Update README.md
Browse files
README.md
CHANGED
@@ -14,11 +14,11 @@ model-index:
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revision: e8379541af4e31359cca9fbcf4b00f2671dba205
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metrics:
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- type: accuracy
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-
value:
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- type: ap
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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: Classification
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dataset:
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@@ -29,11 +29,11 @@ model-index:
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revision: e2d317d38cd51312af73b3d32a06d1a08b442046
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metrics:
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- type: accuracy
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-
value:
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- type: ap
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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: Classification
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dataset:
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@@ -44,9 +44,9 @@ 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: Retrieval
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dataset:
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@@ -57,65 +57,65 @@ 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: 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: 0.1
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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: 13.
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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: 99.57300000000001
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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: Clustering
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dataset:
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@@ -126,7 +126,7 @@ model-index:
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revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
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metrics:
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- type: v_measure
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-
value: 45.
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- task:
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type: Clustering
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dataset:
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@@ -137,7 +137,7 @@ model-index:
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revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
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metrics:
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- type: v_measure
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-
value: 36.
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- task:
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type: Reranking
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dataset:
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@@ -148,9 +148,9 @@ model-index:
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revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
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metrics:
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- type: map
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-
value:
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- type: mrr
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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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@@ -161,17 +161,17 @@ model-index:
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revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
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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:
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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: Classification
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dataset:
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@@ -182,9 +182,9 @@ model-index:
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revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
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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: Clustering
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dataset:
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@@ -195,7 +195,7 @@ model-index:
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revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
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metrics:
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- type: v_measure
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-
value: 38.
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- task:
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type: Clustering
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dataset:
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@@ -206,7 +206,7 @@ model-index:
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revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
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metrics:
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- type: v_measure
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-
value: 33.
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- task:
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type: Retrieval
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dataset:
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@@ -217,65 +217,65 @@ 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: 41.
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- type: map_at_1000
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-
value: 41.
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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: 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: 45.
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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: 46.
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- type: mrr_at_3
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-
value: 43.
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- type: mrr_at_5
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-
value: 44.
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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: 45.
|
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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: 41.
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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: 8.
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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.
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- type: precision_at_3
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-
value: 19.
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- type: precision_at_5
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-
value: 13.
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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:
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- type: recall_at_3
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-
value: 43.
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- type: recall_at_5
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-
value: 48.
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- task:
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type: Retrieval
|
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dataset:
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@@ -286,65 +286,65 @@ 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: 8.
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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.
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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: 14.
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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:
|
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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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@@ -355,65 +355,65 @@ 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: 52.
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- type: map_at_100
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-
value: 53.
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- type: map_at_1000
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-
value: 53.
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- type: map_at_3
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-
value: 49.
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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: 46.708
|
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- type: mrr_at_10
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-
value: 56.
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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: 55.
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- type: ndcg_at_1
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value: 46.708
|
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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: 55.
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- type: precision_at_1
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value: 46.708
|
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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.
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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: 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:
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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:
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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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@@ -424,65 +424,65 @@ 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:
|
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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: 28.
|
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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: 33.
|
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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: 28.
|
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- type: ndcg_at_10
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-
value: 38.
|
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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: 28.
|
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- type: precision_at_10
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-
value: 5.
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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.
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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: 9.
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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:
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- type: recall_at_1000
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-
value:
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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
|
488 |
dataset:
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@@ -493,65 +493,65 @@ 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:
|
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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.
|
539 |
- type: precision_at_3
|
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-
value:
|
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- type: precision_at_5
|
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-
value: 8.
|
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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:
|
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- type: recall_at_3
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-
value:
|
553 |
- type: recall_at_5
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-
value:
|
555 |
- task:
|
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type: Retrieval
|
557 |
dataset:
|
@@ -562,65 +562,65 @@ model-index:
|
|
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revision: None
|
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metrics:
|
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- type: map_at_1
|
565 |
-
value: 28.
|
566 |
- type: map_at_10
|
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-
value:
|
568 |
- type: map_at_100
|
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-
value:
|
570 |
- type: map_at_1000
|
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-
value:
|
572 |
- type: map_at_3
|
573 |
-
value: 35.
|
574 |
- type: map_at_5
|
575 |
-
value: 36.
|
576 |
- type: mrr_at_1
|
577 |
value: 33.782000000000004
|
578 |
- type: mrr_at_10
|
579 |
-
value: 43.
|
580 |
- type: mrr_at_100
|
581 |
-
value: 43.
|
582 |
- type: mrr_at_1000
|
583 |
-
value:
|
584 |
- type: mrr_at_3
|
585 |
-
value: 40.
|
586 |
- type: mrr_at_5
|
587 |
-
value: 42.
|
588 |
- type: ndcg_at_1
|
589 |
value: 33.782000000000004
|
590 |
- type: ndcg_at_10
|
591 |
-
value: 43.
|
592 |
- type: ndcg_at_100
|
593 |
-
value: 48.
|
594 |
- type: ndcg_at_1000
|
595 |
-
value:
|
596 |
- type: ndcg_at_3
|
597 |
-
value: 38.
|
598 |
- type: ndcg_at_5
|
599 |
-
value: 41.
|
600 |
- type: precision_at_1
|
601 |
value: 33.782000000000004
|
602 |
- type: precision_at_10
|
603 |
-
value: 7.
|
604 |
- type: precision_at_100
|
605 |
-
value: 1.
|
606 |
- type: precision_at_1000
|
607 |
-
value: 0.
|
608 |
- type: precision_at_3
|
609 |
-
value: 18.
|
610 |
- type: precision_at_5
|
611 |
-
value:
|
612 |
- type: recall_at_1
|
613 |
-
value: 28.
|
614 |
- type: recall_at_10
|
615 |
-
value: 54.
|
616 |
- type: recall_at_100
|
617 |
-
value:
|
618 |
- type: recall_at_1000
|
619 |
-
value:
|
620 |
- type: recall_at_3
|
621 |
-
value:
|
622 |
- type: recall_at_5
|
623 |
-
value:
|
624 |
- task:
|
625 |
type: Retrieval
|
626 |
dataset:
|
@@ -631,65 +631,65 @@ model-index:
|
|
631 |
revision: None
|
632 |
metrics:
|
633 |
- type: map_at_1
|
634 |
-
value: 25.
|
635 |
- type: map_at_10
|
636 |
-
value:
|
637 |
- type: map_at_100
|
638 |
-
value:
|
639 |
- type: map_at_1000
|
640 |
-
value:
|
641 |
- type: map_at_3
|
642 |
-
value:
|
643 |
- type: map_at_5
|
644 |
-
value:
|
645 |
- type: mrr_at_1
|
646 |
-
value:
|
647 |
- type: mrr_at_10
|
648 |
-
value:
|
649 |
- type: mrr_at_100
|
650 |
-
value:
|
651 |
- type: mrr_at_1000
|
652 |
-
value:
|
653 |
- type: mrr_at_3
|
654 |
-
value:
|
655 |
- type: mrr_at_5
|
656 |
-
value:
|
657 |
- type: ndcg_at_1
|
658 |
-
value:
|
659 |
- type: ndcg_at_10
|
660 |
-
value:
|
661 |
- type: ndcg_at_100
|
662 |
-
value:
|
663 |
- type: ndcg_at_1000
|
664 |
-
value:
|
665 |
- type: ndcg_at_3
|
666 |
-
value: 35.
|
667 |
- type: ndcg_at_5
|
668 |
-
value:
|
669 |
- type: precision_at_1
|
670 |
-
value:
|
671 |
- type: precision_at_10
|
672 |
-
value: 7.
|
673 |
- type: precision_at_100
|
674 |
-
value: 1.
|
675 |
- type: precision_at_1000
|
676 |
-
value: 0.
|
677 |
- type: precision_at_3
|
678 |
-
value:
|
679 |
- type: precision_at_5
|
680 |
-
value:
|
681 |
- type: recall_at_1
|
682 |
-
value: 25.
|
683 |
- type: recall_at_10
|
684 |
-
value:
|
685 |
- type: recall_at_100
|
686 |
-
value:
|
687 |
- type: recall_at_1000
|
688 |
-
value: 90.
|
689 |
- type: recall_at_3
|
690 |
-
value:
|
691 |
- type: recall_at_5
|
692 |
-
value:
|
693 |
- task:
|
694 |
type: Retrieval
|
695 |
dataset:
|
@@ -700,65 +700,65 @@ model-index:
|
|
700 |
revision: None
|
701 |
metrics:
|
702 |
- type: map_at_1
|
703 |
-
value:
|
704 |
- type: map_at_10
|
705 |
-
value:
|
706 |
- type: map_at_100
|
707 |
-
value:
|
708 |
- type: map_at_1000
|
709 |
-
value:
|
710 |
- type: map_at_3
|
711 |
-
value:
|
712 |
- type: map_at_5
|
713 |
-
value:
|
714 |
- type: mrr_at_1
|
715 |
-
value:
|
716 |
- type: mrr_at_10
|
717 |
-
value:
|
718 |
- type: mrr_at_100
|
719 |
-
value:
|
720 |
- type: mrr_at_1000
|
721 |
-
value:
|
722 |
- type: mrr_at_3
|
723 |
-
value:
|
724 |
- type: mrr_at_5
|
725 |
-
value:
|
726 |
- type: ndcg_at_1
|
727 |
-
value:
|
728 |
- type: ndcg_at_10
|
729 |
-
value:
|
730 |
- type: ndcg_at_100
|
731 |
-
value:
|
732 |
- type: ndcg_at_1000
|
733 |
-
value:
|
734 |
- type: ndcg_at_3
|
735 |
-
value:
|
736 |
- type: ndcg_at_5
|
737 |
-
value:
|
738 |
- type: precision_at_1
|
739 |
-
value:
|
740 |
- type: precision_at_10
|
741 |
-
value: 6.
|
742 |
- type: precision_at_100
|
743 |
-
value: 1.
|
744 |
- type: precision_at_1000
|
745 |
-
value: 0.
|
746 |
- type: precision_at_3
|
747 |
-
value: 15.
|
748 |
- type: precision_at_5
|
749 |
-
value:
|
750 |
- type: recall_at_1
|
751 |
-
value:
|
752 |
- type: recall_at_10
|
753 |
-
value:
|
754 |
- type: recall_at_100
|
755 |
-
value:
|
756 |
- type: recall_at_1000
|
757 |
-
value:
|
758 |
- type: recall_at_3
|
759 |
-
value:
|
760 |
- type: recall_at_5
|
761 |
-
value:
|
762 |
- task:
|
763 |
type: Retrieval
|
764 |
dataset:
|
@@ -769,65 +769,65 @@ model-index:
|
|
769 |
revision: None
|
770 |
metrics:
|
771 |
- type: map_at_1
|
772 |
-
value:
|
773 |
- type: map_at_10
|
774 |
-
value:
|
775 |
- type: map_at_100
|
776 |
-
value:
|
777 |
- type: map_at_1000
|
778 |
-
value:
|
779 |
- type: map_at_3
|
780 |
-
value:
|
781 |
- type: map_at_5
|
782 |
-
value:
|
783 |
- type: mrr_at_1
|
784 |
-
value:
|
785 |
- type: mrr_at_10
|
786 |
-
value:
|
787 |
- type: mrr_at_100
|
788 |
-
value:
|
789 |
- type: mrr_at_1000
|
790 |
-
value:
|
791 |
- type: mrr_at_3
|
792 |
-
value:
|
793 |
- type: mrr_at_5
|
794 |
-
value:
|
795 |
- type: ndcg_at_1
|
796 |
-
value:
|
797 |
- type: ndcg_at_10
|
798 |
-
value:
|
799 |
- type: ndcg_at_100
|
800 |
-
value:
|
801 |
- type: ndcg_at_1000
|
802 |
-
value:
|
803 |
- type: ndcg_at_3
|
804 |
-
value:
|
805 |
- type: ndcg_at_5
|
806 |
-
value:
|
807 |
- type: precision_at_1
|
808 |
-
value:
|
809 |
- type: precision_at_10
|
810 |
-
value: 5.
|
811 |
- type: precision_at_100
|
812 |
-
value: 0.
|
813 |
- type: precision_at_1000
|
814 |
-
value: 0.
|
815 |
- type: precision_at_3
|
816 |
-
value: 12.
|
817 |
- type: precision_at_5
|
818 |
-
value: 8.
|
819 |
- type: recall_at_1
|
820 |
-
value:
|
821 |
- type: recall_at_10
|
822 |
-
value:
|
823 |
- type: recall_at_100
|
824 |
-
value:
|
825 |
- type: recall_at_1000
|
826 |
-
value: 81.
|
827 |
- type: recall_at_3
|
828 |
-
value:
|
829 |
- type: recall_at_5
|
830 |
-
value: 37.
|
831 |
- task:
|
832 |
type: Retrieval
|
833 |
dataset:
|
@@ -838,65 +838,65 @@ model-index:
|
|
838 |
revision: None
|
839 |
metrics:
|
840 |
- type: map_at_1
|
841 |
-
value: 16.
|
842 |
- type: map_at_10
|
843 |
-
value:
|
844 |
- type: map_at_100
|
845 |
-
value:
|
846 |
- type: map_at_1000
|
847 |
-
value:
|
848 |
- type: map_at_3
|
849 |
-
value: 21.
|
850 |
- type: map_at_5
|
851 |
-
value: 22.
|
852 |
- type: mrr_at_1
|
853 |
-
value:
|
854 |
- type: mrr_at_10
|
855 |
-
value:
|
856 |
- type: mrr_at_100
|
857 |
-
value:
|
858 |
- type: mrr_at_1000
|
859 |
-
value:
|
860 |
- type: mrr_at_3
|
861 |
-
value:
|
862 |
- type: mrr_at_5
|
863 |
-
value:
|
864 |
- type: ndcg_at_1
|
865 |
-
value:
|
866 |
- type: ndcg_at_10
|
867 |
-
value:
|
868 |
- type: ndcg_at_100
|
869 |
-
value:
|
870 |
- type: ndcg_at_1000
|
871 |
-
value:
|
872 |
- type: ndcg_at_3
|
873 |
-
value:
|
874 |
- type: ndcg_at_5
|
875 |
-
value:
|
876 |
- type: precision_at_1
|
877 |
-
value:
|
878 |
- type: precision_at_10
|
879 |
-
value: 4.
|
880 |
- type: precision_at_100
|
881 |
-
value: 0.
|
882 |
- type: precision_at_1000
|
883 |
-
value: 0.
|
884 |
- type: precision_at_3
|
885 |
-
value:
|
886 |
- type: precision_at_5
|
887 |
-
value:
|
888 |
- type: recall_at_1
|
889 |
-
value: 16.
|
890 |
- type: recall_at_10
|
891 |
-
value:
|
892 |
- type: recall_at_100
|
893 |
-
value:
|
894 |
- type: recall_at_1000
|
895 |
-
value:
|
896 |
- type: recall_at_3
|
897 |
-
value:
|
898 |
- type: recall_at_5
|
899 |
-
value:
|
900 |
- task:
|
901 |
type: Retrieval
|
902 |
dataset:
|
@@ -907,65 +907,65 @@ model-index:
|
|
907 |
revision: None
|
908 |
metrics:
|
909 |
- type: map_at_1
|
910 |
-
value:
|
911 |
- type: map_at_10
|
912 |
-
value:
|
913 |
- type: map_at_100
|
914 |
-
value:
|
915 |
- type: map_at_1000
|
916 |
-
value:
|
917 |
- type: map_at_3
|
918 |
-
value:
|
919 |
- type: map_at_5
|
920 |
-
value:
|
921 |
- type: mrr_at_1
|
922 |
-
value:
|
923 |
- type: mrr_at_10
|
924 |
-
value:
|
925 |
- type: mrr_at_100
|
926 |
-
value:
|
927 |
- type: mrr_at_1000
|
928 |
-
value:
|
929 |
- type: mrr_at_3
|
930 |
-
value: 34.
|
931 |
- type: mrr_at_5
|
932 |
-
value:
|
933 |
- type: ndcg_at_1
|
934 |
-
value:
|
935 |
- type: ndcg_at_10
|
936 |
-
value:
|
937 |
- type: ndcg_at_100
|
938 |
-
value:
|
939 |
- type: ndcg_at_1000
|
940 |
-
value:
|
941 |
- type: ndcg_at_3
|
942 |
-
value:
|
943 |
- type: ndcg_at_5
|
944 |
-
value:
|
945 |
- type: precision_at_1
|
946 |
-
value:
|
947 |
- type: precision_at_10
|
948 |
-
value:
|
949 |
- type: precision_at_100
|
950 |
-
value: 0.
|
951 |
- type: precision_at_1000
|
952 |
-
value: 0.
|
953 |
- type: precision_at_3
|
954 |
-
value: 14.
|
955 |
- type: precision_at_5
|
956 |
-
value:
|
957 |
- type: recall_at_1
|
958 |
-
value:
|
959 |
- type: recall_at_10
|
960 |
-
value:
|
961 |
- type: recall_at_100
|
962 |
-
value:
|
963 |
- type: recall_at_1000
|
964 |
-
value:
|
965 |
- type: recall_at_3
|
966 |
-
value:
|
967 |
- type: recall_at_5
|
968 |
-
value:
|
969 |
- task:
|
970 |
type: Retrieval
|
971 |
dataset:
|
@@ -976,65 +976,65 @@ model-index:
|
|
976 |
revision: None
|
977 |
metrics:
|
978 |
- type: map_at_1
|
979 |
-
value:
|
980 |
- type: map_at_10
|
981 |
-
value:
|
982 |
- type: map_at_100
|
983 |
-
value:
|
984 |
- type: map_at_1000
|
985 |
-
value:
|
986 |
- type: map_at_3
|
987 |
-
value:
|
988 |
- type: map_at_5
|
989 |
-
value:
|
990 |
- type: mrr_at_1
|
991 |
-
value:
|
992 |
- type: mrr_at_10
|
993 |
-
value:
|
994 |
- type: mrr_at_100
|
995 |
-
value:
|
996 |
- type: mrr_at_1000
|
997 |
-
value:
|
998 |
- type: mrr_at_3
|
999 |
-
value:
|
1000 |
- type: mrr_at_5
|
1001 |
-
value:
|
1002 |
- type: ndcg_at_1
|
1003 |
-
value:
|
1004 |
- type: ndcg_at_10
|
1005 |
-
value:
|
1006 |
- type: ndcg_at_100
|
1007 |
-
value:
|
1008 |
- type: ndcg_at_1000
|
1009 |
-
value:
|
1010 |
- type: ndcg_at_3
|
1011 |
-
value:
|
1012 |
- type: ndcg_at_5
|
1013 |
-
value:
|
1014 |
- type: precision_at_1
|
1015 |
-
value:
|
1016 |
- type: precision_at_10
|
1017 |
-
value: 6.
|
1018 |
- type: precision_at_100
|
1019 |
-
value: 1.
|
1020 |
- type: precision_at_1000
|
1021 |
value: 0.231
|
1022 |
- type: precision_at_3
|
1023 |
-
value: 14.
|
1024 |
- type: precision_at_5
|
1025 |
-
value: 10.
|
1026 |
- type: recall_at_1
|
1027 |
-
value:
|
1028 |
- type: recall_at_10
|
1029 |
-
value:
|
1030 |
- type: recall_at_100
|
1031 |
-
value:
|
1032 |
- type: recall_at_1000
|
1033 |
-
value: 90.
|
1034 |
- type: recall_at_3
|
1035 |
-
value:
|
1036 |
- type: recall_at_5
|
1037 |
-
value:
|
1038 |
- task:
|
1039 |
type: Retrieval
|
1040 |
dataset:
|
@@ -1045,65 +1045,65 @@ model-index:
|
|
1045 |
revision: None
|
1046 |
metrics:
|
1047 |
- type: map_at_1
|
1048 |
-
value:
|
1049 |
- type: map_at_10
|
1050 |
-
value:
|
1051 |
- type: map_at_100
|
1052 |
-
value:
|
1053 |
- type: map_at_1000
|
1054 |
-
value:
|
1055 |
- type: map_at_3
|
1056 |
-
value:
|
1057 |
- type: map_at_5
|
1058 |
-
value:
|
1059 |
- type: mrr_at_1
|
1060 |
-
value:
|
1061 |
- type: mrr_at_10
|
1062 |
-
value:
|
1063 |
- type: mrr_at_100
|
1064 |
-
value:
|
1065 |
- type: mrr_at_1000
|
1066 |
-
value:
|
1067 |
- type: mrr_at_3
|
1068 |
-
value:
|
1069 |
- type: mrr_at_5
|
1070 |
-
value:
|
1071 |
- type: ndcg_at_1
|
1072 |
-
value:
|
1073 |
- type: ndcg_at_10
|
1074 |
-
value:
|
1075 |
- type: ndcg_at_100
|
1076 |
-
value:
|
1077 |
- type: ndcg_at_1000
|
1078 |
-
value:
|
1079 |
- type: ndcg_at_3
|
1080 |
-
value:
|
1081 |
- type: ndcg_at_5
|
1082 |
-
value:
|
1083 |
- type: precision_at_1
|
1084 |
-
value:
|
1085 |
- type: precision_at_10
|
1086 |
-
value:
|
1087 |
- type: precision_at_100
|
1088 |
-
value: 0.
