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Parent(s):
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Update README.md
Browse files
README.md
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@@ -11,7 +11,7 @@ datasets:
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language: en
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license: apache-2.0
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model-index:
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- name: jina-
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results:
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- task:
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type: Classification
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@@ -23,11 +23,11 @@ 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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@@ -38,11 +38,11 @@ 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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@@ -53,561 +53,652 @@ 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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type:
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name: MTEB
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config: default
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split: test
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revision: None
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metrics:
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- type: map_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:
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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:
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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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type: BeIR/cqadupstack
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-
name: MTEB
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config: default
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split: test
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revision: None
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metrics:
|
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- type: map_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: 1.
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- type: precision_at_1000
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value: 0.19499999999999998
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- type: precision_at_3
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-
value:
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- type: precision_at_5
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-
value:
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- type: recall_at_1
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-
value:
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- type: recall_at_10
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-
value:
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- type: recall_at_100
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-
value:
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- type: recall_at_1000
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-
value:
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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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type: BeIR/cqadupstack
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-
name: MTEB
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config: default
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split: test
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revision: None
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metrics:
|
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- type: map_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: 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:
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- type: precision_at_5
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-
value:
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- type: recall_at_1
|
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-
value:
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- type: recall_at_10
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-
value:
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- type: recall_at_100
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-
value:
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- type: recall_at_1000
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-
value:
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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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type: BeIR/cqadupstack
|
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-
name: MTEB
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config: default
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split: test
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revision: None
|
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metrics:
|
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- type: map_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:
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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:
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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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type: BeIR/cqadupstack
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-
name: MTEB
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config: default
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split: test
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revision: None
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metrics:
|
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- type: map_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: 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:
|
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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
|
403 |
-
value:
|
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- task:
|
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type: Retrieval
|
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dataset:
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type: BeIR/cqadupstack
|
408 |
-
name: MTEB
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config: default
|
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split: test
|
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revision: None
|
412 |
metrics:
|
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- type: map_at_1
|
414 |
-
value:
|
415 |
- type: map_at_10
|
416 |
-
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:
|
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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:
|
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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
|
475 |
dataset:
|
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type: BeIR/cqadupstack
|
477 |
-
name: MTEB
|
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config: default
|
479 |
split: test
|
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revision: None
|
481 |
metrics:
|
482 |
- type: map_at_1
|
483 |
-
value:
|
484 |
- type: map_at_10
|
485 |
-
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:
|
508 |
- type: ndcg_at_10
|
509 |
-
value:
|
510 |
- type: ndcg_at_100
|
511 |
-
value:
|
512 |
- type: ndcg_at_1000
|
513 |
-
value:
|
514 |
- type: ndcg_at_3
|
515 |
-
value:
|
516 |
- type: ndcg_at_5
|
517 |
-
value:
|
518 |
- type: precision_at_1
|
519 |
-
value:
|
520 |
- type: precision_at_10
|
521 |
-
value:
|
522 |
- type: precision_at_100
|
523 |
-
value: 1.
|
524 |
- type: precision_at_1000
|
525 |
-
value: 0.
|
526 |
- type: precision_at_3
|
527 |
-
value:
|
528 |
- type: precision_at_5
|
529 |
-
value:
|
530 |
- type: recall_at_1
|
531 |
-
value:
|
532 |
- type: recall_at_10
|
533 |
-
value:
|
534 |
- type: recall_at_100
|
535 |
-
value:
|
536 |
- type: recall_at_1000
|
537 |
-
value:
|
538 |
- type: recall_at_3
|
539 |
-
value:
|
540 |
- type: recall_at_5
|
541 |
-
value:
|
542 |
- task:
|
543 |
type: Retrieval
|
544 |
dataset:
|
545 |
type: BeIR/cqadupstack
|
546 |
-
name: MTEB
|
547 |
config: default
|
548 |
split: test
|
549 |
revision: None
|
550 |
metrics:
|
551 |
- type: map_at_1
|
552 |
-
value:
|
553 |
- type: map_at_10
|
554 |
-
value:
|
555 |
- type: map_at_100
|
556 |
-
value:
|
557 |
- type: map_at_1000
|
558 |
-
value:
|
559 |
- type: map_at_3
|
560 |
-
value:
|
561 |
- type: map_at_5
|
562 |
-
value:
|
563 |
- type: mrr_at_1
|
564 |
-
value:
|
565 |
- type: mrr_at_10
|
566 |
-
value:
|
567 |
- type: mrr_at_100
|
568 |
-
value:
|
569 |
- type: mrr_at_1000
|
570 |
-
value:
|
571 |
- type: mrr_at_3
|
572 |
-
value:
|
573 |
- type: mrr_at_5
|
574 |
-
value:
|
575 |
- type: ndcg_at_1
|
576 |
-
value:
|
577 |
- type: ndcg_at_10
|
578 |
-
value:
|
579 |
- type: ndcg_at_100
|
580 |
-
value:
|
581 |
- type: ndcg_at_1000
|
582 |
-
value:
|
583 |
- type: ndcg_at_3
|
584 |
-
value:
|
585 |
- type: ndcg_at_5
|
586 |
-
value:
|
587 |
- type: precision_at_1
|
588 |
-
value:
|
589 |
- type: precision_at_10
|
590 |
-
value:
|
591 |
- type: precision_at_100
|
592 |
-
value: 1.
|
593 |
- type: precision_at_1000
|
594 |
-
value: 0.
|
595 |
- type: precision_at_3
|
596 |
-
value:
|
597 |
- type: precision_at_5
|
598 |
-
value:
|
599 |
- type: recall_at_1
|
600 |
-
value:
|
601 |
- type: recall_at_10
|
602 |
-
value:
|
603 |
- type: recall_at_100
|
604 |
-
value:
|
605 |
- type: recall_at_1000
|
606 |
-
value: 91.
|
607 |
- type: recall_at_3
|
608 |
-
value:
|
609 |
- type: recall_at_5
|
610 |
-
value:
|
611 |
- task:
|
612 |
type: Retrieval
|
613 |
dataset:
|
@@ -618,65 +709,65 @@ model-index:
|
|
618 |
revision: None
|
619 |
metrics:
|
620 |
- type: map_at_1
|
621 |
-
value:
|
622 |
- type: map_at_10
|
623 |
-
value:
|
624 |
- type: map_at_100
|
625 |
-
value:
|
626 |
- type: map_at_1000
|
627 |
-
value:
|
628 |
- type: map_at_3
|
629 |
-
value:
|
630 |
- type: map_at_5
|
631 |
-
value:
|
632 |
- type: mrr_at_1
|
633 |
-
value:
|
634 |
- type: mrr_at_10
|
635 |
-
value:
|
636 |
- type: mrr_at_100
|
637 |
-
value:
|
638 |
- type: mrr_at_1000
|
639 |
-
value:
|
640 |
- type: mrr_at_3
|
641 |
-
value:
|
642 |
- type: mrr_at_5
|
643 |
-
value:
|
644 |
- type: ndcg_at_1
|
645 |
-
value:
|
646 |
- type: ndcg_at_10
|
647 |
-
value:
|
648 |
- type: ndcg_at_100
|
649 |
-
value:
|
650 |
- type: ndcg_at_1000
|
651 |
-
value:
|
652 |
- type: ndcg_at_3
|
653 |
-
value:
|
654 |
- type: ndcg_at_5
|
655 |
-
value:
|
656 |
- type: precision_at_1
|
657 |
-
value:
|
658 |
- type: precision_at_10
|
659 |
-
value: 5.
|
660 |
- type: precision_at_100
|
661 |
-
value: 0.
|
662 |
- type: precision_at_1000
|
663 |
-
value: 0.
|
664 |
- type: precision_at_3
|
665 |
-
value:
|
666 |
- type: precision_at_5
|
667 |
-
value:
|
668 |
- type: recall_at_1
|
669 |
-
value:
|
670 |
- type: recall_at_10
|
671 |
-
value:
|
672 |
- type: recall_at_100
|
673 |
-
value:
|
674 |
- type: recall_at_1000
|
675 |
-
value:
|
676 |
- type: recall_at_3
|
677 |
-
value:
|
678 |
- type: recall_at_5
|
679 |
-
value:
|
680 |
- task:
|
681 |
type: Retrieval
|
682 |
dataset:
|
@@ -687,65 +778,65 @@ model-index:
|
|
687 |
revision: None
|
688 |
metrics:
|
689 |
- type: map_at_1
|
690 |
-
value:
|
691 |
- type: map_at_10
|
692 |
-
value:
|
693 |
- type: map_at_100
|
694 |
-
value:
|
695 |
- type: map_at_1000
|
696 |
-
value:
|
697 |
- type: map_at_3
|
698 |
-
value:
|
699 |
- type: map_at_5
|
700 |
-
value:
|
701 |
- type: mrr_at_1
|
702 |
-
value:
|
703 |
- type: mrr_at_10
|
704 |
-
value:
|
705 |
- type: mrr_at_100
|
706 |
-
value:
|
707 |
- type: mrr_at_1000
|
708 |
-
value:
|
709 |
- type: mrr_at_3
|
710 |
-
value:
|
711 |
- type: mrr_at_5
|
712 |
-
value:
|
713 |
- type: ndcg_at_1
|
714 |
-
value:
|
715 |
- type: ndcg_at_10
|
716 |
-
value:
|
717 |
- type: ndcg_at_100
|
718 |
-
value:
|
719 |
- type: ndcg_at_1000
|
720 |
-
value:
|
721 |
- type: ndcg_at_3
|
722 |
-
value:
|
723 |
- type: ndcg_at_5
|
724 |
-
value:
|
725 |
- type: precision_at_1
|
726 |
-
value:
|
727 |
- type: precision_at_10
|
728 |
-
value: 5.
|
729 |
- type: precision_at_100
|
730 |
-
value: 0.
|
731 |
- type: precision_at_1000
|
732 |
-
value: 0.
|
733 |
- type: precision_at_3
|
734 |
-
value:
|
735 |
- type: precision_at_5
|
736 |
-
value: 8.
|
737 |
- type: recall_at_1
|
738 |
-
value:
|
739 |
- type: recall_at_10
|
740 |
-
value:
|
741 |
- type: recall_at_100
|
742 |
-
value:
|
743 |
- type: recall_at_1000
|
744 |
-
value:
|
745 |
- type: recall_at_3
|
746 |
-
value:
|
747 |
- type: recall_at_5
|
748 |
-
value:
|
749 |
- task:
|
750 |
type: Retrieval
|
751 |
dataset:
|
@@ -756,65 +847,65 @@ model-index:
|
|
756 |
revision: None
|
757 |
metrics:
|
758 |
- type: map_at_1
|
759 |
-
value:
|
760 |
- type: map_at_10
|
761 |
-
value:
|
762 |
- type: map_at_100
|
763 |
-
value:
|
764 |
- type: map_at_1000
|
765 |
-
value:
|
766 |
- type: map_at_3
|
767 |
-
value:
|
768 |
- type: map_at_5
|
769 |
-
value:
|
770 |
- type: mrr_at_1
|
771 |
-
value:
|
772 |
- type: mrr_at_10
|
773 |
-
value:
|
774 |
- type: mrr_at_100
|
775 |
-
value:
|
776 |
- type: mrr_at_1000
|
777 |
-
value:
|
778 |
- type: mrr_at_3
|
779 |
-
value:
|
780 |
- type: mrr_at_5
|
781 |
-
value:
|
782 |
- type: ndcg_at_1
|
783 |
-
value:
|
784 |
- type: ndcg_at_10
|
785 |
-
value:
|
786 |
- type: ndcg_at_100
|
787 |
-
value:
|
788 |
- type: ndcg_at_1000
|
789 |
-
value:
|
790 |
- type: ndcg_at_3
|
791 |
-
value:
|
792 |
- type: ndcg_at_5
|
793 |
-
value:
|
794 |
- type: precision_at_1
|
795 |
-
value:
|
796 |
- type: precision_at_10
|
797 |
-
value:
|
798 |
- type: precision_at_100
|
799 |
-
value: 1.
|
800 |
- type: precision_at_1000
|
801 |
-
value: 0.
|
802 |
- type: precision_at_3
|
803 |
-
value:
|
804 |
- type: precision_at_5
|
805 |
-
value:
|
806 |
- type: recall_at_1
|
807 |
-
value:
|
808 |
- type: recall_at_10
|
809 |
-
value:
|
810 |
- type: recall_at_100
|
811 |
-
value:
|
812 |
- type: recall_at_1000
|
813 |
-
value:
|
814 |
- type: recall_at_3
|
815 |
-
value:
|
816 |
- type: recall_at_5
|
817 |
-
value:
|
818 |
- task:
|
819 |
type: Retrieval
|
820 |
dataset:
|
@@ -825,65 +916,65 @@ model-index:
|
|
825 |
revision: None
|
826 |
metrics:
|
827 |
- type: map_at_1
|
828 |
-
value:
|
829 |
- type: map_at_10
|
830 |
-
value:
|
831 |
- type: map_at_100
|
832 |
-
value:
|
833 |
- type: map_at_1000
|
834 |
-
value:
|
835 |
- type: map_at_3
|
836 |
-
value:
|
837 |
- type: map_at_5
|
838 |
-
value:
|
839 |
- type: mrr_at_1
|
840 |
-
value:
|
841 |
- type: mrr_at_10
|
842 |
-
value:
|
843 |
- type: mrr_at_100
|
844 |
-
value:
|
845 |
- type: mrr_at_1000
|
846 |
-
value:
|
847 |
- type: mrr_at_3
|
848 |
-
value:
|
849 |
- type: mrr_at_5
|
850 |
-
value:
|
851 |
- type: ndcg_at_1
|
852 |
-
value:
|
853 |
- type: ndcg_at_10
|
854 |
-
value:
|
855 |
- type: ndcg_at_100
|
856 |
-
value:
|
857 |
- type: ndcg_at_1000
|
858 |
-
value:
|
859 |
- type: ndcg_at_3
|
860 |
-
value:
|
861 |
- type: ndcg_at_5
|
862 |
-
value:
|
863 |
- type: precision_at_1
|
864 |
-
value:
|
865 |
- type: precision_at_10
|
866 |
-
value:
|
867 |
- type: precision_at_100
|
868 |
-
value: 1.
|
869 |
- type: precision_at_1000
|
870 |
-
value: 0.
|
871 |
- type: precision_at_3
|
872 |
-
value:
|
873 |
- type: precision_at_5
|
874 |
-
value:
|
875 |
- type: recall_at_1
|
876 |
-
value:
|
877 |
- type: recall_at_10
|
878 |
-
value:
|
879 |
- type: recall_at_100
|
880 |
-
value:
|
881 |
- type: recall_at_1000
|
882 |
-
value:
|
883 |
- type: recall_at_3
|
884 |
-
value:
|
885 |
- type: recall_at_5
|
886 |
-
value:
|
887 |
- task:
|
888 |
type: Retrieval
|
889 |
dataset:
|
@@ -894,225 +985,65 @@ model-index:
|
|
894 |
revision: None
|
895 |
metrics:
|
896 |
- type: map_at_1
|
897 |
-
value:
|
898 |
-
- type: map_at_10
|
899 |
-
value: 28.96
|
900 |
-
- type: map_at_100
|
901 |
-
value: 29.904999999999998
|
902 |
-
- type: map_at_1000
|
903 |
-
value: 30.019000000000002
|
904 |
-
- type: map_at_3
|
905 |
-
value: 26.461000000000002
|
906 |
-
- type: map_at_5
|
907 |
-
value: 27.801
|
908 |
-
- type: mrr_at_1
|
909 |
-
value: 23.105
|
910 |
-
- type: mrr_at_10
|
911 |
-
value: 31.137999999999998
|
912 |
-
- type: mrr_at_100
|
913 |
-
value: 31.965
|
914 |
-
- type: mrr_at_1000
|
915 |
-
value: 32.039
|
916 |
-
- type: mrr_at_3
|
917 |
-
value: 28.589
|
918 |
-
- type: mrr_at_5
|
919 |
-
value: 30.04
|
920 |
-
- type: ndcg_at_1
|
921 |
-
value: 23.105
|
922 |
-
- type: ndcg_at_10
|
923 |
-
value: 33.841
|
924 |
-
- type: ndcg_at_100
|
925 |
-
value: 38.76
|
926 |
-
- type: ndcg_at_1000
|
927 |
-
value: 41.297
|
928 |
-
- type: ndcg_at_3
|
929 |
-
value: 28.833
|
930 |
-
- type: ndcg_at_5
|
931 |
-
value: 31.19
|
932 |
-
- type: precision_at_1
|
933 |
-
value: 23.105
|
934 |
-
- type: precision_at_10
|
935 |
-
value: 5.434
|
936 |
-
- type: precision_at_100
|
937 |
-
value: 0.8540000000000001
|
938 |
-
- type: precision_at_1000
|
939 |
-
value: 0.11800000000000001
|
940 |
-
- type: precision_at_3
|
941 |
-
value: 12.384
|
942 |
-
- type: precision_at_5
|
943 |
-
value: 8.799
|
944 |
-
- type: recall_at_1
|
945 |
-
value: 21.047
|
946 |
-
- type: recall_at_10
|
947 |
-
value: 46.768
|
948 |
-
- type: recall_at_100
|
949 |
-
value: 69.782
|
950 |
-
- type: recall_at_1000
|
951 |
-
value: 88.384
|
952 |
-
- type: recall_at_3
|
953 |
-
value: 33.444
|
954 |
-
- type: recall_at_5
|
955 |
-
value: 39.062999999999995
|
956 |
-
- task:
|
957 |
-
type: Retrieval
|
958 |
-
dataset:
|
959 |
-
type: arguana
|
960 |
-
name: MTEB ArguAna
|
961 |
-
config: default
|
962 |
-
split: test
|
963 |
-
revision: None
|
964 |
-
metrics:
|
965 |
-
- type: map_at_1
|
966 |
-
value: 26.031
|
967 |
- type: map_at_10
|
968 |
-
value:
|
969 |
- type: map_at_100
|
970 |
-
value:
|
971 |
- type: map_at_1000
|
972 |
-
value:
|
973 |
- type: map_at_3
|
974 |
-
value:
|
975 |
- type: map_at_5
|
976 |
-
value:
|
977 |
- type: mrr_at_1
|
978 |
-
value:
|
979 |
- type: mrr_at_10
|
980 |
-
value:
|
981 |
- type: mrr_at_100
|
982 |
-
value:
|
983 |
- type: mrr_at_1000
|
984 |
-
value:
|
985 |
- type: mrr_at_3
|
986 |
-
value:
|
987 |
- type: mrr_at_5
|
988 |
-
value:
|
989 |
- type: ndcg_at_1
|
990 |
-
value:
|
991 |
- type: ndcg_at_10
|
992 |
-
value:
|
993 |
- type: ndcg_at_100
|
994 |
-
value:
|
995 |
- type: ndcg_at_1000
|
996 |
-
value:
|
997 |
- type: ndcg_at_3
|
998 |
-
value:
|
999 |
- type: ndcg_at_5
|
1000 |
-
value:
|
1001 |
- type: precision_at_1
|
1002 |
-
value:
|
1003 |
- type: precision_at_10
|
1004 |
-
value:
|
1005 |
- type: precision_at_100
|
1006 |
-
value: 0.
