Update README.md
Browse files
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: 57.
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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:
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- type: euclidean_spearman
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-
value:
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- type: manhattan_pearson
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-
value:
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- type: manhattan_spearman
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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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@@ -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:
|
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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: 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: 49.
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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: 71.
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- type: cos_sim_spearman
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-
value: 72.
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- type: euclidean_pearson
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-
value: 71.
|
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- type: euclidean_spearman
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-
value: 72.
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- type: manhattan_pearson
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-
value: 71.
|
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- type: manhattan_spearman
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-
value: 72.
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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:
|
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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: 88.
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- type: mrr
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-
value:
|
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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: 89.
|
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- type: mrr
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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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@@ -138,65 +138,65 @@ model-index:
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|
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revision: None
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metrics:
|
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- type: map_at_1
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-
value: 26.
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- type: map_at_10
|
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-
value:
|
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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: 35.
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- type: map_at_5
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-
value: 38.
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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: 49.
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- type: mrr_at_100
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-
value: 50.
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- type: mrr_at_1000
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-
value: 50.
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- type: mrr_at_3
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-
value: 46.
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- type: mrr_at_5
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-
value: 48.
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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: 46.
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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: 55.
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- type: ndcg_at_3
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-
value: 41.
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- type: ndcg_at_5
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-
value: 43.
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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: 10.
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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: 0.184
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- type: precision_at_3
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-
value: 23.
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- type: precision_at_5
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-
value:
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- type: recall_at_1
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-
value: 26.
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- type: recall_at_10
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-
value: 57.
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- type: recall_at_100
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-
value:
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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: 41.
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- type: recall_at_5
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-
value:
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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:
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- type: cos_sim_f1
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-
value:
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- type: cos_sim_precision
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-
value:
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- type: cos_sim_recall
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-
value: 90.
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- type: dot_accuracy
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-
value:
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- type: dot_ap
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-
value:
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- type: dot_f1
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-
value:
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- type: dot_precision
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-
value:
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- type: dot_recall
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-
value: 90.
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- type: euclidean_accuracy
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-
value:
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- type: euclidean_ap
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-
value:
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- type: euclidean_f1
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-
value:
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- type: euclidean_precision
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-
value:
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- type: euclidean_recall
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-
value: 90.
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- type: manhattan_accuracy
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-
value: 85.
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- type: manhattan_ap
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-
value:
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- type: manhattan_f1
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-
value:
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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:
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- type: max_f1
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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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@@ -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:
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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:
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- type: map_at_5
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-
value:
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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:
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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:
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- type: mrr_at_5
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-
value:
|
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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:
|
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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:
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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: 9.
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- type: precision_at_100
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-
value:
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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:
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- type: precision_at_5
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-
value:
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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:
|
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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:
|
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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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-
value: 26.
|
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- type: map_at_10
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-
value: 81.
|
337 |
- type: map_at_100
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-
value:
|
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- type: map_at_1000
|
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-
value: 84.
|
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- type: map_at_3
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-
value: 56.
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- type: map_at_5
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-
value: 71.
|
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- type: mrr_at_1
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-
value: 91.
|
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- type: mrr_at_10
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-
value:
|
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- type: mrr_at_100
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-
value: 94.
|
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- type: mrr_at_1000
|
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-
value: 94.
|
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- type: mrr_at_3
|
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-
value: 93.
|
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- type: mrr_at_5
|
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-
value:
|
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- type: ndcg_at_1
|
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-
value: 91.
|
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- type: ndcg_at_10
|
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-
value: 88.
|
361 |
- type: ndcg_at_100
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-
value: 90.
|
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- type: ndcg_at_1000
|
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-
value: 91.
|
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- type: ndcg_at_3
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-
value: 87.
|
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- type: ndcg_at_5
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-
value: 86.
|
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- type: precision_at_1
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-
value: 91.
|
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- type: precision_at_10
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-
value:
|
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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: 78.
|
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- type: precision_at_5
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-
value: 66.
|
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- type: recall_at_1
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-
value: 26.
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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: 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: 58.
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- type: recall_at_5
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-
value: 75.
|
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- task:
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type: Retrieval
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dataset:
|
@@ -402,63 +402,63 @@ model-index:
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- type: map_at_1
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value: 52.7
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- type: map_at_10
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-
value: 62.
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- type: map_at_100
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-
value: 62.
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- type: map_at_1000
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-
value: 62.
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- type: map_at_3
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-
value: 59.
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- type: map_at_5
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-
value: 61.
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- type: mrr_at_1
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value: 52.7
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- type: mrr_at_10
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-
value: 62.
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- type: mrr_at_100
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-
value: 62.
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- type: mrr_at_1000
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-
value: 62.
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- type: mrr_at_3
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-
value: 59.
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- type: mrr_at_5
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-
value: 61.
|
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- type: ndcg_at_1
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value: 52.7
|
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- type: ndcg_at_10
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-
value: 67.
|
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- type: ndcg_at_100
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-
value: 69.
|
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- type: ndcg_at_1000
|
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-
value: 70.
|
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- type: ndcg_at_3
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-
value: 62.
|
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- type: ndcg_at_5
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-
value: 64.
|
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- type: precision_at_1
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value: 52.7
|
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- type: precision_at_10
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-
value: 8.
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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: 0.097
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- type: precision_at_3
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-
value:
|
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- type: precision_at_5
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-
value:
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- type: recall_at_1
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value: 52.7
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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: 94.
|
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- type: recall_at_1000
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-
value: 97.
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- type: recall_at_3
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-
value:
|
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- type: recall_at_5
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-
value:
|
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- task:
|
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type: Classification
|
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dataset:
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@@ -469,9 +469,9 @@ model-index:
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revision: None
|
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metrics:
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- type: accuracy
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-
value: 52.
|
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- type: f1
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-
value: 42.
|
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- task:
|
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type: Classification
|
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dataset:
|
@@ -482,11 +482,11 @@ model-index:
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|
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revision: None
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metrics:
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- type: accuracy
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-
value:
|
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- type: ap
|
487 |
-
value:
|
488 |
- 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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@@ -497,17 +497,17 @@ model-index:
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revision: None
|
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metrics:
|
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- type: cos_sim_pearson
|
500 |
-
value: 74.
|
501 |
- type: cos_sim_spearman
|
502 |
-
value: 79.
|
503 |
- type: euclidean_pearson
|
504 |
-
value: 79.
|
505 |
- type: euclidean_spearman
|
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-
value: 79.
|
507 |
- type: manhattan_pearson
|
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-
value: 79.
|
509 |
- type: manhattan_spearman
|
510 |
-
value: 79.
|
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- task:
|
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type: Reranking
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dataset:
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@@ -518,9 +518,9 @@ model-index:
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|
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revision: None
|
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metrics:
|
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- type: map
|
521 |
-
value: 31.
|
522 |
- type: mrr
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523 |
-
value: 30.
|
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- task:
|
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type: Retrieval
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526 |
dataset:
|
@@ -531,65 +531,65 @@ model-index:
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|
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revision: None
|
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metrics:
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- type: map_at_1
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534 |
-
value:
|
535 |
- type: map_at_10
|
536 |
-
value:
|
537 |
- type: map_at_100
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-
value: 75.
|
539 |
- type: map_at_1000
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-
value: 75.
