45.36774158404125
|
22 |
- type: euclidean_spearman
|
23 |
+
value: 46.97947004232487
|
24 |
- type: manhattan_pearson
|
25 |
+
value: 45.23486628014998
|
26 |
- type: manhattan_spearman
|
27 |
+
value: 46.87721960765866
|
28 |
- task:
|
29 |
type: STS
|
30 |
dataset:
|
|
|
35 |
revision: None
|
36 |
metrics:
|
37 |
- type: cos_sim_pearson
|
38 |
+
value: 49.5294624928126
|
39 |
- type: cos_sim_spearman
|
40 |
+
value: 51.34771777448503
|
41 |
- type: euclidean_pearson
|
42 |
+
value: 53.56859824288157
|
43 |
- type: euclidean_spearman
|
44 |
+
value: 51.34771439634126
|
45 |
- type: manhattan_pearson
|
46 |
+
value: 53.581640877132685
|
47 |
- type: manhattan_spearman
|
48 |
+
value: 51.349656519071274
|
49 |
- task:
|
50 |
type: Classification
|
51 |
dataset:
|
|
|
56 |
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
|
57 |
metrics:
|
58 |
- type: accuracy
|
59 |
+
value: 39.318
|
60 |
- type: f1
|
61 |
+
value: 37.37720144558489
|
62 |
- task:
|
63 |
type: STS
|
64 |
dataset:
|
|
|
69 |
revision: None
|
70 |
metrics:
|
71 |
- type: cos_sim_pearson
|
72 |
+
value: 62.12016334764962
|
73 |
- type: cos_sim_spearman
|
74 |
+
value: 65.08208654969742
|
75 |
- type: euclidean_pearson
|
76 |
+
value: 63.53078822303454
|
77 |
- type: euclidean_spearman
|
78 |
+
value: 65.0820865487212
|
79 |
- type: manhattan_pearson
|
80 |
+
value: 63.510532363654725
|
81 |
- type: manhattan_spearman
|
82 |
+
value: 65.06622789125241
|
83 |
- task:
|
84 |
type: Clustering
|
85 |
dataset:
|
|
|
90 |
revision: None
|
91 |
metrics:
|
92 |
- type: v_measure
|
93 |
+
value: 39.5071157612481
|
94 |
- task:
|
95 |
type: Clustering
|
96 |
dataset:
|
|
|
101 |
revision: None
|
102 |
metrics:
|
103 |
- type: v_measure
|
104 |
+
value: 37.99964332311132
|
105 |
- task:
|
106 |
type: Reranking
|
107 |
dataset:
|
|
|
112 |
revision: None
|
113 |
metrics:
|
114 |
- type: map
|
115 |
+
value: 84.67010533089491
|
116 |
- type: mrr
|
117 |
+
value: 86.99488095238095
|
118 |
- task:
|
119 |
type: Reranking
|
120 |
dataset:
|
|
|
125 |
revision: None
|
126 |
metrics:
|
127 |
- type: map
|
128 |
+
value: 85.27288868896477
|
129 |
- type: mrr
|
130 |
+
value: 87.5929761904762
|
131 |
- task:
|
132 |
type: Retrieval
|
133 |
dataset:
|
|
|
138 |
revision: None
|
139 |
metrics:
|
140 |
- type: map_at_1
|
141 |
+
value: 23.949
|
142 |
- type: map_at_10
|
143 |
+
value: 35.394
|
144 |
- type: map_at_100
|
145 |
+
value: 37.235
|
146 |
- type: map_at_1000
|
147 |
+
value: 37.364999999999995
|
148 |
- type: map_at_3
|
149 |
+
value: 31.433
|
150 |
- type: map_at_5
|
151 |
+
value: 33.668
|
152 |
- type: mrr_at_1
|
153 |
+
value: 36.834
|
154 |
- type: mrr_at_10
|
155 |
+
value: 44.451
|
156 |
- type: mrr_at_100
|
157 |
+
value: 45.445
|
158 |
- type: mrr_at_1000
|
159 |
+
value: 45.501000000000005
|
160 |
- type: mrr_at_3
|
161 |
+
value: 42.010999999999996
|
162 |
- type: mrr_at_5
|
163 |
+
value: 43.34
|
164 |
- type: ndcg_at_1
|
165 |
+
value: 36.834
|
166 |
- type: ndcg_at_10
|
167 |
+
value: 41.803000000000004
|
168 |
- type: ndcg_at_100
|
169 |
+
value: 49.091