|
1007 |
- type: precision_at_1000
|
1008 |
-
value: 0.
|
1009 |
- type: precision_at_3
|
1010 |
-
value:
|
1011 |
- type: precision_at_5
|
1012 |
-
value:
|
1013 |
- type: recall_at_1
|
1014 |
-
value:
|
1015 |
- type: recall_at_10
|
1016 |
-
value:
|
1017 |
- type: recall_at_100
|
1018 |
-
value:
|
1019 |
- type: recall_at_1000
|
1020 |
-
value:
|
1021 |
- type: recall_at_3
|
1022 |
-
value:
|
1023 |
- type: recall_at_5
|
1024 |
-
value:
|
1025 |
-
- task:
|
1026 |
-
type: Clustering
|
1027 |
-
dataset:
|
1028 |
-
type: mteb/arxiv-clustering-p2p
|
1029 |
-
name: MTEB ArxivClusteringP2P
|
1030 |
-
config: default
|
1031 |
-
split: test
|
1032 |
-
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
|
1033 |
-
metrics:
|
1034 |
-
- type: v_measure
|
1035 |
-
value: 41.76036539849672
|
1036 |
-
- task:
|
1037 |
-
type: Clustering
|
1038 |
-
dataset:
|
1039 |
-
type: mteb/arxiv-clustering-s2s
|
1040 |
-
name: MTEB ArxivClusteringS2S
|
1041 |
-
config: default
|
1042 |
-
split: test
|
1043 |
-
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
|
1044 |
-
metrics:
|
1045 |
-
- type: v_measure
|
1046 |
-
value: 34.27585676831497
|
1047 |
-
- task:
|
1048 |
-
type: Reranking
|
1049 |
-
dataset:
|
1050 |
-
type: mteb/askubuntudupquestions-reranking
|
1051 |
-
name: MTEB AskUbuntuDupQuestions
|
1052 |
-
config: default
|
1053 |
-
split: test
|
1054 |
-
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
|
1055 |
-
metrics:
|
1056 |
-
- type: map
|
1057 |
-
value: 63.47328704612227
|
1058 |
-
- type: mrr
|
1059 |
-
value: 76.63182078002022
|
1060 |
-
- task:
|
1061 |
-
type: STS
|
1062 |
-
dataset:
|
1063 |
-
type: mteb/biosses-sts
|
1064 |
-
name: MTEB BIOSSES
|
1065 |
-
config: default
|
1066 |
-
split: test
|
1067 |
-
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
|
1068 |
-
metrics:
|
1069 |
-
- type: cos_sim_pearson
|
1070 |
-
value: 87.42072640664271
|
1071 |
-
- type: cos_sim_spearman
|
1072 |
-
value: 84.31336692039407
|
1073 |
-
- type: euclidean_pearson
|
1074 |
-
value: 54.93250871487246
|
1075 |
-
- type: euclidean_spearman
|
1076 |
-
value: 55.91091252228738
|
1077 |
-
- type: manhattan_pearson
|
1078 |
-
value: 54.78812442894107
|
1079 |
-
- type: manhattan_spearman
|
1080 |
-
value: 55.35005636930548
|
1081 |
-
- task:
|
1082 |
-
type: Classification
|
1083 |
-
dataset:
|
1084 |
-
type: mteb/banking77
|
1085 |
-
name: MTEB Banking77Classification
|
1086 |
-
config: default
|
1087 |
-
split: test
|
1088 |
-
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
|
1089 |
-
metrics:
|
1090 |
-
- type: accuracy
|
1091 |
-
value: 86.28896103896103
|
1092 |
-
- type: f1
|
1093 |
-
value: 86.23389676482913
|
1094 |
-
- task:
|
1095 |
-
type: Clustering
|
1096 |
-
dataset:
|
1097 |
-
type: mteb/biorxiv-clustering-p2p
|
1098 |
-
name: MTEB BiorxivClusteringP2P
|
1099 |
-
config: default
|
1100 |
-
split: test
|
1101 |
-
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
|
1102 |
-
metrics:
|
1103 |
-
- type: v_measure
|
1104 |
-
value: 33.73729294301578
|
1105 |
-
- task:
|
1106 |
-
type: Clustering
|
1107 |
-
dataset:
|
1108 |
-
type: mteb/biorxiv-clustering-s2s
|
1109 |
-
name: MTEB BiorxivClusteringS2S
|
1110 |
-
config: default
|
1111 |
-
split: test
|
1112 |
-
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
|
1113 |
-
metrics:
|
1114 |
-
- type: v_measure
|
1115 |
-
value: 30.641078215958288
|
1116 |
- task:
|
1117 |
type: Retrieval
|
1118 |
dataset:
|
@@ -1123,65 +1054,65 @@ model-index:
|
|
1123 |
revision: None
|
1124 |
metrics:
|
1125 |
- type: map_at_1
|
1126 |
-
value: 8.
|
1127 |
- type: map_at_10
|
1128 |
-
value: 14.
|
1129 |
- type: map_at_100
|
1130 |
-
value:
|
1131 |
- type: map_at_1000
|
1132 |
-
value: 16.
|
1133 |
- type: map_at_3
|
1134 |
-
value:
|
1135 |
- type: map_at_5
|
1136 |
-
value: 13.
|
1137 |
- type: mrr_at_1
|
1138 |
-
value:
|
1139 |
- type: mrr_at_10
|
1140 |
-
value:
|
1141 |
- type: mrr_at_100
|
1142 |
-
value:
|
1143 |
- type: mrr_at_1000
|
1144 |
-
value:
|
1145 |
- type: mrr_at_3
|
1146 |
-
value:
|
1147 |
- type: mrr_at_5
|
1148 |
-
value: 27.
|
1149 |
- type: ndcg_at_1
|
1150 |
-
value:
|
1151 |
- type: ndcg_at_10
|
1152 |
-
value: 21.
|
1153 |
- type: ndcg_at_100
|
1154 |
-
value: 27.
|
1155 |
- type: ndcg_at_1000
|
1156 |
-
value: 31.
|
1157 |
- type: ndcg_at_3
|
1158 |
-
value:
|
1159 |
- type: ndcg_at_5
|
1160 |
-
value: 18.
|
1161 |
- type: precision_at_1
|
1162 |
-
value:
|
1163 |
- type: precision_at_10
|
1164 |
-
value: 6.
|
1165 |
- type: precision_at_100
|
1166 |
-
value: 1.
|
1167 |
- type: precision_at_1000
|
1168 |
-
value: 0.
|
1169 |
- type: precision_at_3
|
1170 |
-
value: 12.
|
1171 |
- type: precision_at_5
|
1172 |
-
value: 9.
|
1173 |
- type: recall_at_1
|
1174 |
-
value: 8.
|
1175 |
- type: recall_at_10
|
1176 |
-
value:
|
1177 |
- type: recall_at_100
|
1178 |
-
value:
|
1179 |
- type: recall_at_1000
|
1180 |
-
value: 68.
|
1181 |
- type: recall_at_3
|
1182 |
-
value:
|
1183 |
- type: recall_at_5
|
1184 |
-
value: 20.
|
1185 |
- task:
|
1186 |
type: Retrieval
|
1187 |
dataset:
|
@@ -1192,65 +1123,65 @@ model-index:
|
|
1192 |
revision: None
|
1193 |
metrics:
|
1194 |
- type: map_at_1
|
1195 |
-
value: 8.
|
1196 |
- type: map_at_10
|
1197 |
-
value:
|
1198 |
- type: map_at_100
|
1199 |
-
value:
|
1200 |
- type: map_at_1000
|
1201 |
-
value:
|
1202 |
- type: map_at_3
|
1203 |
-
value: 12.
|
1204 |
- type: map_at_5
|
1205 |
-
value:
|
1206 |
- type: mrr_at_1
|
1207 |
-
value:
|
1208 |
- type: mrr_at_10
|
1209 |
-
value:
|
1210 |
- type: mrr_at_100
|
1211 |
-
value:
|
1212 |
- type: mrr_at_1000
|
1213 |
-
value:
|
1214 |
- type: mrr_at_3
|
1215 |
-
value:
|
1216 |
- type: mrr_at_5
|
1217 |
-
value:
|
1218 |
- type: ndcg_at_1
|
1219 |
-
value:
|
1220 |
- type: ndcg_at_10
|
1221 |
-
value:
|
1222 |
- type: ndcg_at_100
|
1223 |
-
value:
|
1224 |
- type: ndcg_at_1000
|
1225 |
-
value:
|
1226 |
- type: ndcg_at_3
|
1227 |
-
value:
|
1228 |
- type: ndcg_at_5
|
1229 |
-
value:
|
1230 |
- type: precision_at_1
|
1231 |
-
value:
|
1232 |
- type: precision_at_10
|
1233 |
-
value:
|
1234 |
- type: precision_at_100
|
1235 |
-
value: 8.
|
1236 |
- type: precision_at_1000
|
1237 |
-
value: 1.
|
1238 |
- type: precision_at_3
|
1239 |
-
value:
|
1240 |
- type: precision_at_5
|
1241 |
-
value:
|
1242 |
- type: recall_at_1
|
1243 |
-
value: 8.
|
1244 |
- type: recall_at_10
|
1245 |
-
value:
|
1246 |
- type: recall_at_100
|
1247 |
-
value:
|
1248 |
- type: recall_at_1000
|
1249 |
-
value:
|
1250 |
- type: recall_at_3
|
1251 |
-
value:
|
1252 |
- type: recall_at_5
|
1253 |
-
value:
|
1254 |
- task:
|
1255 |
type: Classification
|
1256 |
dataset:
|
@@ -1261,9 +1192,9 @@ model-index:
|
|
1261 |
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
|
1262 |
metrics:
|
1263 |
- type: accuracy
|
1264 |
-
value:
|
1265 |
- type: f1
|
1266 |
-
value:
|
1267 |
- task:
|
1268 |
type: Retrieval
|
1269 |
dataset:
|
@@ -1274,65 +1205,65 @@ model-index:
|
|
1274 |
revision: None
|
1275 |
metrics:
|
1276 |
- type: map_at_1
|
1277 |
-
value:
|
1278 |
- type: map_at_10
|
1279 |
-
value:
|
1280 |
- type: map_at_100
|
1281 |
-
value:
|
1282 |
- type: map_at_1000
|
1283 |
-
value:
|
1284 |
- type: map_at_3
|
1285 |
-
value:
|
1286 |
- type: map_at_5
|
1287 |
-
value:
|
1288 |
- type: mrr_at_1
|
1289 |
-
value:
|
1290 |
- type: mrr_at_10
|
1291 |
-
value:
|
1292 |
- type: mrr_at_100
|
1293 |
-
value:
|
1294 |
- type: mrr_at_1000
|
1295 |
-
value:
|
1296 |
- type: mrr_at_3
|
1297 |
-
value:
|
1298 |
- type: mrr_at_5
|
1299 |
-
value:
|
1300 |
- type: ndcg_at_1
|
1301 |
-
value:
|
1302 |
- type: ndcg_at_10
|
1303 |
-
value:
|
1304 |
- type: ndcg_at_100
|
1305 |
-
value:
|
1306 |
- type: ndcg_at_1000
|
1307 |
-
value:
|
1308 |
- type: ndcg_at_3
|
1309 |
-
value:
|
1310 |
- type: ndcg_at_5
|
1311 |
-
value:
|
1312 |
- type: precision_at_1
|
1313 |
-
value:
|
1314 |
- type: precision_at_10
|
1315 |
-
value: 9.
|
1316 |
- type: precision_at_100
|
1317 |
-
value: 1.
|
1318 |
- type: precision_at_1000
|
1319 |
value: 0.108
|
1320 |
- type: precision_at_3
|
1321 |
-
value:
|
1322 |
- type: precision_at_5
|
1323 |
-
value:
|
1324 |
- type: recall_at_1
|
1325 |
-
value:
|
1326 |
- type: recall_at_10
|
1327 |
-
value:
|
1328 |
- type: recall_at_100
|
1329 |
-
value:
|
1330 |
- type: recall_at_1000
|
1331 |
-
value:
|
1332 |
- type: recall_at_3
|
1333 |
-
value:
|
1334 |
- type: recall_at_5
|
1335 |
-
value:
|
1336 |
- task:
|
1337 |
type: Retrieval
|
1338 |
dataset:
|
@@ -1343,65 +1274,65 @@ model-index:
|
|
1343 |
revision: None
|
1344 |
metrics:
|
1345 |
- type: map_at_1
|
1346 |
-
value:
|
1347 |
- type: map_at_10
|
1348 |
-
value:
|
1349 |
- type: map_at_100
|
1350 |
-
value:
|
1351 |
- type: map_at_1000
|
1352 |
-
value:
|
1353 |
- type: map_at_3
|
1354 |
-
value:
|
1355 |
- type: map_at_5
|
1356 |
-
value:
|
1357 |
- type: mrr_at_1
|
1358 |
-
value:
|
1359 |
- type: mrr_at_10
|
1360 |
-
value:
|
1361 |
- type: mrr_at_100
|
1362 |
-
value:
|
1363 |
- type: mrr_at_1000
|
1364 |
-
value:
|
1365 |
- type: mrr_at_3
|
1366 |
-
value:
|
1367 |
- type: mrr_at_5
|
1368 |
-
value:
|
1369 |
- type: ndcg_at_1
|
1370 |
-
value:
|
1371 |
- type: ndcg_at_10
|
1372 |
-
value:
|
1373 |
- type: ndcg_at_100
|
1374 |
-
value:
|
1375 |
- type: ndcg_at_1000
|
1376 |
-
value:
|
1377 |
- type: ndcg_at_3
|
1378 |
-
value:
|
1379 |
- type: ndcg_at_5
|
1380 |
-
value:
|
1381 |
- type: precision_at_1
|
1382 |
-
value:
|
1383 |
- type: precision_at_10
|
1384 |
-
value:
|
1385 |
- type: precision_at_100
|
1386 |
-
value: 1.
|
1387 |
- type: precision_at_1000
|
1388 |
-
value: 0.
|
1389 |
- type: precision_at_3
|
1390 |
-
value:
|
1391 |
- type: precision_at_5
|
1392 |
-
value:
|
1393 |
- type: recall_at_1
|
1394 |
-
value:
|
1395 |
- type: recall_at_10
|
1396 |
-
value:
|
1397 |
- type: recall_at_100
|
1398 |
-
value:
|
1399 |
- type: recall_at_1000
|
1400 |
-
value:
|
1401 |
- type: recall_at_3
|
1402 |
-
value:
|
1403 |
- type: recall_at_5
|
1404 |
-
value:
|
1405 |
- task:
|
1406 |
type: Retrieval
|
1407 |
dataset:
|
@@ -1412,65 +1343,65 @@ model-index:
|
|
1412 |
revision: None
|
1413 |
metrics:
|
1414 |
- type: map_at_1
|
1415 |
-
value:
|
1416 |
- type: map_at_10
|
1417 |
-
value:
|
1418 |
- type: map_at_100
|
1419 |
-
value:
|
1420 |
- type: map_at_1000
|
1421 |
-
value:
|
1422 |
- type: map_at_3
|
1423 |
-
value:
|
1424 |
- type: map_at_5
|
1425 |
-
value:
|
1426 |
- type: mrr_at_1
|
1427 |
-
value:
|
1428 |
- type: mrr_at_10
|
1429 |
-
value:
|
1430 |
- type: mrr_at_100
|
1431 |
-
value:
|
1432 |
- type: mrr_at_1000
|
1433 |
-
value:
|
1434 |
- type: mrr_at_3
|
1435 |
-
value:
|
1436 |
- type: mrr_at_5
|
1437 |
-
value:
|
1438 |
- type: ndcg_at_1
|
1439 |
-
value:
|
1440 |
- type: ndcg_at_10
|
1441 |
-
value:
|
1442 |
- type: ndcg_at_100
|
1443 |
-
value: 57.
|
1444 |
- type: ndcg_at_1000
|
1445 |
-
value:
|
1446 |
- type: ndcg_at_3
|
1447 |
-
value:
|
1448 |
- type: ndcg_at_5
|
1449 |
-
value:
|
1450 |
- type: precision_at_1
|
1451 |
-
value:
|
1452 |
- type: precision_at_10
|
1453 |
-
value: 11.
|
1454 |
- type: precision_at_100
|
1455 |
-
value: 1.
|
1456 |
- type: precision_at_1000
|
1457 |
-
value: 0.
|
1458 |
- type: precision_at_3
|
1459 |
-
value:
|
1460 |
- type: precision_at_5
|
1461 |
-
value: 20.
|
1462 |
- type: recall_at_1
|
1463 |
-
value:
|
1464 |
- type: recall_at_10
|
1465 |
-
value: 55.
|
1466 |
- type: recall_at_100
|
1467 |
-
value:
|
1468 |
- type: recall_at_1000
|
1469 |
-
value:
|
1470 |
- type: recall_at_3
|
1471 |
-
value:
|
1472 |
- type: recall_at_5
|
1473 |
-
value:
|
1474 |
- task:
|
1475 |
type: Classification
|
1476 |
dataset:
|
@@ -1481,11 +1412,11 @@ model-index:
|
|
1481 |
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
|
1482 |
metrics:
|
1483 |
- type: accuracy
|
1484 |
-
value:
|
1485 |
- type: ap
|
1486 |
-
value:
|
1487 |
- type: f1
|
1488 |
-
value:
|
1489 |
- task:
|
1490 |
type: Retrieval
|
1491 |
dataset:
|
@@ -1496,65 +1427,65 @@ model-index:
|
|
1496 |
revision: None
|
1497 |
metrics:
|
1498 |
- type: map_at_1
|
1499 |
-
value:
|
1500 |
- type: map_at_10
|
1501 |
-
value:
|
1502 |
- type: map_at_100
|
1503 |
-
value:
|
1504 |
- type: map_at_1000
|
1505 |
-
value:
|
1506 |
- type: map_at_3
|
1507 |
-
value:
|
1508 |
- type: map_at_5
|
1509 |
-
value:
|
1510 |
- type: mrr_at_1
|
1511 |
-
value:
|
1512 |
- type: mrr_at_10
|
1513 |
-
value:
|
1514 |
- type: mrr_at_100
|
1515 |
-
value:
|
1516 |
- type: mrr_at_1000
|
1517 |
-
value:
|
1518 |
- type: mrr_at_3
|
1519 |
-
value:
|
1520 |
- type: mrr_at_5
|
1521 |
-
value:
|
1522 |
- type: ndcg_at_1
|
1523 |
-
value:
|
1524 |
- type: ndcg_at_10
|
1525 |
-
value:
|
1526 |
- type: ndcg_at_100
|
1527 |
-
value:
|
1528 |
- type: ndcg_at_1000
|
1529 |
-
value:
|
1530 |
- type: ndcg_at_3
|
1531 |
-
value:
|
1532 |
- type: ndcg_at_5
|
1533 |
-
value:
|
1534 |
- type: precision_at_1
|
1535 |
-
value:
|
1536 |
- type: precision_at_10
|
1537 |
-
value:
|
1538 |
- type: precision_at_100
|
1539 |
-
value: 0.
|
1540 |
- type: precision_at_1000
|
1541 |
-
value: 0.
