Update README.md
Browse files
README.md
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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: 88.
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- type: ap
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-
value:
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- type: f1
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-
value: 88.
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| 46 |
- task:
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type: Classification
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| 48 |
dataset:
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@@ -53,9 +53,9 @@ model-index:
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revision: 1399c76144fd37290681b995c656ef9b2e06e26d
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metrics:
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- type: accuracy
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-
value:
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- type: f1
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-
value:
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- task:
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type: Retrieval
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dataset:
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|
@@ -66,65 +66,65 @@ model-index:
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revision: None
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metrics:
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- type: map_at_1
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| 69 |
-
value:
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- type: map_at_10
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| 71 |
-
value:
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- type: map_at_100
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| 73 |
-
value:
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| 74 |
- type: map_at_1000
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| 75 |
-
value:
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| 76 |
- type: map_at_3
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| 77 |
-
value:
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| 78 |
- type: map_at_5
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| 79 |
-
value:
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| 80 |
- type: mrr_at_1
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| 81 |
-
value:
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| 82 |
- type: mrr_at_10
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-
value:
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| 84 |
- type: mrr_at_100
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| 85 |
-
value:
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| 86 |
- type: mrr_at_1000
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| 87 |
-
value:
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| 88 |
- type: mrr_at_3
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| 89 |
-
value:
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| 90 |
- type: mrr_at_5
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| 91 |
-
value:
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| 92 |
- type: ndcg_at_1
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| 93 |
-
value:
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| 94 |
- type: ndcg_at_10
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| 95 |
-
value:
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| 96 |
- type: ndcg_at_100
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| 97 |
-
value:
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| 98 |
- type: ndcg_at_1000
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| 99 |
-
value:
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| 100 |
- type: ndcg_at_3
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| 101 |
-
value:
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| 102 |
- type: ndcg_at_5
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| 103 |
-
value:
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| 104 |
- type: precision_at_1
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| 105 |
-
value:
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| 106 |
- type: precision_at_10
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| 107 |
-
value: 7.
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| 108 |
- type: precision_at_100
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| 109 |
-
value: 0.
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| 110 |
- type: precision_at_1000
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value: 0.1
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| 112 |
- type: precision_at_3
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| 113 |
-
value: 13.
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| 114 |
- type: precision_at_5
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| 115 |
-
value: 10.
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| 116 |
- type: recall_at_1
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| 117 |
-
value:
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| 118 |
- type: recall_at_10
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| 119 |
-
value:
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| 120 |
- type: recall_at_100
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| 121 |
-
value: 97.
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| 122 |
- type: recall_at_1000
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| 123 |
-
value: 99.
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| 124 |
- type: recall_at_3
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-
value:
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| 126 |
- type: recall_at_5
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-
value:
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| 128 |
- task:
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type: Clustering
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dataset:
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@@ -135,7 +135,7 @@ model-index:
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revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
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metrics:
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- type: v_measure
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-
value: 45.
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- task:
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type: Clustering
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dataset:
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@@ -146,7 +146,7 @@ model-index:
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revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
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metrics:
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- type: v_measure
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-
value:
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- task:
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type: Reranking
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dataset:
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@@ -157,9 +157,9 @@ model-index:
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revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
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metrics:
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- type: map
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-
value: 62.
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- type: mrr
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-
value:
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- task:
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type: STS
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dataset:
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@@ -170,17 +170,17 @@ model-index:
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revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
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metrics:
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- type: cos_sim_pearson
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-
value:
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- type: cos_sim_spearman
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-
value:
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- type: euclidean_pearson
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-
value:
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- type: euclidean_spearman
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-
value:
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- type: manhattan_pearson
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-
value:
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- type: manhattan_spearman
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-
value:
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- task:
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type: Classification
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dataset:
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@@ -191,9 +191,9 @@ model-index:
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revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
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metrics:
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- type: accuracy
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-
value:
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- type: f1
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-
value: 83.
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- task:
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type: Clustering
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dataset:
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@@ -204,7 +204,7 @@ model-index:
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revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
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metrics:
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- type: v_measure
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-
value: 37.