|
1089 |
- type: precision_at_1000
|
1090 |
-
value: 0.
|
1091 |
- type: precision_at_3
|
1092 |
-
value: 11.
|
1093 |
- type: precision_at_5
|
1094 |
-
value: 8.
|
1095 |
- type: recall_at_1
|
1096 |
-
value:
|
1097 |
- type: recall_at_10
|
1098 |
-
value:
|
1099 |
- type: recall_at_100
|
1100 |
-
value:
|
1101 |
- type: recall_at_1000
|
1102 |
-
value:
|
1103 |
- type: recall_at_3
|
1104 |
-
value: 31.
|
1105 |
- type: recall_at_5
|
1106 |
-
value:
|
1107 |
- task:
|
1108 |
type: Retrieval
|
1109 |
dataset:
|
@@ -1114,65 +1114,65 @@ model-index:
|
|
1114 |
revision: None
|
1115 |
metrics:
|
1116 |
- type: map_at_1
|
1117 |
-
value:
|
1118 |
- type: map_at_10
|
1119 |
-
value:
|
1120 |
- type: map_at_100
|
1121 |
-
value:
|
1122 |
- type: map_at_1000
|
1123 |
-
value:
|
1124 |
- type: map_at_3
|
1125 |
-
value:
|
1126 |
- type: map_at_5
|
1127 |
-
value:
|
1128 |
- type: mrr_at_1
|
1129 |
-
value:
|
1130 |
- type: mrr_at_10
|
1131 |
-
value:
|
1132 |
- type: mrr_at_100
|
1133 |
-
value:
|
1134 |
- type: mrr_at_1000
|
1135 |
-
value:
|
1136 |
- type: mrr_at_3
|
1137 |
-
value:
|
1138 |
- type: mrr_at_5
|
1139 |
-
value:
|
1140 |
- type: ndcg_at_1
|
1141 |
-
value:
|
1142 |
- type: ndcg_at_10
|
1143 |
-
value:
|
1144 |
- type: ndcg_at_100
|
1145 |
-
value:
|
1146 |
- type: ndcg_at_1000
|
1147 |
-
value:
|
1148 |
- type: ndcg_at_3
|
1149 |
-
value:
|
1150 |
- type: ndcg_at_5
|
1151 |
-
value:
|
1152 |
- type: precision_at_1
|
1153 |
-
value:
|
1154 |
- type: precision_at_10
|
1155 |
-
value:
|
1156 |
- type: precision_at_100
|
1157 |
-
value:
|
1158 |
- type: precision_at_1000
|
1159 |
-
value: 0.
|
1160 |
- type: precision_at_3
|
1161 |
-
value:
|
1162 |
- type: precision_at_5
|
1163 |
-
value:
|
1164 |
- type: recall_at_1
|
1165 |
-
value:
|
1166 |
- type: recall_at_10
|
1167 |
-
value:
|
1168 |
- type: recall_at_100
|
1169 |
-
value:
|
1170 |
- type: recall_at_1000
|
1171 |
-
value:
|
1172 |
- type: recall_at_3
|
1173 |
-
value:
|
1174 |
- type: recall_at_5
|
1175 |
-
value:
|
1176 |
- task:
|
1177 |
type: Retrieval
|
1178 |
dataset:
|
@@ -1183,65 +1183,65 @@ model-index:
|
|
1183 |
revision: None
|
1184 |
metrics:
|
1185 |
- type: map_at_1
|
1186 |
-
value: 8.
|
1187 |
- type: map_at_10
|
1188 |
-
value:
|
1189 |
- type: map_at_100
|
1190 |
-
value:
|
1191 |
- type: map_at_1000
|
1192 |
-
value:
|
1193 |
- type: map_at_3
|
1194 |
-
value: 14.
|
1195 |
- type: map_at_5
|
1196 |
-
value:
|
1197 |
- type: mrr_at_1
|
1198 |
-
value:
|
1199 |
- type: mrr_at_10
|
1200 |
-
value:
|
1201 |
- type: mrr_at_100
|
1202 |
-
value:
|
1203 |
- type: mrr_at_1000
|
1204 |
-
value:
|
1205 |
- type: mrr_at_3
|
1206 |
-
value:
|
1207 |
- type: mrr_at_5
|
1208 |
-
value:
|
1209 |
- type: ndcg_at_1
|
1210 |
-
value:
|
1211 |
- type: ndcg_at_10
|
1212 |
-
value:
|
1213 |
- type: ndcg_at_100
|
1214 |
-
value:
|
1215 |
- type: ndcg_at_1000
|
1216 |
-
value:
|
1217 |
- type: ndcg_at_3
|
1218 |
-
value:
|
1219 |
- type: ndcg_at_5
|
1220 |
-
value:
|
1221 |
- type: precision_at_1
|
1222 |
-
value:
|
1223 |
- type: precision_at_10
|
1224 |
-
value:
|
1225 |
- type: precision_at_100
|
1226 |
-
value:
|
1227 |
- type: precision_at_1000
|
1228 |
-
value: 2.
|
1229 |
- type: precision_at_3
|
1230 |
-
value:
|
1231 |
- type: precision_at_5
|
1232 |
-
value:
|
1233 |
- type: recall_at_1
|
1234 |
-
value: 8.
|
1235 |
- type: recall_at_10
|
1236 |
-
value:
|
1237 |
- type: recall_at_100
|
1238 |
-
value:
|
1239 |
- type: recall_at_1000
|
1240 |
-
value:
|
1241 |
- type: recall_at_3
|
1242 |
-
value: 15.
|
1243 |
- type: recall_at_5
|
1244 |
-
value:
|
1245 |
- task:
|
1246 |
type: Classification
|
1247 |
dataset:
|
@@ -1252,9 +1252,9 @@ model-index:
|
|
1252 |
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
|
1253 |
metrics:
|
1254 |
- type: accuracy
|
1255 |
-
value: 48.
|
1256 |
- type: f1
|
1257 |
-
value: 43.
|
1258 |
- task:
|
1259 |
type: Retrieval
|
1260 |
dataset:
|
@@ -1265,65 +1265,65 @@ model-index:
|
|
1265 |
revision: None
|
1266 |
metrics:
|
1267 |
- type: map_at_1
|
1268 |
-
value:
|
1269 |
- type: map_at_10
|
1270 |
-
value:
|
1271 |
- type: map_at_100
|
1272 |
-
value:
|
1273 |
- type: map_at_1000
|
1274 |
-
value:
|
1275 |
- type: map_at_3
|
1276 |
-
value:
|
1277 |
- type: map_at_5
|
1278 |
-
value:
|
1279 |
- type: mrr_at_1
|
1280 |
-
value:
|
1281 |
- type: mrr_at_10
|
1282 |
-
value:
|
1283 |
- type: mrr_at_100
|
1284 |
-
value:
|
1285 |
- type: mrr_at_1000
|
1286 |
-
value:
|
1287 |
- type: mrr_at_3
|
1288 |
-
value:
|
1289 |
- type: mrr_at_5
|
1290 |
-
value:
|
1291 |
- type: ndcg_at_1
|
1292 |
-
value:
|
1293 |
- type: ndcg_at_10
|
1294 |
-
value:
|
1295 |
- type: ndcg_at_100
|
1296 |
-
value:
|
1297 |
- type: ndcg_at_1000
|
1298 |
-
value:
|
1299 |
- type: ndcg_at_3
|
1300 |
-
value:
|
1301 |
- type: ndcg_at_5
|
1302 |
-
value:
|
1303 |
- type: precision_at_1
|
1304 |
-
value:
|
1305 |
- type: precision_at_10
|
1306 |
-
value:
|
1307 |
- type: precision_at_100
|
1308 |
-
value: 1.
|
1309 |
- type: precision_at_1000
|
1310 |
-
value: 0.
|
1311 |
- type: precision_at_3
|
1312 |
-
value:
|
1313 |
- type: precision_at_5
|
1314 |
-
value:
|
1315 |
- type: recall_at_1
|
1316 |
-
value:
|
1317 |
- type: recall_at_10
|
1318 |
-
value:
|
1319 |
- type: recall_at_100
|
1320 |
-
value:
|
1321 |
- type: recall_at_1000
|
1322 |
-
value:
|
1323 |
- type: recall_at_3
|
1324 |
-
value:
|
1325 |
- type: recall_at_5
|
1326 |
-
value:
|
1327 |
- task:
|
1328 |
type: Retrieval
|
1329 |
dataset:
|
@@ -1334,65 +1334,65 @@ model-index:
|
|
1334 |
revision: None
|
1335 |
metrics:
|
1336 |
- type: map_at_1
|
1337 |
-
value: 19.
|
1338 |
- type: map_at_10
|
1339 |
-
value: 31.
|
1340 |
- type: map_at_100
|
1341 |
-
value:
|
1342 |
- type: map_at_1000
|
1343 |
-
value: 33.
|
1344 |
- type: map_at_3
|
1345 |
-
value: 27.
|
1346 |
- type: map_at_5
|
1347 |
-
value: 29.
|
1348 |
- type: mrr_at_1
|
1349 |
-
value:
|
1350 |
- type: mrr_at_10
|
1351 |
-
value:
|
1352 |
- type: mrr_at_100
|
1353 |
-
value:
|
1354 |
- type: mrr_at_1000
|
1355 |
-
value:
|
1356 |
- type: mrr_at_3
|
1357 |
-
value:
|
1358 |
- type: mrr_at_5
|
1359 |
-
value:
|
1360 |
- type: ndcg_at_1
|
1361 |
-
value:
|
1362 |
- type: ndcg_at_10
|
1363 |
-
value:
|
1364 |
- type: ndcg_at_100
|
1365 |
-
value:
|
1366 |
- type: ndcg_at_1000
|
1367 |
-
value: 48.
|
1368 |
- type: ndcg_at_3
|
1369 |
-
value: 35.
|
1370 |
- type: ndcg_at_5
|
1371 |
-
value: 36.
|
1372 |
- type: precision_at_1
|
1373 |
-
value:
|
1374 |
- type: precision_at_10
|
1375 |
value: 10.494
|
1376 |
- type: precision_at_100
|
1377 |
-
value: 1.
|
1378 |
- type: precision_at_1000
|
1379 |
-
value: 0.
|
1380 |
- type: precision_at_3
|
1381 |
-
value: 23.
|
1382 |
- type: precision_at_5
|
1383 |
-
value: 17.
|
1384 |
- type: recall_at_1
|
1385 |
-
value: 19.
|
1386 |
- type: recall_at_10
|
1387 |
-
value: 45.
|
1388 |
- type: recall_at_100
|
1389 |
-
value: 68.
|
1390 |
- type: recall_at_1000
|
1391 |
-
value: 87.
|
1392 |
- type: recall_at_3
|
1393 |
-
value: 31.
|
1394 |
- type: recall_at_5
|
1395 |
-
value: 38.
|
1396 |
- task:
|
1397 |
type: Retrieval
|
1398 |
dataset:
|
@@ -1403,65 +1403,65 @@ model-index:
|
|
1403 |
revision: None
|
1404 |
metrics:
|
1405 |
- type: map_at_1
|
1406 |
-
value:
|
1407 |
- type: map_at_10
|
1408 |
-
value:
|
1409 |
- type: map_at_100
|
1410 |
-
value:
|
1411 |
- type: map_at_1000
|
1412 |
-
value:
|
1413 |
- type: map_at_3
|
1414 |
-
value:
|
1415 |
- type: map_at_5
|
1416 |
-
value:
|
1417 |
- type: mrr_at_1
|
1418 |
-
value:
|
1419 |
- type: mrr_at_10
|
1420 |
-
value:
|
1421 |
- type: mrr_at_100
|
1422 |
-
value:
|
1423 |
- type: mrr_at_1000
|
1424 |
-
value:
|
1425 |
- type: mrr_at_3
|
1426 |
-
value:
|
1427 |
- type: mrr_at_5
|
1428 |
-
value:
|
1429 |
- type: ndcg_at_1
|
1430 |
-
value:
|
1431 |
- type: ndcg_at_10
|
1432 |
-
value:
|
1433 |
- type: ndcg_at_100
|
1434 |
-
value:
|
1435 |
- type: ndcg_at_1000
|
1436 |
-
value:
|
1437 |
- type: ndcg_at_3
|
1438 |
-
value:
|
1439 |
- type: ndcg_at_5
|
1440 |
-
value:
|
1441 |
- type: precision_at_1
|
1442 |
-
value:
|
1443 |
- type: precision_at_10
|
1444 |
-
value:
|
1445 |
- type: precision_at_100
|
1446 |
-
value: 1.
|
1447 |
- type: precision_at_1000
|
1448 |
-
value: 0.
|
1449 |
- type: precision_at_3
|
1450 |
-
value:
|
1451 |
- type: precision_at_5
|
1452 |
-
value:
|
1453 |
- type: recall_at_1
|
1454 |
-
value:
|
1455 |
- type: recall_at_10
|
1456 |
-
value:
|
1457 |
- type: recall_at_100
|
1458 |
-
value:
|
1459 |
- type: recall_at_1000
|
1460 |
-
value:
|
1461 |
- type: recall_at_3
|
1462 |
-
value:
|
1463 |
- type: recall_at_5
|
1464 |
-
value:
|
1465 |
- task:
|
1466 |
type: Classification
|
1467 |
dataset:
|
@@ -1472,11 +1472,11 @@ model-index:
|
|
1472 |
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
|
1473 |
metrics:
|
1474 |
- type: accuracy
|
1475 |
-
value: 83.
|
1476 |
- type: ap
|
1477 |
-
value: 78.
|
1478 |
- type: f1
|
1479 |
-
value: 83.
|
1480 |
- task:
|
1481 |
type: Retrieval
|
1482 |
dataset:
|
@@ -1487,65 +1487,65 @@ model-index:
|
|
1487 |
revision: None
|
1488 |
metrics:
|
1489 |
- type: map_at_1
|
1490 |
-
value: 23.
|
1491 |
- type: map_at_10
|
1492 |
-
value:
|
1493 |
- type: map_at_100
|
1494 |
-
value: 37.
|
1495 |
- type: map_at_1000
|
1496 |
-
value: 37.
|
1497 |
- type: map_at_3
|
1498 |
-
value: 32.
|
1499 |
- type: map_at_5
|
1500 |
-
value: 34.
|
1501 |
- type: mrr_at_1
|
1502 |
-
value:
|
1503 |
- type: mrr_at_10
|
1504 |
-
value:
|
1505 |
- type: mrr_at_100
|
1506 |
-
value:
|
1507 |
- type: mrr_at_1000
|
1508 |
-
value:
|
1509 |
- type: mrr_at_3
|
1510 |
-
value:
|
1511 |
- type: mrr_at_5
|
1512 |
-
value: 35.
|
1513 |
- type: ndcg_at_1
|
1514 |
-
value:
|
1515 |
- type: ndcg_at_10
|
1516 |
-
value:
|
1517 |
- type: ndcg_at_100
|
1518 |
-
value: 48.
|
1519 |
- type: ndcg_at_1000
|
1520 |
-
value: 49.
|
1521 |
- type: ndcg_at_3
|
1522 |
-
value: 35.
|
1523 |
- type: ndcg_at_5
|
1524 |
-
value: 39.
|
1525 |
- type: precision_at_1
|
1526 |
-
value:
|
1527 |
- type: precision_at_10
|
1528 |
-
value: 6.
|
1529 |
- type: precision_at_100
|
1530 |
-
value: 0.
|
1531 |
- type: precision_at_1000
|
1532 |
value: 0.104
|
1533 |
- type: precision_at_3
|
1534 |
-
value:
|
1535 |
- type: precision_at_5
|
1536 |
-
value: 11.
|
1537 |
- type: recall_at_1
|
1538 |
-
value: 23.
|
1539 |
- type: recall_at_10
|
1540 |
-
value:
|
1541 |
- type: recall_at_100
|
1542 |
-
value: 89.
|
1543 |
- type: recall_at_1000
|
1544 |
-
value: 97.
|
1545 |
- type: recall_at_3
|
1546 |
-
value: 43.
|
1547 |
- type: recall_at_5
|
1548 |
-
value: 53.
|
1549 |
- task:
|
1550 |
type: Classification
|
1551 |
dataset:
|
@@ -1556,9 +1556,9 @@ model-index:
|
|
1556 |
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
|
1557 |
metrics:
|
1558 |
- type: accuracy
|
1559 |
-
value: 93.
|
1560 |
- type: f1
|
1561 |
-
value: 93.
|
1562 |
- task:
|
1563 |
type: Classification
|
1564 |
dataset:
|
@@ -1569,9 +1569,9 @@ model-index:
|
|
1569 |
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
|
1570 |
metrics:
|
1571 |
- type: accuracy
|
1572 |
-
value: 75.
|
1573 |
- type: f1
|
1574 |
-
value:
|
1575 |
- task:
|
1576 |
type: Classification
|
1577 |
dataset:
|
@@ -1582,9 +1582,9 @@ model-index:
|
|
1582 |
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
|
1583 |
metrics:
|
1584 |
- type: accuracy
|
1585 |
-
value:
|
1586 |
- type: f1
|
1587 |
-
value:
|
1588 |
- task:
|
1589 |
type: Classification
|
1590 |
dataset:
|
@@ -1595,9 +1595,9 @@ model-index:
|
|
1595 |
revision: 7d571f92784cd94a019292a1f45445077d0ef634
|
1596 |
metrics:
|
1597 |
- type: accuracy
|
1598 |
-
value:
|
1599 |
- type: f1
|
1600 |
-
value:
|
1601 |
- task:
|
1602 |
type: Clustering
|
1603 |
dataset:
|
@@ -1608,7 +1608,7 @@ model-index:
|
|
1608 |
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
|
1609 |
metrics:
|
1610 |
- type: v_measure
|
1611 |
-
value: 32.
|
1612 |
- task:
|
1613 |
type: Clustering
|
1614 |
dataset:
|
@@ -1619,7 +1619,7 @@ model-index:
|
|
1619 |
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
|
1620 |
metrics:
|
1621 |
- type: v_measure
|
1622 |
-
value: 30.
|
1623 |
- task:
|
1624 |
type: Reranking
|
1625 |
dataset:
|
@@ -1630,9 +1630,9 @@ model-index:
|
|
1630 |
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
|
1631 |
metrics:
|
1632 |
- type: map
|
1633 |
-
value:
|
1634 |
- type: mrr
|
1635 |
-
value:
|
1636 |
- task:
|
1637 |
type: Retrieval
|
1638 |
dataset:
|
@@ -1643,65 +1643,65 @@ model-index:
|
|
1643 |
revision: None
|
1644 |
metrics:
|
1645 |
- type: map_at_1
|
1646 |
-
value: 5.
|
1647 |
- type: map_at_10
|
1648 |
-
value: 13.
|
1649 |
- type: map_at_100
|
1650 |
-
value: 16.
|
1651 |
- type: map_at_1000
|
1652 |
-
value: 17.
|
1653 |
- type: map_at_3
|
1654 |
-
value: 10.
|
1655 |
- type: map_at_5
|
1656 |
-
value: 11.
|
1657 |
- type: mrr_at_1
|
1658 |
value: 45.201
|
1659 |
- type: mrr_at_10
|
1660 |
-
value: 54.
|
1661 |
- type: mrr_at_100
|
1662 |
-
value: 54.
|
1663 |
- type: mrr_at_1000
|
1664 |
-
value: 54.
|
1665 |
- type: mrr_at_3
|
1666 |
-
value:
|
1667 |
- type: mrr_at_5
|
1668 |
-
value: 53.
|
1669 |
- type: ndcg_at_1
|
1670 |
-
value: 43.
|
1671 |
- type: ndcg_at_10
|
1672 |
-
value: 35.
|
1673 |
- type: ndcg_at_100
|
1674 |
-
value: 31.
|
1675 |
- type: ndcg_at_1000
|
1676 |
-
value: 39.
|
1677 |
- type: ndcg_at_3
|
1678 |
-
value: 41.
|
1679 |
- type: ndcg_at_5
|
1680 |
-
value: 39.
|
1681 |
- type: precision_at_1
|
1682 |
-
value: 44.