|
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- type: map_at_3
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-
value:
|
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- type: map_at_5
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-
value:
|
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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:
|
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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:
|
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- type: mrr_at_5
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-
value:
|
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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:
|
561 |
- type: ndcg_at_100
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-
value: 80.
|
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- type: ndcg_at_1000
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-
value:
|
565 |
- type: ndcg_at_3
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-
value: 75.
|
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- type: ndcg_at_5
|
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-
value: 77.
|
569 |
- type: precision_at_1
|
570 |
-
value:
|
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- type: precision_at_10
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-
value: 9.
|
573 |
- type: precision_at_100
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-
value: 1.
|
575 |
- type: precision_at_1000
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value: 0.105
|
577 |
- type: precision_at_3
|
578 |
-
value: 28.
|
579 |
- type: precision_at_5
|
580 |
-
value: 18.
|
581 |
- type: recall_at_1
|
582 |
-
value:
|
583 |
- type: recall_at_10
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584 |
-
value: 89.
|
585 |
- type: recall_at_100
|
586 |
-
value: 96.
|
587 |
- type: recall_at_1000
|
588 |
-
value: 98.
|
589 |
- type: recall_at_3
|
590 |
-
value: 80.
|
591 |
- type: recall_at_5
|
592 |
-
value: 85.
|
593 |
- task:
|
594 |
type: Classification
|
595 |
dataset:
|
@@ -600,9 +600,9 @@ model-index:
|
|
600 |
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
|
601 |
metrics:
|
602 |
- type: accuracy
|
603 |
-
value: 77.
|
604 |
- type: f1
|
605 |
-
value:
|
606 |
- task:
|
607 |
type: Classification
|
608 |
dataset:
|
@@ -613,9 +613,9 @@ model-index:
|
|
613 |
revision: 7d571f92784cd94a019292a1f45445077d0ef634
|
614 |
metrics:
|
615 |
- type: accuracy
|
616 |
-
value:
|
617 |
- type: f1
|
618 |
-
value:
|
619 |
- task:
|
620 |
type: Retrieval
|
621 |
dataset:
|
@@ -626,65 +626,65 @@ model-index:
|
|
626 |
revision: None
|
627 |
metrics:
|
628 |
- type: map_at_1
|
629 |
-
value:
|
630 |
- type: map_at_10
|
631 |
-
value: 61.
|
632 |
- type: map_at_100
|
633 |
-
value: 61.
|
634 |
- type: map_at_1000
|
635 |
-
value: 61.
|
636 |
- type: map_at_3
|
637 |
-
value: 59.
|
638 |
- type: map_at_5
|
639 |
-
value: 60.
|
640 |
- type: mrr_at_1
|
641 |
value: 54.900000000000006
|
642 |
- type: mrr_at_10
|
643 |
-
value: 61.
|
644 |
- type: mrr_at_100
|
645 |
-
value: 61.
|
646 |
- type: mrr_at_1000
|
647 |
-
value:
|
648 |
- type: mrr_at_3
|
649 |
-
value: 59.
|
650 |
- type: mrr_at_5
|
651 |
-
value: 60.
|
652 |
- type: ndcg_at_1
|
653 |
-
value:
|
654 |
- type: ndcg_at_10
|
655 |
-
value: 64.
|
656 |
- type: ndcg_at_100
|
657 |
-
value:
|
658 |
- type: ndcg_at_1000
|
659 |
-
value: 68.
|
660 |
- type: ndcg_at_3
|
661 |
-
value: 61.
|
662 |
- type: ndcg_at_5
|
663 |
-
value: 62.
|
664 |
- type: precision_at_1
|
665 |
-
value:
|
666 |
- type: precision_at_10
|
667 |
-
value: 7.
|
668 |
- type: precision_at_100
|
669 |
value: 0.878
|
670 |
- type: precision_at_1000
|
671 |
value: 0.098
|
672 |
- type: precision_at_3
|
673 |
-
value:
|
674 |
- type: precision_at_5
|
675 |
-
value: 13.
|
676 |
- type: recall_at_1
|
677 |
-
value:
|
678 |
- type: recall_at_10
|
679 |
-
value:
|
680 |
- type: recall_at_100
|
681 |
value: 87.8
|
682 |
- type: recall_at_1000
|
683 |
-
value:
|
684 |
- type: recall_at_3
|
685 |
-
value:
|
686 |
- type: recall_at_5
|
687 |
-
value: 69.
|
688 |
- task:
|
689 |
type: Classification
|
690 |
dataset:
|
@@ -695,9 +695,9 @@ model-index:
|
|
695 |
revision: None
|
696 |
metrics:
|
697 |
- type: accuracy
|
698 |
-
value: 78.
|
699 |
- type: f1
|
700 |
-
value: 78.
|
701 |
- task:
|
702 |
type: PairClassification
|
703 |
dataset:
|
@@ -708,51 +708,51 @@ model-index:
|
|
708 |
revision: None
|
709 |
metrics:
|
710 |
- type: cos_sim_accuracy
|
711 |
-
value:
|
712 |
- type: cos_sim_ap
|
713 |
-
value:
|
714 |
- type: cos_sim_f1
|
715 |
-
value:
|
716 |
- type: cos_sim_precision
|
717 |
-
value:
|
718 |
- type: cos_sim_recall
|
719 |
-
value:
|
720 |
- type: dot_accuracy
|
721 |
-
value:
|
722 |
- type: dot_ap
|
723 |
-
value:
|
724 |
- type: dot_f1
|
725 |
-
value:
|
726 |
- type: dot_precision
|
727 |
-
value:
|
728 |
- type: dot_recall
|
729 |
-
value:
|
730 |
- type: euclidean_accuracy
|
731 |
-
value:
|
732 |
- type: euclidean_ap
|
733 |
-
value:
|
734 |
- type: euclidean_f1
|
735 |
-
value:
|
736 |
- type: euclidean_precision
|
737 |
-
value:
|
738 |
- type: euclidean_recall
|
739 |
-
value:
|
740 |
- type: manhattan_accuracy
|
741 |
-
value:
|
742 |
- type: manhattan_ap
|
743 |
-
value:
|
744 |
- type: manhattan_f1
|
745 |
-
value:
|
746 |
- type: manhattan_precision
|
747 |
-
value:
|
748 |
- type: manhattan_recall
|
749 |
-
value:
|
750 |
- type: max_accuracy
|
751 |
-
value:
|
752 |
- type: max_ap
|
753 |
-
value:
|
754 |
- type: max_f1
|
755 |
-
value:
|
756 |
- task:
|
757 |
type: Classification
|
758 |
dataset:
|
@@ -763,11 +763,11 @@ model-index:
|
|
763 |
revision: None
|
764 |
metrics:
|
765 |
- type: accuracy
|
766 |
-
value: 94.
|
767 |
- type: ap
|
768 |
-
value: 92.
|
769 |
- type: f1
|
770 |
-
value: 94.
|
771 |
- task:
|
772 |
type: STS
|
773 |
dataset:
|
@@ -778,17 +778,17 @@ model-index:
|
|
778 |
revision: None
|
779 |
metrics:
|
780 |
- type: cos_sim_pearson
|
781 |
-
value:
|
782 |
- type: cos_sim_spearman
|
783 |
-
value:
|
784 |
- type: euclidean_pearson
|
785 |
-
value: 45.
|
786 |
- type: euclidean_spearman
|
787 |
-
value:
|
788 |
- type: manhattan_pearson
|
789 |
-
value: 45.