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- task:
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type: Clustering
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dataset:
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@@ -215,7 +215,7 @@ model-index:
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revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
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metrics:
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- type: v_measure
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-
value:
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- task:
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type: Retrieval
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dataset:
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|
@@ -226,65 +226,65 @@ model-index:
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revision: None
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metrics:
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| 228 |
- type: map_at_1
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-
value:
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| 230 |
- 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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| 238 |
- type: map_at_5
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-
value:
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| 240 |
- type: mrr_at_1
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-
value:
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| 242 |
- type: mrr_at_10
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| 243 |
-
value:
|
| 244 |
- type: mrr_at_100
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| 245 |
-
value:
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| 246 |
- type: mrr_at_1000
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| 247 |
-
value:
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| 248 |
- type: mrr_at_3
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| 249 |
-
value:
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| 250 |
- type: mrr_at_5
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| 251 |
-
value:
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| 252 |
- type: ndcg_at_1
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-
value:
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| 254 |
- type: ndcg_at_10
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-
value:
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| 256 |
- type: ndcg_at_100
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| 257 |
-
value:
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| 258 |
- 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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| 266 |
- 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: 20.
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| 274 |
- type: precision_at_5
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-
value: 14.
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| 276 |
- type: recall_at_1
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-
value:
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| 278 |
- 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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| 282 |
- type: recall_at_1000
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-
value: 95.
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- type: recall_at_3
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-
value:
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| 286 |
- type: recall_at_5
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-
value:
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| 288 |
- task:
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type: Retrieval
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| 290 |
dataset:
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@@ -295,65 +295,65 @@ model-index:
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| 295 |
revision: None
|
| 296 |
metrics:
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| 297 |
- type: map_at_1
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| 298 |
-
value:
|
| 299 |
- type: map_at_10
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-
value:
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| 301 |
- type: map_at_100
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-
value:
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| 303 |
- type: map_at_1000
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-
value:
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- type: map_at_3
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| 306 |
-
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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| 313 |
- type: mrr_at_100
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-
value:
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- type: mrr_at_1000
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-
value:
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- type: mrr_at_3
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-
value:
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- type: mrr_at_5
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-
value:
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- type: ndcg_at_1
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-
value:
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- type: ndcg_at_10
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-
value:
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- type: ndcg_at_100
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-
value:
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- type: ndcg_at_1000
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-
value:
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- type: ndcg_at_3
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-
value:
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- type: ndcg_at_5
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-
value:
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- type: precision_at_1
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-
value:
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- type: precision_at_10
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-
value: 8.
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| 337 |
- type: precision_at_100
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| 338 |
-
value: 1.
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| 339 |
- type: precision_at_1000
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-
value: 0.
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| 341 |
- type: precision_at_3
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| 342 |
-
value: 19.
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| 343 |
- type: precision_at_5
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-
value: 13.
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| 345 |
- type: recall_at_1
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| 346 |
-
value:
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| 347 |
- type: recall_at_10
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| 348 |
-
value:
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- type: recall_at_100
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-
value: 73.
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| 351 |
- 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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@@ -364,65 +364,65 @@ model-index:
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revision: None
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metrics:
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| 366 |
- type: map_at_1
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-
value:
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| 368 |
- 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: 15.
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| 414 |
- 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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@@ -433,65 +433,65 @@ model-index:
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revision: None
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metrics:
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- type: map_at_1
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| 436 |
-
value:
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| 437 |
- 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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| 441 |
- 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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| 453 |
- 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: 0.11100000000000002
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- type: precision_at_3
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-
value: 13.
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- type: precision_at_5
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-
value: 9.
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| 483 |
- type: recall_at_1
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-
value:
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- type: recall_at_10
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-
value: 49.
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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: 90.
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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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@@ -502,65 +502,65 @@ model-index:
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revision: None
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metrics:
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- type: map_at_1
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-
value:
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- type: map_at_10
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-
value:
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- type: map_at_100
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-
value:
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- type: map_at_1000
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-
value:
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- type: map_at_3
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-
value:
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- type: map_at_5
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-
value:
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- type: mrr_at_1
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-
value:
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- type: mrr_at_10
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-
value:
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- type: mrr_at_100
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-
value:
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- type: mrr_at_1000
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-
value:
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- type: mrr_at_3
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-
value:
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- type: mrr_at_5
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-
value:
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- type: ndcg_at_1
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-
value:
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- type: ndcg_at_10
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-
value:
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- type: ndcg_at_100
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-
value:
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- type: ndcg_at_1000
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-
value:
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- type: ndcg_at_3
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-
value:
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- type: ndcg_at_5
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-
value:
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- type: precision_at_1
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| 541 |
-
value:
|
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- type: precision_at_10
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-
value: 4.