|
1683 |
- type: precision_at_10
|
1684 |
-
value: 26.
|
1685 |
- type: precision_at_100
|
1686 |
-
value: 7.
|
1687 |
- type: precision_at_1000
|
1688 |
-
value: 2.
|
1689 |
- type: precision_at_3
|
1690 |
-
value: 39.
|
1691 |
- type: precision_at_5
|
1692 |
-
value: 34.
|
1693 |
- type: recall_at_1
|
1694 |
-
value: 5.
|
1695 |
- type: recall_at_10
|
1696 |
-
value:
|
1697 |
- type: recall_at_100
|
1698 |
-
value: 30.
|
1699 |
- type: recall_at_1000
|
1700 |
-
value: 61.
|
1701 |
- type: recall_at_3
|
1702 |
-
value: 11.
|
1703 |
- type: recall_at_5
|
1704 |
-
value: 13.
|
1705 |
- task:
|
1706 |
type: Retrieval
|
1707 |
dataset:
|
@@ -1712,65 +1712,65 @@ model-index:
|
|
1712 |
revision: None
|
1713 |
metrics:
|
1714 |
- type: map_at_1
|
1715 |
-
value:
|
1716 |
- type: map_at_10
|
1717 |
-
value:
|
1718 |
- type: map_at_100
|
1719 |
-
value:
|
1720 |
- type: map_at_1000
|
1721 |
-
value:
|
1722 |
- type: map_at_3
|
1723 |
-
value:
|
1724 |
- type: map_at_5
|
1725 |
-
value:
|
1726 |
- type: mrr_at_1
|
1727 |
-
value:
|
1728 |
- type: mrr_at_10
|
1729 |
-
value:
|
1730 |
- type: mrr_at_100
|
1731 |
-
value:
|
1732 |
- type: mrr_at_1000
|
1733 |
-
value:
|
1734 |
- type: mrr_at_3
|
1735 |
-
value:
|
1736 |
- type: mrr_at_5
|
1737 |
-
value:
|
1738 |
- type: ndcg_at_1
|
1739 |
-
value:
|
1740 |
- type: ndcg_at_10
|
1741 |
-
value:
|
1742 |
- type: ndcg_at_100
|
1743 |
-
value:
|
1744 |
- type: ndcg_at_1000
|
1745 |
-
value:
|
1746 |
- type: ndcg_at_3
|
1747 |
-
value:
|
1748 |
- type: ndcg_at_5
|
1749 |
-
value:
|
1750 |
- type: precision_at_1
|
1751 |
-
value:
|
1752 |
- type: precision_at_10
|
1753 |
-
value: 9.
|
1754 |
- type: precision_at_100
|
1755 |
-
value: 1.
|
1756 |
- type: precision_at_1000
|
1757 |
value: 0.12
|
1758 |
- type: precision_at_3
|
1759 |
-
value:
|
1760 |
- type: precision_at_5
|
1761 |
-
value: 16.
|
1762 |
- type: recall_at_1
|
1763 |
-
value:
|
1764 |
- type: recall_at_10
|
1765 |
-
value:
|
1766 |
- type: recall_at_100
|
1767 |
-
value: 95.
|
1768 |
- type: recall_at_1000
|
1769 |
-
value:
|
1770 |
- type: recall_at_3
|
1771 |
-
value:
|
1772 |
- type: recall_at_5
|
1773 |
-
value:
|
1774 |
- task:
|
1775 |
type: Retrieval
|
1776 |
dataset:
|
@@ -1781,65 +1781,65 @@ model-index:
|
|
1781 |
revision: None
|
1782 |
metrics:
|
1783 |
- type: map_at_1
|
1784 |
-
value: 70.
|
1785 |
- type: map_at_10
|
1786 |
-
value:
|
1787 |
- type: map_at_100
|
1788 |
-
value:
|
1789 |
- type: map_at_1000
|
1790 |
-
value:
|
1791 |
- type: map_at_3
|
1792 |
-
value:
|
1793 |
- type: map_at_5
|
1794 |
-
value:
|
1795 |
- type: mrr_at_1
|
1796 |
-
value:
|
1797 |
- type: mrr_at_10
|
1798 |
-
value: 87.
|
1799 |
- type: mrr_at_100
|
1800 |
-
value: 87.
|
1801 |
- type: mrr_at_1000
|
1802 |
-
value: 87.
|
1803 |
- type: mrr_at_3
|
1804 |
-
value: 86.
|
1805 |
- type: mrr_at_5
|
1806 |
-
value:
|
1807 |
- type: ndcg_at_1
|
1808 |
-
value:
|
1809 |
- type: ndcg_at_10
|
1810 |
-
value:
|
1811 |
- type: ndcg_at_100
|
1812 |
-
value: 89.
|
1813 |
- type: ndcg_at_1000
|
1814 |
-
value: 89.
|
1815 |
- type: ndcg_at_3
|
1816 |
-
value:
|
1817 |
- type: ndcg_at_5
|
1818 |
-
value:
|
1819 |
- type: precision_at_1
|
1820 |
-
value:
|
1821 |
- type: precision_at_10
|
1822 |
-
value: 13.
|
1823 |
- type: precision_at_100
|
1824 |
-
value: 1.
|
1825 |
- type: precision_at_1000
|
1826 |
value: 0.156
|
1827 |
- type: precision_at_3
|
1828 |
-
value: 37.
|
1829 |
- type: precision_at_5
|
1830 |
-
value: 24.
|
1831 |
- type: recall_at_1
|
1832 |
-
value: 70.
|
1833 |
- type: recall_at_10
|
1834 |
-
value: 95.
|
1835 |
- type: recall_at_100
|
1836 |
-
value: 99.
|
1837 |
- type: recall_at_1000
|
1838 |
-
value: 99.
|
1839 |
- type: recall_at_3
|
1840 |
-
value:
|
1841 |
- type: recall_at_5
|
1842 |
-
value: 91.
|
1843 |
- task:
|
1844 |
type: Clustering
|
1845 |
dataset:
|
@@ -1850,7 +1850,7 @@ model-index:
|
|
1850 |
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
|
1851 |
metrics:
|
1852 |
- type: v_measure
|
1853 |
-
value: 56.
|
1854 |
- task:
|
1855 |
type: Clustering
|
1856 |
dataset:
|
@@ -1861,7 +1861,7 @@ model-index:
|
|
1861 |
revision: 282350215ef01743dc01b456c7f5241fa8937f16
|
1862 |
metrics:
|
1863 |
- type: v_measure
|
1864 |
-
value:
|
1865 |
- task:
|
1866 |
type: Retrieval
|
1867 |
dataset:
|
@@ -1872,65 +1872,65 @@ model-index:
|
|
1872 |
revision: None
|
1873 |
metrics:
|
1874 |
- type: map_at_1
|
1875 |
-
value: 4.
|
1876 |
- type: map_at_10
|
1877 |
-
value:
|
1878 |
- type: map_at_100
|
1879 |
-
value: 12.
|
1880 |
- type: map_at_1000
|
1881 |
-
value:
|
1882 |
- type: map_at_3
|
1883 |
-
value:
|
1884 |
- type: map_at_5
|
1885 |
-
value: 9.
|
1886 |
- type: mrr_at_1
|
1887 |
-
value:
|
1888 |
- type: mrr_at_10
|
1889 |
-
value:
|
1890 |
- type: mrr_at_100
|
1891 |
-
value:
|
1892 |
- type: mrr_at_1000
|
1893 |
-
value:
|
1894 |
- type: mrr_at_3
|
1895 |
-
value:
|
1896 |
- type: mrr_at_5
|
1897 |
-
value:
|
1898 |
- type: ndcg_at_1
|
1899 |
-
value:
|
1900 |
- type: ndcg_at_10
|
1901 |
-
value: 18.
|
1902 |
- type: ndcg_at_100
|
1903 |
-
value: 25.
|
1904 |
- type: ndcg_at_1000
|
1905 |
-
value: 30.
|
1906 |
- type: ndcg_at_3
|
1907 |
-
value: 17.
|
1908 |
- type: ndcg_at_5
|
1909 |
-
value: 15.
|
1910 |
- type: precision_at_1
|
1911 |
-
value:
|
1912 |
- type: precision_at_10
|
1913 |
-
value: 9.
|
1914 |
- type: precision_at_100
|
1915 |
-
value: 1.
|
1916 |
- type: precision_at_1000
|
1917 |
-
value: 0.
|
1918 |
- type: precision_at_3
|
1919 |
-
value: 16.
|
1920 |
- type: precision_at_5
|
1921 |
-
value: 13.
|
1922 |
- type: recall_at_1
|
1923 |
-
value: 4.
|
1924 |
- type: recall_at_10
|
1925 |
-
value: 19.
|
1926 |
- type: recall_at_100
|
1927 |
-
value:
|
1928 |
- type: recall_at_1000
|
1929 |
-
value:
|
1930 |
- type: recall_at_3
|
1931 |
-
value: 10.
|
1932 |
- type: recall_at_5
|
1933 |
-
value: 13.
|
1934 |
- task:
|
1935 |
type: STS
|
1936 |
dataset:
|
@@ -1941,17 +1941,17 @@ model-index:
|
|
1941 |
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
|
1942 |
metrics:
|
1943 |
- type: cos_sim_pearson
|
1944 |
-
value:
|
1945 |
- type: cos_sim_spearman
|
1946 |
-
value:
|
1947 |
- type: euclidean_pearson
|
1948 |
-
value:
|
1949 |
- type: euclidean_spearman
|
1950 |
-
value:
|
1951 |
- type: manhattan_pearson
|
1952 |
-
value:
|
1953 |
- type: manhattan_spearman
|
1954 |
-
value:
|
1955 |
- task:
|
1956 |
type: STS
|
1957 |
dataset:
|
@@ -1962,17 +1962,17 @@ model-index:
|
|
1962 |
revision: a0d554a64d88156834ff5ae9920b964011b16384
|
1963 |
metrics:
|
1964 |
- type: cos_sim_pearson
|
1965 |
-
value:
|
1966 |
- type: cos_sim_spearman
|
1967 |
-
value:
|
1968 |
- type: euclidean_pearson
|
1969 |
-
value:
|
1970 |
- type: euclidean_spearman
|
1971 |
-
value:
|
1972 |
- type: manhattan_pearson
|
1973 |
-
value:
|
1974 |
- type: manhattan_spearman
|
1975 |
-
value: 78.
|
1976 |
- task:
|
1977 |
type: STS
|
1978 |
dataset:
|
@@ -1983,17 +1983,17 @@ model-index:
|
|
1983 |
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
|
1984 |
metrics:
|
1985 |
- type: cos_sim_pearson
|
1986 |
-
value:
|
1987 |
- type: cos_sim_spearman
|
1988 |
-
value:
|
1989 |
- type: euclidean_pearson
|
1990 |
-
value:
|
1991 |
- type: euclidean_spearman
|
1992 |
-
value:
|
1993 |
- type: manhattan_pearson
|
1994 |
-
value:
|
1995 |
- type: manhattan_spearman
|
1996 |
-
value:
|
1997 |
- task:
|
1998 |
type: STS
|
1999 |
dataset:
|
@@ -2004,17 +2004,17 @@ model-index:
|
|
2004 |
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
|
2005 |
metrics:
|
2006 |
- type: cos_sim_pearson
|
2007 |
-
value:
|
2008 |
- type: cos_sim_spearman
|
2009 |
-
value:
|
2010 |
- type: euclidean_pearson
|
2011 |
-
value:
|
2012 |
- type: euclidean_spearman
|
2013 |
-
value:
|
2014 |
- type: manhattan_pearson
|
2015 |
-
value:
|
2016 |
- type: manhattan_spearman
|
2017 |
-
value:
|
2018 |
- task:
|
2019 |
type: STS
|
2020 |
dataset:
|
@@ -2025,17 +2025,17 @@ model-index:
|
|
2025 |
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
|
2026 |
metrics:
|
2027 |
- type: cos_sim_pearson
|
2028 |
-
value:
|
2029 |
- type: cos_sim_spearman
|
2030 |
-
value:
|
2031 |
- type: euclidean_pearson
|
2032 |
-
value:
|
2033 |
- type: euclidean_spearman
|
2034 |
-
value:
|
2035 |
- type: manhattan_pearson
|
2036 |
-
value:
|
2037 |
- type: manhattan_spearman
|
2038 |
-
value:
|
2039 |
- task:
|
2040 |
type: STS
|
2041 |
dataset:
|
@@ -2046,17 +2046,17 @@ model-index:
|
|
2046 |
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
|
2047 |
metrics:
|
2048 |
- type: cos_sim_pearson
|
2049 |
-
value: 83.
|
2050 |
- type: cos_sim_spearman
|
2051 |
-
value:
|
2052 |
- type: euclidean_pearson
|
2053 |
-
value:
|
2054 |
- type: euclidean_spearman
|
2055 |
-
value:
|
2056 |
- type: manhattan_pearson
|
2057 |
-
value:
|
2058 |
- type: manhattan_spearman
|
2059 |
-
value:
|
2060 |
- task:
|
2061 |
type: STS
|
2062 |
dataset:
|
@@ -2067,17 +2067,17 @@ model-index:
|
|
2067 |
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
|
2068 |
metrics:
|
2069 |
- type: cos_sim_pearson
|
2070 |
-
value:
|
2071 |
- type: cos_sim_spearman
|
2072 |
-
value:
|
2073 |
- type: euclidean_pearson
|
2074 |
-
value:
|
2075 |
- type: euclidean_spearman
|
2076 |
-
value:
|
2077 |
- type: manhattan_pearson
|
2078 |
-
value:
|
2079 |
- type: manhattan_spearman
|
2080 |
-
value:
|
2081 |
- task:
|
2082 |
type: STS
|
2083 |
dataset:
|
@@ -2088,17 +2088,17 @@ model-index:
|
|
2088 |
revision: eea2b4fe26a775864c896887d910b76a8098ad3f
|
2089 |
metrics:
|
2090 |
- type: cos_sim_pearson
|
2091 |
-
value:
|
2092 |
- type: cos_sim_spearman
|
2093 |
-
value:
|
2094 |
- type: euclidean_pearson
|
2095 |
-
value: 66.
|
2096 |
- type: euclidean_spearman
|
2097 |
-
value:
|
2098 |
- type: manhattan_pearson
|
2099 |
-
value: 66.
|
2100 |
- type: manhattan_spearman
|
2101 |
-
value:
|
2102 |
- task:
|
2103 |
type: STS
|
2104 |
dataset:
|
@@ -2109,17 +2109,17 @@ model-index:
|
|
2109 |
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
|
2110 |
metrics:
|
2111 |
- type: cos_sim_pearson
|
2112 |
-
value:
|
2113 |
- type: cos_sim_spearman
|
2114 |
-
value:
|
2115 |
- type: euclidean_pearson
|
2116 |
-
value:
|
2117 |
- type: euclidean_spearman
|
2118 |
-
value:
|
2119 |
- type: manhattan_pearson
|
2120 |
-
value:
|
2121 |
- type: manhattan_spearman
|
2122 |
-
value:
|
2123 |
- task:
|
2124 |
type: Reranking
|
2125 |
dataset:
|
@@ -2130,9 +2130,9 @@ model-index:
|
|
2130 |
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
|
2131 |
metrics:
|
2132 |
- type: map
|
2133 |
-
value:
|
2134 |
- type: mrr
|
2135 |
-
value:
|
2136 |
- task:
|
2137 |
type: Retrieval
|
2138 |
dataset:
|
@@ -2143,65 +2143,65 @@ model-index:
|
|
2143 |
revision: None
|
2144 |
metrics:
|
2145 |
- type: map_at_1
|
2146 |
-
value:
|
2147 |
- type: map_at_10
|
2148 |
-
value: 67.
|
2149 |
- type: map_at_100
|
2150 |
-
value: 67.
|
2151 |
- type: map_at_1000
|
2152 |
-
value: 67.
|
2153 |
- type: map_at_3
|
2154 |
-
value: 64.
|
2155 |
- type: map_at_5
|
2156 |
-
value:
|
2157 |
- type: mrr_at_1
|
2158 |
-
value:
|
2159 |
- type: mrr_at_10
|
2160 |
-
value: 68.
|
2161 |
- type: mrr_at_100
|
2162 |
-
value: 68.
|
2163 |
- type: mrr_at_1000
|
2164 |
-
value: 68.
|
2165 |
- type: mrr_at_3
|
2166 |
-
value: 66.
|
2167 |
- type: mrr_at_5
|
2168 |
-
value: 67.
|
2169 |
- type: ndcg_at_1
|
2170 |
-
value:
|
2171 |
- type: ndcg_at_10
|
2172 |
-
value: 71.
|
2173 |
- type: ndcg_at_100
|
2174 |
-
value: 73.
|
2175 |
- type: ndcg_at_1000
|
2176 |
-
value: 74.
|
2177 |
- type: ndcg_at_3
|
2178 |
-
value: 67.
|
2179 |
- type: ndcg_at_5
|
2180 |
-
value:
|
2181 |
- type: precision_at_1
|
2182 |
-
value:
|
2183 |
- type: precision_at_10
|
2184 |
-
value: 9.
|
2185 |
- type: precision_at_100
|
2186 |
-
value: 1.
|
2187 |
- type: precision_at_1000
|
2188 |
value: 0.11199999999999999
|
2189 |
- type: precision_at_3
|
2190 |
-
value: 26.
|
2191 |
- type: precision_at_5
|
2192 |
-
value:
|
2193 |
- type: recall_at_1
|
2194 |
-
value:
|
2195 |
- type: recall_at_10
|
2196 |
-
value: 83.
|
2197 |
- type: recall_at_100
|
2198 |
-
value:
|
2199 |
- type: recall_at_1000
|
2200 |
-
value: 99.
|
2201 |
- type: recall_at_3
|
2202 |
-
value:
|
2203 |
- type: recall_at_5
|
2204 |
-
value:
|
2205 |
- task:
|
2206 |
type: PairClassification
|
2207 |
dataset:
|
@@ -2212,51 +2212,51 @@ model-index:
|
|
2212 |
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
|
2213 |
metrics:
|
2214 |
- type: cos_sim_accuracy
|
2215 |
-
value: 99.
|
2216 |
- type: cos_sim_ap
|
2217 |
-
value:
|
2218 |
- type: cos_sim_f1
|
2219 |
-
value:
|
2220 |
- type: cos_sim_precision
|
2221 |
-
value:
|
2222 |
- type: cos_sim_recall
|
2223 |
-
value: 88.
|
2224 |
- type: dot_accuracy
|
2225 |
-
value: 99.
|
2226 |
- type: dot_ap
|
2227 |
-
value:
|
2228 |
- type: dot_f1
|
2229 |
-
value:
|
2230 |
- type: dot_precision
|
2231 |
-
value:
|
2232 |
- type: dot_recall
|
2233 |
-
value: 88.
|
2234 |
- type: euclidean_accuracy
|
2235 |
-
value: 99.
|
2236 |
- type: euclidean_ap
|
2237 |
-
value:
|
2238 |
- type: euclidean_f1
|
2239 |
-
value:
|
2240 |
- type: euclidean_precision
|
2241 |
-
value:
|
2242 |
- type: euclidean_recall
|
2243 |
-
value: 88.
|
2244 |
- type: manhattan_accuracy
|
2245 |
-
value: 99.
|
2246 |
- type: manhattan_ap
|
2247 |
-
value:
|
2248 |
- type: manhattan_f1
|
2249 |
-
value:
|
2250 |
- type: manhattan_precision
|
2251 |
-
value:
|
2252 |
- type: manhattan_recall
|
2253 |
-
value:
|
2254 |
- type: max_accuracy
|
2255 |
-
value: 99.
|
2256 |
- type: max_ap
|
2257 |
-
value:
|
2258 |
- type: max_f1
|
2259 |
-
value:
|
2260 |
- task:
|
2261 |
type: Clustering
|
2262 |
dataset:
|
@@ -2267,7 +2267,7 @@ model-index:
|
|
2267 |
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
|
2268 |
metrics:
|
2269 |
- type: v_measure
|
2270 |
-
value: 63.
|
2271 |
- task:
|
2272 |
type: Clustering
|
2273 |
dataset:
|
@@ -2278,7 +2278,7 @@ model-index:
|
|
2278 |
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
|
2279 |
metrics:
|
2280 |
- type: v_measure
|
2281 |
-
value: 33.