|
170 |
- type: ndcg_at_1000
|
171 |
+
value: 51.474
|
172 |
- type: ndcg_at_3
|
173 |
+
value: 36.736000000000004
|
174 |
- type: ndcg_at_5
|
175 |
+
value: 38.868
|
176 |
- type: precision_at_1
|
177 |
+
value: 36.834
|
178 |
- type: precision_at_10
|
179 |
+
value: 9.354999999999999
|
180 |
- type: precision_at_100
|
181 |
+
value: 1.5310000000000001
|
182 |
- type: precision_at_1000
|
183 |
value: 0.183
|
184 |
- type: precision_at_3
|
185 |
+
value: 20.78
|
186 |
- type: precision_at_5
|
187 |
+
value: 15.238999999999999
|
188 |
- type: recall_at_1
|
189 |
+
value: 23.949
|
190 |
- type: recall_at_10
|
191 |
+
value: 51.68000000000001
|
192 |
- type: recall_at_100
|
193 |
+
value: 81.938
|
194 |
- type: recall_at_1000
|
195 |
+
value: 98.091
|
196 |
- type: recall_at_3
|
197 |
+
value: 36.408
|
198 |
- type: recall_at_5
|
199 |
+
value: 42.952
|
200 |
- task:
|
201 |
type: PairClassification
|
202 |
dataset:
|
|
|
207 |
revision: None
|
208 |
metrics:
|
209 |
- type: cos_sim_accuracy
|
210 |
+
value: 76.24774503908598
|
211 |
- type: cos_sim_ap
|
212 |
+
value: 84.76081551540754
|
213 |
- type: cos_sim_f1
|
214 |
+
value: 77.76321537789427
|
215 |
- type: cos_sim_precision
|
216 |
+
value: 72.96577167452347
|
217 |
- type: cos_sim_recall
|
218 |
+
value: 83.23591302314706
|
219 |
- type: dot_accuracy
|
220 |
+
value: 76.24774503908598
|
221 |
- type: dot_ap
|
222 |
+
value: 84.75968761251127
|
223 |
- type: dot_f1
|
224 |
+
value: 77.76321537789427
|
225 |
- type: dot_precision
|
226 |
+
value: 72.96577167452347
|
227 |
- type: dot_recall
|
228 |
+
value: 83.23591302314706
|
229 |
- type: euclidean_accuracy
|
230 |
+
value: 76.24774503908598
|
231 |
- type: euclidean_ap
|
232 |
+
value: 84.7608250840413
|
233 |
- type: euclidean_f1
|
234 |
+
value: 77.76321537789427
|
235 |
- type: euclidean_precision
|
236 |
+
value: 72.96577167452347
|
237 |
- type: euclidean_recall
|
238 |
+
value: 83.23591302314706
|
239 |
- type: manhattan_accuracy
|
240 |
+
value: 76.19963920625375
|
241 |
- type: manhattan_ap
|
242 |
+
value: 84.76313920535411
|
243 |
- type: manhattan_f1
|
244 |
+
value: 77.74253527288636
|
245 |
- type: manhattan_precision
|
246 |
+
value: 73.0374023838882
|
247 |
- type: manhattan_recall
|
248 |
+
value: 83.09562777647884
|
249 |
- type: max_accuracy
|
250 |
+
value: 76.24774503908598
|
251 |
- type: max_ap
|
252 |
+
value: 84.76313920535411
|
253 |
- type: max_f1
|
254 |
+
value: 77.76321537789427
|
255 |
- task:
|
256 |
type: Retrieval
|
257 |
dataset:
|
|
|
262 |
revision: None
|
263 |
metrics:
|
264 |
- type: map_at_1
|
265 |
+
value: 66.149
|
266 |
- type: map_at_10
|
267 |
+
value: 75.22999999999999
|
268 |
- type: map_at_100
|
269 |
+
value: 75.536
|
270 |
- type: map_at_1000
|
271 |
+
value: 75.542
|
272 |
- type: map_at_3
|
273 |
+
value: 73.384
|
274 |
- type: map_at_5
|
275 |
+
value: 74.459
|
276 |
- type: mrr_at_1
|
277 |
+
value: 66.28
|
278 |
- type: mrr_at_10
|
279 |
+
value: 75.232
|
280 |
- type: mrr_at_100
|
281 |
+
value: 75.52799999999999
|
282 |
- type: mrr_at_1000
|
283 |
+
value: 75.534