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| 544 |
- type: precision_at_100
|
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-
value: 0.
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- type: precision_at_1000
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-
value: 0.
|
| 548 |
- type: precision_at_3
|
| 549 |
-
value:
|
| 550 |
- type: precision_at_5
|
| 551 |
-
value:
|
| 552 |
- type: recall_at_1
|
| 553 |
-
value:
|
| 554 |
- type: recall_at_10
|
| 555 |
-
value:
|
| 556 |
- type: recall_at_100
|
| 557 |
-
value:
|
| 558 |
- type: recall_at_1000
|
| 559 |
-
value: 84.
|
| 560 |
- type: recall_at_3
|
| 561 |
-
value:
|
| 562 |
- type: recall_at_5
|
| 563 |
-
value:
|
| 564 |
- task:
|
| 565 |
type: Retrieval
|
| 566 |
dataset:
|
|
@@ -571,65 +571,65 @@ model-index:
|
|
| 571 |
revision: None
|
| 572 |
metrics:
|
| 573 |
- type: map_at_1
|
| 574 |
-
value:
|
| 575 |
- type: map_at_10
|
| 576 |
-
value:
|
| 577 |
- type: map_at_100
|
| 578 |
-
value:
|
| 579 |
- type: map_at_1000
|
| 580 |
-
value:
|
| 581 |
- type: map_at_3
|
| 582 |
-
value:
|
| 583 |
- type: map_at_5
|
| 584 |
-
value:
|
| 585 |
- type: mrr_at_1
|
| 586 |
-
value:
|
| 587 |
- type: mrr_at_10
|
| 588 |
-
value:
|
| 589 |
- type: mrr_at_100
|
| 590 |
-
value:
|
| 591 |
- type: mrr_at_1000
|
| 592 |
-
value:
|
| 593 |
- type: mrr_at_3
|
| 594 |
-
value:
|
| 595 |
- type: mrr_at_5
|
| 596 |
-
value:
|
| 597 |
- type: ndcg_at_1
|
| 598 |
-
value:
|
| 599 |
- type: ndcg_at_10
|
| 600 |
-
value:
|
| 601 |
- type: ndcg_at_100
|
| 602 |
-
value:
|
| 603 |
- type: ndcg_at_1000
|
| 604 |
-
value:
|
| 605 |
- type: ndcg_at_3
|
| 606 |
-
value:
|
| 607 |
- type: ndcg_at_5
|
| 608 |
-
value:
|
| 609 |
- type: precision_at_1
|
| 610 |
-
value:
|
| 611 |
- type: precision_at_10
|
| 612 |
-
value: 7.
|
| 613 |
- type: precision_at_100
|
| 614 |
-
value: 1.
|
| 615 |
- type: precision_at_1000
|
| 616 |
-
value: 0.
|
| 617 |
- type: precision_at_3
|
| 618 |
-
value:
|
| 619 |
- type: precision_at_5
|
| 620 |
-
value: 12.