|
790 |
- type: manhattan_spearman
|
791 |
-
value:
|
792 |
- task:
|
793 |
type: STS
|
794 |
dataset:
|
@@ -799,17 +799,17 @@ model-index:
|
|
799 |
revision: None
|
800 |
metrics:
|
801 |
- type: cos_sim_pearson
|
802 |
-
value:
|
803 |
- type: cos_sim_spearman
|
804 |
-
value:
|
805 |
- type: euclidean_pearson
|
806 |
-
value:
|
807 |
- type: euclidean_spearman
|
808 |
-
value:
|
809 |
- type: manhattan_pearson
|
810 |
-
value:
|
811 |
- type: manhattan_spearman
|
812 |
-
value:
|
813 |
- task:
|
814 |
type: STS
|
815 |
dataset:
|
@@ -820,17 +820,17 @@ model-index:
|
|
820 |
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
|
821 |
metrics:
|
822 |
- type: cos_sim_pearson
|
823 |
-
value:
|
824 |
- type: cos_sim_spearman
|
825 |
-
value:
|
826 |
- type: euclidean_pearson
|
827 |
-
value:
|
828 |
- type: euclidean_spearman
|
829 |
-
value:
|
830 |
- type: manhattan_pearson
|
831 |
-
value:
|
832 |
- type: manhattan_spearman
|
833 |
-
value:
|
834 |
- task:
|
835 |
type: STS
|
836 |
dataset:
|
@@ -841,17 +841,17 @@ model-index:
|
|
841 |
revision: None
|
842 |
metrics:
|
843 |
- type: cos_sim_pearson
|
844 |
-
value:
|
845 |
- type: cos_sim_spearman
|
846 |
-
value:
|
847 |
- type: euclidean_pearson
|
848 |
-
value:
|
849 |
- type: euclidean_spearman
|
850 |
-
value:
|
851 |
- type: manhattan_pearson
|
852 |
-
value:
|
853 |
- type: manhattan_spearman
|
854 |
-
value:
|
855 |
- task:
|
856 |
type: Reranking
|
857 |
dataset:
|
@@ -862,9 +862,9 @@ model-index:
|
|
862 |
revision: None
|
863 |
metrics:
|
864 |
- type: map
|
865 |
-
value:
|
866 |
- type: mrr
|
867 |
-
value: 77.
|
868 |
- task:
|
869 |
type: Retrieval
|
870 |
dataset:
|
@@ -875,65 +875,65 @@ model-index:
|
|
875 |
revision: None
|
876 |
metrics:
|
877 |
- type: map_at_1
|
878 |
-
value:
|
879 |
- type: map_at_10
|
880 |
-
value:
|
881 |
- type: map_at_100
|
882 |
-
value:
|
883 |
- type: map_at_1000
|
884 |
-
value:
|
885 |
- type: map_at_3
|
886 |
-
value:
|
887 |
- type: map_at_5
|
888 |
-
value:
|
889 |
- type: mrr_at_1
|
890 |
-
value:
|
891 |
- type: mrr_at_10
|
892 |
-
value:
|
893 |
- type: mrr_at_100
|
894 |
-
value:
|
895 |
- type: mrr_at_1000
|
896 |
-
value:
|
897 |
- type: mrr_at_3
|
898 |
-
value:
|
899 |
- type: mrr_at_5
|
900 |
-
value:
|
901 |
- type: ndcg_at_1
|
902 |
-
value:
|
903 |
- type: ndcg_at_10
|
904 |
-
value:
|
905 |
- type: ndcg_at_100
|
906 |
-
value:
|
907 |
- type: ndcg_at_1000
|
908 |
-
value:
|
909 |
- type: ndcg_at_3
|
910 |
-
value:
|
911 |
- type: ndcg_at_5
|
912 |
-
value:
|
913 |
- type: precision_at_1
|
914 |
-
value:
|
915 |
- type: precision_at_10
|
916 |
-
value:
|
917 |
- type: precision_at_100
|
918 |
-
value:
|
919 |
- type: precision_at_1000
|
920 |
-
value: 0.
|
921 |
- type: precision_at_3
|
922 |
-
value:
|
923 |
- type: precision_at_5
|
924 |
-
value:
|
925 |
- type: recall_at_1
|
926 |
-
value:
|
927 |
- type: recall_at_10
|
928 |
-
value:
|
929 |
- type: recall_at_100
|
930 |
-
value:
|
931 |
- type: recall_at_1000
|
932 |
-
value: 98.
|
933 |
- type: recall_at_3
|
934 |
-
value:
|
935 |
- type: recall_at_5
|
936 |
-
value:
|
937 |
- task:
|
938 |
type: Classification
|
939 |
dataset:
|
@@ -944,9 +944,9 @@ model-index:
|
|
944 |
revision: None
|
945 |
metrics:
|
946 |
- type: accuracy
|
947 |
-
value: 54.
|
948 |
- type: f1
|
949 |
-
value: 52.
|
950 |
- task:
|
951 |
type: Clustering
|
952 |
dataset:
|
@@ -957,7 +957,7 @@ model-index:
|
|
957 |
revision: None
|
958 |
metrics:
|
959 |
- type: v_measure
|
960 |
-
value:
|
961 |
- task:
|
962 |
type: Clustering
|
963 |
dataset:
|
@@ -968,7 +968,7 @@ model-index:
|
|
968 |
revision: None
|
969 |
metrics:
|
970 |
- type: v_measure
|
971 |
-
value:
|
972 |
- task:
|
973 |
type: Retrieval
|
974 |
dataset:
|
@@ -979,65 +979,65 @@ model-index:
|
|
979 |
revision: None
|
980 |
metrics:
|
981 |
- type: map_at_1
|
982 |
-
value:
|
983 |
- type: map_at_10
|
984 |
-
value:
|
985 |
- type: map_at_100
|
986 |
-
value:
|
987 |
- type: map_at_1000
|
988 |
-
value:
|
989 |
- type: map_at_3
|
990 |
-
value:
|
991 |
- type: map_at_5
|
992 |
-
value:
|
993 |
- type: mrr_at_1
|
994 |
-
value:
|
995 |
- type: mrr_at_10
|
996 |
-
value:
|
997 |
- type: mrr_at_100
|
998 |
-
value:
|
999 |
- type: mrr_at_1000
|
1000 |
-
value:
|
1001 |
- type: mrr_at_3
|
1002 |
-
value:
|
1003 |
- type: mrr_at_5
|
1004 |
-
value:
|
1005 |
- type: ndcg_at_1
|
1006 |
-
value:
|
1007 |
- type: ndcg_at_10
|
1008 |
-
value:
|
1009 |
- type: ndcg_at_100
|
1010 |
-
value:
|
1011 |
- type: ndcg_at_1000
|
1012 |
-
value:
|
1013 |
- type: ndcg_at_3
|
1014 |
-
value:
|
1015 |
- type: ndcg_at_5
|
1016 |
-
value:
|
1017 |
- type: precision_at_1
|
1018 |
-
value:
|
1019 |
- type: precision_at_10
|
1020 |
-
value: 8.
|
1021 |
- type: precision_at_100
|
1022 |
-
value: 0.