|
284 |
- type: mrr_at_3
|
285 |
+
value: 73.446
|
286 |
- type: mrr_at_5
|
287 |
+
value: 74.473
|
288 |
- type: ndcg_at_1
|
289 |
+
value: 66.386
|
290 |
- type: ndcg_at_10
|
291 |
+
value: 79.295
|
292 |
- type: ndcg_at_100
|
293 |
+
value: 80.741
|
294 |
- type: ndcg_at_1000
|
295 |
+
value: 80.891
|
296 |
- type: ndcg_at_3
|
297 |
+
value: 75.613
|
298 |
- type: ndcg_at_5
|
299 |
+
value: 77.46300000000001
|
300 |
- type: precision_at_1
|
301 |
+
value: 66.386
|
302 |
- type: precision_at_10
|
303 |
+
value: 9.283
|
304 |
- type: precision_at_100
|
305 |
+
value: 0.996
|
306 |
- type: precision_at_1000
|
307 |
value: 0.101
|
308 |
- type: precision_at_3
|
309 |
+
value: 27.503
|
310 |
- type: precision_at_5
|
311 |
+
value: 17.408
|
312 |
- type: recall_at_1
|
313 |
+
value: 66.149
|
314 |
- type: recall_at_10
|
315 |
+
value: 91.886
|
316 |
- type: recall_at_100
|
317 |
+
value: 98.52499999999999
|
318 |
- type: recall_at_1000
|
319 |
value: 99.684
|
320 |
- type: recall_at_3
|
321 |
+
value: 81.849
|
322 |
- type: recall_at_5
|
323 |
+
value: 86.275
|
324 |
- task:
|
325 |
type: Retrieval
|
326 |
dataset:
|
|
|
331 |
revision: None
|
332 |
metrics:
|
333 |
- type: map_at_1
|
334 |
+
value: 25.166
|
335 |
- type: map_at_10
|
336 |
+
value: 78.805
|
337 |
- type: map_at_100
|
338 |
+
value: 81.782
|
339 |
- type: map_at_1000
|
340 |
+
value: 81.818
|
341 |
- type: map_at_3
|
342 |
+
value: 54.226
|
343 |
- type: map_at_5
|
344 |
+
value: 68.783
|
345 |
- type: mrr_at_1
|
346 |
+
value: 88.6
|
347 |
- type: mrr_at_10
|
348 |
+
value: 92.244
|
349 |
- type: mrr_at_100
|
350 |
+
value: 92.31899999999999
|
351 |
- type: mrr_at_1000
|
352 |
+
value: 92.321
|
353 |
- type: mrr_at_3
|
354 |
+
value: 91.867
|
355 |
- type: mrr_at_5
|
356 |
+
value: 92.119
|
357 |
- type: ndcg_at_1
|
358 |
+
value: 88.6
|
359 |
- type: ndcg_at_10
|
360 |
+
value: 86.432
|
361 |
- type: ndcg_at_100
|
362 |
+
value: 89.357
|
363 |
- type: ndcg_at_1000
|
364 |
+
value: 89.688
|
365 |
- type: ndcg_at_3
|
366 |
+
value: 84.90299999999999
|
367 |
- type: ndcg_at_5
|
368 |
+
value: 84.137
|
369 |
- type: precision_at_1
|
370 |
+
value: 88.6
|
371 |
- type: precision_at_10
|
372 |
+
value: 41.685
|
373 |
- type: precision_at_100
|
374 |
+
value: 4.811
|
375 |
- type: precision_at_1000
|
376 |
value: 0.48900000000000005
|
377 |
- type: precision_at_3
|
378 |
+
value: 76.44999999999999
|
379 |
- type: precision_at_5
|
380 |
+
value: 64.87
|
381 |
- type: recall_at_1
|
382 |
+
value: 25.166
|
383 |
- type: recall_at_10
|
384 |
+
value: 88.227
|
385 |
- type: recall_at_100
|
386 |
+
value: 97.597
|
387 |
- type: recall_at_1000
|
388 |
+
value: 99.359
|
389 |
- type: recall_at_3
|
390 |
+
value: 56.946
|
391 |
- type: recall_at_5
|
392 |
+
value: 74.261
|
393 |
- task:
|
394 |
type: Retrieval
|
395 |
dataset:
|
|
|
400 |
revision: None
|
401 |
metrics:
|
402 |
- type: map_at_1
|
403 |
+
value: 48.3
|
404 |
- type: map_at_10
|
405 |
+
value: 57.635999999999996
|
406 |
- type: map_at_100
|
407 |
+
value: 58.306000000000004
|
408 |
- type: map_at_1000