|
2282 |
- task:
|
2283 |
type: Reranking
|
2284 |
dataset:
|
@@ -2289,9 +2289,9 @@ model-index:
|
|
2289 |
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
|
2290 |
metrics:
|
2291 |
- type: map
|
2292 |
-
value:
|
2293 |
- type: mrr
|
2294 |
-
value:
|
2295 |
- task:
|
2296 |
type: Summarization
|
2297 |
dataset:
|
@@ -2302,13 +2302,13 @@ model-index:
|
|
2302 |
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
|
2303 |
metrics:
|
2304 |
- type: cos_sim_pearson
|
2305 |
-
value: 30.
|
2306 |
- type: cos_sim_spearman
|
2307 |
-
value:
|
2308 |
- type: dot_pearson
|
2309 |
-
value: 30.
|
2310 |
- type: dot_spearman
|
2311 |
-
value:
|
2312 |
- task:
|
2313 |
type: Retrieval
|
2314 |
dataset:
|
@@ -2319,65 +2319,65 @@ model-index:
|
|
2319 |
revision: None
|
2320 |
metrics:
|
2321 |
- type: map_at_1
|
2322 |
-
value: 0.
|
2323 |
- type: map_at_10
|
2324 |
-
value: 2.
|
2325 |
- type: map_at_100
|
2326 |
-
value:
|
2327 |
- type: map_at_1000
|
2328 |
-
value:
|
2329 |
- type: map_at_3
|
2330 |
-
value: 0.
|
2331 |
- type: map_at_5
|
2332 |
-
value: 1.
|
2333 |
- type: mrr_at_1
|
2334 |
-
value:
|
2335 |
- type: mrr_at_10
|
2336 |
-
value:
|
2337 |
- type: mrr_at_100
|
2338 |
-
value:
|
2339 |
- type: mrr_at_1000
|
2340 |
-
value:
|
2341 |
- type: mrr_at_3
|
2342 |
-
value:
|
2343 |
- type: mrr_at_5
|
2344 |
-
value:
|
2345 |
- type: ndcg_at_1
|
2346 |
-
value:
|
2347 |
- type: ndcg_at_10
|
2348 |
-
value:
|
2349 |
- type: ndcg_at_100
|
2350 |
-
value:
|
2351 |
- type: ndcg_at_1000
|
2352 |
-
value:
|
2353 |
- type: ndcg_at_3
|
2354 |
-
value:
|
2355 |
- type: ndcg_at_5
|
2356 |
-
value:
|
2357 |
- type: precision_at_1
|
2358 |
-
value:
|
2359 |
- type: precision_at_10
|
2360 |
-
value:
|
2361 |
- type: precision_at_100
|
2362 |
-
value:
|
2363 |
- type: precision_at_1000
|
2364 |
-
value:
|
2365 |
- type: precision_at_3
|
2366 |
-
value:
|
2367 |
- type: precision_at_5
|
2368 |
-
value:
|
2369 |
- type: recall_at_1
|
2370 |
-
value: 0.
|
2371 |
- type: recall_at_10
|
2372 |
-
value: 2.
|
2373 |
- type: recall_at_100
|
2374 |
-
value:
|
2375 |
- type: recall_at_1000
|
2376 |
-
value:
|
2377 |
- type: recall_at_3
|
2378 |
-
value: 0.
|
2379 |
- type: recall_at_5
|
2380 |
-
value: 1.
|
2381 |
- task:
|
2382 |
type: Retrieval
|
2383 |
dataset:
|
@@ -2388,65 +2388,65 @@ model-index:
|
|
2388 |
revision: None
|
2389 |
metrics:
|
2390 |
- type: map_at_1
|
2391 |
-
value: 2.
|
2392 |
- type: map_at_10
|
2393 |
-
value: 11.
|
2394 |
- type: map_at_100
|
2395 |
-
value:
|
2396 |
- type: map_at_1000
|
2397 |
-
value: 19.
|
2398 |
- type: map_at_3
|
2399 |
-
value:
|
2400 |
- type: map_at_5
|
2401 |
-
value: 8.
|
2402 |
- type: mrr_at_1
|
2403 |
value: 28.571
|
2404 |
- type: mrr_at_10
|
2405 |
-
value:
|
2406 |
- type: mrr_at_100
|
2407 |
-
value:
|
2408 |
- type: mrr_at_1000
|
2409 |
-
value:
|
2410 |
- type: mrr_at_3
|
2411 |
-
value:
|
2412 |
- type: mrr_at_5
|
2413 |
-
value: 46.
|
2414 |
- type: ndcg_at_1
|
2415 |
value: 25.509999999999998
|
2416 |
- type: ndcg_at_10
|
2417 |
-
value:
|
2418 |
- type: ndcg_at_100
|
2419 |
-
value: 39.
|
2420 |
- type: ndcg_at_1000
|
2421 |
-
value: 50.
|
2422 |
- type: ndcg_at_3
|
2423 |
-
value:
|
2424 |
- type: ndcg_at_5
|
2425 |
-
value:
|
2426 |
- type: precision_at_1
|
2427 |
value: 28.571
|
2428 |
- type: precision_at_10
|
2429 |
-
value:
|
2430 |
- type: precision_at_100
|
2431 |
-
value: 8.
|
2432 |
- type: precision_at_1000
|
2433 |
-
value: 1.
|
2434 |
- type: precision_at_3
|
2435 |
-
value:
|
2436 |
- type: precision_at_5
|
2437 |
-
value: 31.
|
2438 |
- type: recall_at_1
|
2439 |
-
value: 2.
|
2440 |
- type: recall_at_10
|
2441 |
-
value:
|
2442 |
- type: recall_at_100
|
2443 |
-
value:
|
2444 |
- type: recall_at_1000
|
2445 |
-
value: 83.
|
2446 |
- type: recall_at_3
|
2447 |
-
value:
|
2448 |
- type: recall_at_5
|
2449 |
-
value: 11.
|
2450 |
- task:
|
2451 |
type: Classification
|
2452 |
dataset:
|
@@ -2457,11 +2457,11 @@ model-index:
|
|
2457 |
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
|
2458 |
metrics:
|
2459 |
- type: accuracy
|
2460 |
-
value:
|
2461 |
- type: ap
|
2462 |
-
value: 14.
|
2463 |
- type: f1
|
2464 |
-
value:
|
2465 |
- task:
|
2466 |
type: Classification
|
2467 |
dataset:
|
@@ -2472,9 +2472,9 @@ model-index:
|
|
2472 |
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
|
2473 |
metrics:
|
2474 |
- type: accuracy
|
2475 |
-
value:
|
2476 |
- type: f1
|
2477 |
-
value:
|
2478 |
- task:
|
2479 |
type: Clustering
|
2480 |
dataset:
|
@@ -2485,7 +2485,7 @@ model-index:
|
|
2485 |
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
|
2486 |
metrics:
|
2487 |
- type: v_measure
|
2488 |
-
value:
|
2489 |
- task:
|
2490 |
type: PairClassification
|
2491 |
dataset:
|
@@ -2496,51 +2496,51 @@ model-index:
|
|
2496 |
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
|
2497 |
metrics:
|
2498 |
- type: cos_sim_accuracy
|
2499 |
-
value: 85.
|
2500 |
- type: cos_sim_ap
|
2501 |
-
value: 72.
|
2502 |
- type: cos_sim_f1
|
2503 |
-
value: 66.
|
2504 |
- type: cos_sim_precision
|
2505 |
-
value:
|
2506 |
- type: cos_sim_recall
|
2507 |
-
value:
|
2508 |
- type: dot_accuracy
|
2509 |
-
value: 85.
|
2510 |
- type: dot_ap
|
2511 |
-
value: 72.
|
2512 |
- type: dot_f1
|
2513 |
-
value: 66.
|
2514 |
- type: dot_precision
|
2515 |
-
value:
|
2516 |
- type: dot_recall
|
2517 |
-
value:
|
2518 |
- type: euclidean_accuracy
|
2519 |
-
value: 85.
|
2520 |
- type: euclidean_ap
|
2521 |
-
value: 72.
|
2522 |
- type: euclidean_f1
|
2523 |
-
value: 66.
|
2524 |
- type: euclidean_precision
|
2525 |
-
value:
|
2526 |
- type: euclidean_recall
|
2527 |
-
value:
|
2528 |
- type: manhattan_accuracy
|
2529 |
-
value: 85.
|
2530 |
- type: manhattan_ap
|
2531 |
-
value: 72.
|
2532 |
- type: manhattan_f1
|
2533 |
-
value: 66.
|
2534 |
- type: manhattan_precision
|
2535 |
-
value: 60.
|
2536 |
- type: manhattan_recall
|
2537 |
-
value:
|
2538 |
- type: max_accuracy
|
2539 |
-
value: 85.
|
2540 |
- type: max_ap
|
2541 |
-
value: 72.
|
2542 |
- type: max_f1
|
2543 |
-
value: 66.
|
2544 |
- task:
|
2545 |
type: PairClassification
|
2546 |
dataset:
|
@@ -2551,49 +2551,49 @@ model-index:
|
|
2551 |
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
|
2552 |
metrics:
|
2553 |
- type: cos_sim_accuracy
|
2554 |
-
value: 89.
|
2555 |
- type: cos_sim_ap
|
2556 |
-
value: 86.
|
2557 |
- type: cos_sim_f1
|
2558 |
-
value: 78.
|
2559 |
- type: cos_sim_precision
|
2560 |
-
value:
|
2561 |
- type: cos_sim_recall
|
2562 |
-
value:
|
2563 |
- type: dot_accuracy
|
2564 |
-
value: 89.
|
2565 |
- type: dot_ap
|
2566 |
-
value: 86.
|
2567 |
- type: dot_f1
|
2568 |
-
value: 78.
|
2569 |
- type: dot_precision
|
2570 |
-
value:
|
2571 |
- type: dot_recall
|
2572 |
-
value:
|
2573 |
- type: euclidean_accuracy
|
2574 |
-
value: 89.
|
2575 |
- type: euclidean_ap
|
2576 |
-
value: 86.
|
2577 |
- type: euclidean_f1
|
2578 |
-
value: 78.
|
2579 |
- type: euclidean_precision
|
2580 |
-
value:
|
2581 |
- type: euclidean_recall
|
2582 |
-
value:
|
2583 |
- type: manhattan_accuracy
|
2584 |
-
value: 89.
|
2585 |
- type: manhattan_ap
|
2586 |
-
value: 86.
|
2587 |
- type: manhattan_f1
|
2588 |
-
value: 78.
|
2589 |
- type: manhattan_precision
|
2590 |
-
value: 77.
|
2591 |
- type: manhattan_recall
|
2592 |
-
value:
|
2593 |
- type: max_accuracy
|
2594 |
-
value: 89.
|
2595 |
- type: max_ap
|
2596 |
-
value: 86.
|
2597 |
- type: max_f1
|
2598 |
-
value: 78.
|
2599 |
---
|
|
|
14 |
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
|
15 |
metrics:
|
16 |
- type: accuracy
|
17 |
+
value: 78.67164179104476
|
18 |
- type: ap
|
19 |
+
value: 42.7379383648841
|
20 |
- type: f1
|
21 |
+
value: 72.79997373883408
|
22 |
- task:
|
23 |
type: Classification
|
24 |
dataset:
|
|
|
29 |
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
|
30 |
metrics:
|
31 |
- type: accuracy
|
32 |
+
value: 90.413775
|
33 |
- type: ap
|
34 |
+
value: 87.08812293673202
|
35 |
- type: f1
|
36 |
+
value: 90.39246586225426
|
37 |
- task:
|
38 |
type: Classification
|
39 |
dataset:
|
|
|
44 |
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
|
45 |
metrics:
|
46 |
- type: accuracy
|
47 |
+
value: 47.80799999999999
|
48 |
- type: f1
|
49 |
+
value: 47.25679462673503
|
50 |
- task:
|
51 |
type: Retrieval
|
52 |
dataset:
|
|
|
57 |
revision: None
|
58 |
metrics:
|
59 |
- type: map_at_1
|
60 |
+
value: 30.37
|
61 |
- type: map_at_10
|
62 |
+
value: 45.748
|
63 |
- type: map_at_100
|
64 |
+
value: 46.617
|
65 |
- type: map_at_1000
|
66 |
+
value: 46.622
|
67 |
- type: map_at_3
|
68 |
+
value: 40.564
|
69 |
- type: map_at_5
|
70 |
+
value: 43.69
|
71 |
- type: mrr_at_1
|
72 |
+
value: 30.868000000000002
|
73 |
- type: mrr_at_10
|
74 |
+
value: 45.905
|
75 |
- type: mrr_at_100
|
76 |
+
value: 46.787
|
77 |
- type: mrr_at_1000
|
78 |
+
value: 46.792
|
79 |
- type: mrr_at_3
|
80 |
+
value: 40.717999999999996
|
81 |
- type: mrr_at_5
|
82 |
+
value: 43.851
|
83 |
- type: ndcg_at_1
|
84 |
+
value: 30.37
|
85 |
- type: ndcg_at_10
|
86 |
+
value: 54.662
|
87 |
- type: ndcg_at_100
|
88 |
+
value: 58.23700000000001
|
89 |
- type: ndcg_at_1000
|
90 |
+
value: 58.373
|
91 |
- type: ndcg_at_3
|
92 |
+
value: 44.069
|
93 |
- type: ndcg_at_5
|
94 |
+
value: 49.728
|
95 |
- type: precision_at_1
|
96 |
+
value: 30.37
|
97 |
- type: precision_at_10
|
98 |
+
value: 8.321000000000002
|
99 |
- type: precision_at_100
|
100 |
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value: 0.985
|
101 |
- type: precision_at_1000
|
102 |
value: 0.1
|
103 |
- type: precision_at_3
|
104 |
+
value: 18.089
|
105 |
- type: precision_at_5
|
106 |
+
value: 13.613
|
107 |
- type: recall_at_1
|
108 |
+
value: 30.37
|
109 |
- type: recall_at_10
|
110 |
+
value: 83.21499999999999
|
111 |
- type: recall_at_100
|
112 |
+
value: 98.506
|
113 |
- type: recall_at_1000
|
114 |
value: 99.57300000000001
|
115 |
- type: recall_at_3
|
116 |
+
value: 54.266999999999996
|
117 |
- type: recall_at_5
|
118 |
+
value: 68.065
|
119 |
- task:
|
120 |
type: Clustering
|
121 |
dataset:
|
|
|
126 |
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
|
127 |
metrics:
|
128 |
- type: v_measure
|
129 |
+
value: 45.85329429748079
|
130 |
- task:
|
131 |
type: Clustering
|
132 |
dataset:
|
|
|
137 |
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
|
138 |
metrics:
|
139 |
- type: v_measure
|
140 |
+
value: 36.12666783330692
|
141 |
- task:
|
142 |
type: Reranking
|
143 |
dataset:
|
|
|
148 |
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
|
149 |
metrics:
|
150 |
- type: map
|
151 |
+
value: 57.58783867794241
|
152 |
- type: mrr
|
153 |
+
value: 71.84078617596622
|
154 |
- task:
|
155 |
type: STS
|
156 |
dataset:
|
|
|
161 |
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
|
162 |
metrics:
|
163 |
- type: cos_sim_pearson
|
164 |
+
value: 87.92453139507079
|
165 |
- type: cos_sim_spearman
|
166 |
+
value: 85.37122234964886
|
167 |
- type: euclidean_pearson
|
168 |
+
value: 86.19345621799168
|
169 |
- type: euclidean_spearman
|
170 |
+
value: 85.37122234964886
|
171 |
- type: manhattan_pearson
|
172 |
+
value: 86.4685290616604
|
173 |
- type: manhattan_spearman
|
174 |
+
value: 85.91400580167537
|
175 |
- task:
|
176 |
type: Classification
|
177 |
dataset:
|
|
|
182 |
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
|
183 |
metrics:
|
184 |
- type: accuracy
|
185 |
+
value: 83.81818181818181
|
186 |
- type: f1
|
187 |
+
value: 83.76155217378863
|
188 |
- task:
|
189 |
type: Clustering
|
190 |
dataset:
|
|
|
195 |
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
|
196 |
metrics:
|
197 |
- type: v_measure
|
198 |
+
value: 38.46362764203256
|
199 |
- task:
|
200 |
type: Clustering
|
201 |
dataset:
|
|
|
206 |
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
|
207 |
metrics:
|
208 |
- type: v_measure
|
209 |
+
value: 33.13807021168658
|
210 |
- task:
|
211 |
type: Retrieval
|
212 |
dataset:
|
|
|
217 |
revision: None
|
218 |
metrics:
|
219 |
- type: map_at_1
|
220 |
+
value: 29.725
|
221 |
- type: map_at_10
|
222 |
+
value: 39.654
|
223 |
- type: map_at_100
|
224 |
+
value: 41.022
|
225 |
- type: map_at_1000
|
226 |
+
value: 41.144999999999996
|
227 |
- type: map_at_3
|
228 |
+
value: 36.819
|
229 |
- type: map_at_5
|
230 |
+
value: 38.376
|
231 |
- type: mrr_at_1
|
232 |
+
value: 36.195
|
233 |
- type: mrr_at_10
|
234 |
+
value: 45.171
|
235 |
- type: mrr_at_100
|
236 |
+
value: 45.987
|
237 |
- type: mrr_at_1000
|
238 |
+
value: 46.033
|
239 |
- type: mrr_at_3
|
240 |
+
value: 43.038
|
241 |
- type: mrr_at_5
|
242 |
+
value: 44.196000000000005
|
243 |
- type: ndcg_at_1
|
244 |
+
value: 36.195
|
245 |
- type: ndcg_at_10
|
246 |
+
value: 45.194
|
247 |
- type: ndcg_at_100
|
248 |
+
value: 50.516000000000005
|
249 |
- type: ndcg_at_1000
|
250 |
+
value: 52.739000000000004
|
251 |
- type: ndcg_at_3
|
252 |
+
value: 41.142
|
253 |
- type: ndcg_at_5
|
254 |
+
value: 42.973
|
255 |
- type: precision_at_1
|
256 |
+
value: 36.195
|
257 |
- type: precision_at_10
|
258 |
+
value: 8.312
|
259 |
- type: precision_at_100
|
260 |
+
value: 1.346
|
261 |
- type: precision_at_1000
|
262 |
+
value: 0.182
|
263 |
- type: precision_at_3
|
264 |
+
value: 19.599
|
265 |
- type: precision_at_5
|
266 |
+
value: 13.847999999999999
|
267 |
- type: recall_at_1
|
268 |
+
value: 29.725
|
269 |
- type: recall_at_10
|
270 |
+
value: 55.51199999999999
|
271 |
- type: recall_at_100
|
272 |
+
value: 78.182
|
273 |
- type: recall_at_1000
|
274 |
+
value: 92.727
|
275 |
- type: recall_at_3
|
276 |
+
value: 43.287
|
277 |
- type: recall_at_5
|
278 |
+
value: 48.732
|
279 |
- task:
|
280 |
type: Retrieval
|
281 |
dataset:
|
|
|
286 |
revision: None
|
287 |
metrics:
|
288 |
- type: map_at_1
|
289 |
+
value: 30.23
|
290 |
- type: map_at_10
|
291 |
+
value: 40.091
|
292 |
- type: map_at_100
|
293 |
+
value: 41.251
|
294 |
- type: map_at_1000
|
295 |
+
value: 41.384
|
296 |
- type: map_at_3
|
297 |
+
value: 37.247
|
298 |
- type: map_at_5
|
299 |
+
value: 38.865
|
300 |
- type: mrr_at_1
|
301 |
+
value: 38.279999999999994
|
302 |
- type: mrr_at_10
|
303 |
+
value: 46.288000000000004
|
304 |
- type: mrr_at_100
|
305 |
+
value: 47.022999999999996
|
306 |
- type: mrr_at_1000
|
307 |
+
value: 47.068
|
308 |
- type: mrr_at_3
|
309 |
+
value: 44.395
|
310 |
- type: mrr_at_5
|
311 |
+
value: 45.446
|
312 |
- type: ndcg_at_1
|
313 |
+
value: 38.279999999999994
|
314 |
- type: ndcg_at_10
|
315 |
+
value: 45.647
|
316 |
- type: ndcg_at_100
|
317 |
+
value: 49.851
|
318 |
- type: ndcg_at_1000
|
319 |
+
value: 51.991
|
320 |
- type: ndcg_at_3
|
321 |
+
value: 41.795
|
322 |
- type: ndcg_at_5
|
323 |
+
value: 43.578
|
324 |
- type: precision_at_1
|
325 |
+
value: 38.279999999999994
|
326 |
- type: precision_at_10
|
327 |
+
value: 8.522
|
328 |
- type: precision_at_100
|
329 |
+
value: 1.361
|
330 |
- type: precision_at_1000
|
331 |
+
value: 0.185
|
332 |
- type: precision_at_3
|
333 |
+
value: 20.297
|
334 |
- type: precision_at_5
|
335 |
+
value: 14.255
|
336 |
- type: recall_at_1
|
337 |
+
value: 30.23
|
338 |
- type: recall_at_10
|
339 |
+
value: 55.094
|
340 |
- type: recall_at_100
|
341 |
+
value: 72.887
|
342 |
- type: recall_at_1000
|
343 |
+
value: 86.295
|
344 |
- type: recall_at_3
|
345 |