|
1542 |
- type: precision_at_3
|
1543 |
-
value:
|
1544 |
- type: precision_at_5
|
1545 |
-
value:
|
1546 |
- type: recall_at_1
|
1547 |
-
value:
|
1548 |
- type: recall_at_10
|
1549 |
-
value:
|
1550 |
- type: recall_at_100
|
1551 |
-
value:
|
1552 |
- type: recall_at_1000
|
1553 |
-
value: 97.
|
1554 |
- type: recall_at_3
|
1555 |
-
value:
|
1556 |
- type: recall_at_5
|
1557 |
-
value:
|
1558 |
- task:
|
1559 |
type: Classification
|
1560 |
dataset:
|
@@ -1565,9 +1496,9 @@ model-index:
|
|
1565 |
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
|
1566 |
metrics:
|
1567 |
- type: accuracy
|
1568 |
-
value:
|
1569 |
- type: f1
|
1570 |
-
value:
|
1571 |
- task:
|
1572 |
type: Classification
|
1573 |
dataset:
|
@@ -1578,9 +1509,9 @@ model-index:
|
|
1578 |
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
|
1579 |
metrics:
|
1580 |
- type: accuracy
|
1581 |
-
value:
|
1582 |
- type: f1
|
1583 |
-
value:
|
1584 |
- task:
|
1585 |
type: Classification
|
1586 |
dataset:
|
@@ -1591,9 +1522,9 @@ model-index:
|
|
1591 |
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
|
1592 |
metrics:
|
1593 |
- type: accuracy
|
1594 |
-
value:
|
1595 |
- type: f1
|
1596 |
-
value:
|
1597 |
- task:
|
1598 |
type: Classification
|
1599 |
dataset:
|
@@ -1604,9 +1535,9 @@ model-index:
|
|
1604 |
revision: 7d571f92784cd94a019292a1f45445077d0ef634
|
1605 |
metrics:
|
1606 |
- type: accuracy
|
1607 |
-
value:
|
1608 |
- type: f1
|
1609 |
-
value: 77.
|
1610 |
- task:
|
1611 |
type: Clustering
|
1612 |
dataset:
|
@@ -1617,7 +1548,7 @@ model-index:
|
|
1617 |
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
|
1618 |
metrics:
|
1619 |
- type: v_measure
|
1620 |
-
value: 30.
|
1621 |
- task:
|
1622 |
type: Clustering
|
1623 |
dataset:
|
@@ -1628,7 +1559,7 @@ model-index:
|
|
1628 |
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
|
1629 |
metrics:
|
1630 |
- type: v_measure
|
1631 |
-
value:
|
1632 |
- task:
|
1633 |
type: Reranking
|
1634 |
dataset:
|
@@ -1639,9 +1570,9 @@ model-index:
|
|
1639 |
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
|
1640 |
metrics:
|
1641 |
- type: map
|
1642 |
-
value: 31.
|
1643 |
- type: mrr
|
1644 |
-
value: 32.
|
1645 |
- task:
|
1646 |
type: Retrieval
|
1647 |
dataset:
|
@@ -1652,65 +1583,65 @@ model-index:
|
|
1652 |
revision: None
|
1653 |
metrics:
|
1654 |
- type: map_at_1
|
1655 |
-
value: 5.
|
1656 |
- type: map_at_10
|
1657 |
-
value:
|
1658 |
- type: map_at_100
|
1659 |
-
value:
|
1660 |
- type: map_at_1000
|
1661 |
-
value: 16.
|
1662 |
- type: map_at_3
|
1663 |
-
value: 8.
|
1664 |
- type: map_at_5
|
1665 |
-
value:
|
1666 |
- type: mrr_at_1
|
1667 |
-
value:
|
1668 |
- type: mrr_at_10
|
1669 |
-
value:
|
1670 |
- type: mrr_at_100
|
1671 |
-
value:
|
1672 |
- type: mrr_at_1000
|
1673 |
-
value: 53.
|
1674 |
- type: mrr_at_3
|
1675 |
-
value: 50.
|
1676 |
- type: mrr_at_5
|
1677 |
-
value:
|
1678 |
- type: ndcg_at_1
|
1679 |
-
value:
|
1680 |
- type: ndcg_at_10
|
1681 |
-
value:
|
1682 |
- type: ndcg_at_100
|
1683 |
-
value:
|
1684 |
- type: ndcg_at_1000
|
1685 |
-
value:
|
1686 |
- type: ndcg_at_3
|
1687 |
-
value:
|
1688 |
- type: ndcg_at_5
|
1689 |
-
value:
|
1690 |
- type: precision_at_1
|
1691 |
-
value:
|
1692 |
- type: precision_at_10
|
1693 |
-
value: 24.
|
1694 |
- type: precision_at_100
|
1695 |
-
value:
|
1696 |
- type: precision_at_1000
|
1697 |
-
value: 2.
|
1698 |
- type: precision_at_3
|
1699 |
-
value:
|
1700 |
- type: precision_at_5
|
1701 |
-
value: 31.
|
1702 |
- type: recall_at_1
|
1703 |
-
value: 5.
|
1704 |
- type: recall_at_10
|
1705 |
-
value:
|
1706 |
- type: recall_at_100
|
1707 |
-
value:
|
1708 |
- type: recall_at_1000
|
1709 |
-
value:
|
1710 |
- type: recall_at_3
|
1711 |
-
value: 9.
|
1712 |
- type: recall_at_5
|
1713 |
-
value: 12.
|
1714 |
- task:
|
1715 |
type: Retrieval
|
1716 |
dataset:
|
@@ -1721,65 +1652,65 @@ model-index:
|
|
1721 |
revision: None
|
1722 |
metrics:
|
1723 |
- type: map_at_1
|
1724 |
-
value:
|
1725 |
- type: map_at_10
|
1726 |
-
value:
|
1727 |
- type: map_at_100
|
1728 |
-
value:
|
1729 |
- type: map_at_1000
|
1730 |
-
value:
|
1731 |
- type: map_at_3
|
1732 |
-
value:
|
1733 |
- type: map_at_5
|
1734 |
-
value:
|
1735 |
- type: mrr_at_1
|
1736 |
-
value:
|
1737 |
- type: mrr_at_10
|
1738 |
-
value:
|
1739 |
- type: mrr_at_100
|
1740 |
-
value:
|
1741 |
- type: mrr_at_1000
|
1742 |
-
value:
|
1743 |
- type: mrr_at_3
|
1744 |
-
value:
|
1745 |
- type: mrr_at_5
|
1746 |
-
value:
|
1747 |
- type: ndcg_at_1
|
1748 |
-
value:
|
1749 |
- type: ndcg_at_10
|
1750 |
-
value:
|
1751 |
- type: ndcg_at_100
|
1752 |
-
value:
|
1753 |
- type: ndcg_at_1000
|
1754 |
-
value:
|
1755 |
- type: ndcg_at_3
|
1756 |
-
value:
|
1757 |
- type: ndcg_at_5
|
1758 |
-
value:
|
1759 |
- type: precision_at_1
|
1760 |
-
value:
|
1761 |
- type: precision_at_10
|
1762 |
-
value: 8.
|
1763 |
- type: precision_at_100
|
1764 |
-
value: 1.
|
1765 |
- type: precision_at_1000
|
1766 |
value: 0.11800000000000001
|
1767 |
- type: precision_at_3
|
1768 |
-
value:
|
1769 |
- type: precision_at_5
|
1770 |
-
value:
|
1771 |
- type: recall_at_1
|
1772 |
-
value:
|
1773 |
- type: recall_at_10
|
1774 |
-
value:
|
1775 |
- type: recall_at_100
|
1776 |
-
value: 90.
|
1777 |
- type: recall_at_1000
|
1778 |
-
value:
|
1779 |
- type: recall_at_3
|
1780 |
-
value:
|
1781 |
- type: recall_at_5
|
1782 |
-
value:
|
1783 |
- task:
|
1784 |
type: Retrieval
|
1785 |
dataset:
|
@@ -1790,65 +1721,65 @@ model-index:
|
|
1790 |
revision: None
|
1791 |
metrics:
|
1792 |
- type: map_at_1
|
1793 |
-
value: 70.
|
1794 |
- type: map_at_10
|
1795 |
-
value: 84.
|
1796 |
- type: map_at_100
|
1797 |
-
value:
|
1798 |
- type: map_at_1000
|
1799 |
-
value: 85.
|
1800 |
- type: map_at_3
|
1801 |
-
value: 81.
|
1802 |
- type: map_at_5
|
1803 |
-
value: 83.
|
1804 |
- type: mrr_at_1
|
1805 |
-
value: 81.
|
1806 |
- type: mrr_at_10
|
1807 |
-
value: 87.
|
1808 |
- type: mrr_at_100
|
1809 |
-
value: 87.
|
1810 |
- type: mrr_at_1000
|
1811 |
-
value: 87.
|
1812 |
- type: mrr_at_3
|
1813 |
-
value: 86.
|
1814 |
- type: mrr_at_5
|
1815 |
-
value: 87.
|
1816 |
- type: ndcg_at_1
|
1817 |
-
value: 81.
|
1818 |
- type: ndcg_at_10
|
1819 |
-
value: 88.
|
1820 |
- type: ndcg_at_100
|
1821 |
-
value: 89.
|
1822 |
- type: ndcg_at_1000
|
1823 |
-
value: 89.
|
1824 |
- type: ndcg_at_3
|
1825 |
-
value: 85.
|
1826 |
- type: ndcg_at_5
|
1827 |
-
value: 86.
|
1828 |
- type: precision_at_1
|
1829 |
-
value: 81.
|
1830 |
- type: precision_at_10
|
1831 |
-
value: 13.
|
1832 |
- type: precision_at_100
|
1833 |
-
value: 1.
|
1834 |
- type: precision_at_1000
|
1835 |
value: 0.157
|
1836 |
- type: precision_at_3
|
1837 |
-
value: 37.
|
1838 |
- type: precision_at_5
|
1839 |
-
value: 24.
|
1840 |
- type: recall_at_1
|
1841 |
-
value: 70.
|
1842 |
- type: recall_at_10
|
1843 |
-
value: 95.
|
1844 |
- type: recall_at_100
|
1845 |
-
value: 99.
|
1846 |
- type: recall_at_1000
|
1847 |
-
value: 99.
|
1848 |
- type: recall_at_3
|
1849 |
-
value: 87.
|
1850 |
- type: recall_at_5
|
1851 |
-
value: 91.
|
1852 |
- task:
|
1853 |
type: Clustering
|
1854 |
dataset:
|
@@ -1859,7 +1790,7 @@ model-index:
|
|
1859 |
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
|
1860 |
metrics:
|
1861 |
- type: v_measure
|
1862 |
-
value:
|
1863 |
- task:
|
1864 |
type: Clustering
|
1865 |
dataset:
|
@@ -1870,7 +1801,7 @@ model-index:
|
|
1870 |
revision: 282350215ef01743dc01b456c7f5241fa8937f16
|
1871 |
metrics:
|
1872 |
- type: v_measure
|
1873 |
-
value:
|
1874 |
- task:
|
1875 |
type: Retrieval
|
1876 |
dataset:
|
@@ -1881,65 +1812,65 @@ model-index:
|
|
1881 |
revision: None
|
1882 |
metrics:
|
1883 |
- type: map_at_1
|
1884 |
-
value: 4.
|
1885 |
- type: map_at_10
|
1886 |
-
value:
|
1887 |
- type: map_at_100
|
1888 |
-
value:
|
1889 |
- type: map_at_1000
|
1890 |
-
value: 13.
|
1891 |
- type: map_at_3
|
1892 |
-
value:
|
1893 |
- type: map_at_5
|
1894 |
-
value: 9.
|
1895 |
- type: mrr_at_1
|
1896 |
-
value:
|
1897 |
- type: mrr_at_10
|
1898 |
-
value:
|
1899 |
- type: mrr_at_100
|
1900 |
-
value:
|
1901 |
- type: mrr_at_1000
|
1902 |
-
value:
|
1903 |
- type: mrr_at_3
|
1904 |
-
value:
|
1905 |
- type: mrr_at_5
|
1906 |
-
value:
|
1907 |
- type: ndcg_at_1
|
1908 |
-
value:
|
1909 |
- type: ndcg_at_10
|
1910 |
-
value:
|
1911 |
- type: ndcg_at_100
|
1912 |
-
value:
|
1913 |
- type: ndcg_at_1000
|
1914 |
-
value:
|
1915 |
- type: ndcg_at_3
|
1916 |
-
value:
|
1917 |
- type: ndcg_at_5
|
1918 |
-
value:
|
1919 |
- type: precision_at_1
|
1920 |
-
value:
|
1921 |
- type: precision_at_10
|
1922 |
-
value: 9.
|
1923 |
- type: precision_at_100
|
1924 |
-
value: 2.
|
1925 |
- type: precision_at_1000
|
1926 |
-
value: 0.
|
1927 |
- type: precision_at_3
|
1928 |
-
value:
|
1929 |
- type: precision_at_5
|
1930 |
-
value: 13.
|
1931 |
- type: recall_at_1
|
1932 |
-
value: 4.
|
1933 |
- type: recall_at_10
|
1934 |
-
value:
|
1935 |
- type: recall_at_100
|
1936 |
-
value:
|
1937 |
- type: recall_at_1000
|
1938 |
-
value:
|
1939 |
- type: recall_at_3
|
1940 |
-
value:
|
1941 |
- type: recall_at_5
|
1942 |
-
value: 13.
|
1943 |
- task:
|
1944 |
type: STS
|
1945 |
dataset:
|
@@ -1950,17 +1881,17 @@ model-index:
|
|
1950 |
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
|
1951 |
metrics:
|
1952 |
- type: cos_sim_pearson
|
1953 |
-
value:
|
1954 |
- type: cos_sim_spearman
|
1955 |
-
value:
|
1956 |
- type: euclidean_pearson
|
1957 |
-
value:
|
1958 |
- type: euclidean_spearman
|
1959 |
-
value:
|
1960 |
- type: manhattan_pearson
|
1961 |
-
value:
|
1962 |
- type: manhattan_spearman
|
1963 |
-
value:
|
1964 |
- task:
|
1965 |
type: STS
|
1966 |
dataset:
|
@@ -1971,17 +1902,17 @@ model-index:
|
|
1971 |
revision: a0d554a64d88156834ff5ae9920b964011b16384
|
1972 |
metrics:
|
1973 |
- type: cos_sim_pearson
|
1974 |
-
value:
|
1975 |
- type: cos_sim_spearman
|
1976 |
-
value:
|
1977 |
- type: euclidean_pearson
|
1978 |
-
value:
|
1979 |
- type: euclidean_spearman
|
1980 |
-
value: 58.
|
1981 |
- type: manhattan_pearson
|
1982 |
-
value:
|
1983 |
- type: manhattan_spearman
|
1984 |
-
value: 58.
|
1985 |
- task:
|
1986 |
type: STS
|
1987 |
dataset:
|
@@ -1992,17 +1923,17 @@ model-index:
|
|
1992 |
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
|
1993 |
metrics:
|
1994 |
- type: cos_sim_pearson
|
1995 |
-
value:
|
1996 |
- type: cos_sim_spearman
|
1997 |
-
value:
|
1998 |
- type: euclidean_pearson
|
1999 |
-
value:
|
2000 |
- type: euclidean_spearman
|
2001 |
-
value:
|
2002 |
- type: manhattan_pearson
|
2003 |
-
value:
|
2004 |
- type: manhattan_spearman
|
2005 |
-
value:
|
2006 |
- task:
|
2007 |
type: STS
|
2008 |
dataset:
|
@@ -2013,17 +1944,17 @@ model-index:
|
|
2013 |
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
|
2014 |
metrics:
|
2015 |
- type: cos_sim_pearson
|
2016 |
-
value: 82.
|
2017 |
- type: cos_sim_spearman
|
2018 |
-
value:
|
2019 |
- type: euclidean_pearson
|
2020 |
-
value:
|
2021 |
- type: euclidean_spearman
|
2022 |
-
value:
|
2023 |
- type: manhattan_pearson
|
2024 |
-
value:
|
2025 |
- type: manhattan_spearman
|
2026 |
-
value:
|
2027 |
- task:
|
2028 |
type: STS
|
2029 |
dataset:
|
@@ -2034,17 +1965,17 @@ model-index:
|
|
2034 |
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
|
2035 |
metrics:
|
2036 |
- type: cos_sim_pearson
|
2037 |
-
value:
|
2038 |
- type: cos_sim_spearman
|
2039 |
-
value: 86.
|
2040 |
- type: euclidean_pearson
|
2041 |
-
value: 69.
|
2042 |
- type: euclidean_spearman
|
2043 |
-
value: 70.
|
2044 |
- type: manhattan_pearson
|
2045 |
-
value:
|
2046 |
- type: manhattan_spearman
|
2047 |
-
value:
|
2048 |
- task:
|
2049 |
type: STS
|
2050 |
dataset:
|
@@ -2055,17 +1986,17 @@ model-index:
|
|
2055 |
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
|
2056 |
metrics:
|
2057 |
- type: cos_sim_pearson
|
2058 |
-
value:
|
2059 |
- type: cos_sim_spearman
|
2060 |
-
value:
|
2061 |
- type: euclidean_pearson
|
2062 |
-
value:
|
2063 |
- type: euclidean_spearman
|
2064 |
-
value: 72.
|
2065 |
- type: manhattan_pearson
|
2066 |
-
value: 71.
|
2067 |
- type: manhattan_spearman
|
2068 |
-
value: 72.
|
2069 |
- task:
|
2070 |
type: STS
|
2071 |
dataset:
|
@@ -2076,17 +2007,17 @@ model-index:
|
|
2076 |
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
|
2077 |
metrics:
|
2078 |
- type: cos_sim_pearson
|
2079 |
-
value:
|
2080 |
- type: cos_sim_spearman
|
2081 |
-
value:
|
2082 |
- type: euclidean_pearson
|
2083 |
-
value: 77.
|
2084 |
- type: euclidean_spearman
|
2085 |
-
value: 75.
|
2086 |
- type: manhattan_pearson
|
2087 |
-
value: 77.
|
2088 |
- type: manhattan_spearman
|
2089 |
-
value: 75.
|
2090 |
- task:
|
2091 |
type: STS
|
2092 |
dataset:
|
@@ -2097,17 +2028,17 @@ model-index:
|
|
2097 |
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
|
2098 |
metrics:
|
2099 |
- type: cos_sim_pearson
|
2100 |
-
value:
|
2101 |
- type: cos_sim_spearman
|
2102 |
-
value:
|
2103 |
- type: euclidean_pearson
|
2104 |
-
value:
|
2105 |
- type: euclidean_spearman
|
2106 |
-
value: 58.
|
2107 |
- type: manhattan_pearson
|
2108 |
-
value:
|
2109 |
- type: manhattan_spearman
|
2110 |
-
value: 58.
|
2111 |
- task:
|
2112 |
type: STS
|
2113 |
dataset:
|
@@ -2118,17 +2049,17 @@ model-index:
|
|
2118 |
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
|
2119 |
metrics:
|
2120 |
- type: cos_sim_pearson
|
2121 |
-
value: 84.