|
| 621 |
- type: recall_at_1
|
| 622 |
-
value:
|
| 623 |
- type: recall_at_10
|
| 624 |
-
value:
|
| 625 |
- type: recall_at_100
|
| 626 |
-
value:
|
| 627 |
- type: recall_at_1000
|
| 628 |
-
value:
|
| 629 |
- type: recall_at_3
|
| 630 |
-
value:
|
| 631 |
- type: recall_at_5
|
| 632 |
-
value:
|
| 633 |
- task:
|
| 634 |
type: Retrieval
|
| 635 |
dataset:
|
|
@@ -640,65 +640,65 @@ model-index:
|
|
| 640 |
revision: None
|
| 641 |
metrics:
|
| 642 |
- type: map_at_1
|
| 643 |
-
value:
|
| 644 |
- type: map_at_10
|
| 645 |
-
value:
|
| 646 |
- type: map_at_100
|
| 647 |
-
value:
|
| 648 |
- type: map_at_1000
|
| 649 |
-
value:
|
| 650 |
- type: map_at_3
|
| 651 |
-
value:
|
| 652 |
- type: map_at_5
|
| 653 |
-
value:
|
| 654 |
- type: mrr_at_1
|
| 655 |
-
value:
|
| 656 |
- type: mrr_at_10
|
| 657 |
-
value:
|
| 658 |
- type: mrr_at_100
|
| 659 |
-
value:
|
| 660 |
- type: mrr_at_1000
|
| 661 |
-
value:
|
| 662 |
- type: mrr_at_3
|
| 663 |
-
value:
|
| 664 |
- type: mrr_at_5
|
| 665 |
-
value:
|
| 666 |
- type: ndcg_at_1
|
| 667 |
-
value:
|
| 668 |
- type: ndcg_at_10
|
| 669 |
-
value:
|
| 670 |
- type: ndcg_at_100
|
| 671 |
-
value:
|
| 672 |
- type: ndcg_at_1000
|
| 673 |
-
value:
|
| 674 |
- type: ndcg_at_3
|
| 675 |
-
value:
|
| 676 |
- type: ndcg_at_5
|
| 677 |
-
value:
|
| 678 |
- type: precision_at_1
|
| 679 |
-
value:
|
| 680 |
- type: precision_at_10
|
| 681 |
-
value:
|
| 682 |
- type: precision_at_100
|
| 683 |
-
value: 1.
|
| 684 |
- type: precision_at_1000
|
| 685 |
-
value: 0.
|
| 686 |
- type: precision_at_3
|
| 687 |
-
value:
|
| 688 |
- type: precision_at_5
|
| 689 |
-
value: 11.
|
| 690 |
- type: recall_at_1
|
| 691 |
-
value:
|
| 692 |
- type: recall_at_10
|
| 693 |
-
value:
|
| 694 |
- type: recall_at_100
|
| 695 |
-
value:
|
| 696 |
- type: recall_at_1000
|
| 697 |
-
value:
|
| 698 |
- type: recall_at_3
|
| 699 |
-
value:
|
| 700 |
- type: recall_at_5
|
| 701 |
-
value: 41.
|
| 702 |
- task:
|
| 703 |
type: Retrieval
|
| 704 |
dataset:
|
|
@@ -709,65 +709,65 @@ model-index:
|
|
| 709 |
revision: None
|
| 710 |
metrics:
|
| 711 |
- type: map_at_1
|
| 712 |
-
value:
|
| 713 |
- type: map_at_10
|
| 714 |
-
value:
|
| 715 |
- type: map_at_100
|
| 716 |
-
value:
|
| 717 |
- type: map_at_1000
|
| 718 |
-
value:
|
| 719 |
- type: map_at_3
|
| 720 |
-
value:
|
| 721 |
- type: map_at_5
|
| 722 |
-
value:
|
| 723 |
- type: mrr_at_1
|
| 724 |
-
value:
|
| 725 |
- type: mrr_at_10
|
| 726 |
-
value:
|
| 727 |
- type: mrr_at_100
|
| 728 |
-
value:
|
| 729 |
- type: mrr_at_1000
|
| 730 |
-
value:
|
| 731 |
- type: mrr_at_3
|
| 732 |
-
value:
|
| 733 |
- type: mrr_at_5
|
| 734 |
-
value:
|
| 735 |
- type: ndcg_at_1
|
| 736 |
-
value:
|
| 737 |
- type: ndcg_at_10
|
| 738 |
-
value:
|
| 739 |
- type: ndcg_at_100
|
| 740 |
-
value:
|
| 741 |
- type: ndcg_at_1000
|
| 742 |
-
value:
|
| 743 |
- type: ndcg_at_3
|
| 744 |
-
value:
|
| 745 |
- type: ndcg_at_5
|
| 746 |
-
value:
|
| 747 |
- type: precision_at_1
|
| 748 |
-
value:
|
| 749 |
- type: precision_at_10
|
| 750 |
-
value: 6.
|
| 751 |
- type: precision_at_100
|
| 752 |
-
value: 1.
|
| 753 |
- type: precision_at_1000
|
| 754 |
-
value: 0.