|
1023 |
- type: precision_at_1000
|
1024 |
value: 0.099
|
1025 |
- type: precision_at_3
|
1026 |
-
value:
|
1027 |
- type: precision_at_5
|
1028 |
-
value:
|
1029 |
- type: recall_at_1
|
1030 |
-
value:
|
1031 |
- type: recall_at_10
|
1032 |
-
value:
|
1033 |
- type: recall_at_100
|
1034 |
-
value:
|
1035 |
- type: recall_at_1000
|
1036 |
-
value:
|
1037 |
- type: recall_at_3
|
1038 |
-
value:
|
1039 |
- type: recall_at_5
|
1040 |
-
value:
|
1041 |
- task:
|
1042 |
type: Classification
|
1043 |
dataset:
|
@@ -1048,11 +1048,11 @@ model-index:
|
|
1048 |
revision: None
|
1049 |
metrics:
|
1050 |
- type: accuracy
|
1051 |
-
value: 89.
|
1052 |
- type: ap
|
1053 |
-
value: 75.
|
1054 |
- type: f1
|
1055 |
-
value:
|
1056 |
---
|
1057 |
|
1058 |
### 使用方法
|
|
|
14 |
revision: None
|
15 |
metrics:
|
16 |
- type: cos_sim_pearson
|
17 |
+
value: 57.37728676415047
|
18 |
- type: cos_sim_spearman
|
19 |
+
value: 60.89131895307699
|
20 |
- type: euclidean_pearson
|
21 |
+
value: 60.056754800315595
|
22 |
- type: euclidean_spearman
|
23 |
+
value: 60.891479787418966
|
24 |
- type: manhattan_pearson
|
25 |
+
value: 60.03850823371572
|
26 |
- type: manhattan_spearman
|
27 |
+
value: 60.8597150048781
|
28 |
- task:
|
29 |
type: STS
|
30 |
dataset:
|
|
|
35 |
revision: None
|
36 |
metrics:
|
37 |
- type: cos_sim_pearson
|
38 |
+
value: 57.29704921148904
|
39 |
- type: cos_sim_spearman
|
40 |
+
value: 58.81607331373972
|
41 |
- type: euclidean_pearson
|
42 |
+
value: 63.69251756281332
|
43 |
- type: euclidean_spearman
|
44 |
+
value: 58.81608232068536
|
45 |
- type: manhattan_pearson
|
46 |
+
value: 63.665668138742284
|
47 |
- type: manhattan_spearman
|
48 |
+
value: 58.80224314871406
|
49 |
- task:
|
50 |
type: Classification
|
51 |
dataset:
|
|
|
56 |
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
|
57 |
metrics:
|
58 |
- type: accuracy
|
59 |
+
value: 49.672
|
60 |
- type: f1
|
61 |
+
value: 47.27737512126165
|
62 |
- task:
|
63 |
type: STS
|
64 |
dataset:
|
|
|
69 |
revision: None
|
70 |
metrics:
|
71 |
- type: cos_sim_pearson
|
72 |
+
value: 71.65025725548176
|
73 |
- type: cos_sim_spearman
|
74 |
+
value: 72.53278026251562
|
75 |
- type: euclidean_pearson
|
76 |
+
value: 71.29771814474996
|
77 |
- type: euclidean_spearman
|
78 |
+
value: 72.53241999594584
|
79 |
- type: manhattan_pearson
|
80 |
+
value: 71.29290351258575
|
81 |
- type: manhattan_spearman
|
82 |
+
value: 72.52505531587519
|
83 |
- task:
|
84 |
type: Clustering
|
85 |
dataset:
|
|
|
90 |
revision: None
|
91 |
metrics:
|
92 |
- type: v_measure
|
93 |
+
value: 60.19892651814847
|
94 |
- task:
|
95 |
type: Clustering
|
96 |
dataset:
|
|
|
101 |
revision: None
|
102 |
metrics:
|
103 |
- type: v_measure
|
104 |
+
value: 58.39897986042561
|
105 |
- task:
|
106 |
type: Reranking
|
107 |
dataset:
|
|
|
112 |
revision: None
|
113 |
metrics:
|
114 |
- type: map
|
115 |
+
value: 88.73563192647498
|
116 |
- type: mrr
|
117 |
+
value: 91.00214285714286
|
118 |
- task:
|
119 |
type: Reranking
|
120 |
dataset:
|
|
|
125 |
revision: None
|
126 |
metrics:
|
127 |
- type: map
|
128 |
+
value: 89.42396184634322
|
129 |
- type: mrr
|
130 |
+
value: 91.90503968253968
|
131 |
- task:
|
132 |
type: Retrieval
|
133 |
dataset:
|
|
|
138 |
revision: None
|
139 |
metrics:
|
140 |
- type: map_at_1
|
141 |
+
value: 26.950000000000003
|
142 |
- type: map_at_10
|
143 |
+
value: 39.982
|
144 |
- type: map_at_100
|
145 |
+
value: 41.844
|
146 |
- type: map_at_1000
|
147 |
+
value: 41.948
|
148 |
- type: map_at_3
|
149 |
+
value: 35.664
|
150 |
- type: map_at_5
|
151 |
+
value: 38.061
|
152 |
- type: mrr_at_1
|
153 |
+
value: 41.11
|
154 |
- type: mrr_at_10
|
155 |
+
value: 49.183
|
156 |
- type: mrr_at_100
|
157 |
+
value: 50.166999999999994
|
158 |
- type: mrr_at_1000
|
159 |
+
value: 50.205999999999996
|
160 |
- type: mrr_at_3
|
161 |
+
value: 46.778
|
162 |
- type: mrr_at_5
|
163 |
+
value: 48.120000000000005
|
164 |
- type: ndcg_at_1
|
165 |
+
value: 41.11
|
166 |
- type: ndcg_at_10
|
167 |
+
value: 46.678
|
168 |
- type: ndcg_at_100
|
169 |
+
value: 53.876000000000005
|
170 |
- type: ndcg_at_1000
|
171 |
+
value: 55.627
|
172 |
- type: ndcg_at_3
|
173 |
+
value: 41.429
|
174 |
- type: ndcg_at_5
|
175 |
+
value: 43.551
|
176 |
- type: precision_at_1
|
177 |
+
value: 41.11
|
178 |
- type: precision_at_10
|
179 |
+
value: 10.325
|
180 |
- type: precision_at_100
|
181 |
+
value: 1.6119999999999999
|
182 |
- type: precision_at_1000
|
183 |
value: 0.184
|
184 |
- type: precision_at_3
|
185 |
+
value: 23.498
|
186 |
- type: precision_at_5
|
187 |
+
value: 16.894000000000002
|
188 |
- type: recall_at_1
|
189 |
+
value: 26.950000000000003
|
190 |
- type: recall_at_10
|
191 |
+
value: 57.239
|
192 |
- type: recall_at_100
|
193 |
+
value: 86.9
|
194 |
- type: recall_at_1000
|
195 |
+
value: 98.581
|
196 |
- type: recall_at_3
|
197 |
+
value: 41.221000000000004
|
198 |
- type: recall_at_5
|
199 |
+
value: 47.976
|
200 |
- task:
|
201 |
type: PairClassification
|
202 |
dataset:
|
|
|
207 |
revision: None
|
208 |
metrics:
|
209 |
- type: cos_sim_accuracy
|
210 |
+
value: 86.13968597726043
|
211 |
- type: cos_sim_ap