|
2122 |
- type: cos_sim_spearman
|
2123 |
-
value:
|
2124 |
- type: euclidean_pearson
|
2125 |
-
value:
|
2126 |
- type: euclidean_spearman
|
2127 |
-
value:
|
2128 |
- type: manhattan_pearson
|
2129 |
-
value:
|
2130 |
- type: manhattan_spearman
|
2131 |
-
value:
|
2132 |
- task:
|
2133 |
type: Reranking
|
2134 |
dataset:
|
@@ -2139,9 +2070,9 @@ model-index:
|
|
2139 |
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
|
2140 |
metrics:
|
2141 |
- type: map
|
2142 |
-
value:
|
2143 |
- type: mrr
|
2144 |
-
value: 94.
|
2145 |
- task:
|
2146 |
type: Retrieval
|
2147 |
dataset:
|
@@ -2152,65 +2083,65 @@ model-index:
|
|
2152 |
revision: None
|
2153 |
metrics:
|
2154 |
- type: map_at_1
|
2155 |
-
value:
|
2156 |
- type: map_at_10
|
2157 |
-
value:
|
2158 |
- type: map_at_100
|
2159 |
-
value:
|
2160 |
- type: map_at_1000
|
2161 |
-
value:
|
2162 |
- type: map_at_3
|
2163 |
-
value:
|
2164 |
- type: map_at_5
|
2165 |
-
value:
|
2166 |
- type: mrr_at_1
|
2167 |
-
value:
|
2168 |
- type: mrr_at_10
|
2169 |
-
value:
|
2170 |
- type: mrr_at_100
|
2171 |
-
value:
|
2172 |
- type: mrr_at_1000
|
2173 |
-
value:
|
2174 |
- type: mrr_at_3
|
2175 |
-
value:
|
2176 |
- type: mrr_at_5
|
2177 |
-
value:
|
2178 |
- type: ndcg_at_1
|
2179 |
-
value:
|
2180 |
- type: ndcg_at_10
|
2181 |
-
value:
|
2182 |
- type: ndcg_at_100
|
2183 |
-
value: 63.
|
2184 |
- type: ndcg_at_1000
|
2185 |
-
value:
|
2186 |
- type: ndcg_at_3
|
2187 |
-
value:
|
2188 |
- type: ndcg_at_5
|
2189 |
-
value: 57.
|
2190 |
- type: precision_at_1
|
2191 |
-
value:
|
2192 |
- type: precision_at_10
|
2193 |
-
value: 8.
|
2194 |
- type: precision_at_100
|
2195 |
-
value: 1.
|
2196 |
- type: precision_at_1000
|
2197 |
-
value: 0.
|
2198 |
- type: precision_at_3
|
2199 |
-
value:
|
2200 |
- type: precision_at_5
|
2201 |
-
value: 14.
|
2202 |
- type: recall_at_1
|
2203 |
-
value:
|
2204 |
- type: recall_at_10
|
2205 |
-
value:
|
2206 |
- type: recall_at_100
|
2207 |
-
value:
|
2208 |
- type: recall_at_1000
|
2209 |
-
value: 98.
|
2210 |
- type: recall_at_3
|
2211 |
-
value:
|
2212 |
- type: recall_at_5
|
2213 |
-
value:
|
2214 |
- task:
|
2215 |
type: PairClassification
|
2216 |
dataset:
|
@@ -2221,51 +2152,51 @@ model-index:
|
|
2221 |
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
|
2222 |
metrics:
|
2223 |
- type: cos_sim_accuracy
|
2224 |
-
value: 99.
|
2225 |
- type: cos_sim_ap
|
2226 |
-
value:
|
2227 |
- type: cos_sim_f1
|
2228 |
-
value:
|
2229 |
- type: cos_sim_precision
|
2230 |
-
value:
|
2231 |
- type: cos_sim_recall
|
2232 |
-
value:
|
2233 |
- type: dot_accuracy
|
2234 |
-
value: 99.
|
2235 |
- type: dot_ap
|
2236 |
-
value:
|
2237 |
- type: dot_f1
|
2238 |
-
value:
|
2239 |
- type: dot_precision
|
2240 |
-
value:
|
2241 |
- type: dot_recall
|
2242 |
-
value:
|
2243 |
- type: euclidean_accuracy
|
2244 |
-
value: 99.
|
2245 |
- type: euclidean_ap
|
2246 |
-
value:
|
2247 |
- type: euclidean_f1
|
2248 |
-
value:
|
2249 |
- type: euclidean_precision
|
2250 |
-
value:
|
2251 |
- type: euclidean_recall
|
2252 |
-
value:
|
2253 |
- type: manhattan_accuracy
|
2254 |
-
value: 99.
|
2255 |
- type: manhattan_ap
|
2256 |
-
value: 85.
|
2257 |
- type: manhattan_f1
|
2258 |
-
value:
|
2259 |
- type: manhattan_precision
|
2260 |
-
value:
|
2261 |
- type: manhattan_recall
|
2262 |
-
value:
|
2263 |
- type: max_accuracy
|
2264 |
-
value: 99.
|
2265 |
- type: max_ap
|
2266 |
-
value:
|
2267 |
- type: max_f1
|
2268 |
-
value:
|
2269 |
- task:
|
2270 |
type: Clustering
|
2271 |
dataset:
|
@@ -2276,7 +2207,7 @@ model-index:
|
|
2276 |
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
|
2277 |
metrics:
|
2278 |
- type: v_measure
|
2279 |
-
value:
|
2280 |
- task:
|
2281 |
type: Clustering
|
2282 |
dataset:
|
@@ -2287,7 +2218,7 @@ model-index:
|
|
2287 |
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
|
2288 |
metrics:
|
2289 |
- type: v_measure
|
2290 |
-
value:
|
2291 |
- task:
|
2292 |
type: Reranking
|
2293 |
dataset:
|
@@ -2298,9 +2229,9 @@ model-index:
|
|
2298 |
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
|
2299 |
metrics:
|
2300 |
- type: map
|
2301 |
-
value:
|
2302 |
- type: mrr
|
2303 |
-
value: 51.
|
2304 |
- task:
|
2305 |
type: Summarization
|
2306 |
dataset:
|
@@ -2311,13 +2242,13 @@ model-index:
|
|
2311 |
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
|
2312 |
metrics:
|
2313 |
- type: cos_sim_pearson
|
2314 |
-
value:
|
2315 |
- type: cos_sim_spearman
|
2316 |
-
value:
|
2317 |
- type: dot_pearson
|
2318 |
-
value:
|
2319 |
- type: dot_spearman
|
2320 |
-
value:
|
2321 |
- task:
|
2322 |
type: Retrieval
|
2323 |
dataset:
|
@@ -2328,65 +2259,65 @@ model-index:
|
|
2328 |
revision: None
|
2329 |
metrics:
|
2330 |
- type: map_at_1
|
2331 |
-
value: 0.
|
2332 |
- type: map_at_10
|
2333 |
-
value: 1.
|
2334 |
- type: map_at_100
|
2335 |
-
value: 6.
|
2336 |
- type: map_at_1000
|
2337 |
-
value: 15.
|
2338 |
- type: map_at_3
|
2339 |
-
value: 0.
|
2340 |
- type: map_at_5
|
2341 |
value: 0.712
|
2342 |
- type: mrr_at_1
|
2343 |
-
value:
|
2344 |
- type: mrr_at_10
|
2345 |
-
value:
|
2346 |
- type: mrr_at_100
|
2347 |
-
value:
|
2348 |
- type: mrr_at_1000
|
2349 |
-
value:
|
2350 |
- type: mrr_at_3
|
2351 |
-
value:
|
2352 |
- type: mrr_at_5
|
2353 |
-
value:
|
2354 |
- type: ndcg_at_1
|
2355 |
-
value:
|
2356 |
- type: ndcg_at_10
|
2357 |
-
value:
|
2358 |
- type: ndcg_at_100
|
2359 |
-
value:
|
2360 |
- type: ndcg_at_1000
|
2361 |
-
value: 38.
|
2362 |
- type: ndcg_at_3
|
2363 |
-
value:
|
2364 |
- type: ndcg_at_5
|
2365 |
-
value:
|
2366 |
- type: precision_at_1
|
2367 |
-
value:
|
2368 |
- type: precision_at_10
|
2369 |
-
value: 59.
|
2370 |
- type: precision_at_100
|
2371 |
-
value:
|
2372 |
- type: precision_at_1000
|
2373 |
-
value: 17.
|
2374 |
- type: precision_at_3
|
2375 |
-
value:
|
2376 |
- type: precision_at_5
|
2377 |
-
value:
|
2378 |
- type: recall_at_1
|
2379 |
-
value: 0.
|
2380 |
- type: recall_at_10
|
2381 |
-
value: 1.
|
2382 |
- type: recall_at_100
|
2383 |
-
value:
|
2384 |
- type: recall_at_1000
|
2385 |
-
value: 35.
|
2386 |
- type: recall_at_3
|
2387 |
-
value: 0.
|
2388 |
- type: recall_at_5
|
2389 |
-
value: 0.
|
2390 |
- task:
|
2391 |
type: Retrieval
|
2392 |
dataset:
|
@@ -2397,65 +2328,65 @@ model-index:
|
|
2397 |
revision: None
|
2398 |
metrics:
|
2399 |
- type: map_at_1
|
2400 |
-
value:
|
2401 |
- type: map_at_10
|
2402 |
-
value:
|
2403 |
- type: map_at_100
|
2404 |
-
value:
|
2405 |
- type: map_at_1000
|
2406 |
-
value:
|
2407 |
- type: map_at_3
|
2408 |
-
value:
|
2409 |
- type: map_at_5
|
2410 |
-
value:
|
2411 |
- type: mrr_at_1
|
2412 |
-
value:
|
2413 |
- type: mrr_at_10
|
2414 |
-
value:
|
2415 |
- type: mrr_at_100
|
2416 |
-
value:
|
2417 |
- type: mrr_at_1000
|
2418 |
-
value:
|
2419 |
- type: mrr_at_3
|
2420 |
-
value:
|
2421 |
- type: mrr_at_5
|
2422 |
-
value:
|
2423 |
- type: ndcg_at_1
|
2424 |
-
value:
|
2425 |
- type: ndcg_at_10
|
2426 |
-
value:
|
2427 |
- type: ndcg_at_100
|
2428 |
-
value:
|
2429 |
- type: ndcg_at_1000
|
2430 |
-
value:
|
2431 |
- type: ndcg_at_3
|
2432 |
-
value:
|
2433 |
- type: ndcg_at_5
|
2434 |
-
value:
|
2435 |
- type: precision_at_1
|
2436 |
-
value:
|
2437 |
- type: precision_at_10
|
2438 |
-
value:
|
2439 |
- type: precision_at_100
|
2440 |
-
value:
|
2441 |
- type: precision_at_1000
|
2442 |
-
value: 1.
|
2443 |
- type: precision_at_3
|
2444 |
-
value:
|
2445 |
- type: precision_at_5
|
2446 |
-
value: 20.
|
2447 |
- type: recall_at_1
|
2448 |
-
value:
|
2449 |
- type: recall_at_10
|
2450 |
-
value:
|
2451 |
- type: recall_at_100
|
2452 |
-
value:
|
2453 |
- type: recall_at_1000
|
2454 |
-
value:
|
2455 |
- type: recall_at_3
|
2456 |
-
value:
|
2457 |
- type: recall_at_5
|
2458 |
-
value: 7.
|
2459 |
- task:
|
2460 |
type: Classification
|
2461 |
dataset:
|
@@ -2466,11 +2397,11 @@ model-index:
|
|
2466 |
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
|
2467 |
metrics:
|
2468 |
- type: accuracy
|
2469 |
-
value:
|
2470 |
- type: ap
|
2471 |
-
value:
|
2472 |
- type: f1
|
2473 |
-
value:
|
2474 |
- task:
|
2475 |
type: Classification
|
2476 |
dataset:
|
@@ -2481,9 +2412,9 @@ model-index:
|
|
2481 |
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
|
2482 |
metrics:
|
2483 |
- type: accuracy
|
2484 |
-
value:
|
2485 |
- type: f1
|
2486 |
-
value:
|
2487 |
- task:
|
2488 |
type: Clustering
|
2489 |
dataset:
|
@@ -2494,7 +2425,7 @@ model-index:
|
|
2494 |
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
|
2495 |
metrics:
|
2496 |
- type: v_measure
|
2497 |
-
value:
|
2498 |
- task:
|
2499 |
type: PairClassification
|
2500 |
dataset:
|
@@ -2505,51 +2436,51 @@ model-index:
|
|
2505 |
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
|
2506 |
metrics:
|
2507 |
- type: cos_sim_accuracy
|
2508 |
-
value:
|
2509 |
- type: cos_sim_ap
|
2510 |
-
value:
|
2511 |
- type: cos_sim_f1
|
2512 |
-
value:
|
2513 |
- type: cos_sim_precision
|
2514 |
-
value:
|
2515 |
- type: cos_sim_recall
|
2516 |
-
value:
|
2517 |
- type: dot_accuracy
|
2518 |
-
value:
|
2519 |
- type: dot_ap
|
2520 |
-
value:
|
2521 |
- type: dot_f1
|
2522 |
-
value:
|
2523 |
- type: dot_precision
|
2524 |
-
value:
|
2525 |
- type: dot_recall
|
2526 |
-
value:
|
2527 |
- type: euclidean_accuracy
|
2528 |
-
value:
|
2529 |
- type: euclidean_ap
|
2530 |
-
value:
|
2531 |
- type: euclidean_f1
|
2532 |
-
value:
|
2533 |
- type: euclidean_precision
|
2534 |
-
value:
|
2535 |
- type: euclidean_recall
|
2536 |
-
value: 66.
|
2537 |
- type: manhattan_accuracy
|
2538 |
-
value:
|
2539 |
- type: manhattan_ap
|
2540 |
-
value:
|
2541 |
- type: manhattan_f1
|
2542 |
-
value:
|
2543 |
- type: manhattan_precision
|
2544 |
-
value:
|
2545 |
- type: manhattan_recall
|
2546 |
-
value:
|
2547 |
- type: max_accuracy
|
2548 |
-
value:
|
2549 |
- type: max_ap
|
2550 |
-
value:
|
2551 |
- type: max_f1
|
2552 |
-
value:
|
2553 |
- task:
|
2554 |
type: PairClassification
|
2555 |
dataset:
|
@@ -2560,51 +2491,51 @@ model-index:
|
|
2560 |
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
|
2561 |
metrics:
|
2562 |
- type: cos_sim_accuracy
|
2563 |
-
value:
|
2564 |
- type: cos_sim_ap
|
2565 |
-
value:
|
2566 |
- type: cos_sim_f1
|
2567 |
-
value:
|
2568 |
- type: cos_sim_precision
|
2569 |
-
value:
|
2570 |
- type: cos_sim_recall
|
2571 |
-
value:
|
2572 |
- type: dot_accuracy
|
2573 |
-
value:
|
2574 |
- type: dot_ap
|
2575 |
-
value:
|
2576 |
- type: dot_f1
|
2577 |
-
value:
|
2578 |
- type: dot_precision
|
2579 |
-
value:
|
2580 |
- type: dot_recall
|
2581 |
-
value:
|
2582 |
- type: euclidean_accuracy
|
2583 |
-
value:
|
2584 |
- type: euclidean_ap
|
2585 |
-
value:
|
2586 |
- type: euclidean_f1
|
2587 |
-
value:
|
2588 |
- type: euclidean_precision
|
2589 |
-
value:
|
2590 |
- type: euclidean_recall
|
2591 |
-
value:
|
2592 |
- type: manhattan_accuracy
|
2593 |
-
value:
|
2594 |
- type: manhattan_ap
|
2595 |
-
value:
|
2596 |
- type: manhattan_f1
|
2597 |
-
value:
|
2598 |
- type: manhattan_precision
|
2599 |
-
value:
|
2600 |
- type: manhattan_recall
|
2601 |
-
value:
|
2602 |
- type: max_accuracy
|
2603 |
-
value:
|
2604 |
- type: max_ap
|
2605 |
-
value:
|
2606 |
- type: max_f1
|
2607 |
-
value:
|
2608 |
---
|
2609 |
|
2610 |
<br><br>
|
|
|
11 |
language: en
|
12 |
license: apache-2.0
|
13 |
model-index:
|
14 |
+
- name: jina-triplets-large
|
15 |
results:
|
16 |
- task:
|
17 |
type: Classification
|
|
|
23 |
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
|
24 |
metrics:
|
25 |
- type: accuracy
|
26 |
+
value: 68.92537313432835
|
27 |
- type: ap
|
28 |
+
value: 29.723758877632513
|
29 |
- type: f1
|
30 |
+
value: 61.909704211663794
|
31 |
- task:
|
32 |
type: Classification
|
33 |
dataset:
|
|
|
38 |
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
|
39 |
metrics:
|
40 |
- type: accuracy
|
41 |
+
value: 69.13669999999999
|
42 |
- type: ap
|
43 |
+
value: 65.30216072238086
|
44 |
- type: f1
|
45 |
+
value: 67.1890891071034
|
46 |
- task:
|
47 |
type: Classification
|
48 |
dataset:
|
|
|
53 |
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
|
54 |
metrics:
|
55 |
- type: accuracy
|
56 |
+
value: 31.384
|
57 |
- type: f1
|
58 |
+
value: 30.016752348953723
|
59 |
- task:
|
60 |
type: Retrieval
|
61 |
dataset:
|
62 |
+
type: arguana
|
63 |
+
name: MTEB ArguAna
|
64 |
config: default
|
65 |
split: test
|
66 |
revision: None
|
67 |
metrics:
|
68 |
- type: map_at_1
|
69 |
+
value: 23.613
|
70 |
- type: map_at_10
|
71 |
+
value: 37.897
|
72 |
- type: map_at_100
|
73 |
+
value: 39.093
|
74 |
- type: map_at_1000
|
75 |
+
value: 39.109
|
76 |
- type: map_at_3
|
77 |
+
value: 32.824
|
78 |
- type: map_at_5
|
79 |
+
value: 35.679
|
80 |
- type: mrr_at_1
|
81 |
+
value: 23.826
|
82 |
- type: mrr_at_10
|
83 |
+
value: 37.997
|
84 |
- type: mrr_at_100
|
85 |
+
value: 39.186
|
86 |
- type: mrr_at_1000
|
87 |
+
value: 39.202
|
88 |
- type: mrr_at_3
|
89 |
+
value: 32.918
|
90 |
- type: mrr_at_5
|
91 |
+
value: 35.748999999999995
|
92 |
- type: ndcg_at_1
|
93 |
+
value: 23.613
|
94 |
- type: ndcg_at_10
|
95 |
+
value: 46.482
|
96 |
- type: ndcg_at_100
|
97 |
+
value: 51.55499999999999
|
98 |
- type: ndcg_at_1000
|
99 |
+
value: 51.974
|
100 |
- type: ndcg_at_3
|
101 |
+
value: 35.964
|
102 |
- type: ndcg_at_5
|
103 |
+
value: 41.144999999999996
|
104 |
- type: precision_at_1
|
105 |
+
value: 23.613
|
106 |
- type: precision_at_10
|
107 |
+
value: 7.417999999999999
|
108 |
- type: precision_at_100
|
109 |
+
value: 0.963
|
110 |
- type: precision_at_1000
|
111 |
+
value: 0.1
|
112 |
- type: precision_at_3
|
113 |
+
value: 15.031
|
114 |
- type: precision_at_5
|
115 |
+
value: 11.55
|
116 |
- type: recall_at_1
|
117 |
+
value: 23.613
|
118 |
- type: recall_at_10
|
119 |
+
value: 74.182
|
120 |
- type: recall_at_100
|
121 |
+
value: 96.30199999999999
|
122 |
- type: recall_at_1000
|
123 |
+
value: 99.57300000000001
|
124 |
- type: recall_at_3
|
125 |
+
value: 45.092
|
126 |
- type: recall_at_5
|
127 |
+
value: 57.752
|
128 |
+
- task:
|
129 |
+
type: Clustering
|
130 |
+
dataset:
|
131 |
+
type: mteb/arxiv-clustering-p2p
|
132 |
+
name: MTEB ArxivClusteringP2P
|
133 |
+
config: default
|
134 |
+
split: test
|
135 |
+
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
|
136 |
+
metrics:
|
137 |
+
- type: v_measure
|
138 |
+
value: 40.51285742156528
|
139 |
+
- task:
|
140 |
+
type: Clustering
|
141 |
+
dataset:
|
142 |
+
type: mteb/arxiv-clustering-s2s
|
143 |
+
name: MTEB ArxivClusteringS2S
|
144 |
+
config: default
|
145 |
+
split: test
|
146 |
+
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
|
147 |
+
metrics:
|
148 |
+
- type: v_measure
|
149 |
+
value: 31.5825964077496
|
150 |
+
- task:
|
151 |
+
type: Reranking
|
152 |
+
dataset:
|
153 |
+
type: mteb/askubuntudupquestions-reranking
|
154 |
+
name: MTEB AskUbuntuDupQuestions
|
155 |
+
config: default
|
156 |
+
split: test
|
157 |
+
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
|
158 |
+
metrics:
|
159 |
+
- type: map
|
160 |
+
value: 62.830281630546835
|
161 |
+
- type: mrr
|
162 |
+
value: 75.93072593765115
|
163 |
+
- task:
|
164 |
+
type: STS
|
165 |
+
dataset:
|
166 |
+
type: mteb/biosses-sts
|
167 |
+
name: MTEB BIOSSES
|
168 |
+
config: default
|
169 |
+
split: test
|
170 |
+
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
|
171 |
+
metrics:
|
172 |
+
- type: cos_sim_pearson
|
173 |
+
value: 87.26764516732737
|
174 |
+
- type: cos_sim_spearman
|
175 |
+
value: 84.42541766631741
|
176 |
+
- type: euclidean_pearson
|
177 |
+
value: 48.71357447655235
|
178 |
+
- type: euclidean_spearman
|
179 |
+
value: 49.2023259276511
|
180 |
+
- type: manhattan_pearson
|
181 |
+
value: 48.36366272727299
|
182 |
+
- type: manhattan_spearman
|
183 |
+
value: 48.457128224924354
|
184 |
+
- task:
|
185 |
+
type: Classification
|
186 |
+
dataset:
|
187 |
+
type: mteb/banking77
|
188 |
+
name: MTEB Banking77Classification
|
189 |
+
config: default
|
190 |
+
split: test