|
409 |
+
value: 58.326
|
410 |
- type: map_at_3
|
411 |
+
value: 54.900000000000006
|
412 |
- type: map_at_5
|
413 |
+
value: 56.620000000000005
|
414 |
- type: mrr_at_1
|
415 |
+
value: 48.3
|
416 |
- type: mrr_at_10
|
417 |
+
value: 57.635999999999996
|
418 |
- type: mrr_at_100
|
419 |
+
value: 58.306000000000004
|
420 |
- type: mrr_at_1000
|
421 |
+
value: 58.326
|
422 |
- type: mrr_at_3
|
423 |
+
value: 54.900000000000006
|
424 |
- type: mrr_at_5
|
425 |
+
value: 56.620000000000005
|
426 |
- type: ndcg_at_1
|
427 |
+
value: 48.3
|
428 |
- type: ndcg_at_10
|
429 |
+
value: 62.638000000000005
|
430 |
- type: ndcg_at_100
|
431 |
+
value: 65.726
|
432 |
- type: ndcg_at_1000
|
433 |
+
value: 66.253
|
434 |
- type: ndcg_at_3
|
435 |
+
value: 57.081
|
436 |
- type: ndcg_at_5
|
437 |
+
value: 60.217
|
438 |
- type: precision_at_1
|
439 |
+
value: 48.3
|
440 |
- type: precision_at_10
|
441 |
+
value: 7.85
|
442 |
- type: precision_at_100
|
443 |
+
value: 0.9249999999999999
|
444 |
- type: precision_at_1000
|
445 |
value: 0.097
|
446 |
- type: precision_at_3
|
447 |
value: 21.133
|
448 |
- type: precision_at_5
|
449 |
+
value: 14.219999999999999
|
450 |
- type: recall_at_1
|
451 |
+
value: 48.3
|
452 |
- type: recall_at_10
|
453 |
+
value: 78.5
|
454 |
- type: recall_at_100
|
455 |
+
value: 92.5
|
456 |
- type: recall_at_1000
|
457 |
value: 96.6
|
458 |
- type: recall_at_3
|
459 |
value: 63.4
|
460 |
- type: recall_at_5
|
461 |
+
value: 71.1
|
462 |
- task:
|
463 |
type: Classification
|
464 |
dataset:
|
|
|
469 |
revision: None
|
470 |
metrics:
|
471 |
- type: accuracy
|
472 |
+
value: 47.9646017699115
|
473 |
- type: f1
|
474 |
+
value: 35.03552351349023
|
475 |
- task:
|
476 |
type: Classification
|
477 |
dataset:
|
|
|
482 |
revision: None
|
483 |
metrics:
|
484 |
- type: accuracy
|
485 |
+
value: 84.8968105065666
|
486 |
- type: ap
|
487 |
+
value: 52.564605306946774
|
488 |
- type: f1
|
489 |
+
value: 79.59880155481291
|
490 |
- task:
|
491 |
type: STS
|
492 |
dataset:
|
|
|
497 |
revision: None
|
498 |
metrics:
|
499 |
- type: cos_sim_pearson
|
500 |
+
value: 70.03662039861051
|
501 |
- type: cos_sim_spearman
|
502 |
+
value: 76.9642260444222
|
503 |
- type: euclidean_pearson
|
504 |
+
value: 75.47376966815843
|
505 |
- type: euclidean_spearman
|
506 |
+
value: 76.9642282583736
|
507 |
- type: manhattan_pearson
|
508 |
+
value: 75.45535385433548
|
509 |
- type: manhattan_spearman
|
510 |
+
value: 76.94609742735338
|
511 |
- task:
|
512 |
type: Retrieval
|
513 |
dataset:
|
|
|
518 |
revision: None
|
519 |
metrics:
|
520 |
- type: map_at_1
|
521 |
+
value: 65.604
|
522 |
- type: map_at_10
|
523 |
+
value: 74.522
|
524 |
- type: map_at_100
|
525 |
+
value: 74.878
|
526 |
- type: map_at_1000
|
527 |
+
value: 74.889
|
528 |
- type: map_at_3
|
529 |
+
value: 72.61
|
530 |
- type: map_at_5
|
531 |
+
value: 73.882
|
532 |
- type: mrr_at_1
|
533 |
+
value: 67.75099999999999
|
534 |
- type: mrr_at_10
|
535 |
+
value: 75.08399999999999
|
536 |
- type: mrr_at_100
|
537 |
+
value: 75.402
|
538 |
- type: mrr_at_1000
|
539 |
+
value: 75.412