+
value: 43.244
|
346 |
- type: recall_at_5
|
347 |
+
value: 48.507
|
348 |
- task:
|
349 |
type: Retrieval
|
350 |
dataset:
|
|
|
355 |
revision: None
|
356 |
metrics:
|
357 |
- type: map_at_1
|
358 |
+
value: 40.854
|
359 |
- type: map_at_10
|
360 |
+
value: 52.232
|
361 |
- type: map_at_100
|
362 |
+
value: 53.129000000000005
|
363 |
- type: map_at_1000
|
364 |
+
value: 53.185
|
365 |
- type: map_at_3
|
366 |
+
value: 49.094
|
367 |
- type: map_at_5
|
368 |
+
value: 50.834999999999994
|
369 |
- type: mrr_at_1
|
370 |
value: 46.708
|
371 |
- type: mrr_at_10
|
372 |
+
value: 56.021
|
373 |
- type: mrr_at_100
|
374 |
+
value: 56.584
|
375 |
- type: mrr_at_1000
|
376 |
+
value: 56.611999999999995
|
377 |
- type: mrr_at_3
|
378 |
+
value: 53.657
|
379 |
- type: mrr_at_5
|
380 |
+
value: 55.027
|
381 |
- type: ndcg_at_1
|
382 |
value: 46.708
|
383 |
- type: ndcg_at_10
|
384 |
+
value: 57.89
|
385 |
- type: ndcg_at_100
|
386 |
+
value: 61.541999999999994
|
387 |
- type: ndcg_at_1000
|
388 |
+
value: 62.754
|
389 |
- type: ndcg_at_3
|
390 |
+
value: 52.632
|
391 |
- type: ndcg_at_5
|
392 |
+
value: 55.104
|
393 |
- type: precision_at_1
|
394 |
value: 46.708
|
395 |
- type: precision_at_10
|
396 |
+
value: 9.122
|
397 |
- type: precision_at_100
|
398 |
+
value: 1.187
|
399 |
- type: precision_at_1000
|
400 |
+
value: 0.134
|
401 |
- type: precision_at_3
|
402 |
+
value: 23.072
|
403 |
- type: precision_at_5
|
404 |
+
value: 15.661
|
405 |
- type: recall_at_1
|
406 |
+
value: 40.854
|
407 |
- type: recall_at_10
|
408 |
+
value: 70.98
|
409 |
- type: recall_at_100
|
410 |
+
value: 86.947
|
411 |
- type: recall_at_1000
|
412 |
+
value: 95.62
|
413 |
- type: recall_at_3
|
414 |
+
value: 56.782999999999994
|
415 |
- type: recall_at_5
|
416 |
+
value: 62.980000000000004
|
417 |
- task:
|
418 |
type: Retrieval
|
419 |
dataset:
|
|
|
424 |
revision: None
|
425 |
metrics:
|
426 |
- type: map_at_1
|
427 |
+
value: 26.366
|
428 |
- type: map_at_10
|
429 |
+
value: 33.674
|
430 |
- type: map_at_100
|
431 |
+
value: 34.58
|
432 |
- type: map_at_1000
|
433 |
+
value: 34.662
|
434 |
- type: map_at_3
|
435 |
+
value: 31.596999999999998
|
436 |
- type: map_at_5
|
437 |
+
value: 32.596000000000004
|
438 |
- type: mrr_at_1
|
439 |
+
value: 28.588
|
440 |
- type: mrr_at_10
|
441 |
+
value: 35.912
|
442 |
- type: mrr_at_100
|
443 |
+
value: 36.696
|
444 |
- type: mrr_at_1000
|
445 |
+
value: 36.760999999999996
|
446 |
- type: mrr_at_3
|
447 |
+
value: 33.823
|
448 |
- type: mrr_at_5
|
449 |
+
value: 34.829
|
450 |
- type: ndcg_at_1
|
451 |
+
value: 28.588
|
452 |
- type: ndcg_at_10
|
453 |
+
value: 38.031
|
454 |
- type: ndcg_at_100
|
455 |
+
value: 42.678
|
456 |
- type: ndcg_at_1000
|
457 |
+
value: 44.871
|
458 |
- type: ndcg_at_3
|
459 |
+
value: 33.815
|
460 |
- type: ndcg_at_5
|
461 |
+
value: 35.531
|
462 |
- type: precision_at_1
|
463 |
+
value: 28.588
|
464 |
- type: precision_at_10
|
465 |
+
value: 5.638
|
466 |
- type: precision_at_100
|
467 |
+
value: 0.8380000000000001
|
468 |
- type: precision_at_1000
|
469 |
+
value: 0.106
|
470 |
- type: precision_at_3
|
471 |
+
value: 13.974
|
472 |
- type: precision_at_5
|
473 |
+
value: 9.401
|
474 |
- type: recall_at_1
|
475 |
+
value: 26.366
|
476 |
- type: recall_at_10
|
477 |
+
value: 49.353
|
478 |
- type: recall_at_100
|
479 |
+
value: 71.194
|
480 |
- type: recall_at_1000
|
481 |
+
value: 87.842
|
482 |
- type: recall_at_3
|
483 |
+
value: 37.829
|
484 |
- type: recall_at_5
|
485 |
+
value: 41.976
|
486 |
- task:
|
487 |
type: Retrieval
|
488 |
dataset:
|
|
|
493 |
revision: None
|
494 |
metrics:
|
495 |
- type: map_at_1
|
496 |
+
value: 16.634
|
497 |
- type: map_at_10
|
498 |
+
value: 23.271
|
499 |
- type: map_at_100
|
500 |
+
value: 24.366
|
501 |
- type: map_at_1000
|
502 |
+
value: 24.484
|
503 |
- type: map_at_3
|
504 |
+
value: 21.075
|
505 |
- type: map_at_5
|
506 |
+
value: 22.364
|
507 |
- type: mrr_at_1
|
508 |
+
value: 20.522000000000002
|
509 |
- type: mrr_at_10
|
510 |
+
value: 27.735
|
511 |
- type: mrr_at_100
|
512 |
+
value: 28.691
|
513 |
- type: mrr_at_1000
|
514 |
+
value: 28.762999999999998
|
515 |
- type: mrr_at_3
|
516 |
+
value: 25.518
|
517 |
- type: mrr_at_5
|
518 |
+
value: 26.762000000000004
|
519 |
- type: ndcg_at_1
|
520 |
+
value: 20.522000000000002
|
521 |
- type: ndcg_at_10
|
522 |
+
value: 27.791
|
523 |
- type: ndcg_at_100
|
524 |
+
value: 33.101
|
525 |
- type: ndcg_at_1000
|
526 |
+
value: 36.075
|
527 |
- type: ndcg_at_3
|
528 |
+
value: 23.74
|
529 |
- type: ndcg_at_5
|
530 |
+
value: 25.691000000000003
|
531 |
- type: precision_at_1
|
532 |
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value: 20.522000000000002
|
533 |
- type: precision_at_10
|
534 |
+
value: 4.963
|
535 |
- type: precision_at_100
|
536 |
+
value: 0.873
|
537 |
- type: precision_at_1000
|
538 |
+
value: 0.128
|
539 |
- type: precision_at_3
|
540 |
+
value: 11.111
|
541 |
- type: precision_at_5
|
542 |
+
value: 8.01
|
543 |
- type: recall_at_1
|
544 |
+
value: 16.634
|
545 |
- type: recall_at_10
|
546 |
+
value: 37.498
|
547 |
- type: recall_at_100
|
548 |
+
value: 60.598
|
549 |
- type: recall_at_1000
|
550 |
+
value: 81.828
|
551 |
- type: recall_at_3
|
552 |
+
value: 26.136
|
553 |
- type: recall_at_5
|
554 |
+
value: 31.211
|
555 |
- task:
|
556 |
type: Retrieval
|
557 |
dataset:
|
|
|
562 |
revision: None
|
563 |
metrics:
|
564 |
- type: map_at_1
|
565 |
+
value: 28.200999999999997
|
566 |
- type: map_at_10
|
567 |
+
value: 37.619
|
568 |
- type: map_at_100
|
569 |
+
value: 38.834999999999994
|
570 |
- type: map_at_1000
|
571 |
+
value: 38.951
|
572 |
- type: map_at_3
|
573 |
+
value: 35.119
|
574 |
- type: map_at_5
|
575 |
+
value: 36.559999999999995
|
576 |
- type: mrr_at_1
|
577 |
value: 33.782000000000004
|
578 |
- type: mrr_at_10
|
579 |
+
value: 43.033
|
580 |
- type: mrr_at_100
|
581 |
+
value: 43.761
|
582 |
- type: mrr_at_1000
|
583 |
+
value: 43.818
|
584 |
- type: mrr_at_3
|
585 |
+
value: 40.727999999999994
|
586 |
- type: mrr_at_5
|
587 |
+
value: 42.129
|
588 |
- type: ndcg_at_1
|
589 |
value: 33.782000000000004
|
590 |
- type: ndcg_at_10
|
591 |
+
value: 43.178
|
592 |
- type: ndcg_at_100
|
593 |
+
value: 48.27
|
594 |
- type: ndcg_at_1000
|
595 |
+
value: 50.559
|
596 |
- type: ndcg_at_3
|
597 |
+
value: 38.974
|
598 |
- type: ndcg_at_5
|
599 |
+
value: 41.019
|
600 |
- type: precision_at_1
|
601 |
value: 33.782000000000004
|
602 |
- type: precision_at_10
|
603 |
+
value: 7.575
|
604 |
- type: precision_at_100
|
605 |
+
value: 1.1820000000000002
|
606 |
- type: precision_at_1000
|
607 |
+
value: 0.154
|
608 |
- type: precision_at_3
|
609 |
+
value: 18.223
|
610 |
- type: precision_at_5
|
611 |
+
value: 12.742999999999999
|
612 |
- type: recall_at_1
|
613 |
+
value: 28.200999999999997
|
614 |
- type: recall_at_10
|
615 |
+
value: 54.089
|
616 |
- type: recall_at_100
|
617 |
+
value: 75.57000000000001
|
618 |
- type: recall_at_1000
|
619 |
+
value: 90.827
|
620 |
- type: recall_at_3
|
621 |
+
value: 42.435
|
622 |
- type: recall_at_5
|
623 |
+
value: 47.652
|
624 |
- task:
|
625 |
type: Retrieval
|
626 |
dataset:
|
|
|
631 |
revision: None
|
632 |
metrics:
|
633 |
- type: map_at_1
|
634 |
+
value: 25.313000000000002
|
635 |
- type: map_at_10
|
636 |
+
value: 34.329
|
637 |
- type: map_at_100
|
638 |
+
value: 35.445
|
639 |
- type: map_at_1000
|
640 |
+
value: 35.556
|
641 |
- type: map_at_3
|
642 |
+
value: 31.659
|
643 |
- type: map_at_5
|
644 |
+
value: 32.981
|
645 |
- type: mrr_at_1
|
646 |
+
value: 30.822
|
647 |
- type: mrr_at_10
|
648 |
+
value: 39.084
|
649 |
- type: mrr_at_100
|
650 |
+
value: 39.97
|
651 |
- type: mrr_at_1000
|
652 |
+
value: 40.025
|
653 |
- type: mrr_at_3
|
654 |
+
value: 36.815
|
655 |
- type: mrr_at_5
|
656 |
+
value: 38.002
|
657 |
- type: ndcg_at_1
|
658 |
+
value: 30.822
|
659 |
- type: ndcg_at_10
|
660 |
+
value: 39.512
|
661 |
- type: ndcg_at_100
|
662 |
+
value: 44.925
|
663 |
- type: ndcg_at_1000
|
664 |
+
value: 47.274
|
665 |
- type: ndcg_at_3
|
666 |
+
value: 35.055
|
667 |
- type: ndcg_at_5
|
668 |
+
value: 36.788
|
669 |
- type: precision_at_1
|
670 |
+
value: 30.822
|
671 |
- type: precision_at_10
|
672 |
+
value: 7.1
|
673 |
- type: precision_at_100
|
674 |
+
value: 1.15
|
675 |
- type: precision_at_1000
|
676 |
+
value: 0.151
|
677 |
- type: precision_at_3
|
678 |
+
value: 16.476
|
679 |
- type: precision_at_5
|
680 |
+
value: 11.461
|
681 |
- type: recall_at_1
|
682 |
+
value: 25.313000000000002
|
683 |
- type: recall_at_10
|
684 |
+
value: 50.178
|
685 |
- type: recall_at_100
|
686 |
+
value: 74.312
|
687 |
- type: recall_at_1000
|
688 |
+
value: 90.50200000000001
|
689 |
- type: recall_at_3
|
690 |
+
value: 37.626
|
691 |
- type: recall_at_5
|
692 |
+
value: 42.34
|
693 |
- task:
|
694 |
type: Retrieval
|
695 |
dataset:
|
|
|
700 |
revision: None
|
701 |
metrics:
|
702 |
- type: map_at_1
|
703 |
+
value: 25.502250000000004
|
704 |
- type: map_at_10
|
705 |
+
value: 33.655166666666666
|
706 |
- type: map_at_100
|
707 |
+
value: 34.72833333333333
|
708 |
- type: map_at_1000
|
709 |
+
value: 34.84375
|
710 |
- type: map_at_3
|
711 |
+
value: 31.253999999999998
|
712 |
- type: map_at_5
|
713 |
+
value: 32.55075
|
714 |
- type: mrr_at_1
|
715 |
+
value: 29.91975
|
716 |
- type: mrr_at_10
|
717 |
+
value: 37.65441666666667
|
718 |
- type: mrr_at_100
|
719 |
+
value: 38.464416666666665
|
720 |
- type: mrr_at_1000
|
721 |
+
value: 38.52591666666667
|
722 |
- type: mrr_at_3
|
723 |
+
value: 35.57858333333333
|
724 |
- type: mrr_at_5
|
725 |
+
value: 36.71083333333333
|
726 |
- type: ndcg_at_1
|
727 |
+
value: 29.91975
|
728 |
- type: ndcg_at_10
|
729 |
+
value: 38.47316666666667
|
730 |
- type: ndcg_at_100
|
731 |
+
value: 43.256416666666674
|
732 |
- type: ndcg_at_1000
|
733 |
+
value: 45.70658333333333
|
734 |
- type: ndcg_at_3
|
735 |
+
value: 34.350833333333334
|
736 |
- type: ndcg_at_5
|
737 |
+
value: 36.184583333333336
|
738 |
- type: precision_at_1
|
739 |
+
value: 29.91975
|
740 |
- type: precision_at_10
|
741 |
+
value: 6.5489999999999995
|
742 |
- type: precision_at_100
|
743 |
+
value: 1.0553333333333332
|
744 |
- type: precision_at_1000
|
745 |
+
value: 0.14516666666666667
|
746 |
- type: precision_at_3
|
747 |
+
value: 15.579083333333333
|
748 |
- type: precision_at_5
|
749 |
+
value: 10.851083333333332
|
750 |
- type: recall_at_1
|
751 |
+
value: 25.502250000000004
|
752 |
- type: recall_at_10
|
753 |
+
value: 48.7965
|
754 |
- type: recall_at_100
|
755 |
+
value: 69.93500000000002
|
756 |
- type: recall_at_1000
|
757 |
+
value: 87.17049999999999
|
758 |
- type: recall_at_3
|
759 |
+
value: 37.20433333333333
|
760 |
- type: recall_at_5
|
761 |
+
value: 42.00783333333333
|
762 |
- task:
|
763 |
type: Retrieval
|
764 |
dataset:
|
|
|
769 |
revision: None
|
770 |
metrics:
|
771 |
- type: map_at_1
|
772 |
+
value: 23.777
|
773 |
- type: map_at_10
|
774 |
+
value: 29.932
|
775 |
- type: map_at_100
|
776 |
+
value: 30.778
|
777 |
- type: map_at_1000
|
778 |
+
value: 30.879
|
779 |
- type: map_at_3
|
780 |
+
value: 27.898
|
781 |
- type: map_at_5
|
782 |
+
value: 29.086000000000002
|
783 |
- type: mrr_at_1
|
784 |
+
value: 26.227
|
785 |
- type: mrr_at_10
|
786 |
+
value: 32.443
|
787 |
- type: mrr_at_100
|
788 |
+
value: 33.212
|
789 |
- type: mrr_at_1000
|
790 |
+
value: 33.29
|
791 |
- type: mrr_at_3
|
792 |
+
value: 30.419
|
793 |
- type: mrr_at_5
|
794 |
+
value: 31.616
|
795 |
- type: ndcg_at_1
|
796 |
+
value: 26.227
|
797 |
- type: ndcg_at_10
|
798 |
+
value: 33.774
|
799 |
- type: ndcg_at_100
|
800 |
+
value: 37.917
|
801 |
- type: ndcg_at_1000
|
802 |
+
value: 40.557
|
803 |
- type: ndcg_at_3
|
804 |
+
value: 29.875
|
805 |
- type: ndcg_at_5
|
806 |
+
value: 31.845000000000002
|
807 |
- type: precision_at_1
|
808 |
+
value: 26.227
|
809 |
- type: precision_at_10
|
810 |
+
value: 5.153
|
811 |
- type: precision_at_100
|
812 |
+
value: 0.784
|
813 |
- type: precision_at_1000
|
814 |
+
value: 0.108
|
815 |
- type: precision_at_3
|
816 |
+
value: 12.423
|
817 |
- type: precision_at_5
|
818 |
+
value: 8.773
|
819 |
- type: recall_at_1
|
820 |
+
value: 23.777
|
821 |
- type: recall_at_10
|
822 |
+
value: 43.142
|
823 |
- type: recall_at_100
|
824 |
+
value: 61.68900000000001
|
825 |
- type: recall_at_1000
|
826 |
+
value: 81.37100000000001
|
827 |
- type: recall_at_3
|
828 |
+
value: 32.582
|
829 |
- type: recall_at_5
|
830 |
+
value: 37.403
|
831 |
- task:
|
832 |
type: Retrieval
|
833 |
dataset:
|
|
|
838 |
revision: None
|
839 |
metrics:
|
840 |
- type: map_at_1
|
841 |
+
value: 16.659
|
842 |
- type: map_at_10
|
843 |
+
value: 22.926
|
844 |
- type: map_at_100
|
845 |
+
value: 23.837
|
846 |
- type: map_at_1000
|
847 |
+
value: 23.953
|
848 |
- type: map_at_3
|
849 |
+
value: 21.029999999999998
|
850 |
- type: map_at_5
|
851 |
+
value: 22.019
|
852 |
- type: mrr_at_1
|
853 |
+
value: 19.649
|
854 |
- type: mrr_at_10
|
855 |
+
value: 26.32
|
856 |
- type: mrr_at_100
|
857 |
+
value: 27.143
|
858 |
- type: mrr_at_1000
|
859 |
+
value: 27.222
|
860 |
- type: mrr_at_3
|
861 |
+
value: 24.484
|
862 |
- type: mrr_at_5
|
863 |
+
value: 25.468000000000004
|
864 |
- type: ndcg_at_1
|
865 |
+
value: 19.649
|
866 |
- type: ndcg_at_10
|
867 |
+
value: 26.941
|
868 |
- type: ndcg_at_100
|
869 |
+
value: 31.522
|
870 |
- type: ndcg_at_1000
|
871 |
+
value: 34.538999999999994
|
872 |
- type: ndcg_at_3
|
873 |
+
value: 23.419999999999998
|
874 |
- type: ndcg_at_5
|
875 |
+
value: 24.927
|
876 |
- type: precision_at_1
|
877 |
+
value: 19.649
|
878 |
- type: precision_at_10
|
879 |
+
value: 4.7010000000000005
|
880 |
- type: precision_at_100
|
881 |
+
value: 0.8130000000000001
|
882 |
- type: precision_at_1000
|
883 |
+
value: 0.124
|
884 |
- type: precision_at_3
|
885 |
+
value: 10.735999999999999
|
886 |
- type: precision_at_5
|
887 |
+
value: 7.591
|
888 |
- type: recall_at_1
|
889 |
+
value: 16.659
|
890 |
- type: recall_at_10
|
891 |
+
value: 35.721000000000004
|
892 |
- type: recall_at_100
|
893 |
+
value: 56.43
|
894 |
- type: recall_at_1000
|
895 |
+
value: 78.464
|
896 |
- type: recall_at_3
|
897 |
+
value: 25.878
|
898 |
- type: recall_at_5
|
899 |
+
value: 29.731999999999996
|
900 |
- task:
|
901 |
type: Retrieval
|
902 |
dataset:
|
|
|
907 |
revision: None
|
908 |
metrics:
|
909 |
- type: map_at_1
|
910 |
+
value: 24.309
|
911 |
- type: map_at_10
|
912 |
+
value: 31.990000000000002
|
913 |
- type: map_at_100
|
914 |
+
value: 32.895
|
915 |
- type: map_at_1000
|
916 |
+
value: 33.0
|
917 |
- type: map_at_3
|
918 |
+
value: 29.848999999999997
|
919 |
- type: map_at_5
|
920 |
+
value: 30.942999999999998
|
921 |
- type: mrr_at_1
|
922 |
+
value: 28.638
|
923 |
- type: mrr_at_10
|
924 |
+
value: 36.036
|
925 |
- type: mrr_at_100
|
926 |
+
value: 36.787
|
927 |
- type: mrr_at_1000
|
928 |
+
value: 36.855
|
929 |
- type: mrr_at_3
|
930 |
+
value: 34.08
|
931 |
- type: mrr_at_5
|
932 |
+
value: 35.073
|
933 |
- type: ndcg_at_1
|
934 |
+
value: 28.638
|
935 |
- type: ndcg_at_10
|
936 |
+
value: 36.588
|
937 |
- type: ndcg_at_100
|
938 |
+
value: 41.152
|
939 |
- type: ndcg_at_1000
|
940 |
+
value: 43.769999999999996
|
941 |
- type: ndcg_at_3
|
942 |
+
value: 32.632
|
943 |