|
191 |
+
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
|
192 |
+
metrics:
|
193 |
+
- type: accuracy
|
194 |
+
value: 85.3409090909091
|
195 |
+
- type: f1
|
196 |
+
value: 85.25262617676835
|
197 |
+
- task:
|
198 |
+
type: Clustering
|
199 |
+
dataset:
|
200 |
+
type: mteb/biorxiv-clustering-p2p
|
201 |
+
name: MTEB BiorxivClusteringP2P
|
202 |
+
config: default
|
203 |
+
split: test
|
204 |
+
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
|
205 |
+
metrics:
|
206 |
+
- type: v_measure
|
207 |
+
value: 33.560193912974974
|
208 |
+
- task:
|
209 |
+
type: Clustering
|
210 |
+
dataset:
|
211 |
+
type: mteb/biorxiv-clustering-s2s
|
212 |
+
name: MTEB BiorxivClusteringS2S
|
213 |
+
config: default
|
214 |
+
split: test
|
215 |
+
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
|
216 |
+
metrics:
|
217 |
+
- type: v_measure
|
218 |
+
value: 28.4426572644577
|
219 |
- task:
|
220 |
type: Retrieval
|
221 |
dataset:
|
222 |
type: BeIR/cqadupstack
|
223 |
+
name: MTEB CQADupstackAndroidRetrieval
|
224 |
config: default
|
225 |
split: test
|
226 |
revision: None
|
227 |
metrics:
|
228 |
- type: map_at_1
|
229 |
+
value: 27.822999999999997
|
230 |
- type: map_at_10
|
231 |
+
value: 39.088
|
232 |
- type: map_at_100
|
233 |
+
value: 40.561
|
234 |
- type: map_at_1000
|
235 |
+
value: 40.69
|
236 |
- type: map_at_3
|
237 |
+
value: 35.701
|
238 |
- type: map_at_5
|
239 |
+
value: 37.556
|
240 |
- type: mrr_at_1
|
241 |
+
value: 33.906
|
242 |
- type: mrr_at_10
|
243 |
+
value: 44.527
|
244 |
- type: mrr_at_100
|
245 |
+
value: 45.403999999999996
|
246 |
- type: mrr_at_1000
|
247 |
+
value: 45.452
|
248 |
- type: mrr_at_3
|
249 |
+
value: 41.726
|
250 |
- type: mrr_at_5
|
251 |
+
value: 43.314
|
252 |
- type: ndcg_at_1
|
253 |
+
value: 33.906
|
254 |
- type: ndcg_at_10
|
255 |
+
value: 45.591
|
256 |
- type: ndcg_at_100
|
257 |
+
value: 51.041000000000004
|
258 |
- type: ndcg_at_1000
|
259 |
+
value: 53.1
|
260 |
- type: ndcg_at_3
|
261 |
+
value: 40.324
|
262 |
- type: ndcg_at_5
|
263 |
+
value: 42.723
|
264 |
- type: precision_at_1
|
265 |
+
value: 33.906
|
266 |
- type: precision_at_10
|
267 |
+
value: 8.655
|
268 |
- type: precision_at_100
|
269 |
+
value: 1.418
|
270 |
- type: precision_at_1000
|
271 |
value: 0.19499999999999998
|
272 |
- type: precision_at_3
|
273 |
+
value: 19.123
|
274 |
- type: precision_at_5
|
275 |
+
value: 13.963000000000001
|
276 |
- type: recall_at_1
|
277 |
+
value: 27.822999999999997
|
278 |
- type: recall_at_10
|
279 |
+
value: 58.63699999999999
|
280 |
- type: recall_at_100
|
281 |
+
value: 80.874
|
282 |
- type: recall_at_1000
|
283 |
+
value: 93.82000000000001
|
284 |
- type: recall_at_3
|
285 |
+
value: 44.116
|
286 |
- type: recall_at_5
|
287 |
+
value: 50.178999999999995
|
288 |
- task:
|
289 |
type: Retrieval
|
290 |
dataset:
|
291 |
type: BeIR/cqadupstack
|
292 |
+
name: MTEB CQADupstackEnglishRetrieval
|
293 |
config: default
|
294 |
split: test
|
295 |
revision: None
|
296 |
metrics:
|
297 |
- type: map_at_1
|
298 |
+
value: 26.823999999999998
|
299 |
- type: map_at_10
|
300 |
+
value: 37.006
|
301 |
- type: map_at_100
|
302 |
+
value: 38.256
|
303 |
- type: map_at_1000
|
304 |
+
value: 38.397999999999996
|
305 |
- type: map_at_3
|
306 |
+
value: 34.011
|
307 |
- type: map_at_5
|
308 |
+
value: 35.643
|
309 |
- type: mrr_at_1
|
310 |
+
value: 34.268
|
311 |
- type: mrr_at_10
|
312 |
+
value: 43.374
|
313 |
- type: mrr_at_100
|
314 |
+
value: 44.096000000000004
|
315 |
- type: mrr_at_1000
|
316 |
+
value: 44.144
|
317 |
- type: mrr_at_3
|
318 |
+
value: 41.008
|
319 |
- type: mrr_at_5
|
320 |
+
value: 42.359
|
321 |
- type: ndcg_at_1
|
322 |
+
value: 34.268
|
323 |
- type: ndcg_at_10
|
324 |
+
value: 43.02
|
325 |
- type: ndcg_at_100
|
326 |
+
value: 47.747
|
327 |
- type: ndcg_at_1000
|
328 |
+
value: 50.019999999999996
|
329 |
- type: ndcg_at_3
|
330 |
+
value: 38.687
|
331 |
- type: ndcg_at_5
|
332 |
+
value: 40.647
|
333 |
- type: precision_at_1
|
334 |
+
value: 34.268
|
335 |
- type: precision_at_10
|
336 |
+
value: 8.261000000000001
|
337 |
- type: precision_at_100
|
338 |
+
value: 1.376
|
339 |
- type: precision_at_1000
|
340 |
+
value: 0.189
|
341 |
- type: precision_at_3
|
342 |
+
value: 19.108
|
343 |
- type: precision_at_5
|
344 |
+
value: 13.489999999999998
|
345 |
- type: recall_at_1
|
346 |
+
value: 26.823999999999998
|
347 |
- type: recall_at_10
|
348 |
+
value: 53.84100000000001
|
349 |
- type: recall_at_100
|
350 |
+
value: 73.992
|
351 |
- type: recall_at_1000
|
352 |
+
value: 88.524
|
353 |
- type: recall_at_3
|
354 |
+
value: 40.711000000000006
|
355 |
- type: recall_at_5
|
356 |
+
value: 46.477000000000004
|
357 |
- task:
|
358 |
type: Retrieval
|
359 |
dataset:
|
360 |
type: BeIR/cqadupstack
|
361 |
+
name: MTEB CQADupstackGamingRetrieval
|
362 |
config: default
|
363 |
split: test
|
364 |
revision: None
|
365 |
metrics:
|
366 |
- type: map_at_1
|
367 |
+
value: 34.307
|
368 |
- type: map_at_10
|
369 |
+
value: 45.144
|
370 |
- type: map_at_100
|
371 |
+
value: 46.351
|
372 |
- type: map_at_1000
|
373 |
+
value: 46.414
|
374 |
- type: map_at_3
|
375 |
+
value: 42.315000000000005
|
376 |
- type: map_at_5
|
377 |
+
value: 43.991
|
378 |
- type: mrr_at_1
|
379 |
+
value: 39.06
|
380 |
- type: mrr_at_10
|
381 |
+
value: 48.612
|
382 |
- type: mrr_at_100
|
383 |
+
value: 49.425000000000004
|
384 |
- type: mrr_at_1000
|
385 |
+
value: 49.458999999999996
|
386 |
- type: mrr_at_3
|
387 |
+
value: 46.144
|
388 |
- type: mrr_at_5
|
389 |
+
value: 47.654999999999994
|
390 |
- type: ndcg_at_1
|
391 |
+
value: 39.06
|
392 |
- type: ndcg_at_10
|
393 |
+
value: 50.647
|
394 |
- type: ndcg_at_100
|
395 |
+
value: 55.620000000000005
|
396 |
- type: ndcg_at_1000
|
397 |
+
value: 56.976000000000006
|
398 |
- type: ndcg_at_3
|
399 |
+
value: 45.705
|
400 |
- type: ndcg_at_5
|
401 |
+
value: 48.269
|
402 |
- type: precision_at_1
|
403 |
+
value: 39.06
|
404 |
- type: precision_at_10
|
405 |
+
value: 8.082
|
406 |
- type: precision_at_100
|
407 |
+
value: 1.161
|
408 |
- type: precision_at_1000
|
409 |
+
value: 0.133
|
410 |
- type: precision_at_3
|
411 |
+
value: 20.376
|
412 |
- type: precision_at_5
|
413 |
+
value: 14.069
|
414 |
- type: recall_at_1
|
415 |
+
value: 34.307
|
416 |
- type: recall_at_10
|
417 |
+
value: 63.497
|
418 |
- type: recall_at_100
|
419 |
+
value: 85.038
|
420 |
- type: recall_at_1000
|
421 |
+
value: 94.782
|
422 |
- type: recall_at_3
|
423 |
+
value: 50.209
|
424 |
- type: recall_at_5
|
425 |
+
value: 56.525000000000006
|
426 |
- task:
|
427 |
type: Retrieval
|
428 |
dataset:
|
429 |
type: BeIR/cqadupstack
|
430 |
+
name: MTEB CQADupstackGisRetrieval
|
431 |
config: default
|
432 |
split: test
|
433 |
revision: None
|
434 |
metrics:
|
435 |
- type: map_at_1
|
436 |
+
value: 26.448
|
437 |
- type: map_at_10
|
438 |
+
value: 34.86
|
439 |
- type: map_at_100
|
440 |
+
value: 36.004999999999995
|
441 |
- type: map_at_1000
|
442 |
+
value: 36.081
|
443 |
- type: map_at_3
|
444 |
+
value: 32.527
|
445 |
- type: map_at_5
|
446 |
+
value: 33.955
|
447 |
- type: mrr_at_1
|
448 |
+
value: 28.701
|
449 |
- type: mrr_at_10
|
450 |
+
value: 36.909
|
451 |
- type: mrr_at_100
|
452 |
+
value: 37.89
|
453 |
- type: mrr_at_1000
|
454 |
+
value: 37.945
|
455 |
- type: mrr_at_3
|
456 |
+
value: 34.576
|
457 |
- type: mrr_at_5
|
458 |
+
value: 35.966
|
459 |
- type: ndcg_at_1
|
460 |
+
value: 28.701
|
461 |
- type: ndcg_at_10
|
462 |
+
value: 39.507999999999996
|
463 |
- type: ndcg_at_100
|
464 |
+
value: 45.056000000000004
|
465 |
- type: ndcg_at_1000
|
466 |
+
value: 47.034
|
467 |
- type: ndcg_at_3
|
468 |
+
value: 34.985
|
469 |
- type: ndcg_at_5
|
470 |
+
value: 37.384
|
471 |
- type: precision_at_1
|
472 |
+
value: 28.701
|
473 |
- type: precision_at_10
|
474 |
+
value: 5.921
|
475 |
- type: precision_at_100
|
476 |
+
value: 0.914
|
477 |
- type: precision_at_1000
|
478 |
+
value: 0.11199999999999999
|
479 |
- type: precision_at_3
|
480 |
+
value: 14.689
|
481 |
- type: precision_at_5
|
482 |
+
value: 10.237
|
483 |
- type: recall_at_1
|
484 |
+
value: 26.448
|
485 |
- type: recall_at_10
|
486 |
+
value: 51.781
|
487 |
- type: recall_at_100
|
488 |
+
value: 77.142
|
489 |
- type: recall_at_1000
|
490 |
+
value: 92.10000000000001
|
491 |
- type: recall_at_3
|
492 |
+
value: 39.698
|
493 |
- type: recall_at_5
|
494 |
+
value: 45.469
|
495 |
- task:
|
496 |
type: Retrieval
|
497 |
dataset:
|
498 |
type: BeIR/cqadupstack
|
499 |
+
name: MTEB CQADupstackMathematicaRetrieval
|
500 |
config: default
|
501 |
split: test
|
502 |
revision: None
|
503 |
metrics:
|
504 |
- type: map_at_1
|
505 |
+
value: 14.174000000000001
|
506 |
- type: map_at_10
|
507 |
+
value: 22.019
|
508 |
- type: map_at_100
|
509 |
+
value: 23.18
|
510 |
- type: map_at_1000
|
511 |
+
value: 23.304
|
512 |
- type: map_at_3
|
513 |
+
value: 19.332
|
514 |
- type: map_at_5
|
515 |
+
value: 20.816000000000003
|
516 |
- type: mrr_at_1
|
517 |
+
value: 17.785999999999998
|
518 |
- type: mrr_at_10
|
519 |
+
value: 26.233
|
520 |
- type: mrr_at_100
|
521 |
+
value: 27.254
|
522 |
- type: mrr_at_1000
|
523 |
+
value: 27.328000000000003
|
524 |
- type: mrr_at_3
|
525 |
+
value: 23.653
|
526 |
- type: mrr_at_5
|
527 |
+
value: 25.095
|
528 |
- type: ndcg_at_1
|
529 |
+
value: 17.785999999999998
|
530 |
- type: ndcg_at_10
|
531 |
+
value: 27.236
|
532 |
- type: ndcg_at_100
|
533 |
+
value: 32.932
|
534 |
- type: ndcg_at_1000
|
535 |
+
value: 36.134
|
536 |
- type: ndcg_at_3
|
537 |
+
value: 22.33
|
538 |
- type: ndcg_at_5
|
539 |
+
value: 24.573999999999998
|
540 |
- type: precision_at_1
|
541 |
+
value: 17.785999999999998
|
542 |
- type: precision_at_10
|
543 |
+
value: 5.286
|
544 |
- type: precision_at_100
|
545 |
+
value: 0.9369999999999999
|
546 |
- type: precision_at_1000
|
547 |
+
value: 0.136
|
548 |
- type: precision_at_3
|
549 |
+
value: 11.07
|
550 |
- type: precision_at_5
|
551 |
+
value: 8.308
|
552 |
- type: recall_at_1
|
553 |
+
value: 14.174000000000001
|
554 |
- type: recall_at_10
|
555 |
+
value: 39.135
|
556 |
- type: recall_at_100
|
557 |
+
value: 64.095
|
558 |
- type: recall_at_1000
|
559 |
+
value: 87.485
|
560 |
- type: recall_at_3
|
561 |
+
value: 25.496999999999996
|
562 |
- type: recall_at_5
|
563 |
+
value: 31.148999999999997
|
564 |
- task:
|
565 |
type: Retrieval
|
566 |
dataset:
|
567 |
type: BeIR/cqadupstack
|
568 |
+
name: MTEB CQADupstackPhysicsRetrieval
|
569 |
config: default
|
570 |
split: test
|
571 |
revision: None
|
572 |
metrics:
|
573 |
- type: map_at_1
|
574 |
+
value: 24.371000000000002
|
575 |
- type: map_at_10
|
576 |
+
value: 33.074999999999996
|
577 |
- type: map_at_100
|
578 |
+
value: 34.486
|
579 |
- type: map_at_1000
|
580 |
+
value: 34.608
|
581 |
- type: map_at_3
|
582 |
+
value: 30.483
|
583 |
- type: map_at_5
|
584 |
+
value: 31.972
|
585 |
- type: mrr_at_1
|
586 |
+
value: 29.548000000000002
|
587 |
- type: mrr_at_10
|
588 |
+
value: 38.431
|
589 |
- type: mrr_at_100
|
590 |
+
value: 39.347
|
591 |
- type: mrr_at_1000
|
592 |
+
value: 39.4
|
593 |
- type: mrr_at_3
|
594 |
+
value: 35.980000000000004
|
595 |
- type: mrr_at_5
|
596 |
+
value: 37.413999999999994
|
597 |
- type: ndcg_at_1
|
598 |
+
value: 29.548000000000002
|
599 |
- type: ndcg_at_10
|
600 |
+
value: 38.552
|
601 |
- type: ndcg_at_100
|
602 |
+
value: 44.598
|
603 |
- type: ndcg_at_1000
|
604 |
+
value: 47.0
|
605 |
- type: ndcg_at_3
|
606 |
+
value: 34.109
|
607 |
- type: ndcg_at_5
|
608 |
+
value: 36.263
|
609 |
- type: precision_at_1
|
610 |
+
value: 29.548000000000002
|
611 |
- type: precision_at_10
|
612 |
+
value: 6.92
|
613 |
- type: precision_at_100
|
614 |
+
value: 1.179
|
615 |
- type: precision_at_1000
|
616 |
+
value: 0.159
|
617 |
- type: precision_at_3
|
618 |
+
value: 16.137
|
619 |
- type: precision_at_5
|
620 |
+
value: 11.511000000000001
|
621 |
- type: recall_at_1
|
622 |
+
value: 24.371000000000002
|
623 |
- type: recall_at_10
|
624 |
+
value: 49.586999999999996
|
625 |
- type: recall_at_100
|
626 |
+
value: 75.15899999999999
|
627 |
- type: recall_at_1000
|
628 |
+
value: 91.06
|
629 |
- type: recall_at_3
|
630 |
+
value: 37.09
|
631 |
- type: recall_at_5
|
632 |
+
value: 42.588
|
633 |
- task:
|
634 |
type: Retrieval
|
635 |
dataset:
|
636 |
type: BeIR/cqadupstack
|
637 |
+
name: MTEB CQADupstackProgrammersRetrieval
|
638 |
config: default
|
639 |
split: test
|
640 |
revision: None
|
641 |
metrics:
|
642 |
- type: map_at_1
|
643 |
+
value: 24.517
|
644 |
- type: map_at_10
|
645 |
+
value: 32.969
|
646 |
- type: map_at_100
|
647 |
+
value: 34.199
|
648 |
- type: map_at_1000
|
649 |
+
value: 34.322
|
650 |
- type: map_at_3
|
651 |
+
value: 30.270999999999997
|
652 |
- type: map_at_5
|
653 |
+
value: 31.863000000000003
|
654 |
- type: mrr_at_1
|
655 |
+
value: 30.479
|
656 |
- type: mrr_at_10
|
657 |
+
value: 38.633
|
658 |
- type: mrr_at_100
|
659 |
+
value: 39.522
|
660 |
- type: mrr_at_1000
|
661 |
+
value: 39.583
|
662 |
- type: mrr_at_3
|
663 |
+
value: 36.454
|
664 |
- type: mrr_at_5
|
665 |
+
value: 37.744
|
666 |
- type: ndcg_at_1
|
667 |
+
value: 30.479
|
668 |
- type: ndcg_at_10
|
669 |
+
value: 38.269
|
670 |
- type: ndcg_at_100
|
671 |
+
value: 43.91
|
672 |
- type: ndcg_at_1000
|
673 |
+
value: 46.564
|
674 |
- type: ndcg_at_3
|
675 |
+
value: 34.03
|
676 |
- type: ndcg_at_5
|
677 |
+
value: 36.155
|
678 |
- type: precision_at_1
|
679 |
+
value: 30.479
|
680 |
- type: precision_at_10
|
681 |
+
value: 6.815
|
682 |
- type: precision_at_100
|
683 |
+
value: 1.138
|
684 |
- type: precision_at_1000
|
685 |
+
value: 0.158
|
686 |
- type: precision_at_3
|
687 |
+
value: 16.058
|
688 |
- type: precision_at_5
|
689 |
+
value: 11.416
|
690 |
- type: recall_at_1
|
691 |
+
value: 24.517
|
692 |
- type: recall_at_10
|
693 |
+
value: 48.559000000000005
|
694 |
- type: recall_at_100
|
695 |
+
value: 73.307
|
696 |
- type: recall_at_1000
|
697 |
+
value: 91.508
|
698 |
- type: recall_at_3
|
699 |
+
value: 36.563
|
700 |
- type: recall_at_5
|
701 |
+
value: 42.375
|
702 |
- task:
|
703 |
type: Retrieval
|
704 |
dataset:
|
|
|
709 |
revision: None
|
710 |
metrics:
|
711 |
- type: map_at_1
|
712 |
+
value: 23.388
|
713 |
- type: map_at_10
|
714 |
+
value: 29.408
|
715 |
- type: map_at_100
|
716 |
+
value: 30.452
|
717 |
- type: map_at_1000
|
718 |
+
value: 30.546
|
719 |
- type: map_at_3
|
720 |
+
value: 27.139000000000003
|
721 |
- type: map_at_5
|
722 |
+
value: 28.402
|
723 |
- type: mrr_at_1
|
724 |
+
value: 25.46
|
725 |
- type: mrr_at_10
|
726 |
+
value: 31.966
|
727 |
- type: mrr_at_100
|
728 |
+
value: 32.879999999999995
|
729 |
- type: mrr_at_1000
|
730 |
+
value: 32.944
|
731 |
- type: mrr_at_3
|
732 |
+
value: 29.755
|
733 |
- type: mrr_at_5
|
734 |
+
value: 30.974
|
735 |
- type: ndcg_at_1
|
736 |
+
value: 25.46
|
737 |
- type: ndcg_at_10
|
738 |
+
value: 33.449
|
739 |
- type: ndcg_at_100
|
740 |
+
value: 38.67
|
741 |
- type: ndcg_at_1000
|
742 |
+
value: 41.035
|
743 |
- type: ndcg_at_3
|
744 |
+
value: 29.048000000000002
|
745 |
- type: ndcg_at_5
|
746 |
+
value: 31.127
|
747 |
- type: precision_at_1
|
748 |
+
value: 25.46
|
749 |
- type: precision_at_10
|
750 |
+
value: 5.199
|
751 |
- type: precision_at_100
|
752 |
+
value: 0.8670000000000001
|
753 |
- type: precision_at_1000
|
754 |
+
value: 0.11399999999999999
|
755 |
- type: precision_at_3
|
756 |
+
value: 12.168
|
757 |
- type: precision_at_5
|
758 |
+
value: 8.62
|
759 |
- type: recall_at_1
|
760 |
+
value: 23.388
|
761 |
- type: recall_at_10
|
762 |
+
value: 43.428
|
763 |
- type: recall_at_100
|
764 |
+
value: 67.245
|
765 |
- type: recall_at_1000
|
766 |
+
value: 84.75399999999999
|
767 |
- type: recall_at_3
|
768 |
+
value: 31.416
|
769 |
- type: recall_at_5
|
770 |
+
value: 36.451
|
771 |
- task:
|
772 |
type: Retrieval
|
773 |
dataset:
|
|
|
778 |
revision: None
|
779 |
metrics:
|
780 |
- type: map_at_1
|
781 |