|
540 |
- type: mrr_at_3
|
541 |
+
value: 73.446
|
542 |
- type: mrr_at_5
|
543 |
+
value: 74.531
|
544 |
- type: ndcg_at_1
|
545 |
+
value: 67.75099999999999
|
546 |
- type: ndcg_at_10
|
547 |
+
value: 78.172
|
548 |
- type: ndcg_at_100
|
549 |
+
value: 79.753
|
550 |
- type: ndcg_at_1000
|
551 |
+
value: 80.06400000000001
|
552 |
- type: ndcg_at_3
|
553 |
+
value: 74.607
|
554 |
- type: ndcg_at_5
|
555 |
+
value: 76.728
|
556 |
- type: precision_at_1
|
557 |
+
value: 67.75099999999999
|
558 |
- type: precision_at_10
|
559 |
+
value: 9.443999999999999
|
560 |
- type: precision_at_100
|
561 |
+
value: 1.023
|
562 |
- type: precision_at_1000
|
563 |
value: 0.105
|
564 |
- type: precision_at_3
|
565 |
+
value: 28.009
|
566 |
- type: precision_at_5
|
567 |
+
value: 17.934
|
568 |
- type: recall_at_1
|
569 |
+
value: 65.604
|
570 |
- type: recall_at_10
|
571 |
+
value: 88.84100000000001
|
572 |
- type: recall_at_100
|
573 |
+
value: 95.954
|
574 |
- type: recall_at_1000
|
575 |
+
value: 98.425
|
576 |
- type: recall_at_3
|
577 |
+
value: 79.497
|
578 |
- type: recall_at_5
|
579 |
+
value: 84.515
|
580 |
- task:
|
581 |
type: Classification
|
582 |
dataset:
|
|
|
587 |
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
|
588 |
metrics:
|
589 |
- type: accuracy
|
590 |
+
value: 67.64963012777405
|
591 |
- type: f1
|
592 |
+
value: 65.01092085388518
|
593 |
- task:
|
594 |
type: Classification
|
595 |
dataset:
|
|
|
600 |
revision: 7d571f92784cd94a019292a1f45445077d0ef634
|
601 |
metrics:
|
602 |
- type: accuracy
|
603 |
+
value: 72.9724277067922
|
604 |
- type: f1
|
605 |
+
value: 72.48003852874602
|
606 |
- task:
|
607 |
type: Retrieval
|
608 |
dataset:
|
|
|
613 |
revision: None
|
614 |
metrics:
|
615 |
- type: map_at_1
|
616 |
+
value: 48.9
|
617 |
- type: map_at_10
|
618 |
+
value: 55.189
|
619 |
- type: map_at_100
|
620 |
+
value: 55.687
|
621 |
- type: map_at_1000
|
622 |
+
value: 55.74400000000001
|
623 |
- type: map_at_3
|
624 |
+
value: 53.75
|
625 |
- type: map_at_5
|
626 |
+
value: 54.555
|
627 |
- type: mrr_at_1
|
628 |
+
value: 49.1
|
629 |
- type: mrr_at_10
|
630 |
+
value: 55.289
|
631 |
- type: mrr_at_100
|
632 |
+
value: 55.788000000000004
|
633 |
- type: mrr_at_1000
|
634 |
+
value: 55.845
|
635 |
- type: mrr_at_3
|
636 |
+
value: 53.849999999999994
|
637 |
- type: mrr_at_5
|
638 |
+
value: 54.655
|
639 |
- type: ndcg_at_1
|
640 |
+
value: 48.9
|
641 |
- type: ndcg_at_10
|
642 |
+
value: 58.275
|
643 |
- type: ndcg_at_100
|
644 |
+
value: 60.980000000000004
|
645 |
- type: ndcg_at_1000
|
646 |
+
value: 62.672000000000004
|
647 |
- type: ndcg_at_3
|
648 |
+
value: 55.282
|
649 |
- type: ndcg_at_5
|
650 |
+
value: 56.749
|
651 |
- type: precision_at_1
|
652 |
+
value: 48.9
|
653 |
- type: precision_at_10
|
654 |
+
value: 6.800000000000001
|
655 |
- type: precision_at_100
|
656 |
+
value: 0.8130000000000001
|
657 |
- type: precision_at_1000
|
658 |
value: 0.095
|
659 |
- type: precision_at_3
|
660 |
+
value: 19.900000000000002
|
661 |
- type: precision_at_5
|
662 |
+
value: 12.659999999999998
|
663 |