- type: ndcg_at_5
|
944 |
+
value: 34.249
|
945 |
- type: precision_at_1
|
946 |
+
value: 28.638
|
947 |
- type: precision_at_10
|
948 |
+
value: 5.942
|
949 |
- type: precision_at_100
|
950 |
+
value: 0.9249999999999999
|
951 |
- type: precision_at_1000
|
952 |
+
value: 0.127
|
953 |
- type: precision_at_3
|
954 |
+
value: 14.582999999999998
|
955 |
- type: precision_at_5
|
956 |
+
value: 9.944
|
957 |
- type: recall_at_1
|
958 |
+
value: 24.309
|
959 |
- type: recall_at_10
|
960 |
+
value: 46.725
|
961 |
- type: recall_at_100
|
962 |
+
value: 67.11
|
963 |
- type: recall_at_1000
|
964 |
+
value: 85.91499999999999
|
965 |
- type: recall_at_3
|
966 |
+
value: 35.72
|
967 |
- type: recall_at_5
|
968 |
+
value: 39.854
|
969 |
- task:
|
970 |
type: Retrieval
|
971 |
dataset:
|
|
|
976 |
revision: None
|
977 |
metrics:
|
978 |
- type: map_at_1
|
979 |
+
value: 22.997999999999998
|
980 |
- type: map_at_10
|
981 |
+
value: 30.564000000000004
|
982 |
- type: map_at_100
|
983 |
+
value: 32.06
|
984 |
- type: map_at_1000
|
985 |
+
value: 32.282
|
986 |
- type: map_at_3
|
987 |
+
value: 28.12
|
988 |
- type: map_at_5
|
989 |
+
value: 29.395
|
990 |
- type: mrr_at_1
|
991 |
+
value: 27.075
|
992 |
- type: mrr_at_10
|
993 |
+
value: 34.510999999999996
|
994 |
- type: mrr_at_100
|
995 |
+
value: 35.549
|
996 |
- type: mrr_at_1000
|
997 |
+
value: 35.616
|
998 |
- type: mrr_at_3
|
999 |
+
value: 32.444
|
1000 |
- type: mrr_at_5
|
1001 |
+
value: 33.589999999999996
|
1002 |
- type: ndcg_at_1
|
1003 |
+
value: 27.075
|
1004 |
- type: ndcg_at_10
|
1005 |
+
value: 35.582
|
1006 |
- type: ndcg_at_100
|
1007 |
+
value: 41.308
|
1008 |
- type: ndcg_at_1000
|
1009 |
+
value: 44.385999999999996
|
1010 |
- type: ndcg_at_3
|
1011 |
+
value: 31.467
|
1012 |
- type: ndcg_at_5
|
1013 |
+
value: 33.189
|
1014 |
- type: precision_at_1
|
1015 |
+
value: 27.075
|
1016 |
- type: precision_at_10
|
1017 |
+
value: 6.68
|
1018 |
- type: precision_at_100
|
1019 |
+
value: 1.427
|
1020 |
- type: precision_at_1000
|
1021 |
value: 0.231
|
1022 |
- type: precision_at_3
|
1023 |
+
value: 14.625
|
1024 |
- type: precision_at_5
|
1025 |
+
value: 10.356
|
1026 |
- type: recall_at_1
|
1027 |
+
value: 22.997999999999998
|
1028 |
- type: recall_at_10
|
1029 |
+
value: 45.196
|
1030 |
- type: recall_at_100
|
1031 |
+
value: 70.319
|
1032 |
- type: recall_at_1000
|
1033 |
+
value: 90.766
|
1034 |
- type: recall_at_3
|
1035 |
+
value: 33.487
|
1036 |
- type: recall_at_5
|
1037 |
+
value: 38.297
|
1038 |
- task:
|
1039 |
type: Retrieval
|
1040 |
dataset:
|
|
|
1045 |
revision: None
|
1046 |
metrics:
|
1047 |
- type: map_at_1
|
1048 |
+
value: 20.961
|
1049 |
- type: map_at_10
|
1050 |
+
value: 27.58
|
1051 |
- type: map_at_100
|
1052 |
+
value: 28.542
|
1053 |
- type: map_at_1000
|
1054 |
+
value: 28.644
|
1055 |
- type: map_at_3
|
1056 |
+
value: 25.541000000000004
|
1057 |
- type: map_at_5
|
1058 |
+
value: 26.589000000000002
|
1059 |
- type: mrr_at_1
|
1060 |
+
value: 22.551
|
1061 |
- type: mrr_at_10
|
1062 |
+
value: 29.298999999999996
|
1063 |
- type: mrr_at_100
|
1064 |
+
value: 30.17
|
1065 |
- type: mrr_at_1000
|
1066 |
+
value: 30.248
|
1067 |
- type: mrr_at_3
|
1068 |
+
value: 27.542
|
1069 |
- type: mrr_at_5
|
1070 |
+
value: 28.392
|
1071 |
- type: ndcg_at_1
|
1072 |
+
value: 22.551
|
1073 |
- type: ndcg_at_10
|
1074 |
+
value: 31.55
|
1075 |
- type: ndcg_at_100
|
1076 |
+
value: 36.295
|
1077 |
- type: ndcg_at_1000
|
1078 |
+
value: 38.964
|
1079 |
- type: ndcg_at_3
|
1080 |
+
value: 27.663
|
1081 |
- type: ndcg_at_5
|
1082 |
+
value: 29.321
|
1083 |
- type: precision_at_1
|
1084 |
+
value: 22.551
|
1085 |
- type: precision_at_10
|
1086 |
+
value: 4.88
|
1087 |
- type: precision_at_100
|
1088 |
+
value: 0.7779999999999999
|
1089 |
- type: precision_at_1000
|
1090 |
+
value: 0.11199999999999999
|
1091 |
- type: precision_at_3
|
1092 |
+
value: 11.83
|
1093 |
- type: precision_at_5
|
1094 |
+
value: 8.17
|
1095 |
- type: recall_at_1
|
1096 |
+
value: 20.961
|
1097 |
- type: recall_at_10
|
1098 |
+
value: 42.07
|
1099 |
- type: recall_at_100
|
1100 |
+
value: 63.982000000000006
|
1101 |
- type: recall_at_1000
|
1102 |
+
value: 83.889
|
1103 |
- type: recall_at_3
|
1104 |
+
value: 31.445
|
1105 |
- type: recall_at_5
|
1106 |
+
value: 35.410000000000004
|
1107 |
- task:
|
1108 |
type: Retrieval
|
1109 |
dataset:
|
|
|
1114 |
revision: None
|
1115 |
metrics:
|
1116 |
- type: map_at_1
|
1117 |
+
value: 11.314
|
1118 |
- type: map_at_10
|
1119 |
+
value: 18.983
|
1120 |
- type: map_at_100
|
1121 |
+
value: 20.851
|
1122 |
- type: map_at_1000
|
1123 |
+
value: 21.066
|
1124 |
- type: map_at_3
|
1125 |
+
value: 16.014
|
1126 |
- type: map_at_5
|
1127 |
+
value: 17.569000000000003
|
1128 |
- type: mrr_at_1
|
1129 |
+
value: 25.277
|
1130 |
- type: mrr_at_10
|
1131 |
+
value: 36.657000000000004
|
1132 |
- type: mrr_at_100
|
1133 |
+
value: 37.646
|
1134 |
- type: mrr_at_1000
|
1135 |
+
value: 37.686
|
1136 |
- type: mrr_at_3
|
1137 |
+
value: 33.17
|
1138 |
- type: mrr_at_5
|
1139 |
+
value: 35.232
|
1140 |
- type: ndcg_at_1
|
1141 |
+
value: 25.277
|
1142 |
- type: ndcg_at_10
|
1143 |
+
value: 27.011000000000003
|
1144 |
- type: ndcg_at_100
|
1145 |
+
value: 34.418
|
1146 |
- type: ndcg_at_1000
|
1147 |
+
value: 38.089
|
1148 |
- type: ndcg_at_3
|
1149 |
+
value: 22.026
|
1150 |
- type: ndcg_at_5
|
1151 |
+
value: 23.866
|
1152 |
- type: precision_at_1
|
1153 |
+
value: 25.277
|
1154 |
- type: precision_at_10
|
1155 |
+
value: 8.397
|
1156 |
- type: precision_at_100
|
1157 |
+
value: 1.6320000000000001
|
1158 |
- type: precision_at_1000
|
1159 |
+
value: 0.22999999999999998
|
1160 |
- type: precision_at_3
|
1161 |
+
value: 16.156000000000002
|
1162 |
- type: precision_at_5
|
1163 |
+
value: 12.612000000000002
|
1164 |
- type: recall_at_1
|
1165 |
+
value: 11.314
|
1166 |
- type: recall_at_10
|
1167 |
+
value: 32.474
|
1168 |
- type: recall_at_100
|
1169 |
+
value: 57.926
|
1170 |
- type: recall_at_1000
|
1171 |
+
value: 78.387
|
1172 |
- type: recall_at_3
|
1173 |
+
value: 20.415
|
1174 |
- type: recall_at_5
|
1175 |
+
value: 25.407999999999998
|
1176 |
- task:
|
1177 |
type: Retrieval
|
1178 |
dataset:
|
|
|
1183 |
revision: None
|
1184 |
metrics:
|
1185 |
- type: map_at_1
|
1186 |
+
value: 8.835999999999999
|
1187 |
- type: map_at_10
|
1188 |
+
value: 19.73
|
1189 |
- type: map_at_100
|
1190 |
+
value: 28.011000000000003
|
1191 |
- type: map_at_1000
|
1192 |
+
value: 29.519000000000002
|
1193 |
- type: map_at_3
|
1194 |
+
value: 14.249
|
1195 |
- type: map_at_5
|
1196 |
+
value: 16.472
|
1197 |
- type: mrr_at_1
|
1198 |
+
value: 67.0
|
1199 |
- type: mrr_at_10
|
1200 |
+
value: 74.632
|
1201 |
- type: mrr_at_100
|
1202 |
+
value: 74.97200000000001
|
1203 |
- type: mrr_at_1000
|
1204 |
+
value: 74.97500000000001
|
1205 |
- type: mrr_at_3
|
1206 |
+
value: 72.958
|
1207 |
- type: mrr_at_5
|
1208 |
+
value: 73.908
|
1209 |
- type: ndcg_at_1
|
1210 |
+
value: 55.875
|
1211 |
- type: ndcg_at_10
|
1212 |
+
value: 42.071999999999996
|
1213 |
- type: ndcg_at_100
|
1214 |
+
value: 46.091
|
1215 |
- type: ndcg_at_1000
|
1216 |
+
value: 52.737
|
1217 |
- type: ndcg_at_3
|
1218 |
+
value: 47.079
|
1219 |
- type: ndcg_at_5
|
1220 |
+
value: 43.788
|
1221 |
- type: precision_at_1
|
1222 |
+
value: 67.0
|
1223 |
- type: precision_at_10
|
1224 |
+
value: 33.45
|
1225 |
- type: precision_at_100
|
1226 |
+
value: 10.633
|
1227 |
- type: precision_at_1000
|
1228 |
+
value: 2.067
|
1229 |
- type: precision_at_3
|
1230 |
+
value: 49.583
|
1231 |
- type: precision_at_5
|
1232 |
+
value: 41.25
|
1233 |
- type: recall_at_1
|
1234 |
+
value: 8.835999999999999
|
1235 |
- type: recall_at_10
|
1236 |
+
value: 24.872
|
1237 |
- type: recall_at_100
|
1238 |
+
value: 51.427
|
1239 |
- type: recall_at_1000
|
1240 |
+
value: 72.17099999999999
|
1241 |
- type: recall_at_3
|
1242 |
+
value: 15.631999999999998
|
1243 |
- type: recall_at_5
|
1244 |
+
value: 18.956
|
1245 |
- task:
|
1246 |
type: Classification
|
1247 |
dataset:
|
|
|
1252 |
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
|
1253 |
metrics:
|
1254 |
- type: accuracy
|
1255 |
+
value: 48.80500000000001
|
1256 |
- type: f1
|
1257 |
+
value: 43.91955883597831
|
1258 |
- task:
|
1259 |
type: Retrieval
|
1260 |
dataset:
|
|
|
1265 |
revision: None
|
1266 |
metrics:
|
1267 |
- type: map_at_1
|
1268 |
+
value: 61.480999999999995
|
1269 |
- type: map_at_10
|
1270 |
+
value: 72.162
|
1271 |
- type: map_at_100
|
1272 |
+
value: 72.487
|
1273 |
- type: map_at_1000
|
1274 |
+
value: 72.504
|
1275 |
- type: map_at_3
|
1276 |
+
value: 70.354
|
1277 |
- type: map_at_5
|
1278 |
+
value: 71.509
|
1279 |
- type: mrr_at_1
|
1280 |
+
value: 66.262
|
1281 |
- type: mrr_at_10
|
1282 |
+
value: 76.605
|
1283 |
- type: mrr_at_100
|
1284 |
+
value: 76.833
|
1285 |
- type: mrr_at_1000
|
1286 |
+
value: 76.839
|
1287 |
- type: mrr_at_3
|
1288 |
+
value: 74.977
|
1289 |
- type: mrr_at_5
|
1290 |
+
value: 76.06
|
1291 |
- type: ndcg_at_1
|
1292 |
+
value: 66.262
|
1293 |
- type: ndcg_at_10
|
1294 |
+
value: 77.323
|
1295 |
- type: ndcg_at_100
|
1296 |
+
value: 78.685
|
1297 |
- type: ndcg_at_1000
|
1298 |
+
value: 79.032
|
1299 |
- type: ndcg_at_3
|
1300 |
+
value: 74.015
|
1301 |
- type: ndcg_at_5
|
1302 |
+
value: 75.916
|
1303 |
- type: precision_at_1
|
1304 |
+
value: 66.262
|
1305 |
- type: precision_at_10
|
1306 |
+
value: 9.757
|
1307 |
- type: precision_at_100
|
1308 |
+
value: 1.059
|
1309 |
- type: precision_at_1000
|
1310 |
+
value: 0.11100000000000002
|
1311 |
- type: precision_at_3
|
1312 |
+
value: 29.032999999999998
|
1313 |
- type: precision_at_5
|
1314 |
+
value: 18.5
|
1315 |
- type: recall_at_1
|
1316 |
+
value: 61.480999999999995
|
1317 |
- type: recall_at_10
|
1318 |
+
value: 88.878
|
1319 |
- type: recall_at_100
|
1320 |
+
value: 94.719
|
1321 |
- type: recall_at_1000
|
1322 |
+
value: 97.066
|
1323 |
- type: recall_at_3
|
1324 |
+
value: 79.95100000000001
|
1325 |
- type: recall_at_5
|
1326 |
+
value: 84.691
|
1327 |
- task:
|
1328 |
type: Retrieval
|
1329 |
dataset:
|
|
|
1334 |
revision: None
|
1335 |
metrics:
|
1336 |
- type: map_at_1
|
1337 |
+
value: 19.925
|
1338 |
- type: map_at_10
|
1339 |
+
value: 31.621
|
1340 |
- type: map_at_100
|
1341 |
+
value: 33.282000000000004
|
1342 |
- type: map_at_1000
|
1343 |
+
value: 33.455
|
1344 |
- type: map_at_3
|
1345 |
+
value: 27.504
|
1346 |
- type: map_at_5
|
1347 |
+
value: 29.921999999999997
|
1348 |
- type: mrr_at_1
|
1349 |
+
value: 39.660000000000004
|
1350 |
- type: mrr_at_10
|
1351 |
+
value: 47.366
|
1352 |
- type: mrr_at_100
|
1353 |
+
value: 48.179
|
1354 |
- type: mrr_at_1000
|
1355 |
+
value: 48.219
|
1356 |
- type: mrr_at_3
|
1357 |
+
value: 45.062000000000005
|
1358 |
- type: mrr_at_5
|
1359 |
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value: 46.404
|
1360 |
- type: ndcg_at_1
|
1361 |
+
value: 39.660000000000004
|
1362 |
- type: ndcg_at_10
|
1363 |
+
value: 39.019
|
1364 |
- type: ndcg_at_100
|
1365 |
+
value: 45.286
|
1366 |
- type: ndcg_at_1000
|
1367 |
+
value: 48.370000000000005
|
1368 |
- type: ndcg_at_3
|
1369 |
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value: 35.421
|
1370 |
- type: ndcg_at_5
|
1371 |
+
value: 36.767
|
1372 |
- type: precision_at_1
|
1373 |
+
value: 39.660000000000004
|
1374 |
- type: precision_at_10
|
1375 |
value: 10.494
|
1376 |
- type: precision_at_100
|
1377 |
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value: 1.7069999999999999
|
1378 |
- type: precision_at_1000
|
1379 |
+
value: 0.22599999999999998
|
1380 |
- type: precision_at_3
|
1381 |
+
value: 23.200000000000003
|
1382 |
- type: precision_at_5
|
1383 |
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value: 17.253
|
1384 |
- type: recall_at_1
|
1385 |
+
value: 19.925
|
1386 |
- type: recall_at_10
|
1387 |
+
value: 45.48
|
1388 |
- type: recall_at_100
|
1389 |
+
value: 68.585
|
1390 |
- type: recall_at_1000
|
1391 |
+
value: 87.128
|
1392 |
- type: recall_at_3
|
1393 |
+
value: 31.913000000000004
|
1394 |
- type: recall_at_5
|
1395 |
+
value: 38.107
|
1396 |
- task:
|
1397 |
type: Retrieval
|
1398 |
dataset:
|
|
|
1403 |
revision: None
|
1404 |
metrics:
|
1405 |
- type: map_at_1
|
1406 |
+
value: 37.961
|
1407 |
- type: map_at_10
|
1408 |
+
value: 55.010000000000005
|
1409 |
- type: map_at_100
|
1410 |
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value: 55.896
|
1411 |
- type: map_at_1000
|
1412 |
+
value: 55.962
|
1413 |
- type: map_at_3
|
1414 |
+
value: 52.03
|
1415 |
- type: map_at_5
|
1416 |
+
value: 53.866
|
1417 |
- type: mrr_at_1
|
1418 |
+
value: 75.922
|
1419 |
- type: mrr_at_10
|
1420 |
+
value: 81.655
|
1421 |
- type: mrr_at_100
|
1422 |
+
value: 81.879
|
1423 |
- type: mrr_at_1000
|
1424 |
+
value: 81.889
|
1425 |
- type: mrr_at_3
|
1426 |
+
value: 80.657
|
1427 |
- type: mrr_at_5
|
1428 |
+
value: 81.291
|
1429 |
- type: ndcg_at_1
|
1430 |
+
value: 75.922
|
1431 |
- type: ndcg_at_10
|
1432 |
+
value: 64.119
|
1433 |
- type: ndcg_at_100
|
1434 |
+
value: 67.25
|
1435 |
- type: ndcg_at_1000
|
1436 |
+
value: 68.55499999999999
|
1437 |
- type: ndcg_at_3
|
1438 |
+
value: 59.792
|
1439 |
- type: ndcg_at_5
|
1440 |
+
value: 62.165000000000006
|
1441 |
- type: precision_at_1
|
1442 |
+
value: 75.922
|
1443 |
- type: precision_at_10
|
1444 |
+
value: 13.155
|
1445 |
- type: precision_at_100
|
1446 |
+
value: 1.5599999999999998
|
1447 |
- type: precision_at_1000
|
1448 |
+
value: 0.173
|
1449 |
- type: precision_at_3
|
1450 |
+
value: 37.461
|
1451 |
- type: precision_at_5
|
1452 |
+
value: 24.351
|
1453 |
- type: recall_at_1
|
1454 |
+
value: 37.961
|
1455 |
- type: recall_at_10
|
1456 |
+
value: 65.77300000000001
|
1457 |
- type: recall_at_100
|
1458 |
+
value: 78.015
|
1459 |
- type: recall_at_1000
|
1460 |
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value: 86.685
|
1461 |
- type: recall_at_3
|
1462 |
+
value: 56.192
|
1463 |
- type: recall_at_5
|
1464 |
+
value: 60.878
|
1465 |
- task:
|
1466 |
type: Classification
|
1467 |
dataset:
|
|
|
1472 |
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
|
1473 |
metrics:
|
1474 |
- type: accuracy
|
1475 |
+
value: 83.7804
|
1476 |
- type: ap
|
1477 |
+
value: 78.89508987851809
|
1478 |
- type: f1
|
1479 |
+
value: 83.72392373438922
|
1480 |
- task:
|
1481 |
type: Retrieval
|
1482 |
dataset:
|
|
|
1487 |
revision: None
|
1488 |
metrics:
|
1489 |
- type: map_at_1
|
1490 |
+
value: 23.807000000000002
|
1491 |
- type: map_at_10
|
1492 |
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value: 36.411
|
1493 |
- type: map_at_100
|
1494 |
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value: 37.574000000000005
|
1495 |
- type: map_at_1000
|
1496 |
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value: 37.618
|
1497 |
- type: map_at_3
|
1498 |
+
value: 32.653
|
1499 |
- type: map_at_5
|
1500 |
+
value: 34.902
|
1501 |
- type: mrr_at_1
|
1502 |
+
value: 24.499000000000002
|
1503 |
- type: mrr_at_10
|
1504 |
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value: 37.045
|
1505 |
- type: mrr_at_100
|
1506 |
+
value: 38.135999999999996
|
1507 |
- type: mrr_at_1000
|
1508 |
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value: 38.175
|
1509 |
- type: mrr_at_3