+
value: 17.136000000000003
|
782 |
- type: map_at_10
|
783 |
+
value: 24.102999999999998
|
784 |
- type: map_at_100
|
785 |
+
value: 25.219
|
786 |
- type: map_at_1000
|
787 |
+
value: 25.344
|
788 |
- type: map_at_3
|
789 |
+
value: 22.004
|
790 |
- type: map_at_5
|
791 |
+
value: 23.145
|
792 |
- type: mrr_at_1
|
793 |
+
value: 20.613
|
794 |
- type: mrr_at_10
|
795 |
+
value: 27.753
|
796 |
- type: mrr_at_100
|
797 |
+
value: 28.698
|
798 |
- type: mrr_at_1000
|
799 |
+
value: 28.776000000000003
|
800 |
- type: mrr_at_3
|
801 |
+
value: 25.711000000000002
|
802 |
- type: mrr_at_5
|
803 |
+
value: 26.795
|
804 |
- type: ndcg_at_1
|
805 |
+
value: 20.613
|
806 |
- type: ndcg_at_10
|
807 |
+
value: 28.510999999999996
|
808 |
- type: ndcg_at_100
|
809 |
+
value: 33.924
|
810 |
- type: ndcg_at_1000
|
811 |
+
value: 36.849
|
812 |
- type: ndcg_at_3
|
813 |
+
value: 24.664
|
814 |
- type: ndcg_at_5
|
815 |
+
value: 26.365
|
816 |
- type: precision_at_1
|
817 |
+
value: 20.613
|
818 |
- type: precision_at_10
|
819 |
+
value: 5.069
|
820 |
- type: precision_at_100
|
821 |
+
value: 0.918
|
822 |
- type: precision_at_1000
|
823 |
+
value: 0.136
|
824 |
- type: precision_at_3
|
825 |
+
value: 11.574
|
826 |
- type: precision_at_5
|
827 |
+
value: 8.211
|
828 |
- type: recall_at_1
|
829 |
+
value: 17.136000000000003
|
830 |
- type: recall_at_10
|
831 |
+
value: 38.232
|
832 |
- type: recall_at_100
|
833 |
+
value: 62.571
|
834 |
- type: recall_at_1000
|
835 |
+
value: 83.23
|
836 |
- type: recall_at_3
|
837 |
+
value: 27.468999999999998
|
838 |
- type: recall_at_5
|
839 |
+
value: 31.852999999999998
|
840 |
- task:
|
841 |
type: Retrieval
|
842 |
dataset:
|
|
|
847 |
revision: None
|
848 |
metrics:
|
849 |
- type: map_at_1
|
850 |
+
value: 25.580000000000002
|
851 |
- type: map_at_10
|
852 |
+
value: 33.449
|
853 |
- type: map_at_100
|
854 |
+
value: 34.58
|
855 |
- type: map_at_1000
|
856 |
+
value: 34.692
|
857 |
- type: map_at_3
|
858 |
+
value: 30.660999999999998
|
859 |
- type: map_at_5
|
860 |
+
value: 32.425
|
861 |
- type: mrr_at_1
|
862 |
+
value: 30.037000000000003
|
863 |
- type: mrr_at_10
|
864 |
+
value: 37.443
|
865 |
- type: mrr_at_100
|
866 |
+
value: 38.32
|
867 |
- type: mrr_at_1000
|
868 |
+
value: 38.384
|
869 |
- type: mrr_at_3
|
870 |
+
value: 34.778999999999996
|
871 |
- type: mrr_at_5
|
872 |
+
value: 36.458
|
873 |
- type: ndcg_at_1
|
874 |
+
value: 30.037000000000003
|
875 |
- type: ndcg_at_10
|
876 |
+
value: 38.46
|
877 |
- type: ndcg_at_100
|
878 |
+
value: 43.746
|
879 |
- type: ndcg_at_1000
|
880 |
+
value: 46.28
|
881 |
- type: ndcg_at_3
|
882 |
+
value: 33.52
|
883 |
- type: ndcg_at_5
|
884 |
+
value: 36.175000000000004
|
885 |
- type: precision_at_1
|
886 |
+
value: 30.037000000000003
|
887 |
- type: precision_at_10
|
888 |
+
value: 6.418
|
889 |
- type: precision_at_100
|
890 |
+
value: 1.0210000000000001
|
891 |
- type: precision_at_1000
|
892 |
+
value: 0.136
|
893 |
- type: precision_at_3
|
894 |
+
value: 15.018999999999998
|
895 |
- type: precision_at_5
|
896 |
+
value: 10.877
|
897 |
- type: recall_at_1
|
898 |
+
value: 25.580000000000002
|
899 |
- type: recall_at_10
|
900 |
+
value: 49.830000000000005
|
901 |
- type: recall_at_100
|
902 |
+
value: 73.04899999999999
|
903 |
- type: recall_at_1000
|
904 |
+
value: 90.751
|
905 |
- type: recall_at_3
|
906 |
+
value: 36.370999999999995
|
907 |
- type: recall_at_5
|
908 |
+
value: 43.104
|
909 |
- task:
|
910 |
type: Retrieval
|
911 |
dataset:
|
|
|
916 |
revision: None
|
917 |
metrics:
|
918 |
- type: map_at_1
|
919 |
+
value: 24.071
|
920 |
- type: map_at_10
|
921 |
+
value: 33.384
|
922 |
- type: map_at_100
|
923 |
+
value: 35.004999999999995
|
924 |
- type: map_at_1000
|
925 |
+
value: 35.215999999999994
|
926 |
- type: map_at_3
|
927 |
+
value: 30.459000000000003
|
928 |
- type: map_at_5
|
929 |
+
value: 31.769
|
930 |
- type: mrr_at_1
|
931 |
+
value: 28.854000000000003
|
932 |
- type: mrr_at_10
|
933 |
+
value: 37.512
|
934 |
- type: mrr_at_100
|
935 |
+
value: 38.567
|
936 |
- type: mrr_at_1000
|
937 |
+
value: 38.618
|
938 |
- type: mrr_at_3
|
939 |
+
value: 35.211
|
940 |
- type: mrr_at_5
|
941 |
+
value: 36.13
|
942 |
- type: ndcg_at_1
|
943 |
+
value: 28.854000000000003
|
944 |
- type: ndcg_at_10
|
945 |
+
value: 39.216
|
946 |
- type: ndcg_at_100
|
947 |
+
value: 45.214
|
948 |
- type: ndcg_at_1000
|
949 |
+
value: 47.573
|
950 |
- type: ndcg_at_3
|
951 |
+
value: 34.597
|
952 |
- type: ndcg_at_5
|
953 |
+
value: 36.063
|
954 |
- type: precision_at_1
|
955 |
+
value: 28.854000000000003
|
956 |
- type: precision_at_10
|
957 |
+
value: 7.648000000000001
|
958 |
- type: precision_at_100
|
959 |
+
value: 1.545
|
960 |
- type: precision_at_1000
|
961 |
+
value: 0.241
|
962 |
- type: precision_at_3
|
963 |
+
value: 16.667
|
964 |
- type: precision_at_5
|
965 |
+
value: 11.818
|
966 |
- type: recall_at_1
|
967 |
+
value: 24.071
|
968 |
- type: recall_at_10
|
969 |
+
value: 50.802
|
970 |
- type: recall_at_100
|
971 |
+
value: 77.453
|
972 |
- type: recall_at_1000
|
973 |
+
value: 92.304
|
974 |
- type: recall_at_3
|
975 |
+
value: 36.846000000000004
|
976 |
- type: recall_at_5
|
977 |
+
value: 41.14
|
978 |
- task:
|
979 |
type: Retrieval
|
980 |
dataset:
|
|
|
985 |
revision: None
|
986 |
metrics:
|
987 |
- type: map_at_1
|
988 |
+
value: 23.395
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
989 |
- type: map_at_10
|
990 |
+
value: 29.189999999999998
|
991 |
- type: map_at_100
|
992 |
+
value: 30.226999999999997
|
993 |
- type: map_at_1000
|
994 |
+
value: 30.337999999999997
|
995 |
- type: map_at_3
|
996 |
+
value: 27.342
|
997 |
- type: map_at_5
|
998 |
+
value: 28.116999999999997
|
999 |
- type: mrr_at_1
|
1000 |
+
value: 25.323
|
1001 |
- type: mrr_at_10
|
1002 |
+
value: 31.241000000000003
|
1003 |
- type: mrr_at_100
|
1004 |
+
value: 32.225
|
1005 |
- type: mrr_at_1000
|
1006 |
+
value: 32.304
|
1007 |
- type: mrr_at_3
|
1008 |
+
value: 29.452
|
1009 |
- type: mrr_at_5
|
1010 |
+
value: 30.209000000000003
|
1011 |
- type: ndcg_at_1
|
1012 |
+
value: 25.323
|
1013 |
- type: ndcg_at_10
|
1014 |
+
value: 33.024
|
1015 |
- type: ndcg_at_100
|
1016 |
+
value: 38.279
|
1017 |
- type: ndcg_at_1000
|
1018 |
+
value: 41.026
|
1019 |
- type: ndcg_at_3
|
1020 |
+
value: 29.243000000000002
|
1021 |
- type: ndcg_at_5
|
1022 |
+
value: 30.564000000000004
|
1023 |
- type: precision_at_1
|
1024 |
+
value: 25.323
|
1025 |
- type: precision_at_10
|
1026 |
+
value: 4.972
|
1027 |
- type: precision_at_100
|
1028 |
+
value: 0.8210000000000001
|
1029 |
- type: precision_at_1000
|
1030 |
+
value: 0.116
|
1031 |
- type: precision_at_3
|
1032 |
+
value: 12.076
|
1033 |
- type: precision_at_5
|
1034 |
+
value: 8.133
|
1035 |
- type: recall_at_1
|
1036 |
+
value: 23.395
|
1037 |
- type: recall_at_10
|
1038 |
+
value: 42.994
|
1039 |
- type: recall_at_100
|
1040 |
+
value: 66.985
|
1041 |
- type: recall_at_1000
|
1042 |
+
value: 87.483
|
1043 |
- type: recall_at_3
|
1044 |
+
value: 32.505
|
1045 |
- type: recall_at_5
|
1046 |
+
value: 35.721000000000004
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1047 |
- task:
|
1048 |
type: Retrieval
|
1049 |
dataset:
|
|
|
1054 |
revision: None
|
1055 |
metrics:
|
1056 |
- type: map_at_1
|
1057 |
+
value: 8.322000000000001
|
1058 |
- type: map_at_10
|
1059 |
+
value: 14.491000000000001
|
1060 |
- type: map_at_100
|
1061 |
+
value: 16.066
|
1062 |
- type: map_at_1000
|
1063 |
+
value: 16.238
|
1064 |
- type: map_at_3
|
1065 |
+
value: 12.235
|
1066 |
- type: map_at_5
|
1067 |
+
value: 13.422999999999998
|
1068 |
- type: mrr_at_1
|
1069 |
+
value: 19.479
|
1070 |
- type: mrr_at_10
|
1071 |
+
value: 29.38
|
1072 |
- type: mrr_at_100
|
1073 |
+
value: 30.520999999999997
|
1074 |
- type: mrr_at_1000
|
1075 |
+
value: 30.570999999999998
|
1076 |
- type: mrr_at_3
|
1077 |
+
value: 26.395000000000003
|
1078 |
- type: mrr_at_5
|
1079 |
+
value: 27.982000000000003
|
1080 |
- type: ndcg_at_1
|
1081 |
+
value: 19.479
|
1082 |
- type: ndcg_at_10
|
1083 |
+
value: 21.215
|
1084 |
- type: ndcg_at_100
|
1085 |
+
value: 27.966
|
1086 |
- type: ndcg_at_1000
|
1087 |
+
value: 31.324
|
1088 |
- type: ndcg_at_3
|
1089 |
+
value: 17.194000000000003
|
1090 |
- type: ndcg_at_5
|
1091 |
+
value: 18.593
|
1092 |
- type: precision_at_1
|
1093 |
+
value: 19.479
|
1094 |
- type: precision_at_10
|
1095 |
+
value: 6.5280000000000005
|
1096 |
- type: precision_at_100
|
1097 |
+
value: 1.359
|
1098 |
- type: precision_at_1000
|
1099 |
+
value: 0.198
|
1100 |
- type: precision_at_3
|
1101 |
+
value: 12.703999999999999
|
1102 |
- type: precision_at_5
|
1103 |
+
value: 9.655
|
1104 |
- type: recall_at_1
|
1105 |
+
value: 8.322000000000001
|
1106 |
- type: recall_at_10
|
1107 |
+
value: 26.165
|
1108 |
- type: recall_at_100
|
1109 |
+
value: 49.573
|
1110 |
- type: recall_at_1000
|
1111 |
+
value: 68.501
|
1112 |
- type: recall_at_3
|
1113 |
+
value: 16.179
|
1114 |
- type: recall_at_5
|
1115 |
+
value: 20.175
|
1116 |
- task:
|
1117 |
type: Retrieval
|
1118 |
dataset:
|
|
|
1123 |
revision: None
|
1124 |
metrics:
|
1125 |
- type: map_at_1
|
1126 |
+
value: 8.003
|
1127 |
- type: map_at_10
|
1128 |
+
value: 16.087
|
1129 |
- type: map_at_100
|
1130 |
+
value: 21.363
|
1131 |
- type: map_at_1000
|
1132 |
+
value: 22.64
|
1133 |
- type: map_at_3
|
1134 |
+
value: 12.171999999999999
|
1135 |
- type: map_at_5
|
1136 |
+
value: 13.866
|
1137 |
- type: mrr_at_1
|
1138 |
+
value: 61.25000000000001
|
1139 |
- type: mrr_at_10
|
1140 |
+
value: 68.626
|
1141 |
- type: mrr_at_100
|
1142 |
+
value: 69.134
|
1143 |
- type: mrr_at_1000
|
1144 |
+
value: 69.144
|
1145 |
- type: mrr_at_3
|
1146 |
+
value: 67.042
|
1147 |
- type: mrr_at_5
|
1148 |
+
value: 67.929
|
1149 |
- type: ndcg_at_1
|
1150 |
+
value: 49.0
|
1151 |
- type: ndcg_at_10
|
1152 |
+
value: 34.132
|
1153 |
- type: ndcg_at_100
|
1154 |
+
value: 37.545
|
1155 |
- type: ndcg_at_1000
|
1156 |
+
value: 44.544
|
1157 |
- type: ndcg_at_3
|
1158 |
+
value: 38.946999999999996
|
1159 |
- type: ndcg_at_5
|
1160 |
+
value: 36.317
|
1161 |
- type: precision_at_1
|
1162 |
+
value: 61.25000000000001
|
1163 |
- type: precision_at_10
|
1164 |
+
value: 26.325
|
1165 |
- type: precision_at_100
|
1166 |
+
value: 8.173
|
1167 |
- type: precision_at_1000
|
1168 |
+
value: 1.778
|
1169 |
- type: precision_at_3
|
1170 |
+
value: 41.667
|
1171 |
- type: precision_at_5
|
1172 |
+
value: 34.300000000000004
|
1173 |
- type: recall_at_1
|
1174 |
+
value: 8.003
|
1175 |
- type: recall_at_10
|
1176 |
+
value: 20.577
|
1177 |
- type: recall_at_100
|
1178 |
+
value: 41.884
|
1179 |
- type: recall_at_1000
|
1180 |
+
value: 64.36500000000001
|
1181 |
- type: recall_at_3
|
1182 |
+
value: 13.602
|
1183 |
- type: recall_at_5
|
1184 |
+
value: 16.41
|
1185 |
- task:
|
1186 |
type: Classification
|
1187 |
dataset:
|
|
|
1192 |
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
|
1193 |
metrics:
|
1194 |
- type: accuracy
|
1195 |
+
value: 45.835
|
1196 |
- type: f1
|
1197 |
+
value: 41.66455981281837
|
1198 |
- task:
|
1199 |
type: Retrieval
|
1200 |
dataset:
|
|
|
1205 |
revision: None
|
1206 |
metrics:
|
1207 |
- type: map_at_1
|
1208 |
+
value: 55.717000000000006
|
1209 |
- type: map_at_10
|
1210 |
+
value: 66.34100000000001
|
1211 |
- type: map_at_100
|
1212 |
+
value: 66.776
|
1213 |
- type: map_at_1000
|
1214 |
+
value: 66.794
|
1215 |
- type: map_at_3
|
1216 |
+
value: 64.386
|
1217 |
- type: map_at_5
|
1218 |
+
value: 65.566
|
1219 |
- type: mrr_at_1
|
1220 |
+
value: 60.141
|
1221 |
- type: mrr_at_10
|
1222 |
+
value: 70.928
|
1223 |
- type: mrr_at_100
|
1224 |
+
value: 71.29299999999999
|
1225 |
- type: mrr_at_1000
|
1226 |
+
value: 71.30199999999999
|
1227 |
- type: mrr_at_3
|
1228 |
+
value: 69.07900000000001
|
1229 |
- type: mrr_at_5
|
1230 |
+
value: 70.244
|
1231 |
- type: ndcg_at_1
|
1232 |
+
value: 60.141
|
1233 |
- type: ndcg_at_10
|
1234 |
+
value: 71.90100000000001
|
1235 |
- type: ndcg_at_100
|
1236 |
+
value: 73.836
|
1237 |
- type: ndcg_at_1000
|
1238 |
+
value: 74.214
|
1239 |
- type: ndcg_at_3
|
1240 |
+
value: 68.203
|
1241 |
- type: ndcg_at_5
|
1242 |
+
value: 70.167
|
1243 |
- type: precision_at_1
|
1244 |
+
value: 60.141
|
1245 |
- type: precision_at_10
|
1246 |
+
value: 9.268
|
1247 |
- type: precision_at_100
|
1248 |
+
value: 1.03
|
1249 |
- type: precision_at_1000
|
1250 |
value: 0.108
|
1251 |
- type: precision_at_3
|
1252 |
+
value: 27.028000000000002
|
1253 |
- type: precision_at_5
|
1254 |
+
value: 17.342
|
1255 |
- type: recall_at_1
|
1256 |
+
value: 55.717000000000006
|
1257 |
- type: recall_at_10
|
1258 |
+
value: 84.66799999999999
|
1259 |
- type: recall_at_100
|
1260 |
+
value: 93.28
|
1261 |
- type: recall_at_1000
|
1262 |
+
value: 95.887
|
1263 |
- type: recall_at_3
|
1264 |
+
value: 74.541
|
1265 |
- type: recall_at_5
|
1266 |
+
value: 79.389
|
1267 |
- task:
|
1268 |
type: Retrieval
|
1269 |
dataset:
|
|
|
1274 |
revision: None
|
1275 |
metrics:
|
1276 |
- type: map_at_1
|
1277 |
+
value: 17.744
|
1278 |
- type: map_at_10
|
1279 |
+
value: 29.554000000000002
|
1280 |
- type: map_at_100
|
1281 |
+
value: 31.180000000000003
|
1282 |
- type: map_at_1000
|
1283 |
+
value: 31.372
|
1284 |
- type: map_at_3
|
1285 |
+
value: 25.6
|
1286 |
- type: map_at_5
|
1287 |
+
value: 27.642
|
1288 |
- type: mrr_at_1
|
1289 |
+
value: 35.802
|
1290 |
- type: mrr_at_10
|
1291 |
+
value: 44.812999999999995
|
1292 |
- type: mrr_at_100
|
1293 |
+
value: 45.56
|
1294 |
- type: mrr_at_1000
|
1295 |
+
value: 45.606
|
1296 |
- type: mrr_at_3
|
1297 |
+
value: 42.181000000000004
|
1298 |
- type: mrr_at_5
|
1299 |
+
value: 43.516
|
1300 |
- type: ndcg_at_1
|
1301 |
+
value: 35.802
|
1302 |
- type: ndcg_at_10
|
1303 |
+
value: 37.269999999999996
|
1304 |
- type: ndcg_at_100
|
1305 |
+
value: 43.575
|
1306 |
- type: ndcg_at_1000
|
1307 |
+
value: 46.916000000000004
|
1308 |
- type: ndcg_at_3
|
1309 |
+
value: 33.511
|
1310 |
- type: ndcg_at_5
|
1311 |
+
value: 34.504000000000005
|
1312 |
- type: precision_at_1
|
1313 |
+
value: 35.802
|
1314 |
- type: precision_at_10
|
1315 |
+
value: 10.448
|
1316 |
- type: precision_at_100
|
1317 |
+
value: 1.7129999999999999
|
1318 |
- type: precision_at_1000
|
1319 |
+
value: 0.231
|
1320 |
- type: precision_at_3
|
1321 |
+
value: 22.531000000000002
|
1322 |
- type: precision_at_5
|
1323 |
+
value: 16.512
|
1324 |
- type: recall_at_1
|
1325 |
+
value: 17.744
|
1326 |
- type: recall_at_10
|
1327 |
+
value: 44.616
|
1328 |
- type: recall_at_100
|
1329 |
+
value: 68.51899999999999
|
1330 |
- type: recall_at_1000
|
1331 |
+
value: 88.495
|
1332 |
- type: recall_at_3
|
1333 |
+
value: 30.235
|
1334 |
- type: recall_at_5
|
1335 |
+
value: 35.821999999999996
|
1336 |
- task:
|
1337 |
type: Retrieval
|
1338 |
dataset:
|
|
|
1343 |
revision: None
|
1344 |
metrics:
|
1345 |
- type: map_at_1
|
1346 |
+
value: 33.315
|
1347 |
- type: map_at_10
|
1348 |
+
value: 45.932
|
1349 |
- type: map_at_100
|
1350 |
+
value: 46.708
|
1351 |
- type: map_at_1000
|
1352 |
+
value: 46.778999999999996
|
1353 |
- type: map_at_3
|
1354 |
+
value: 43.472
|
1355 |
- type: map_at_5
|
1356 |
+
value: 45.022
|
1357 |
- type: mrr_at_1
|
1358 |
+
value: 66.631
|
1359 |
- type: mrr_at_10
|
1360 |
+
value: 73.083
|
1361 |
- type: mrr_at_100
|
1362 |
+
value: 73.405
|
1363 |
- type: mrr_at_1000
|
1364 |
+
value: 73.421
|
1365 |
- type: mrr_at_3
|
1366 |
+
value: 71.756
|
1367 |
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value: 72.616
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|
1370 |
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value: 66.631
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1371 |
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value: 59.467000000000006
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value: 51.086
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value: 53.272