- type: recall_at_1
|
664 |
+
value: 48.9
|
665 |
- type: recall_at_10
|
666 |
+
value: 68.0
|
667 |
- type: recall_at_100
|
668 |
+
value: 81.3
|
669 |
- type: recall_at_1000
|
670 |
+
value: 95.0
|
671 |
- type: recall_at_3
|
672 |
+
value: 59.699999999999996
|
673 |
- type: recall_at_5
|
674 |
+
value: 63.3
|
675 |
- task:
|
676 |
type: Classification
|
677 |
dataset:
|
|
|
682 |
revision: None
|
683 |
metrics:
|
684 |
- type: accuracy
|
685 |
+
value: 71.53666666666668
|
686 |
- type: f1
|
687 |
+
value: 70.74267338218574
|
688 |
- task:
|
689 |
type: PairClassification
|
690 |
dataset:
|
|
|
695 |
revision: None
|
696 |
metrics:
|
697 |
- type: cos_sim_accuracy
|
698 |
+
value: 70.43854899837575
|
699 |
- type: cos_sim_ap
|
700 |
+
value: 75.25713109733296
|
701 |
- type: cos_sim_f1
|
702 |
+
value: 73.18777292576418
|
703 |
- type: cos_sim_precision
|
704 |
+
value: 62.397617274758
|
705 |
- type: cos_sim_recall
|
706 |
+
value: 88.48996832101372
|
707 |
- type: dot_accuracy
|
708 |
+
value: 70.43854899837575
|
709 |
- type: dot_ap
|
710 |
+
value: 75.25713109733296
|
711 |
- type: dot_f1
|
712 |
+
value: 73.18777292576418
|
713 |
- type: dot_precision
|
714 |
+
value: 62.397617274758
|
715 |
- type: dot_recall
|
716 |
+
value: 88.48996832101372
|
717 |
- type: euclidean_accuracy
|
718 |
+
value: 70.43854899837575
|
719 |
- type: euclidean_ap
|
720 |
+
value: 75.25713109733296
|
721 |
- type: euclidean_f1
|
722 |
+
value: 73.18777292576418
|
723 |
- type: euclidean_precision
|
724 |
+
value: 62.397617274758
|
725 |
- type: euclidean_recall
|
726 |
+
value: 88.48996832101372
|
727 |
- type: manhattan_accuracy
|
728 |
+
value: 70.60097455332972
|
729 |
- type: manhattan_ap
|
730 |
+
value: 75.22177995740668
|
731 |
- type: manhattan_f1
|
732 |
+
value: 73.13750532141337
|
733 |
- type: manhattan_precision
|
734 |
+
value: 61.26961483594865
|
735 |
- type: manhattan_recall
|
736 |
+
value: 90.70749736008447
|
737 |
- type: max_accuracy
|
738 |
+
value: 70.60097455332972
|
739 |
- type: max_ap
|
740 |
+
value: 75.25713109733296
|
741 |
- type: max_f1
|
742 |
+
value: 73.18777292576418
|
743 |
- task:
|
744 |
type: Classification
|
745 |
dataset:
|
|
|
750 |
revision: None
|
751 |
metrics:
|
752 |
- type: accuracy
|
753 |
+
value: 91.3
|
754 |
- type: ap
|
755 |
+
value: 89.03601366589187
|
756 |
- type: f1
|
757 |
+
value: 91.28612226957141
|
758 |
- task:
|
759 |
type: STS
|
760 |
dataset:
|
|
|
765 |
revision: None
|
766 |
metrics:
|
767 |
- type: cos_sim_pearson
|
768 |
+
value: 24.254041798082984
|
769 |
- type: cos_sim_spearman
|
770 |
+
value: 30.029755057178846
|
771 |
- type: euclidean_pearson
|
772 |
+
value: 30.394005237465905
|
773 |
- type: euclidean_spearman
|
774 |
+
value: 30.029751825186153
|
775 |
- type: manhattan_pearson
|
776 |
+
value: 30.400683181995863
|
777 |
- type: manhattan_spearman
|
778 |
+
value: 29.981240616043326
|
779 |
- task:
|
780 |
type: STS
|
781 |
dataset:
|
|
|
786 |
revision: None
|
787 |
metrics:
|
788 |
- type: cos_sim_pearson
|
789 |
+
value: 35.09911024323138
|
790 |
- type: cos_sim_spearman