|
1510 |
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value: 33.326
|
1511 |
- type: mrr_at_5
|
1512 |
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value: 35.561
|
1513 |
- type: ndcg_at_1
|
1514 |
+
value: 24.512999999999998
|
1515 |
- type: ndcg_at_10
|
1516 |
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value: 43.328
|
1517 |
- type: ndcg_at_100
|
1518 |
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value: 48.779
|
1519 |
- type: ndcg_at_1000
|
1520 |
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value: 49.897999999999996
|
1521 |
- type: ndcg_at_3
|
1522 |
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value: 35.713
|
1523 |
- type: ndcg_at_5
|
1524 |
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value: 39.729
|
1525 |
- type: precision_at_1
|
1526 |
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value: 24.512999999999998
|
1527 |
- type: precision_at_10
|
1528 |
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value: 6.7379999999999995
|
1529 |
- type: precision_at_100
|
1530 |
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value: 0.9450000000000001
|
1531 |
- type: precision_at_1000
|
1532 |
value: 0.104
|
1533 |
- type: precision_at_3
|
1534 |
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value: 15.196000000000002
|
1535 |
- type: precision_at_5
|
1536 |
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value: 11.158
|
1537 |
- type: recall_at_1
|
1538 |
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value: 23.807000000000002
|
1539 |
- type: recall_at_10
|
1540 |
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value: 64.488
|
1541 |
- type: recall_at_100
|
1542 |
+
value: 89.386
|
1543 |
- type: recall_at_1000
|
1544 |
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value: 97.968
|
1545 |
- type: recall_at_3
|
1546 |
+
value: 43.891000000000005
|
1547 |
- type: recall_at_5
|
1548 |
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value: 53.535
|
1549 |
- task:
|
1550 |
type: Classification
|
1551 |
dataset:
|
|
|
1556 |
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
|
1557 |
metrics:
|
1558 |
- type: accuracy
|
1559 |
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value: 93.47013223894209
|
1560 |
- type: f1
|
1561 |
+
value: 93.15020887152107
|
1562 |
- task:
|
1563 |
type: Classification
|
1564 |
dataset:
|
|
|
1569 |
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
|
1570 |
metrics:
|
1571 |
- type: accuracy
|
1572 |
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value: 75.27131782945737
|
1573 |
- type: f1
|
1574 |
+
value: 58.45703758149779
|
1575 |
- task:
|
1576 |
type: Classification
|
1577 |
dataset:
|
|
|
1582 |
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
|
1583 |
metrics:
|
1584 |
- type: accuracy
|
1585 |
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value: 72.76395427034298
|
1586 |
- type: f1
|
1587 |
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value: 70.6084399610629
|
1588 |
- task:
|
1589 |
type: Classification
|
1590 |
dataset:
|
|
|
1595 |
revision: 7d571f92784cd94a019292a1f45445077d0ef634
|
1596 |
metrics:
|
1597 |
- type: accuracy
|
1598 |
+
value: 76.69804976462676
|
1599 |
- type: f1
|
1600 |
+
value: 76.61599181962723
|
1601 |
- task:
|
1602 |
type: Clustering
|
1603 |
dataset:
|
|
|
1608 |
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
|
1609 |
metrics:
|
1610 |
- type: v_measure
|
1611 |
+
value: 32.7253797676744
|
1612 |
- task:
|
1613 |
type: Clustering
|
1614 |
dataset:
|
|
|
1619 |
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
|
1620 |
metrics:
|
1621 |
- type: v_measure
|
1622 |
+
value: 30.547731924629424
|
1623 |
- task:
|
1624 |
type: Reranking
|
1625 |
dataset:
|
|
|
1630 |
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
|
1631 |
metrics:
|
1632 |
- type: map
|
1633 |
+
value: 31.286918745183772
|
1634 |
- type: mrr
|
1635 |
+
value: 32.47449315230336
|
1636 |
- task:
|
1637 |
type: Retrieval
|
1638 |
dataset:
|
|
|
1643 |
revision: None
|
1644 |
metrics:
|
1645 |
- type: map_at_1
|
1646 |
+
value: 5.894
|
1647 |
- type: map_at_10
|
1648 |
+
value: 13.405000000000001
|
1649 |
- type: map_at_100
|
1650 |
+
value: 16.586000000000002
|
1651 |
- type: map_at_1000
|
1652 |
+
value: 17.919
|
1653 |
- type: map_at_3
|
1654 |
+
value: 10.066
|
1655 |
- type: map_at_5
|
1656 |
+
value: 11.679
|
1657 |
- type: mrr_at_1
|
1658 |
value: 45.201
|
1659 |
- type: mrr_at_10
|
1660 |
+
value: 54.018
|
1661 |
- type: mrr_at_100
|
1662 |
+
value: 54.581999999999994
|
1663 |
- type: mrr_at_1000
|
1664 |
+
value: 54.623
|
1665 |
- type: mrr_at_3
|
1666 |
+
value: 51.6
|
1667 |
- type: mrr_at_5
|
1668 |
+
value: 53.473000000000006
|
1669 |
- type: ndcg_at_1
|
1670 |
+
value: 43.189
|
1671 |
- type: ndcg_at_10
|
1672 |
+
value: 35.306
|
1673 |
- type: ndcg_at_100
|
1674 |
+
value: 31.505
|
1675 |
- type: ndcg_at_1000
|
1676 |
+
value: 39.991
|
1677 |
- type: ndcg_at_3
|
1678 |
+
value: 41.108
|
1679 |
- type: ndcg_at_5
|
1680 |
+
value: 39.039
|
1681 |
- type: precision_at_1
|
1682 |
+
value: 44.582
|
1683 |
- type: precision_at_10
|
1684 |
+
value: 26.161
|
1685 |
- type: precision_at_100
|
1686 |
+
value: 7.867
|
1687 |
- type: precision_at_1000
|
1688 |
+
value: 2.043
|
1689 |
- type: precision_at_3
|
1690 |
+
value: 39.112
|
1691 |
- type: precision_at_5
|
1692 |
+
value: 34.18
|
1693 |
- type: recall_at_1
|
1694 |
+
value: 5.894
|
1695 |
- type: recall_at_10
|
1696 |
+
value: 16.88
|
1697 |
- type: recall_at_100
|
1698 |
+
value: 30.671
|
1699 |
- type: recall_at_1000
|
1700 |
+
value: 61.42999999999999
|
1701 |
- type: recall_at_3
|
1702 |
+
value: 11.022
|
1703 |
- type: recall_at_5
|
1704 |
+
value: 13.697999999999999
|
1705 |
- task:
|
1706 |
type: Retrieval
|
1707 |
dataset:
|
|
|
1712 |
revision: None
|
1713 |
metrics:
|
1714 |
- type: map_at_1
|
1715 |
+
value: 38.440999999999995
|
1716 |
- type: map_at_10
|
1717 |
+
value: 54.187
|
1718 |
- type: map_at_100
|
1719 |
+
value: 55.022000000000006
|
1720 |
- type: map_at_1000
|
1721 |
+
value: 55.044000000000004
|
1722 |
- type: map_at_3
|
1723 |
+
value: 50.174
|
1724 |
- type: map_at_5
|
1725 |
+
value: 52.61
|
1726 |
- type: mrr_at_1
|
1727 |
+
value: 42.903000000000006
|
1728 |
- type: mrr_at_10
|
1729 |
+
value: 56.699
|
1730 |
- type: mrr_at_100
|
1731 |
+
value: 57.31
|
1732 |
- type: mrr_at_1000
|
1733 |
+
value: 57.325
|
1734 |
- type: mrr_at_3
|
1735 |
+
value: 53.63099999999999
|
1736 |
- type: mrr_at_5
|
1737 |
+
value: 55.596000000000004
|
1738 |
- type: ndcg_at_1
|
1739 |
+
value: 42.903000000000006
|
1740 |
- type: ndcg_at_10
|
1741 |
+
value: 61.434
|
1742 |
- type: ndcg_at_100
|
1743 |
+
value: 64.852
|
1744 |
- type: ndcg_at_1000
|
1745 |
+
value: 65.36
|
1746 |
- type: ndcg_at_3
|
1747 |
+
value: 54.193000000000005
|
1748 |
- type: ndcg_at_5
|
1749 |
+
value: 58.15
|
1750 |
- type: precision_at_1
|
1751 |
+
value: 42.903000000000006
|
1752 |
- type: precision_at_10
|
1753 |
+
value: 9.623
|
1754 |
- type: precision_at_100
|
1755 |
+
value: 1.1560000000000001
|
1756 |
- type: precision_at_1000
|
1757 |
value: 0.12
|
1758 |
- type: precision_at_3
|
1759 |
+
value: 24.034
|
1760 |
- type: precision_at_5
|
1761 |
+
value: 16.779
|
1762 |
- type: recall_at_1
|
1763 |
+
value: 38.440999999999995
|
1764 |
- type: recall_at_10
|
1765 |
+
value: 80.72399999999999
|
1766 |
- type: recall_at_100
|
1767 |
+
value: 95.329
|
1768 |
- type: recall_at_1000
|
1769 |
+
value: 99.059
|
1770 |
- type: recall_at_3
|
1771 |
+
value: 62.343
|
1772 |
- type: recall_at_5
|
1773 |
+
value: 71.304
|
1774 |
- task:
|
1775 |
type: Retrieval
|
1776 |
dataset:
|
|
|
1781 |
revision: None
|
1782 |
metrics:
|
1783 |
- type: map_at_1
|
1784 |
+
value: 70.85000000000001
|
1785 |
- type: map_at_10
|
1786 |
+
value: 84.54
|
1787 |
- type: map_at_100
|
1788 |
+
value: 85.148
|
1789 |
- type: map_at_1000
|
1790 |
+
value: 85.168
|
1791 |
- type: map_at_3
|
1792 |
+
value: 81.631
|
1793 |
- type: map_at_5
|
1794 |
+
value: 83.45700000000001
|
1795 |
- type: mrr_at_1
|
1796 |
+
value: 81.58
|
1797 |
- type: mrr_at_10
|
1798 |
+
value: 87.732
|
1799 |
- type: mrr_at_100
|
1800 |
+
value: 87.825
|
1801 |
- type: mrr_at_1000
|
1802 |
+
value: 87.82600000000001
|
1803 |
- type: mrr_at_3
|
1804 |
+
value: 86.783
|
1805 |
- type: mrr_at_5
|
1806 |
+
value: 87.437
|
1807 |
- type: ndcg_at_1
|
1808 |
+
value: 81.56
|
1809 |
- type: ndcg_at_10
|
1810 |
+
value: 88.32900000000001
|
1811 |
- type: ndcg_at_100
|
1812 |
+
value: 89.513
|
1813 |
- type: ndcg_at_1000
|
1814 |
+
value: 89.63799999999999
|
1815 |
- type: ndcg_at_3
|
1816 |
+
value: 85.51100000000001
|
1817 |
- type: ndcg_at_5
|
1818 |
+
value: 87.062
|
1819 |
- type: precision_at_1
|
1820 |
+
value: 81.56
|
1821 |
- type: precision_at_10
|
1822 |
+
value: 13.349
|
1823 |
- type: precision_at_100
|
1824 |
+
value: 1.518
|
1825 |
- type: precision_at_1000
|
1826 |
value: 0.156
|
1827 |
- type: precision_at_3
|
1828 |
+
value: 37.293
|
1829 |
- type: precision_at_5
|
1830 |
+
value: 24.502
|
1831 |
- type: recall_at_1
|
1832 |
+
value: 70.85000000000001
|
1833 |
- type: recall_at_10
|
1834 |
+
value: 95.351
|
1835 |
- type: recall_at_100
|
1836 |
+
value: 99.405
|
1837 |
- type: recall_at_1000
|
1838 |
+
value: 99.958
|
1839 |
- type: recall_at_3
|
1840 |
+
value: 87.184
|
1841 |
- type: recall_at_5
|
1842 |
+
value: 91.625
|
1843 |
- task:
|
1844 |
type: Clustering
|
1845 |
dataset:
|
|
|
1850 |
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
|
1851 |
metrics:
|
1852 |
- type: v_measure
|
1853 |
+
value: 56.81818576893834
|
1854 |
- task:
|
1855 |
type: Clustering
|
1856 |
dataset:
|
|
|
1861 |
revision: 282350215ef01743dc01b456c7f5241fa8937f16
|
1862 |
metrics:
|
1863 |
- type: v_measure
|
1864 |
+
value: 61.57033658868022
|
1865 |
- task:
|
1866 |
type: Retrieval
|
1867 |
dataset:
|
|
|
1872 |
revision: None
|
1873 |
metrics:
|
1874 |
- type: map_at_1
|
1875 |
+
value: 4.468
|
1876 |
- type: map_at_10
|
1877 |
+
value: 11.109
|
1878 |
- type: map_at_100
|
1879 |
+
value: 12.921
|
1880 |
- type: map_at_1000
|
1881 |
+
value: 13.187999999999999
|
1882 |
- type: map_at_3
|
1883 |
+
value: 8.094999999999999
|
1884 |
- type: map_at_5
|
1885 |
+
value: 9.664
|
1886 |
- type: mrr_at_1
|
1887 |
+
value: 22.1
|
1888 |
- type: mrr_at_10
|
1889 |
+
value: 32.482
|
1890 |
- type: mrr_at_100
|
1891 |
+
value: 33.558
|
1892 |
- type: mrr_at_1000
|
1893 |
+
value: 33.623999999999995
|
1894 |
- type: mrr_at_3
|
1895 |
+
value: 29.25
|
1896 |
- type: mrr_at_5
|
1897 |
+
value: 31.080000000000002
|
1898 |
- type: ndcg_at_1
|
1899 |
+
value: 22.1
|
1900 |
- type: ndcg_at_10
|
1901 |
+
value: 18.695999999999998
|
1902 |
- type: ndcg_at_100
|
1903 |
+
value: 25.749
|
1904 |
- type: ndcg_at_1000
|
1905 |
+
value: 30.711
|
1906 |
- type: ndcg_at_3
|
1907 |
+
value: 17.974
|
1908 |
- type: ndcg_at_5
|
1909 |
+
value: 15.684000000000001
|
1910 |
- type: precision_at_1
|
1911 |
+
value: 22.1
|
1912 |
- type: precision_at_10
|
1913 |
+
value: 9.56
|
1914 |
- type: precision_at_100
|
1915 |
+
value: 1.966
|
1916 |
- type: precision_at_1000
|
1917 |
+
value: 0.316
|
1918 |
- type: precision_at_3
|
1919 |
+
value: 16.667
|
1920 |
- type: precision_at_5
|
1921 |
+
value: 13.68
|
1922 |
- type: recall_at_1
|
1923 |
+
value: 4.468
|
1924 |
- type: recall_at_10
|
1925 |
+
value: 19.373
|
1926 |
- type: recall_at_100
|
1927 |
+
value: 39.853
|
1928 |
- type: recall_at_1000
|
1929 |
+
value: 64.118
|
1930 |
- type: recall_at_3
|
1931 |
+
value: 10.133000000000001
|
1932 |
- type: recall_at_5
|
1933 |
+
value: 13.877999999999998
|
1934 |
- task:
|
1935 |
type: STS
|
1936 |
dataset:
|
|
|
1941 |
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
|
1942 |
metrics:
|
1943 |
- type: cos_sim_pearson
|
1944 |
+
value: 80.11452150923512
|
1945 |
- type: cos_sim_spearman
|
1946 |
+
value: 77.3007421887329
|
1947 |
- type: euclidean_pearson
|
1948 |
+
value: 78.2493681078981
|
1949 |
- type: euclidean_spearman
|
1950 |
+
value: 77.3007432741821
|
1951 |
- type: manhattan_pearson
|
1952 |
+
value: 78.19716818242554
|
1953 |
- type: manhattan_spearman
|
1954 |
+
value: 77.26439033199102
|
1955 |
- task:
|
1956 |
type: STS
|
1957 |
dataset:
|
|
|
1962 |
revision: a0d554a64d88156834ff5ae9920b964011b16384
|
1963 |
metrics:
|
1964 |
- type: cos_sim_pearson
|
1965 |
+
value: 82.70293570563516
|
1966 |
- type: cos_sim_spearman
|
1967 |
+
value: 77.97040896962338
|
1968 |
- type: euclidean_pearson
|
1969 |
+
value: 77.98827330337348
|
1970 |
- type: euclidean_spearman
|
1971 |
+
value: 77.9704358930525
|
1972 |
- type: manhattan_pearson
|
1973 |
+
value: 78.06991702207395
|
1974 |
- type: manhattan_spearman
|
1975 |
+
value: 78.03857843100195
|
1976 |
- task:
|
1977 |
type: STS
|
1978 |
dataset:
|
|
|
1983 |
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
|
1984 |
metrics:
|
1985 |
- type: cos_sim_pearson
|
1986 |
+
value: 77.81236960157503
|
1987 |
- type: cos_sim_spearman
|
1988 |
+
value: 79.38801416063187
|
1989 |
- type: euclidean_pearson
|
1990 |
+
value: 79.35003045476847
|
1991 |
- type: euclidean_spearman
|
1992 |
+
value: 79.38797289536578
|
1993 |
- type: manhattan_pearson
|
1994 |
+
value: 79.33155563344724
|
1995 |
- type: manhattan_spearman
|
1996 |
+
value: 79.3858955436803
|
1997 |
- task:
|
1998 |
type: STS
|
1999 |
dataset:
|
|
|
2004 |
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
|
2005 |
metrics:
|
2006 |
- type: cos_sim_pearson
|
2007 |
+
value: 77.35604880089507
|
2008 |
- type: cos_sim_spearman
|
2009 |
+
value: 78.17327332594571
|
2010 |
- type: euclidean_pearson
|
2011 |
+
value: 77.30302038209295
|
2012 |
- type: euclidean_spearman
|
2013 |
+
value: 78.17327332594571
|
2014 |
- type: manhattan_pearson
|
2015 |
+
value: 77.31323781935417
|
2016 |
- type: manhattan_spearman
|
2017 |
+
value: 78.20141256686921
|
2018 |
- task:
|
2019 |
type: STS
|
2020 |
dataset:
|
|
|
2025 |
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
|
2026 |
metrics:
|
2027 |
- type: cos_sim_pearson
|
2028 |
+
value: 84.29348597583
|
2029 |
- type: cos_sim_spearman
|
2030 |
+
value: 85.50877410088334
|
2031 |
- type: euclidean_pearson
|
2032 |
+
value: 85.22367284169081
|
2033 |
- type: euclidean_spearman
|
2034 |
+
value: 85.50877410088334
|
2035 |
- type: manhattan_pearson
|
2036 |
+
value: 85.17979979737612
|
2037 |
- type: manhattan_spearman
|
2038 |
+
value: 85.46459282596254
|
2039 |
- task:
|
2040 |
type: STS
|
2041 |
dataset:
|
|
|
2046 |
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
|
2047 |
metrics:
|
2048 |
- type: cos_sim_pearson
|
2049 |
+
value: 83.16190794761513
|
2050 |
- type: cos_sim_spearman
|
2051 |
+
value: 84.94610605287254
|
2052 |
- type: euclidean_pearson
|
2053 |
+
value: 83.95587174131369
|
2054 |
- type: euclidean_spearman
|
2055 |
+
value: 84.94610605287254
|
2056 |
- type: manhattan_pearson
|
2057 |
+
value: 83.99025745366798
|
2058 |
- type: manhattan_spearman
|
2059 |
+
value: 84.98123107148953
|
2060 |
- task:
|
2061 |
type: STS
|
2062 |
dataset:
|
|
|
2067 |
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
|
2068 |
metrics:
|
2069 |
- type: cos_sim_pearson
|
2070 |
+
value: 85.3047190687711