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value: 66.631
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value: 11.178
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1385 |
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value: 1.3559999999999999
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value: 0.156
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value: 31.582
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value: 20.678
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value: 33.315
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1395 |
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value: 55.888000000000005
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1398 |
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value: 67.812
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1399 |
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1400 |
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value: 77.839
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1402 |
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value: 47.373
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1403 |
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1404 |
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value: 51.695
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1405 |
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|
1406 |
type: Classification
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1407 |
dataset:
|
|
|
1412 |
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
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1414 |
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1415 |
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value: 66.424
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1416 |
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1417 |
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value: 61.132235499939256
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value: 66.07094958225315
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|
1421 |
type: Retrieval
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1422 |
dataset:
|
|
|
1427 |
revision: None
|
1428 |
metrics:
|
1429 |
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|
1430 |
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value: 21.575
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1431 |
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1432 |
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value: 33.509
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value: 34.775
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value: 29.673
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value: 31.805
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value: 22.235
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value: 34.1
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value: 35.254999999999995
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value: 35.299
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value: 30.334
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value: 32.419
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value: 22.235
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value: 40.341
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value: 46.161
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value: 47.400999999999996
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value: 32.482
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value: 36.269
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value: 22.235
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value: 6.422999999999999
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value: 0.9329999999999999
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1471 |
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value: 0.104
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value: 13.835
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value: 10.226
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value: 21.575
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value: 61.448
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1482 |
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value: 88.289
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value: 97.76899999999999
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value: 39.971000000000004
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1488 |
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value: 49.053000000000004
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|
1490 |
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1491 |
dataset:
|
|
|
1496 |
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
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1497 |
metrics:
|
1498 |
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1499 |
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value: 92.83401732786137
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1500 |
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1501 |
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value: 92.47678691291068
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1502 |
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1503 |
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1504 |
dataset:
|
|
|
1509 |
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
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1510 |
metrics:
|
1511 |
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1512 |
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value: 76.08983128134975
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1513 |
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1514 |
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value: 59.782936393820904
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1516 |
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1517 |
dataset:
|
|
|
1522 |
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
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1523 |
metrics:
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1524 |
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1525 |
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value: 72.73032952252858
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1526 |
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1527 |
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value: 70.72684765888265
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1529 |
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1530 |
dataset:
|
|
|
1535 |
revision: 7d571f92784cd94a019292a1f45445077d0ef634
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1536 |
metrics:
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1537 |
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1538 |
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value: 77.08473436449226
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1540 |
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value: 77.31457411257054
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1542 |
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1543 |
dataset:
|
|
|
1548 |
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
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1549 |
metrics:
|
1550 |
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1551 |
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value: 30.11980959210532
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1552 |
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|
1553 |
type: Clustering
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1554 |
dataset:
|
|
|
1559 |
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
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1560 |
metrics:
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1561 |
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1562 |
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value: 25.2587629106119
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|
1564 |
type: Reranking
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1565 |
dataset:
|
|
|
1570 |
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1571 |
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1572 |
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1573 |
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value: 31.48268319779204
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1575 |
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value: 32.501885728964304
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|
1577 |
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1578 |
dataset:
|
|
|
1583 |
revision: None
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1584 |
metrics:
|
1585 |
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1586 |
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value: 5.284
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1587 |
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1588 |
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value: 43.344
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1600 |
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value: 52.994
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1603 |
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1606 |
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value: 50.361
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value: 38.753
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value: 36.856
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value: 43.034
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value: 24.118000000000002
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value: 34.675
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value: 31.146
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value: 5.284
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value: 12.391
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1645 |
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1646 |
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1647 |
dataset:
|
|
|
1652 |
revision: None
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1653 |
metrics:
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1654 |
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1655 |
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value: 29.537999999999997
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value: 33.256
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value: 8.540000000000001
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value: 19.834
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1700 |
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value: 14.143
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value: 51.108
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1712 |
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1713 |
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value: 60.006
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1714 |
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|
1715 |
type: Retrieval
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1716 |
dataset:
|
|
|
1721 |
revision: None
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1722 |
metrics:
|
1723 |
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1724 |
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value: 70.526
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1725 |
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1726 |
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1734 |
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value: 83.292
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value: 86.387
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value: 85.319
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value: 13.33
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value: 37.31
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value: 99.479
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value: 87.124
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1781 |
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1782 |
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value: 91.53
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1783 |
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|
1784 |
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1785 |
dataset:
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|
|
1790 |
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
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metrics:
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value: 45.049073872893494
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1795 |
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dataset:
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|
|
1801 |
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metrics:
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1804 |
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value: 55.13810914528368
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1805 |
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1806 |
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1807 |
dataset:
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|
|
1812 |
revision: None
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1813 |
metrics:
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1814 |
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1815 |
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value: 4.593
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value: 9.983
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- type: recall_at_5
|
1873 |
+
value: 13.218
|
1874 |
- task:
|
1875 |
type: STS
|
1876 |
dataset:
|
|
|
1881 |
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
|
1882 |
metrics:
|
1883 |
- type: cos_sim_pearson
|
1884 |
+
value: 82.94432059816452
|
1885 |
- type: cos_sim_spearman
|
1886 |
+
value: 79.19993315048852
|
1887 |
- type: euclidean_pearson
|
1888 |
+
value: 72.43261099671753
|
1889 |
- type: euclidean_spearman
|
1890 |
+
value: 71.51531114998619
|
1891 |
- type: manhattan_pearson
|
1892 |
+
value: 71.83604124130447
|
1893 |
- type: manhattan_spearman
|
1894 |
+
value: 71.24460392842295
|
1895 |
- task:
|
1896 |
type: STS
|
1897 |
dataset:
|
|
|
1902 |
revision: a0d554a64d88156834ff5ae9920b964011b16384
|
1903 |
metrics:
|
1904 |
- type: cos_sim_pearson
|
1905 |
+
value: 84.25401068481673
|
1906 |
- type: cos_sim_spearman
|
1907 |
+
value: 74.5249604699309
|
1908 |
- type: euclidean_pearson
|
1909 |
+
value: 71.1324859629043
|
1910 |
- type: euclidean_spearman
|
1911 |
+
value: 58.77041705276752
|
1912 |
- type: manhattan_pearson
|
1913 |
+
value: 71.01471521586141
|
1914 |
- type: manhattan_spearman
|
1915 |
+
value: 58.69949381017865
|
1916 |
- task:
|
1917 |
type: STS
|
1918 |
dataset:
|
|
|
1923 |
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
|
1924 |
metrics:
|
1925 |
- type: cos_sim_pearson
|
1926 |
+
value: 82.85731544223766
|
1927 |
- type: cos_sim_spearman
|
1928 |
+
value: 83.15607264736185
|
1929 |
- type: euclidean_pearson
|
1930 |
+
value: 75.8803249521361
|
1931 |
- type: euclidean_spearman
|
1932 |
+
value: 76.4862168799065
|
1933 |
- type: manhattan_pearson
|
1934 |
+
value: 75.80451454386811
|
1935 |
- type: manhattan_spearman
|
1936 |
+
value: 76.35986831074699
|
1937 |
- task:
|
1938 |
type: STS
|
1939 |
dataset:
|
|
|
1944 |
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
|
1945 |
metrics:
|
1946 |
- type: cos_sim_pearson
|
1947 |
+