|
791 |
+
value: 37.49790006053554
|
792 |
- type: euclidean_pearson
|
793 |
+
value: 35.65689785105493
|
794 |
- type: euclidean_spearman
|
795 |
+
value: 37.498032509597344
|
796 |
- type: manhattan_pearson
|
797 |
+
value: 35.68350134483341
|
798 |
- type: manhattan_spearman
|
799 |
+
value: 37.54046578100128
|
800 |
- task:
|
801 |
type: STS
|
802 |
dataset:
|
|
|
807 |
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
|
808 |
metrics:
|
809 |
- type: cos_sim_pearson
|
810 |
+
value: 68.26707578158273
|
811 |
- type: cos_sim_spearman
|
812 |
+
value: 69.19741429899995
|
813 |
- type: euclidean_pearson
|
814 |
+
value: 68.53026048034656
|
815 |
- type: euclidean_spearman
|
816 |
+
value: 69.1974135636389
|
817 |
- type: manhattan_pearson
|
818 |
+
value: 70.02306646353263
|
819 |
- type: manhattan_spearman
|
820 |
+
value: 70.46158498712836
|
821 |
- task:
|
822 |
type: STS
|
823 |
dataset:
|
|
|
828 |
revision: None
|
829 |
metrics:
|
830 |
- type: cos_sim_pearson
|
831 |
+
value: 78.88749955421177
|
832 |
- type: cos_sim_spearman
|
833 |
+
value: 79.56695106617856
|
834 |
- type: euclidean_pearson
|
835 |
+
value: 79.13787024514338
|
836 |
- type: euclidean_spearman
|
837 |
+
value: 79.56690827015423
|
838 |
- type: manhattan_pearson
|
839 |
+
value: 79.08154812411563
|
840 |
- type: manhattan_spearman
|
841 |
+
value: 79.52391077945943
|
842 |
- task:
|
843 |
type: Reranking
|
844 |
dataset:
|
|
|
849 |
revision: None
|
850 |
metrics:
|
851 |
- type: map
|
852 |
+
value: 65.78663254562939
|
853 |
- type: mrr
|
854 |
+
value: 74.9786877626248
|
855 |
- task:
|
856 |
type: Retrieval
|
857 |
dataset:
|
|
|
862 |
revision: None
|
863 |
metrics:
|
864 |
- type: map_at_1
|
865 |
+
value: 26.169999999999998
|
866 |
- type: map_at_10
|
867 |
+
value: 74.009
|
868 |
- type: map_at_100
|
869 |
+
value: 77.788
|
870 |
- type: map_at_1000
|
871 |
+
value: 77.866
|
872 |
- type: map_at_3
|
873 |
+
value: 51.861000000000004
|
874 |
- type: map_at_5
|
875 |
+
value: 63.775000000000006
|
876 |
- type: mrr_at_1
|
877 |
+
value: 87.748
|
878 |
- type: mrr_at_10
|
879 |
+
value: 90.737
|
880 |
- type: mrr_at_100
|
881 |
+
value: 90.84400000000001
|
882 |
- type: mrr_at_1000
|
883 |
+
value: 90.849
|
884 |
- type: mrr_at_3
|
885 |
+
value: 90.257
|
886 |
- type: mrr_at_5
|
887 |
+
value: 90.54299999999999
|
888 |
- type: ndcg_at_1
|
889 |
+
value: 87.748
|
890 |
- type: ndcg_at_10
|
891 |
+
value: 82.114
|
892 |
- type: ndcg_at_100
|
893 |
+
value: 86.148
|
894 |
- type: ndcg_at_1000
|
895 |
+
value: 86.913
|
896 |
- type: ndcg_at_3
|
897 |
+
value: 83.54599999999999
|
898 |
- type: ndcg_at_5
|
899 |
+
value: 81.987
|
900 |
- type: precision_at_1
|
901 |
+
value: 87.748
|
902 |
- type: precision_at_10
|
903 |
+
value: 41.076
|
904 |
- type: precision_at_100
|
905 |
+
value: 4.976
|
906 |
- type: precision_at_1000
|
907 |
value: 0.515
|
908 |
- type: precision_at_3
|
909 |
+
value: 73.282
|
910 |
- type: precision_at_5
|
911 |
+
value: 61.351
|
912 |
- type: recall_at_1
|
913 |
+
value: 26.169999999999998
|
914 |