|
212 |
+
value: 90.86724630443385
|
213 |
- type: cos_sim_f1
|
214 |
+
value: 86.9653767820774
|
215 |
- type: cos_sim_precision
|
216 |
+
value: 83.9724680432645
|
217 |
- type: cos_sim_recall
|
218 |
+
value: 90.17951425554382
|
219 |
- type: dot_accuracy
|
220 |
+
value: 86.13968597726043
|
221 |
- type: dot_ap
|
222 |
+
value: 90.85181504536696
|
223 |
- type: dot_f1
|
224 |
+
value: 86.9653767820774
|
225 |
- type: dot_precision
|
226 |
+
value: 83.9724680432645
|
227 |
- type: dot_recall
|
228 |
+
value: 90.17951425554382
|
229 |
- type: euclidean_accuracy
|
230 |
+
value: 86.13968597726043
|
231 |
- type: euclidean_ap
|
232 |
+
value: 90.86657368513809
|
233 |
- type: euclidean_f1
|
234 |
+
value: 86.95208970438327
|
235 |
- type: euclidean_precision
|
236 |
+
value: 84.03940886699507
|
237 |
- type: euclidean_recall
|
238 |
+
value: 90.07391763463569
|
239 |
- type: manhattan_accuracy
|
240 |
+
value: 85.97726042230644
|
241 |
- type: manhattan_ap
|
242 |
+
value: 90.85259484237685
|
243 |
- type: manhattan_f1
|
244 |
+
value: 86.79435483870968
|
245 |
- type: manhattan_precision
|
246 |
+
value: 83.02796528447445
|
247 |
- type: manhattan_recall
|
248 |
+
value: 90.91869060190075
|
249 |
- type: max_accuracy
|
250 |
+
value: 86.13968597726043
|
251 |
- type: max_ap
|
252 |
+
value: 90.86724630443385
|
253 |
- type: max_f1
|
254 |
+
value: 86.9653767820774
|
255 |
- task:
|
256 |
type: Retrieval
|
257 |
dataset:
|
|
|
262 |
revision: None
|
263 |
metrics:
|
264 |
- type: map_at_1
|
265 |
+
value: 73.34
|
266 |
- type: map_at_10
|
267 |
+
value: 81.722
|
268 |
- type: map_at_100
|
269 |
+
value: 81.916
|
270 |
- type: map_at_1000
|
271 |
+
value: 81.919
|
272 |
- type: map_at_3
|
273 |
+
value: 80.25999999999999
|
274 |
- type: map_at_5
|
275 |
+
value: 81.11699999999999
|
276 |
- type: mrr_at_1
|
277 |
+
value: 73.551
|
278 |
- type: mrr_at_10
|
279 |
+
value: 81.727
|
280 |
- type: mrr_at_100
|
281 |
+
value: 81.911
|
282 |
- type: mrr_at_1000
|
283 |
+
value: 81.914
|
284 |
- type: mrr_at_3
|
285 |
+
value: 80.242
|
286 |
- type: mrr_at_5
|
287 |
+
value: 81.149
|
288 |
- type: ndcg_at_1
|
289 |
+
value: 73.551
|
290 |
- type: ndcg_at_10
|
291 |
+
value: 85.244
|
292 |
- type: ndcg_at_100
|
293 |
+
value: 86.005
|
294 |
- type: ndcg_at_1000
|
295 |
+
value: 86.084
|
296 |
- type: ndcg_at_3
|
297 |
+
value: 82.334
|
298 |
- type: ndcg_at_5
|
299 |
+
value: 83.878
|
300 |
- type: precision_at_1
|
301 |
+
value: 73.551
|
302 |
- type: precision_at_10
|
303 |
+
value: 9.705
|
304 |
- type: precision_at_100
|
305 |
+
value: 1.0030000000000001
|
306 |
- type: precision_at_1000
|
307 |
value: 0.101
|
308 |
- type: precision_at_3
|
309 |
+
value: 29.645
|
310 |
- type: precision_at_5
|
311 |
+
value: 18.567
|
312 |
- type: recall_at_1
|
313 |
+
value: 73.34
|
314 |
- type: recall_at_10
|
315 |
+
value: 96.048
|
316 |
- type: recall_at_100
|
317 |
+
value: 99.262
|
318 |
- type: recall_at_1000
|
319 |
+
value: 99.895
|
320 |
- type: recall_at_3
|
321 |
+
value: 88.303
|
322 |
- type: recall_at_5
|
323 |
+
value: 91.99199999999999
|
324 |
- task:
|
325 |
type: Retrieval
|
326 |
dataset:
|
|
|
331 |
revision: None
|
332 |
metrics:
|
333 |
- type: map_at_1
|
334 |
+
value: 26.506
|
335 |
- type: map_at_10
|
336 |
+
value: 81.29899999999999
|
337 |
- type: map_at_100
|
338 |
+
value: 83.997
|
339 |
- type: map_at_1000
|
340 |
+
value: 84.03399999999999
|
341 |
- type: map_at_3
|
342 |
+
value: 56.69
|
343 |
- type: map_at_5
|
344 |
+
value: 71.389
|
345 |
- type: mrr_at_1
|
346 |
+
value: 91.10000000000001
|
347 |
- type: mrr_at_10
|
348 |
+
value: 93.952
|
349 |
- type: mrr_at_100
|
350 |
+
value: 94.00500000000001
|
351 |
- type: mrr_at_1000
|
352 |
+
value: 94.00699999999999
|
353 |
- type: mrr_at_3
|
354 |
+
value: 93.683
|
355 |
- type: mrr_at_5
|
356 |
+
value: 93.858
|
357 |
- type: ndcg_at_1
|
358 |
+
value: 91.10000000000001
|
359 |
- type: ndcg_at_10
|
360 |
+
value: 88.25699999999999
|
361 |
- type: ndcg_at_100
|
362 |
+
value: 90.84100000000001
|
363 |
- type: ndcg_at_1000
|
364 |
+
value: 91.167
|
365 |
- type: ndcg_at_3
|
366 |
+
value: 87.595
|
367 |
- type: ndcg_at_5
|
368 |
+
value: 86.346
|
369 |
- type: precision_at_1
|
370 |
+
value: 91.10000000000001
|
371 |
- type: precision_at_10
|
372 |
+
value: 42.04
|
373 |
- type: precision_at_100
|
374 |
+
value: 4.804
|
375 |
- type: precision_at_1000
|
376 |
value: 0.48900000000000005
|
377 |
- type: precision_at_3
|
378 |
+
value: 78.583
|
379 |
- type: precision_at_5
|
380 |
+
value: 66.09
|
381 |
- type: recall_at_1
|
382 |
+
value: 26.506
|
383 |
- type: recall_at_10
|
384 |
+
value: 89.12299999999999
|
385 |
- type: recall_at_100
|
386 |
+
value: 97.717
|
387 |
- type: recall_at_1000
|
388 |
+
value: 99.285
|
389 |
- type: recall_at_3
|
390 |
+
value: 58.865
|
391 |
- type: recall_at_5
|
392 |
+
value: 75.753
|
393 |
- task:
|
394 |
type: Retrieval
|
395 |
dataset:
|
|
|
402 |
- type: map_at_1
|
403 |
value: 52.7
|
404 |
- type: map_at_10
|
405 |
+
value: 62.239
|
406 |
- type: map_at_100
|
407 |
+
value: 62.744
|
408 |
- type: map_at_1000
|
409 |
+