value: 82.40669043798857
|
1948 |
- type: cos_sim_spearman
|
1949 |
+
value: 78.08686090667834
|
1950 |
- type: euclidean_pearson
|
1951 |
+
value: 74.48574712193803
|
1952 |
- type: euclidean_spearman
|
1953 |
+
value: 70.79423012045118
|
1954 |
- type: manhattan_pearson
|
1955 |
+
value: 74.39099211477354
|
1956 |
- type: manhattan_spearman
|
1957 |
+
value: 70.73135427277684
|
1958 |
- task:
|
1959 |
type: STS
|
1960 |
dataset:
|
|
|
1965 |
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
|
1966 |
metrics:
|
1967 |
- type: cos_sim_pearson
|
1968 |
+
value: 86.03027014209859
|
1969 |
- type: cos_sim_spearman
|
1970 |
+
value: 86.91082847840946
|
1971 |
- type: euclidean_pearson
|
1972 |
+
value: 69.13187603971996
|
1973 |
- type: euclidean_spearman
|
1974 |
+
value: 70.0370035340552
|
1975 |
- type: manhattan_pearson
|
1976 |
+
value: 69.2586635812031
|
1977 |
- type: manhattan_spearman
|
1978 |
+
value: 70.18638387118486
|
1979 |
- task:
|
1980 |
type: STS
|
1981 |
dataset:
|
|
|
1986 |
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
|
1987 |
metrics:
|
1988 |
- type: cos_sim_pearson
|
1989 |
+
value: 82.41190748361883
|
1990 |
- type: cos_sim_spearman
|
1991 |
+
value: 83.64850851235231
|
1992 |
- type: euclidean_pearson
|
1993 |
+
value: 71.60523243575282
|
1994 |
- type: euclidean_spearman
|
1995 |
+
value: 72.26134033805099
|
1996 |
- type: manhattan_pearson
|
1997 |
+
value: 71.50771482066683
|
1998 |
- type: manhattan_spearman
|
1999 |
+
value: 72.13707967973161
|
2000 |
- task:
|
2001 |
type: STS
|
2002 |
dataset:
|
|
|
2007 |
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
|
2008 |
metrics:
|
2009 |
- type: cos_sim_pearson
|
2010 |
+
value: 90.42838477648627
|
2011 |
- type: cos_sim_spearman
|
2012 |
+
value: 90.15798155439076
|
2013 |
- type: euclidean_pearson
|
2014 |
+
value: 77.09619972244516
|
2015 |
- type: euclidean_spearman
|
2016 |
+
value: 75.5953488548861
|
2017 |
- type: manhattan_pearson
|
2018 |
+
value: 77.36892406451771
|
2019 |
- type: manhattan_spearman
|
2020 |
+
value: 75.76625156149356
|
2021 |
- task:
|
2022 |
type: STS
|
2023 |
dataset:
|
|
|
2028 |
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
|
2029 |
metrics:
|
2030 |
- type: cos_sim_pearson
|
2031 |
+
value: 65.76151154879307
|
2032 |
- type: cos_sim_spearman
|
2033 |
+
value: 64.8846800918359
|
2034 |
- type: euclidean_pearson
|
2035 |
+
value: 50.23302700257155
|
2036 |
- type: euclidean_spearman
|
2037 |
+
value: 58.89455187289583
|
2038 |
- type: manhattan_pearson
|
2039 |
+
value: 50.05498582284945
|
2040 |
- type: manhattan_spearman
|
2041 |
+
value: 58.75893793871576
|
2042 |
- task:
|
2043 |
type: STS
|
2044 |
dataset:
|
|
|
2049 |
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
|
2050 |
metrics:
|
2051 |
- type: cos_sim_pearson
|
2052 |
+
value: 84.72381109169437
|
2053 |
- type: cos_sim_spearman
|
2054 |
+
value: 84.59820928231167
|
2055 |
- type: euclidean_pearson
|
2056 |
+
value: 74.85450857429493
|
2057 |
- type: euclidean_spearman
|
2058 |
+
value: 73.83634052565915
|
2059 |
- type: manhattan_pearson
|
2060 |
+
value: 74.97349743979106
|
2061 |
- type: manhattan_spearman
|
2062 |
+
value: 73.9636470375881
|
2063 |
- task:
|
2064 |
type: Reranking
|
2065 |
dataset:
|
|
|
2070 |
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
|
2071 |
metrics:
|
2072 |
- type: map
|
2073 |
+
value: 80.96736259172798
|
2074 |
- type: mrr
|
2075 |
+
value: 94.48378781712114
|
2076 |
- task:
|
2077 |
type: Retrieval
|
2078 |
dataset:
|
|
|
2083 |
revision: None
|
2084 |
metrics:
|
2085 |
- type: map_at_1
|
2086 |
+
value: 46.344
|
2087 |
- type: map_at_10
|
2088 |
+
value: 54.962
|
2089 |
- type: map_at_100
|
2090 |
+
value: 55.772
|
2091 |
- type: map_at_1000
|
2092 |
+
value: 55.81700000000001
|
2093 |
- type: map_at_3
|
2094 |
+
value: 51.832
|
2095 |
- type: map_at_5
|
2096 |
+
value: 53.718999999999994
|
2097 |
- type: mrr_at_1
|
2098 |
+
value: 49.0
|
2099 |
- type: mrr_at_10
|
2100 |
+
value: 56.721
|
2101 |
- type: mrr_at_100
|
2102 |
+
value: 57.287
|
2103 |
- type: mrr_at_1000
|
2104 |
+
value: 57.330000000000005
|
2105 |
- type: mrr_at_3
|
2106 |
+
value: 54.056000000000004
|
2107 |
- type: mrr_at_5
|
2108 |
+
value: 55.822
|
2109 |
- type: ndcg_at_1
|
2110 |
+
value: 49.0
|
2111 |
- type: ndcg_at_10
|
2112 |
+
value: 59.757000000000005
|
2113 |
- type: ndcg_at_100
|
2114 |
+
value: 63.149
|
2115 |
- type: ndcg_at_1000
|
2116 |
+
value: 64.43100000000001
|
2117 |
- type: ndcg_at_3
|
2118 |
+
value: 54.105000000000004
|
2119 |
- type: ndcg_at_5
|
2120 |
+
value: 57.196999999999996
|
2121 |
- type: precision_at_1
|
2122 |
+
value: 49.0
|
2123 |
- type: precision_at_10
|
2124 |
+
value: 8.200000000000001
|
2125 |
- type: precision_at_100
|
2126 |
+
value: 1.0070000000000001
|
2127 |
- type: precision_at_1000
|
2128 |
+
value: 0.11100000000000002
|
2129 |
- type: precision_at_3
|
2130 |
+
value: 20.889
|
2131 |
- type: precision_at_5
|
2132 |
+
value: 14.399999999999999
|
2133 |
- type: recall_at_1
|
2134 |
+
value: 46.344
|
2135 |
- type: recall_at_10
|
2136 |
+
value: 72.722
|
2137 |
- type: recall_at_100
|
2138 |
+
value: 88.167
|
2139 |
- type: recall_at_1000
|
2140 |
+
value: 98.333
|
2141 |
- type: recall_at_3
|
2142 |
+
value: 57.994
|
2143 |
- type: recall_at_5
|
2144 |
+
value: 65.506
|
2145 |
- task:
|
2146 |
type: PairClassification
|
2147 |
dataset:
|
|
|
2152 |
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
|
2153 |
metrics:
|
2154 |
- type: cos_sim_accuracy
|
2155 |
+
value: 99.83366336633664
|
2156 |
- type: cos_sim_ap
|
2157 |
+
value: 96.09329747251944
|
2158 |
- type: cos_sim_f1
|
2159 |
+
value: 91.66255550074001
|
2160 |
- type: cos_sim_precision
|
2161 |
+
value: 90.45764362220059
|
2162 |
- type: cos_sim_recall
|
2163 |
+
value: 92.9
|
2164 |
- type: dot_accuracy
|
2165 |
+
value: 99.32871287128712
|
2166 |
- type: dot_ap
|
2167 |
+
value: 63.95436644147969
|
2168 |
- type: dot_f1
|
2169 |
+
value: 60.61814556331008
|
2170 |
- type: dot_precision
|
2171 |
+
value: 60.437375745526836
|
2172 |
- type: dot_recall
|
2173 |
+
value: 60.8
|
2174 |
- type: euclidean_accuracy
|
2175 |
+
value: 99.66534653465347
|
2176 |
- type: euclidean_ap
|
2177 |
+
value: 85.85143979761818
|
2178 |
- type: euclidean_f1
|
2179 |
+
value: 81.57033805888769
|
2180 |
- type: euclidean_precision
|
2181 |
+
value: 89.68824940047962
|
2182 |
- type: euclidean_recall
|
2183 |
+
value: 74.8
|
2184 |
- type: manhattan_accuracy
|
2185 |
+
value: 99.65742574257426
|
2186 |
- type: manhattan_ap
|
2187 |
+
value: 85.55693926348405
|
2188 |
- type: manhattan_f1
|
2189 |
+
value: 81.13804004214963
|
2190 |
- type: manhattan_precision
|
2191 |
+
value: 85.74610244988864
|
2192 |
- type: manhattan_recall
|
2193 |
+
value: 77.0
|
2194 |
- type: max_accuracy
|
2195 |
+
value: 99.83366336633664
|
2196 |
- type: max_ap
|
2197 |
+
value: 96.09329747251944
|
2198 |
- type: max_f1
|
2199 |
+
value: 91.66255550074001
|
2200 |
- task:
|
2201 |
type: Clustering
|
2202 |
dataset:
|
|
|
2207 |
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
|
2208 |
metrics:
|
2209 |
- type: v_measure
|
2210 |
+
value: 45.23573510003245
|
2211 |
- task:
|
2212 |
type: Clustering
|
2213 |
dataset:
|
|
|
2218 |
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
|
2219 |
metrics:
|
2220 |
- type: v_measure
|
2221 |
+
value: 33.37478638401161
|
2222 |
- task:
|
2223 |
type: Reranking
|
2224 |
dataset:
|
|
|
2229 |
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
|
2230 |
metrics:
|
2231 |
- type: map
|
2232 |
+
value: 50.375920467392476
|
2233 |
- type: mrr
|
2234 |
+
value: 51.17302223919871
|
2235 |
- task:
|
2236 |
type: Summarization
|
2237 |
dataset:
|
|
|
2242 |
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
|
2243 |
metrics:
|
2244 |
- type: cos_sim_pearson
|
2245 |
+
value: 29.768864092288343
|
2246 |
- type: cos_sim_spearman
|
2247 |
+
value: 29.854278347043266
|
2248 |
- type: dot_pearson
|
2249 |
+
value: 20.51281723837505
|
2250 |
- type: dot_spearman
|
2251 |
+
value: 21.799102540913665
|
2252 |
- task:
|
2253 |
type: Retrieval
|
2254 |
dataset:
|
|
|
2259 |
revision: None
|
2260 |
metrics:
|
2261 |
- type: map_at_1
|
2262 |
+
value: 0.2
|
2263 |
- type: map_at_10
|
2264 |
+
value: 1.202
|
2265 |
- type: map_at_100
|
2266 |
+
value: 6.729
|
2267 |
- type: map_at_1000
|
2268 |
+
value: 15.928
|
2269 |
- type: map_at_3
|
2270 |
+
value: 0.492
|
2271 |
- type: map_at_5
|
2272 |
value: 0.712
|
2273 |
- type: mrr_at_1
|
2274 |
+
value: 76.0
|
2275 |
- type: mrr_at_10
|
2276 |
+
value: 84.75
|
2277 |
- type: mrr_at_100
|
2278 |
+
value: 84.75
|
2279 |
- type: mrr_at_1000
|
2280 |
+
value: 84.75
|
2281 |
- type: mrr_at_3
|
2282 |
+
value: 83.0
|
2283 |
- type: mrr_at_5
|
2284 |
+
value: 84.5
|
2285 |
- type: ndcg_at_1
|
2286 |
+
value: 71.0
|
2287 |
- type: ndcg_at_10
|
2288 |
+
value: 57.253
|
2289 |
- type: ndcg_at_100
|
2290 |
+
value: 44.383
|
2291 |
- type: ndcg_at_1000
|
2292 |
+
value: 38.666
|
2293 |
- type: ndcg_at_3
|
2294 |
+
value: 64.324
|
2295 |
- type: ndcg_at_5
|
2296 |
+
value: 60.791
|
2297 |
- type: precision_at_1
|
2298 |
+
value: 76.0
|
2299 |
- type: precision_at_10
|
2300 |
+
value: 59.599999999999994
|
2301 |
- type: precision_at_100
|
2302 |
+
value: 45.440000000000005
|
2303 |
- type: precision_at_1000
|
2304 |
+
value: 17.458000000000002
|
2305 |
- type: precision_at_3
|
2306 |
+
value: 69.333
|
2307 |
- type: precision_at_5
|
2308 |
+
value: 63.2
|
2309 |
- type: recall_at_1
|
2310 |
+
value: 0.2
|
2311 |
- type: recall_at_10
|
2312 |
+
value: 1.4949999999999999
|
2313 |
- type: recall_at_100
|
2314 |
+
value: 10.266
|
2315 |
- type: recall_at_1000
|
2316 |
+
value: 35.853
|
2317 |
- type: recall_at_3
|
2318 |
+
value: 0.5349999999999999
|
2319 |
- type: recall_at_5
|
2320 |
+
value: 0.8109999999999999
|
2321 |
- task:
|
2322 |
type: Retrieval
|
2323 |
dataset:
|
|
|
2328 |
revision: None
|
2329 |
metrics:
|
2330 |
- type: map_at_1
|
2331 |
+
value: 2.0140000000000002
|
2332 |
- type: map_at_10
|
2333 |
+
value: 8.474
|
2334 |
- type: map_at_100
|
2335 |
+
value: 14.058000000000002
|
2336 |
- type: map_at_1000
|
2337 |
+
value: 15.381
|
2338 |
- type: map_at_3
|
2339 |
+
value: 4.508
|
2340 |
- type: map_at_5
|
2341 |
+
value: 5.87
|
2342 |
- type: mrr_at_1
|
2343 |
+
value: 22.448999999999998
|
2344 |
- type: mrr_at_10
|
2345 |
+
value: 37.242
|
2346 |
- type: mrr_at_100
|
2347 |
+
value: 38.291
|
2348 |
- type: mrr_at_1000
|
2349 |
+
value: 38.311
|
2350 |
- type: mrr_at_3
|
2351 |
+
value: 32.312999999999995
|
2352 |
- type: mrr_at_5
|
2353 |
+
value: 34.762
|
2354 |
- type: ndcg_at_1
|
2355 |
+
value: 20.408
|
2356 |
- type: ndcg_at_10
|
2357 |
+
value: 20.729
|
2358 |
- type: ndcg_at_100
|
2359 |
+
value: 33.064
|
2360 |
- type: ndcg_at_1000
|
2361 |
+
value: 44.324999999999996
|
2362 |
- type: ndcg_at_3
|
2363 |
+
value: 21.251
|
2364 |
- type: ndcg_at_5
|
2365 |
+
value: 20.28
|
2366 |
- type: precision_at_1
|
2367 |
+
value: 22.448999999999998
|
2368 |
- type: precision_at_10
|
2369 |
+
value: 18.98
|
2370 |
- type: precision_at_100
|
2371 |
+
value: 7.224
|
2372 |
- type: precision_at_1000
|
2373 |
+
value: 1.471
|
2374 |
- type: precision_at_3
|
2375 |
+
value: 22.448999999999998
|
2376 |
- type: precision_at_5
|
2377 |
+
value: 20.816000000000003
|
2378 |
- type: recall_at_1
|
2379 |
+
value: 2.0140000000000002
|
2380 |
- type: recall_at_10
|
2381 |
+
value: 13.96
|
2382 |
- type: recall_at_100
|
2383 |
+
value: 44.187
|
2384 |
- type: recall_at_1000
|
2385 |
+
value: 79.328
|
2386 |
- type: recall_at_3
|
2387 |
+
value: 5.345
|
2388 |
- type: recall_at_5
|
2389 |
+
value: 7.979
|
2390 |
- task:
|
2391 |
type: Classification
|
2392 |
dataset:
|
|
|
2397 |
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
|
2398 |
metrics:
|
2399 |
- type: accuracy
|
2400 |
+
value: 69.1312
|
2401 |
- type: ap
|
2402 |
+
value: 12.606776505497608
|
2403 |
- type: f1
|
2404 |
+
value: 52.4112415600534
|
2405 |
- task:
|
2406 |
type: Classification
|
2407 |
dataset:
|
|
|
2412 |
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
|
2413 |
metrics:
|
2414 |
- type: accuracy
|
2415 |
+
value: 58.16072439162422
|
2416 |
- type: f1
|
2417 |
+
value: 58.29152785435414
|
2418 |
- task:
|
2419 |
type: Clustering
|
2420 |
dataset:
|
|
|
2425 |
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
|
2426 |
metrics:
|
2427 |
- type: v_measure
|
2428 |
+
value: 40.421119289825924
|
2429 |
- task:
|
2430 |
type: PairClassification
|
2431 |
dataset:
|
|
|
2436 |
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
|
2437 |
metrics:
|
2438 |
- type: cos_sim_accuracy
|
2439 |
+
value: 85.48012159504083
|
2440 |
- type: cos_sim_ap
|
2441 |
+
value: 72.31974877212102
|
2442 |
- type: cos_sim_f1
|
2443 |
+
value: 67.96846573681019
|
2444 |
- type: cos_sim_precision
|
2445 |
+
value: 62.89562289562289
|
2446 |
- type: cos_sim_recall
|
2447 |
+
value: 73.93139841688654
|
2448 |
- type: dot_accuracy
|
2449 |
+
value: 78.52416999463551
|
2450 |
- type: dot_ap
|
2451 |
+
value: 43.65271285411479
|
2452 |
- type: dot_f1
|
2453 |
+
value: 46.94641449960599
|
2454 |
- type: dot_precision
|
2455 |
+
value: 37.456774599182644
|
2456 |
- type: dot_recall
|
2457 |
+
value: 62.875989445910285
|
2458 |
- type: euclidean_accuracy
|
2459 |
+
value: 83.90057817249806
|
2460 |
- type: euclidean_ap
|
2461 |
+
value: 65.96278727778665
|
2462 |
- type: euclidean_f1
|
2463 |
+
value: 63.35733232284957
|
2464 |
- type: euclidean_precision
|
2465 |
+
value: 60.770535497940394
|
2466 |
- type: euclidean_recall
|
2467 |
+
value: 66.17414248021109
|
2468 |
- type: manhattan_accuracy
|
2469 |
+
value: 83.96614412588663
|
2470 |
- type: manhattan_ap
|
2471 |
+
value: 66.03670273156699
|
2472 |
- type: manhattan_f1
|
2473 |
+
value: 63.49128406579917
|
2474 |
- type: manhattan_precision
|
2475 |
+
value: 59.366391184573
|
2476 |
- type: manhattan_recall
|
2477 |
+
value: 68.23218997361478
|
2478 |
- type: max_accuracy
|
2479 |
+
value: 85.48012159504083
|
2480 |
- type: max_ap
|
2481 |
+
value: 72.31974877212102
|
2482 |
- type: max_f1
|
2483 |
+
value: 67.96846573681019
|
2484 |
- task:
|
2485 |
type: PairClassification
|
2486 |
dataset:
|
|
|
2491 |
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
|
2492 |
metrics:
|
2493 |
- type: cos_sim_accuracy
|
2494 |
+
value: 88.97038848139093
|
2495 |
- type: cos_sim_ap
|
2496 |
+
value: 85.982764495556
|
2497 |
- type: cos_sim_f1
|
2498 |
+
value: 78.73283281450284
|
2499 |
- type: cos_sim_precision
|
2500 |
+
value: 75.07857791436754
|
2501 |
- type: cos_sim_recall
|
2502 |
+
value: 82.7610101632276
|
2503 |
- type: dot_accuracy
|
2504 |
+
value: 83.21108394458028
|
2505 |
- type: dot_ap
|
2506 |
+
value: 70.97956937273386
|
2507 |
- type: dot_f1
|
2508 |
+
value: 66.53083038279111
|
2509 |
- type: dot_precision
|
2510 |
+
value: 58.7551622418879
|
2511 |
- type: dot_recall
|
2512 |
+
value: 76.67847243609486
|
2513 |
- type: euclidean_accuracy
|
2514 |
+
value: 84.31520937633407
|
2515 |
- type: euclidean_ap
|
2516 |
+
value: 74.67323411319909
|
2517 |
- type: euclidean_f1
|
2518 |
+
value: 67.21935410935676
|
2519 |
- type: euclidean_precision
|
2520 |
+
value: 65.82773636430733
|
2521 |
- type: euclidean_recall
|
2522 |
+
value: 68.67108099784416
|
2523 |
- type: manhattan_accuracy
|
2524 |
+
value: 84.35013777312066
|
2525 |
- type: manhattan_ap
|
2526 |
+
value: 74.66508905354597
|
2527 |
- type: manhattan_f1
|
2528 |
+
value: 67.28264162375038
|
2529 |
- type: manhattan_precision
|
2530 |
+
value: 66.19970193740686
|
2531 |
- type: manhattan_recall
|
2532 |
+
value: 68.40160147828766
|
2533 |
- type: max_accuracy
|
2534 |
+
value: 88.97038848139093
|
2535 |
- type: max_ap
|
2536 |
+
value: 85.982764495556
|
2537 |
- type: max_f1
|
2538 |
+
value: 78.73283281450284
|
2539 |
---
|
2540 |
|
2541 |
<br><br>
|