- type: recall_at_10
|
915 |
+
value: 81.292
|
916 |
- type: recall_at_100
|
917 |
+
value: 94.285
|
918 |
- type: recall_at_1000
|
919 |
+
value: 98.221
|
920 |
- type: recall_at_3
|
921 |
+
value: 53.824000000000005
|
922 |
- type: recall_at_5
|
923 |
+
value: 67.547
|
924 |
- task:
|
925 |
type: Classification
|
926 |
dataset:
|
|
|
931 |
revision: None
|
932 |
metrics:
|
933 |
- type: accuracy
|
934 |
+
value: 51.564
|
935 |
- type: f1
|
936 |
+
value: 49.711462885083286
|
937 |
- task:
|
938 |
type: Clustering
|
939 |
dataset:
|
|
|
944 |
revision: None
|
945 |
metrics:
|
946 |
- type: v_measure
|
947 |
+
value: 62.57078038998942
|
948 |
- task:
|
949 |
type: Clustering
|
950 |
dataset:
|
|
|
955 |
revision: None
|
956 |
metrics:
|
957 |
- type: v_measure
|
958 |
+
value: 57.842602165392144
|
959 |
- task:
|
960 |
type: Retrieval
|
961 |
dataset:
|
|
|
966 |
revision: None
|
967 |
metrics:
|
968 |
- type: map_at_1
|
969 |
+
value: 52.0
|
970 |
- type: map_at_10
|
971 |
+
value: 62.932
|
972 |
- type: map_at_100
|
973 |
+
value: 63.471999999999994
|
974 |
- type: map_at_1000
|
975 |
+
value: 63.483999999999995
|
976 |
- type: map_at_3
|
977 |
+
value: 60.516999999999996
|
978 |
- type: map_at_5
|
979 |
+
value: 62.097
|
980 |
- type: mrr_at_1
|
981 |
+
value: 52.0
|
982 |
- type: mrr_at_10
|
983 |
+
value: 62.932
|
984 |
- type: mrr_at_100
|
985 |
+
value: 63.471999999999994
|
986 |
- type: mrr_at_1000
|
987 |
+
value: 63.483999999999995
|
988 |
- type: mrr_at_3
|
989 |
+
value: 60.516999999999996
|
990 |
- type: mrr_at_5
|
991 |
+
value: 62.097
|
992 |
- type: ndcg_at_1
|
993 |
+
value: 52.0
|
994 |
- type: ndcg_at_10
|
995 |
+
value: 67.963
|
996 |
- type: ndcg_at_100
|
997 |
+
value: 70.598
|
998 |
- type: ndcg_at_1000
|
999 |
+
value: 70.896
|
1000 |
- type: ndcg_at_3
|
1001 |
+
value: 63.144
|
1002 |
- type: ndcg_at_5
|
1003 |
+
value: 65.988
|
1004 |
- type: precision_at_1
|
1005 |
+
value: 52.0
|
1006 |
- type: precision_at_10
|
1007 |
+
value: 8.36
|
1008 |
- type: precision_at_100
|
1009 |
+
value: 0.959
|
1010 |
- type: precision_at_1000
|
1011 |
value: 0.098
|
1012 |
- type: precision_at_3
|
1013 |
+
value: 23.567
|
1014 |
- type: precision_at_5
|
1015 |
+
value: 15.52
|
1016 |
- type: recall_at_1
|
1017 |
+
value: 52.0
|
1018 |
- type: recall_at_10
|
1019 |
+
value: 83.6
|
1020 |
- type: recall_at_100
|
1021 |
+
value: 95.89999999999999
|
1022 |
- type: recall_at_1000
|
1023 |
value: 98.2
|
1024 |
- type: recall_at_3
|
1025 |
+
value: 70.7
|
1026 |
- type: recall_at_5
|
1027 |
+
value: 77.60000000000001
|
1028 |
- task:
|
1029 |
type: Classification
|
1030 |
dataset:
|
|
|
1035 |
revision: None
|
1036 |
metrics:
|
1037 |
- type: accuracy
|
1038 |
+
value: 86.65999999999998
|
1039 |
- type: ap
|
1040 |
+
value: 69.91988858863054
|
1041 |
- type: f1
|
1042 |
+
value: 84.92982698422784
|
1043 |
- task:
|
1044 |
type: Reranking
|
1045 |
dataset:
|
|
|
1050 |
revision: None
|
1051 |
metrics:
|
1052 |
- type: map
|
1053 |
+
value: 27.838972963193315
|
1054 |
- type: mrr
|
1055 |
+
value: 26.65238095238095
|
1056 |
---
|