value: 62.755
|
410 |
- type: map_at_3
|
411 |
+
value: 59.75
|
412 |
- type: map_at_5
|
413 |
+
value: 61.050000000000004
|
414 |
- type: mrr_at_1
|
415 |
value: 52.7
|
416 |
- type: mrr_at_10
|
417 |
+
value: 62.239
|
418 |
- type: mrr_at_100
|
419 |
+
value: 62.744
|
420 |
- type: mrr_at_1000
|
421 |
+
value: 62.755
|
422 |
- type: mrr_at_3
|
423 |
+
value: 59.75
|
424 |
- type: mrr_at_5
|
425 |
+
value: 61.050000000000004
|
426 |
- type: ndcg_at_1
|
427 |
value: 52.7
|
428 |
- type: ndcg_at_10
|
429 |
+
value: 67.23
|
430 |
- type: ndcg_at_100
|
431 |
+
value: 69.729
|
432 |
- type: ndcg_at_1000
|
433 |
+
value: 70.00999999999999
|
434 |
- type: ndcg_at_3
|
435 |
+
value: 62.025
|
436 |
- type: ndcg_at_5
|
437 |
+
value: 64.37
|
438 |
- type: precision_at_1
|
439 |
value: 52.7
|
440 |
- type: precision_at_10
|
441 |
+
value: 8.309999999999999
|
442 |
- type: precision_at_100
|
443 |
+
value: 0.9490000000000001
|
444 |
- type: precision_at_1000
|
445 |
value: 0.097
|
446 |
- type: precision_at_3
|
447 |
+
value: 22.867
|
448 |
- type: precision_at_5
|
449 |
+
value: 14.860000000000001
|
450 |
- type: recall_at_1
|
451 |
value: 52.7
|
452 |
- type: recall_at_10
|
453 |
+
value: 83.1
|
454 |
- type: recall_at_100
|
455 |
+
value: 94.89999999999999
|
456 |
- type: recall_at_1000
|
457 |
+
value: 97.1
|
458 |
- type: recall_at_3
|
459 |
+
value: 68.60000000000001
|
460 |
- type: recall_at_5
|
461 |
+
value: 74.3
|
462 |
- task:
|
463 |
type: Classification
|
464 |
dataset:
|
|
|
469 |
revision: None
|
470 |
metrics:
|
471 |
- type: accuracy
|
472 |
+
value: 52.64332435552135
|
473 |
- type: f1
|
474 |
+
value: 42.17147347490132
|
475 |
- task:
|
476 |
type: Classification
|
477 |
dataset:
|
|
|
482 |
revision: None
|
483 |
metrics:
|
484 |
- type: accuracy
|
485 |
+
value: 87.5984990619137
|
486 |
- type: ap
|
487 |
+
value: 57.59814850574554
|
488 |
- type: f1
|
489 |
+
value: 82.62140959655022
|
490 |
- task:
|
491 |
type: STS
|
492 |
dataset:
|
|
|
497 |
revision: None
|
498 |
metrics:
|
499 |
- type: cos_sim_pearson
|
500 |
+
value: 74.58027418203673
|
501 |
- type: cos_sim_spearman
|
502 |
+
value: 79.19473724464046
|
503 |
- type: euclidean_pearson
|
504 |
+
value: 79.2941422188887
|
505 |
- type: euclidean_spearman
|
506 |
+
value: 79.1944889378359
|
507 |
- type: manhattan_pearson
|
508 |
+
value: 79.26535092062532
|
509 |
- type: manhattan_spearman
|
510 |
+
value: 79.17298822899023
|
511 |
- task:
|
512 |
type: Reranking
|
513 |
dataset:
|
|
|
518 |
revision: None
|
519 |
metrics:
|
520 |
- type: map
|
521 |
+
value: 31.611379937191025
|
522 |
- type: mrr
|
523 |
+
value: 30.88968253968254
|
524 |
- task:
|
525 |
type: Retrieval
|
526 |
dataset:
|
|
|
531 |
revision: None
|
532 |
metrics:
|
533 |
- type: map_at_1
|
534 |
+
value: 65.603
|
535 |
- type: map_at_10
|
536 |
+
value: 74.834
|
537 |
- type: map_at_100
|
538 |
+
value: 75.16199999999999
|
539 |
- type: map_at_1000
|
540 |
+
value: 75.17399999999999
|
541 |
- type: map_at_3
|
542 |
+
value: 72.979
|
543 |
- type: map_at_5
|
544 |
+
value: 74.154
|
545 |
- type: mrr_at_1
|
546 |
+
value: 67.837
|
547 |
- type: mrr_at_10
|
548 |
+
value: 75.46199999999999
|
549 |
- type: mrr_at_100
|
550 |
+
value: 75.751
|
551 |
- type: mrr_at_1000
|
552 |
+
value: 75.762
|
553 |
- type: mrr_at_3
|
554 |
+
value: 73.832
|
555 |
- type: mrr_at_5
|
556 |
+
value: 74.875
|
557 |
- type: ndcg_at_1
|
558 |
+
value: 67.837
|
559 |
- type: ndcg_at_10
|
560 |
+
value: 78.636
|
561 |
- type: ndcg_at_100
|
562 |
+
value: 80.083
|
563 |
- type: ndcg_at_1000
|
564 |
+
value: 80.394
|
565 |
- type: ndcg_at_3
|
566 |
+
value: 75.12
|
567 |
- type: ndcg_at_5
|
568 |
+
value: 77.12
|
569 |
- type: precision_at_1
|
570 |
+
value: 67.837
|
571 |
- type: precision_at_10
|
572 |
+
value: 9.536999999999999
|
573 |
- type: precision_at_100
|
574 |
+
value: 1.0250000000000001
|
575 |
- type: precision_at_1000
|
576 |
value: 0.105
|
577 |
- type: precision_at_3
|
578 |
+
value: 28.352
|
579 |
- type: precision_at_5
|
580 |
+
value: 18.074
|
581 |
- type: recall_at_1
|
582 |
+
value: 65.603
|
583 |
- type: recall_at_10
|
584 |
+
value: 89.704
|
585 |
- type: recall_at_100
|
586 |
+
value: 96.2
|
587 |
- type: recall_at_1000
|
588 |
+
value: 98.588
|
589 |
- type: recall_at_3
|
590 |
+
value: 80.444
|
591 |
- type: recall_at_5
|
592 |
+
value: 85.205
|
593 |
- task:
|
594 |
type: Classification
|
595 |
dataset:
|
|
|
600 |
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
|
601 |
metrics:
|
602 |
- type: accuracy
|
603 |
+
value: 77.43106926698049
|
604 |
- type: f1
|
605 |
+
value: 73.96808004721824
|
606 |
- task:
|
607 |
type: Classification
|
608 |
dataset:
|
|
|
613 |
revision: 7d571f92784cd94a019292a1f45445077d0ef634
|
614 |
metrics:
|
615 |
- type: accuracy
|
616 |
+
value: 83.86684599865501
|
617 |
- type: f1
|
618 |
+
value: 83.05645257324346
|
619 |
- task:
|
620 |
type: Retrieval
|
621 |
dataset:
|
|
|
626 |
revision: None
|
627 |
metrics:
|
628 |
- type: map_at_1
|
629 |
+
value: 55.00000000000001
|
630 |
- type: map_at_10
|
631 |
+
value: 61.129
|
632 |
- type: map_at_100
|
633 |
+
value: 61.61