|
2071 |
- type: cos_sim_spearman
|
2072 |
+
value: 85.86642469958113
|
2073 |
- type: euclidean_pearson
|
2074 |
+
value: 86.74377658528041
|
2075 |
- type: euclidean_spearman
|
2076 |
+
value: 85.86642469958113
|
2077 |
- type: manhattan_pearson
|
2078 |
+
value: 86.56967885987439
|
2079 |
- type: manhattan_spearman
|
2080 |
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value: 85.63613272583275
|
2081 |
- task:
|
2082 |
type: STS
|
2083 |
dataset:
|
|
|
2088 |
revision: eea2b4fe26a775864c896887d910b76a8098ad3f
|
2089 |
metrics:
|
2090 |
- type: cos_sim_pearson
|
2091 |
+
value: 64.8298932792099
|
2092 |
- type: cos_sim_spearman
|
2093 |
+
value: 64.27626667878636
|
2094 |
- type: euclidean_pearson
|
2095 |
+
value: 66.01603861201576
|
2096 |
- type: euclidean_spearman
|
2097 |
+
value: 64.27626667878636
|
2098 |
- type: manhattan_pearson
|
2099 |
+
value: 66.31232809448106
|
2100 |
- type: manhattan_spearman
|
2101 |
+
value: 64.46190921631559
|
2102 |
- task:
|
2103 |
type: STS
|
2104 |
dataset:
|
|
|
2109 |
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
|
2110 |
metrics:
|
2111 |
- type: cos_sim_pearson
|
2112 |
+
value: 82.73696291316243
|
2113 |
- type: cos_sim_spearman
|
2114 |
+
value: 83.41508337893958
|
2115 |
- type: euclidean_pearson
|
2116 |
+
value: 82.8827053024064
|
2117 |
- type: euclidean_spearman
|
2118 |
+
value: 83.41508337893958
|
2119 |
- type: manhattan_pearson
|
2120 |
+
value: 82.85613329045803
|
2121 |
- type: manhattan_spearman
|
2122 |
+
value: 83.40522047443645
|
2123 |
- task:
|
2124 |
type: Reranking
|
2125 |
dataset:
|
|
|
2130 |
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
|
2131 |
metrics:
|
2132 |
- type: map
|
2133 |
+
value: 75.51490079179645
|
2134 |
- type: mrr
|
2135 |
+
value: 92.6809655486126
|
2136 |
- task:
|
2137 |
type: Retrieval
|
2138 |
dataset:
|
|
|
2143 |
revision: None
|
2144 |
metrics:
|
2145 |
- type: map_at_1
|
2146 |
+
value: 58.594
|
2147 |
- type: map_at_10
|
2148 |
+
value: 67.208
|
2149 |
- type: map_at_100
|
2150 |
+
value: 67.702
|
2151 |
- type: map_at_1000
|
2152 |
+
value: 67.73
|
2153 |
- type: map_at_3
|
2154 |
+
value: 64.815
|
2155 |
- type: map_at_5
|
2156 |
+
value: 65.946
|
2157 |
- type: mrr_at_1
|
2158 |
+
value: 61.667
|
2159 |
- type: mrr_at_10
|
2160 |
+
value: 68.52000000000001
|
2161 |
- type: mrr_at_100
|
2162 |
+
value: 68.888
|
2163 |
- type: mrr_at_1000
|
2164 |
+
value: 68.911
|
2165 |
- type: mrr_at_3
|
2166 |
+
value: 66.833
|
2167 |
- type: mrr_at_5
|
2168 |
+
value: 67.617
|
2169 |
- type: ndcg_at_1
|
2170 |
+
value: 61.667
|
2171 |
- type: ndcg_at_10
|
2172 |
+
value: 71.511
|
2173 |
- type: ndcg_at_100
|
2174 |
+
value: 73.765
|
2175 |
- type: ndcg_at_1000
|
2176 |
+
value: 74.40299999999999
|
2177 |
- type: ndcg_at_3
|
2178 |
+
value: 67.411
|
2179 |
- type: ndcg_at_5
|
2180 |
+
value: 68.88
|
2181 |
- type: precision_at_1
|
2182 |
+
value: 61.667
|
2183 |
- type: precision_at_10
|
2184 |
+
value: 9.433
|
2185 |
- type: precision_at_100
|
2186 |
+
value: 1.0670000000000002
|
2187 |
- type: precision_at_1000
|
2188 |
value: 0.11199999999999999
|
2189 |
- type: precision_at_3
|
2190 |
+
value: 26.222
|
2191 |
- type: precision_at_5
|
2192 |
+
value: 16.866999999999997
|
2193 |
- type: recall_at_1
|
2194 |
+
value: 58.594
|
2195 |
- type: recall_at_10
|
2196 |
+
value: 83.439
|
2197 |
- type: recall_at_100
|
2198 |
+
value: 94.1
|
2199 |
- type: recall_at_1000
|
2200 |
+
value: 99.0
|
2201 |
- type: recall_at_3
|
2202 |
+
value: 71.922
|
2203 |
- type: recall_at_5
|
2204 |
+
value: 75.678
|
2205 |
- task:
|
2206 |
type: PairClassification
|
2207 |
dataset:
|
|
|
2212 |
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
|
2213 |
metrics:
|
2214 |
- type: cos_sim_accuracy
|
2215 |
+
value: 99.7990099009901
|
2216 |
- type: cos_sim_ap
|
2217 |
+
value: 94.8316184070519
|
2218 |
- type: cos_sim_f1
|
2219 |
+
value: 89.75265017667844
|
2220 |
- type: cos_sim_precision
|
2221 |
+
value: 90.62181447502549
|
2222 |
- type: cos_sim_recall
|
2223 |
+
value: 88.9
|
2224 |
- type: dot_accuracy
|
2225 |
+
value: 99.7990099009901
|
2226 |
- type: dot_ap
|
2227 |
+
value: 94.831611518794
|
2228 |
- type: dot_f1
|
2229 |
+
value: 89.75265017667844
|
2230 |
- type: dot_precision
|
2231 |
+
value: 90.62181447502549
|
2232 |
- type: dot_recall
|
2233 |
+
value: 88.9
|
2234 |
- type: euclidean_accuracy
|
2235 |
+
value: 99.7990099009901
|
2236 |
- type: euclidean_ap
|
2237 |
+
value: 94.83161335144017
|
2238 |
- type: euclidean_f1
|
2239 |
+
value: 89.75265017667844
|
2240 |
- type: euclidean_precision
|
2241 |
+
value: 90.62181447502549
|
2242 |
- type: euclidean_recall
|
2243 |
+
value: 88.9
|
2244 |
- type: manhattan_accuracy
|
2245 |
+
value: 99.8
|
2246 |
- type: manhattan_ap
|
2247 |
+
value: 94.84210829841739
|
2248 |
- type: manhattan_f1
|
2249 |
+
value: 89.60905349794238
|
2250 |
- type: manhattan_precision
|
2251 |
+
value: 92.26694915254238
|
2252 |
- type: manhattan_recall
|
2253 |
+
value: 87.1
|
2254 |
- type: max_accuracy
|
2255 |
+
value: 99.8
|
2256 |
- type: max_ap
|
2257 |
+
value: 94.84210829841739
|
2258 |
- type: max_f1
|
2259 |
+
value: 89.75265017667844
|
2260 |
- task:
|
2261 |
type: Clustering
|
2262 |
dataset:
|
|
|
2267 |
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
|
2268 |
metrics:
|
2269 |
- type: v_measure
|
2270 |
+
value: 63.18343792633894
|
2271 |
- task:
|
2272 |
type: Clustering
|
2273 |
dataset:
|
|
|
2278 |
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
|
2279 |
metrics:
|
2280 |
- type: v_measure
|
2281 |
+
value: 33.50944549814364
|
2282 |
- task:
|
2283 |
type: Reranking
|
2284 |
dataset:
|
|
|
2289 |
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
|
2290 |
metrics:
|
2291 |
- type: map
|
2292 |
+
value: 48.89100016028111
|
2293 |
- type: mrr
|
2294 |
+
value: 49.607630931160344
|
2295 |
- task:
|
2296 |
type: Summarization
|
2297 |
dataset:
|
|
|
2302 |
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
|
2303 |
metrics:
|
2304 |
- type: cos_sim_pearson
|
2305 |
+
value: 30.628145384101522
|
2306 |
- type: cos_sim_spearman
|
2307 |
+
value: 31.275306930726675
|
2308 |
- type: dot_pearson
|
2309 |
+
value: 30.62814883550051
|
2310 |
- type: dot_spearman
|
2311 |
+
value: 31.275306930726675
|
2312 |
- task:
|
2313 |
type: Retrieval
|
2314 |
dataset:
|
|
|
2319 |
revision: None
|
2320 |
metrics:
|
2321 |
- type: map_at_1
|
2322 |
+
value: 0.26
|
2323 |
- type: map_at_10
|
2324 |
+
value: 2.163
|
2325 |
- type: map_at_100
|
2326 |
+
value: 12.29
|
2327 |
- type: map_at_1000
|
2328 |
+
value: 29.221999999999998
|
2329 |
- type: map_at_3
|
2330 |
+
value: 0.729
|
2331 |
- type: map_at_5
|
2332 |
+
value: 1.161
|
2333 |
- type: mrr_at_1
|
2334 |
+
value: 96.0
|
2335 |
- type: mrr_at_10
|
2336 |
+
value: 98.0
|
2337 |
- type: mrr_at_100
|
2338 |
+
value: 98.0
|
2339 |
- type: mrr_at_1000
|
2340 |
+
value: 98.0
|
2341 |
- type: mrr_at_3
|
2342 |
+
value: 98.0
|
2343 |
- type: mrr_at_5
|
2344 |
+
value: 98.0
|
2345 |
- type: ndcg_at_1
|
2346 |
+
value: 89.0
|
2347 |
- type: ndcg_at_10
|
2348 |
+
value: 82.312
|
2349 |
- type: ndcg_at_100
|
2350 |
+
value: 61.971
|
2351 |
- type: ndcg_at_1000
|
2352 |
+
value: 54.065
|
2353 |
- type: ndcg_at_3
|
2354 |
+
value: 87.87700000000001
|
2355 |
- type: ndcg_at_5
|
2356 |
+
value: 85.475
|
2357 |
- type: precision_at_1
|
2358 |
+
value: 96.0
|
2359 |
- type: precision_at_10
|
2360 |
+
value: 87.4
|
2361 |
- type: precision_at_100
|
2362 |
+
value: 64.02
|
2363 |
- type: precision_at_1000
|
2364 |
+
value: 24.093999999999998
|
2365 |
- type: precision_at_3
|
2366 |
+
value: 94.0
|
2367 |
- type: precision_at_5
|
2368 |
+
value: 90.8
|
2369 |
- type: recall_at_1
|
2370 |
+
value: 0.26
|
2371 |
- type: recall_at_10
|
2372 |
+
value: 2.302
|
2373 |
- type: recall_at_100
|
2374 |
+
value: 15.148
|
2375 |
- type: recall_at_1000
|
2376 |
+
value: 50.55
|
2377 |
- type: recall_at_3
|
2378 |
+
value: 0.744
|
2379 |
- type: recall_at_5
|
2380 |
+
value: 1.198
|
2381 |
- task:
|
2382 |
type: Retrieval
|
2383 |
dataset:
|
|
|
2388 |
revision: None
|
2389 |
metrics:
|
2390 |
- type: map_at_1
|
2391 |
+
value: 2.217
|
2392 |
- type: map_at_10
|
2393 |
+
value: 11.378
|
2394 |
- type: map_at_100
|
2395 |
+
value: 18.022
|
2396 |
- type: map_at_1000
|
2397 |
+
value: 19.544
|
2398 |
- type: map_at_3
|
2399 |
+
value: 6.079
|
2400 |
- type: map_at_5
|
2401 |
+
value: 8.559
|
2402 |
- type: mrr_at_1
|
2403 |
value: 28.571
|
2404 |
- type: mrr_at_10
|
2405 |
+
value: 48.423
|
2406 |
- type: mrr_at_100
|
2407 |
+
value: 49.028
|
2408 |
- type: mrr_at_1000
|
2409 |
+
value: 49.028
|
2410 |
- type: mrr_at_3
|
2411 |
+
value: 44.897999999999996
|
2412 |
- type: mrr_at_5
|
2413 |
+
value: 46.531
|
2414 |
- type: ndcg_at_1
|
2415 |
value: 25.509999999999998
|
2416 |
- type: ndcg_at_10
|
2417 |
+
value: 27.860000000000003
|
2418 |
- type: ndcg_at_100
|
2419 |
+
value: 39.34
|
2420 |
- type: ndcg_at_1000
|
2421 |
+
value: 50.21
|
2422 |
- type: ndcg_at_3
|
2423 |
+
value: 30.968
|
2424 |
- type: ndcg_at_5
|
2425 |
+
value: 29.541
|
2426 |
- type: precision_at_1
|
2427 |
value: 28.571
|
2428 |
- type: precision_at_10
|
2429 |
+
value: 25.918000000000003
|
2430 |
- type: precision_at_100
|
2431 |
+
value: 8.184
|
2432 |
- type: precision_at_1000
|
2433 |
+
value: 1.545
|
2434 |
- type: precision_at_3
|
2435 |
+
value: 35.374
|
2436 |
- type: precision_at_5
|
2437 |
+
value: 31.837
|
2438 |
- type: recall_at_1
|
2439 |
+
value: 2.217
|
2440 |
- type: recall_at_10
|
2441 |
+
value: 18.511
|
2442 |
- type: recall_at_100
|
2443 |
+
value: 50.178
|
2444 |
- type: recall_at_1000
|
2445 |
+
value: 83.07600000000001
|
2446 |
- type: recall_at_3
|
2447 |
+
value: 7.811999999999999
|
2448 |
- type: recall_at_5
|
2449 |
+
value: 11.684
|
2450 |
- task:
|
2451 |
type: Classification
|
2452 |
dataset:
|
|
|
2457 |
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
|
2458 |
metrics:
|
2459 |
- type: accuracy
|
2460 |
+
value: 71.386
|
2461 |
- type: ap
|
2462 |
+
value: 14.58573366644018
|
2463 |
- type: f1
|
2464 |
+
value: 55.0170316975105
|
2465 |
- task:
|
2466 |
type: Classification
|
2467 |
dataset:
|
|
|
2472 |
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
|
2473 |
metrics:
|
2474 |
- type: accuracy
|
2475 |
+
value: 60.868704018109796
|
2476 |
- type: f1
|
2477 |
+
value: 61.175908652496624
|
2478 |
- task:
|
2479 |
type: Clustering
|
2480 |
dataset:
|
|
|
2485 |
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
|
2486 |
metrics:
|
2487 |
- type: v_measure
|
2488 |
+
value: 48.72082824812323
|
2489 |
- task:
|
2490 |
type: PairClassification
|
2491 |
dataset:
|
|
|
2496 |
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
|
2497 |
metrics:
|
2498 |
- type: cos_sim_accuracy
|
2499 |
+
value: 85.43839780652083
|
2500 |
- type: cos_sim_ap
|
2501 |
+
value: 72.55258980537292
|
2502 |
- type: cos_sim_f1
|
2503 |
+
value: 66.4145419055752
|
2504 |
- type: cos_sim_precision
|
2505 |
+
value: 61.765373269798054
|
2506 |
- type: cos_sim_recall
|
2507 |
+
value: 71.82058047493403
|
2508 |
- type: dot_accuracy
|
2509 |
+
value: 85.43839780652083
|
2510 |
- type: dot_ap
|
2511 |
+
value: 72.55256370197756
|
2512 |
- type: dot_f1
|
2513 |
+
value: 66.4145419055752
|
2514 |
- type: dot_precision
|
2515 |
+
value: 61.765373269798054
|
2516 |
- type: dot_recall
|
2517 |
+
value: 71.82058047493403
|
2518 |
- type: euclidean_accuracy
|
2519 |
+
value: 85.43839780652083
|
2520 |
- type: euclidean_ap
|
2521 |
+
value: 72.55259011957311
|
2522 |
- type: euclidean_f1
|
2523 |
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value: 66.4145419055752
|
2524 |
- type: euclidean_precision
|
2525 |
+
value: 61.765373269798054
|
2526 |
- type: euclidean_recall
|
2527 |
+
value: 71.82058047493403
|
2528 |
- type: manhattan_accuracy
|
2529 |
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value: 85.40263455921799
|
2530 |
- type: manhattan_ap
|
2531 |
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value: 72.47856062032
|
2532 |
- type: manhattan_f1
|
2533 |
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value: 66.39413249969942
|
2534 |
- type: manhattan_precision
|
2535 |
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value: 60.989617848464775
|
2536 |
- type: manhattan_recall
|
2537 |
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value: 72.84960422163589
|
2538 |
- type: max_accuracy
|
2539 |
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value: 85.43839780652083
|
2540 |
- type: max_ap
|
2541 |
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value: 72.55259011957311
|
2542 |
- type: max_f1
|
2543 |
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value: 66.4145419055752
|
2544 |
- task:
|
2545 |
type: PairClassification
|
2546 |
dataset:
|
|
|
2551 |
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
|
2552 |
metrics:
|
2553 |
- type: cos_sim_accuracy
|
2554 |
+
value: 89.24981565568363
|
2555 |
- type: cos_sim_ap
|
2556 |
+
value: 86.38437585690401
|
2557 |
- type: cos_sim_f1
|
2558 |
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value: 78.79039565086076
|
2559 |
- type: cos_sim_precision
|
2560 |
+
value: 77.29629629629629
|
2561 |
- type: cos_sim_recall
|
2562 |
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value: 80.34339390206344
|
2563 |
- type: dot_accuracy
|
2564 |
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value: 89.24981565568363
|
2565 |
- type: dot_ap
|
2566 |
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value: 86.38437587564587
|
2567 |
- type: dot_f1
|
2568 |
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value: 78.79039565086076
|
2569 |
- type: dot_precision
|
2570 |
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value: 77.29629629629629
|
2571 |
- type: dot_recall
|
2572 |
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value: 80.34339390206344
|
2573 |
- type: euclidean_accuracy
|
2574 |
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value: 89.24981565568363
|
2575 |
- type: euclidean_ap
|
2576 |
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value: 86.38437691024106
|
2577 |
- type: euclidean_f1
|
2578 |
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value: 78.79039565086076
|
2579 |
- type: euclidean_precision
|
2580 |
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value: 77.29629629629629
|
2581 |
- type: euclidean_recall
|
2582 |
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value: 80.34339390206344
|
2583 |
- type: manhattan_accuracy
|
2584 |
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value: 89.25563705514806
|
2585 |
- type: manhattan_ap
|
2586 |
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value: 86.35729146774388
|
2587 |
- type: manhattan_f1
|
2588 |
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value: 78.7238059278837
|
2589 |
- type: manhattan_precision
|
2590 |
+
value: 77.23938653034007
|
2591 |
- type: manhattan_recall
|
2592 |
+
value: 80.26639975361873
|
2593 |
- type: max_accuracy
|
2594 |
+
value: 89.25563705514806
|
2595 |
- type: max_ap
|
2596 |
+
value: 86.38437691024106
|
2597 |
- type: max_f1
|
2598 |
+
value: 78.79039565086076
|
2599 |
---
|