|
634 |
- type: map_at_1000
|
635 |
+
value: 61.655
|
636 |
- type: map_at_3
|
637 |
+
value: 59.533
|
638 |
- type: map_at_5
|
639 |
+
value: 60.478
|
640 |
- type: mrr_at_1
|
641 |
value: 54.900000000000006
|
642 |
- type: mrr_at_10
|
643 |
+
value: 61.090999999999994
|
644 |
- type: mrr_at_100
|
645 |
+
value: 61.562
|
646 |
- type: mrr_at_1000
|
647 |
+
value: 61.608
|
648 |
- type: mrr_at_3
|
649 |
+
value: 59.483
|
650 |
- type: mrr_at_5
|
651 |
+
value: 60.428000000000004
|
652 |
- type: ndcg_at_1
|
653 |
+
value: 55.00000000000001
|
654 |
- type: ndcg_at_10
|
655 |
+
value: 64.288
|
656 |
- type: ndcg_at_100
|
657 |
+
value: 66.991
|
658 |
- type: ndcg_at_1000
|
659 |
+
value: 68.27
|
660 |
- type: ndcg_at_3
|
661 |
+
value: 61.014
|
662 |
- type: ndcg_at_5
|
663 |
+
value: 62.68899999999999
|
664 |
- type: precision_at_1
|
665 |
+
value: 55.00000000000001
|
666 |
- type: precision_at_10
|
667 |
+
value: 7.430000000000001
|
668 |
- type: precision_at_100
|
669 |
value: 0.878
|
670 |
- type: precision_at_1000
|
671 |
value: 0.098
|
672 |
- type: precision_at_3
|
673 |
+
value: 21.767
|
674 |
- type: precision_at_5
|
675 |
+
value: 13.86
|
676 |
- type: recall_at_1
|
677 |
+
value: 55.00000000000001
|
678 |
- type: recall_at_10
|
679 |
+
value: 74.3
|
680 |
- type: recall_at_100
|
681 |
value: 87.8
|
682 |
- type: recall_at_1000
|
683 |
+
value: 98.0
|
684 |
- type: recall_at_3
|
685 |
+
value: 65.3
|
686 |
- type: recall_at_5
|
687 |
+
value: 69.3
|
688 |
- task:
|
689 |
type: Classification
|
690 |
dataset:
|
|
|
695 |
revision: None
|
696 |
metrics:
|
697 |
- type: accuracy
|
698 |
+
value: 78.48333333333333
|
699 |
- type: f1
|
700 |
+
value: 78.36516159631131
|
701 |
- task:
|
702 |
type: PairClassification
|
703 |
dataset:
|
|
|
708 |
revision: None
|
709 |
metrics:
|
710 |
- type: cos_sim_accuracy
|
711 |
+
value: 86.13968597726043
|
712 |
- type: cos_sim_ap
|
713 |
+
value: 90.86724630443385
|
714 |
- type: cos_sim_f1
|
715 |
+
value: 86.9653767820774
|
716 |
- type: cos_sim_precision
|
717 |
+
value: 83.9724680432645
|
718 |
- type: cos_sim_recall
|
719 |
+
value: 90.17951425554382
|
720 |
- type: dot_accuracy
|
721 |
+
value: 86.13968597726043
|
722 |
- type: dot_ap
|
723 |
+
value: 90.85181504536696
|
724 |
- type: dot_f1
|
725 |
+
value: 86.9653767820774
|
726 |
- type: dot_precision
|
727 |
+
value: 83.9724680432645
|
728 |
- type: dot_recall
|
729 |
+
value: 90.17951425554382
|
730 |
- type: euclidean_accuracy
|
731 |
+
value: 86.13968597726043
|
732 |
- type: euclidean_ap
|
733 |
+
value: 90.86657368513809
|
734 |
- type: euclidean_f1
|
735 |
+
value: 86.95208970438327
|
736 |
- type: euclidean_precision
|
737 |
+
value: 84.03940886699507
|
738 |
- type: euclidean_recall
|
739 |
+
value: 90.07391763463569
|
740 |
- type: manhattan_accuracy
|
741 |
+
value: 85.97726042230644
|
742 |
- type: manhattan_ap
|
743 |
+
value: 90.85259484237685
|
744 |
- type: manhattan_f1
|
745 |
+
value: 86.79435483870968
|
746 |
- type: manhattan_precision
|
747 |
+
value: 83.02796528447445
|
748 |
- type: manhattan_recall
|
749 |
+
value: 90.91869060190075
|
750 |
- type: max_accuracy
|
751 |
+
value: 86.13968597726043
|
752 |
- type: max_ap
|
753 |
+
value: 90.86724630443385
|
754 |
- type: max_f1
|
755 |
+
value: 86.9653767820774
|
756 |
- task:
|
757 |
type: Classification
|
758 |
dataset:
|
|
|
763 |
revision: None
|
764 |
metrics:
|
765 |
- type: accuracy
|
766 |
+
value: 94.33999999999999
|
767 |
- type: ap
|
768 |
+
value: 92.566213965377
|
769 |
- type: f1
|
770 |
+
value: 94.32981412505542
|
771 |
- task:
|
772 |
type: STS
|
773 |
dataset:
|
|
|
778 |
revision: None
|
779 |
metrics:
|
780 |
- type: cos_sim_pearson
|
781 |
+
value: 40.59979992480721
|
782 |
- type: cos_sim_spearman
|
783 |
+
value: 45.80272854477526
|
784 |
- type: euclidean_pearson
|
785 |
+
value: 45.51435650601272
|
786 |
- type: euclidean_spearman
|
787 |
+
value: 45.80481880049892
|
788 |
- type: manhattan_pearson
|
789 |
+
value: 45.50783698090448
|
790 |
- type: manhattan_spearman
|
791 |
+
value: 45.7962835896273
|
792 |
- task:
|
793 |
type: STS
|
794 |
dataset:
|
|
|
799 |
revision: None
|
800 |
metrics:
|
801 |
- type: cos_sim_pearson
|
802 |
+
value: 41.95530336245604
|
803 |
- type: cos_sim_spearman
|
804 |
+
value: 43.94205325290135
|
805 |
- type: euclidean_pearson
|
806 |
+
value: 38.01893281522651
|
807 |
- type: euclidean_spearman
|
808 |
+
value: 43.9411389356089
|
809 |
- type: manhattan_pearson
|
810 |
+
value: 38.158512461951446
|
811 |
- type: manhattan_spearman
|
812 |
+
value: 44.055211140130815
|
813 |
- task:
|
814 |
type: STS
|
815 |
dataset:
|
|
|
820 |
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
|
821 |
metrics:
|
822 |
- type: cos_sim_pearson
|
823 |
+
value: 63.64131281514482
|
824 |
- type: cos_sim_spearman
|
825 |
+
value: 65.17753570208333
|
826 |
- type: euclidean_pearson
|
827 |
+
value: 62.72868744500848
|
828 |
- type: euclidean_spearman
|
829 |
+
value: 65.17730738350589
|
830 |
- type: manhattan_pearson
|
831 |
+
value: 62.76099444782981
|
832 |
- type: manhattan_spearman
|
833 |
+
value: 65.2421498595002
|
834 |
- task:
|
835 |
type: STS
|
836 |
dataset:
|
|
|
841 |
revision: None
|
842 |
metrics:
|
843 |
- type: cos_sim_pearson
|
844 |
+
value: 79.15762053490425
|
845 |
- type: cos_sim_spearman
|
846 |
+
value: 79.47824157657848
|
847 |
- type: euclidean_pearson
|
848 |
+
value: 79.11217669696227
|
849 |
- type: euclidean_spearman
|
850 |
+
value: 79.47857091559331
|
851 |
- type: manhattan_pearson
|
852 |
+
value: 79.07701011877683
|
853 |
- type: manhattan_spearman
|
854 |
+
value: 79.43942682897884
|
855 |
- task:
|
856 |
type: Reranking
|
857 |
dataset:
|
|
|
862 |
revision: None
|
863 |
metrics:
|
864 |
- type: map
|
865 |
+
value: 67.45068053105526
|
866 |
- type: mrr
|
867 |
+
value: 77.63560439973777
|
868 |
- task:
|
869 |
type: Retrieval
|
870 |
dataset:
|
|
|
875 |
revision: None
|
876 |
metrics:
|
877 |
- type: map_at_1
|
878 |
+
value: 27.837
|
879 |
- type: map_at_10
|
880 |
+
value: 77.803
|
881 |
- type: map_at_100
|
882 |
+
value: 81.402
|
883 |
- type: map_at_1000
|
884 |
+
value: 81.464
|
885 |
- type: map_at_3
|
886 |
+
value: 54.879
|
887 |
- type: map_at_5
|
888 |
+
value: 67.32900000000001
|
889 |
- type: mrr_at_1
|
890 |
+
value: 90.584
|
891 |
- type: mrr_at_10
|
892 |
+
value: 93.059
|
893 |
- type: mrr_at_100
|
894 |
+
value: 93.135
|
895 |
- type: mrr_at_1000
|
896 |
+
value: 93.138
|
897 |
- type: mrr_at_3
|
898 |
+
value: 92.659
|
899 |
- type: mrr_at_5
|
900 |
+
value: 92.914
|
901 |
- type: ndcg_at_1
|
902 |
+
value: 90.584
|
903 |
- type: ndcg_at_10
|
904 |
+
value: 85.29299999999999
|
905 |
- type: ndcg_at_100
|
906 |
+
value: 88.824
|
907 |
- type: ndcg_at_1000
|
908 |
+
value: 89.4
|
909 |
- type: ndcg_at_3
|
910 |
+
value: 86.79599999999999
|
911 |
- type: ndcg_at_5
|
912 |
+
value: 85.353
|
913 |
- type: precision_at_1
|
914 |
+
value: 90.584
|
915 |
- type: precision_at_10
|
916 |
+
value: 42.191
|
917 |
- type: precision_at_100
|
918 |
+
value: 5.0200000000000005
|
919 |
- type: precision_at_1000
|
920 |
+
value: 0.516
|
921 |
- type: precision_at_3
|
922 |
+
value: 75.785
|
923 |
- type: precision_at_5
|
924 |
+
value: 63.417
|
925 |
- type: recall_at_1
|
926 |
+
value: 27.837
|
927 |
- type: recall_at_10
|
928 |
+
value: 84.21600000000001
|
929 |
- type: recall_at_100
|
930 |
+
value: 95.719
|
931 |
- type: recall_at_1000
|
932 |
+
value: 98.565
|
933 |
- type: recall_at_3
|
934 |
+
value: 56.574999999999996
|
935 |
- type: recall_at_5
|
936 |
+
value: 70.682
|
937 |
- task:
|
938 |
type: Classification
|
939 |
dataset:
|
|
|
944 |
revision: None
|
945 |
metrics:
|
946 |
- type: accuracy
|
947 |
+
value: 54.37
|
948 |
- type: f1
|
949 |
+
value: 52.57500124627352
|
950 |
- task:
|
951 |
type: Clustering
|
952 |
dataset:
|
|
|
957 |
revision: None
|
958 |
metrics:
|
959 |
- type: v_measure
|
960 |
+
value: 76.9781904739968
|
961 |
- task:
|
962 |
type: Clustering
|
963 |
dataset:
|
|
|
968 |
revision: None
|
969 |
metrics:
|
970 |
- type: v_measure
|
971 |
+
value: 69.82661181746705
|
972 |
- task:
|
973 |
type: Retrieval
|
974 |
dataset:
|
|
|
979 |
revision: None
|
980 |
metrics:
|
981 |
- type: map_at_1
|
982 |
+
value: 58.699999999999996
|
983 |
- type: map_at_10
|
984 |
+
value: 68.512
|
985 |
- type: map_at_100
|
986 |
+
value: 69.018
|
987 |
- type: map_at_1000
|
988 |
+
value: 69.028
|
989 |
- type: map_at_3
|
990 |
+
value: 66.51700000000001
|
991 |
- type: map_at_5
|
992 |
+
value: 67.91199999999999
|
993 |
- type: mrr_at_1
|
994 |
+
value: 58.599999999999994
|
995 |
- type: mrr_at_10
|
996 |
+
value: 68.462
|
997 |
- type: mrr_at_100
|
998 |
+
value: 68.96799999999999
|
999 |
- type: mrr_at_1000
|
1000 |
+
value: 68.978
|
1001 |
- type: mrr_at_3
|
1002 |
+
value: 66.467
|
1003 |
- type: mrr_at_5
|
1004 |
+
value: 67.862
|
1005 |
- type: ndcg_at_1
|
1006 |
+
value: 58.699999999999996
|
1007 |
- type: ndcg_at_10
|
1008 |
+
value: 72.88900000000001
|
1009 |
- type: ndcg_at_100
|
1010 |
+
value: 75.262
|
1011 |
- type: ndcg_at_1000
|
1012 |
+
value: 75.48700000000001
|
1013 |
- type: ndcg_at_3
|
1014 |
+
value: 68.96
|
1015 |
- type: ndcg_at_5
|
1016 |
+
value: 71.452
|
1017 |
- type: precision_at_1
|
1018 |
+
value: 58.699999999999996
|
1019 |
- type: precision_at_10
|
1020 |
+
value: 8.64
|
1021 |
- type: precision_at_100
|
1022 |
+
value: 0.9730000000000001
|
1023 |
- type: precision_at_1000
|
1024 |
value: 0.099
|
1025 |
- type: precision_at_3
|
1026 |
+
value: 25.333
|
1027 |
- type: precision_at_5
|
1028 |
+
value: 16.400000000000002
|
1029 |
- type: recall_at_1
|
1030 |
+
value: 58.699999999999996
|
1031 |
- type: recall_at_10
|
1032 |
+
value: 86.4
|
1033 |
- type: recall_at_100
|
1034 |
+
value: 97.3
|
1035 |
- type: recall_at_1000
|
1036 |
+
value: 99.0
|
1037 |
- type: recall_at_3
|
1038 |
+
value: 76.0
|
1039 |
- type: recall_at_5
|
1040 |
+
value: 82.0
|
1041 |
- task:
|
1042 |
type: Classification
|
1043 |
dataset:
|
|
|
1048 |
revision: None
|
1049 |
metrics:
|
1050 |
- type: accuracy
|
1051 |
+
value: 89.23
|
1052 |
- type: ap
|
1053 |
+
value: 75.03115536738895
|
1054 |
- type: f1
|
1055 |
+
value: 87.71601665295442
|
1056 |
---
|
1057 |
|
1058 |
### 使用方法
|