|
| 755 |
- type: precision_at_3
|
| 756 |
-
value: 15.
|
| 757 |
- type: precision_at_5
|
| 758 |
-
value:
|
| 759 |
- type: recall_at_1
|
| 760 |
-
value:
|
| 761 |
- type: recall_at_10
|
| 762 |
-
value:
|
| 763 |
- type: recall_at_100
|
| 764 |
-
value:
|
| 765 |
- type: recall_at_1000
|
| 766 |
-
value: 89.
|
| 767 |
- type: recall_at_3
|
| 768 |
-
value:
|
| 769 |
- type: recall_at_5
|
| 770 |
-
value:
|
| 771 |
- task:
|
| 772 |
type: Retrieval
|
| 773 |
dataset:
|
|
@@ -778,65 +778,65 @@ model-index:
|
|
| 778 |
revision: None
|
| 779 |
metrics:
|
| 780 |
- type: map_at_1
|
| 781 |
-
value:
|
| 782 |
- type: map_at_10
|
| 783 |
-
value:
|
| 784 |
- type: map_at_100
|
| 785 |
-
value:
|
| 786 |
- type: map_at_1000
|
| 787 |
-
value:
|
| 788 |
- type: map_at_3
|
| 789 |
-
value:
|
| 790 |
- type: map_at_5
|
| 791 |
-
value:
|
| 792 |
- type: mrr_at_1
|
| 793 |
-
value:
|
| 794 |
- type: mrr_at_10
|
| 795 |
-
value:
|
| 796 |
- type: mrr_at_100
|
| 797 |
-
value:
|
| 798 |
- type: mrr_at_1000
|
| 799 |
-
value:
|
| 800 |
- type: mrr_at_3
|
| 801 |
-
value:
|
| 802 |
- type: mrr_at_5
|
| 803 |
-
value:
|
| 804 |
- type: ndcg_at_1
|
| 805 |
-
value:
|
| 806 |
- type: ndcg_at_10
|
| 807 |
-
value:
|
| 808 |
- type: ndcg_at_100
|
| 809 |
-
value:
|
| 810 |
- type: ndcg_at_1000
|
| 811 |
-
value:
|
| 812 |
- type: ndcg_at_3
|
| 813 |
-
value:
|
| 814 |
- type: ndcg_at_5
|
| 815 |
-
value:
|
| 816 |
- type: precision_at_1
|
| 817 |
-
value:
|
| 818 |
- type: precision_at_10
|
| 819 |
-
value: 5.
|
| 820 |
- type: precision_at_100
|
| 821 |
-
value: 0.
|
| 822 |
- type: precision_at_1000
|
| 823 |
-
value: 0.
|
| 824 |
- type: precision_at_3
|
| 825 |
-
value:
|
| 826 |
- type: precision_at_5
|
| 827 |
-
value: 8.
|
| 828 |
- type: recall_at_1
|
| 829 |
-
value:
|
| 830 |
- type: recall_at_10
|
| 831 |
-
value:
|
| 832 |
- type: recall_at_100
|
| 833 |
-
value: 65.
|
| 834 |
- type: recall_at_1000
|
| 835 |
-
value:
|
| 836 |
- type: recall_at_3
|
| 837 |
-
value:
|
| 838 |
- type: recall_at_5
|
| 839 |
-
value:
|
| 840 |
- task:
|
| 841 |
type: Retrieval
|
| 842 |
dataset:
|
|
@@ -847,65 +847,65 @@ model-index:
|
|
| 847 |
revision: None
|
| 848 |
metrics:
|
| 849 |
- type: map_at_1
|
| 850 |
-
value:
|
| 851 |
- type: map_at_10
|
| 852 |
-
value:
|
| 853 |
- type: map_at_100
|
| 854 |
-
value:
|
| 855 |
- type: map_at_1000
|
| 856 |
-
value:
|
| 857 |
- type: map_at_3
|
| 858 |
-
value:
|
| 859 |
- type: map_at_5
|
| 860 |
-
value:
|
| 861 |
- type: mrr_at_1
|
| 862 |
-
value:
|
| 863 |
- type: mrr_at_10
|
| 864 |
-
value:
|
| 865 |
- type: mrr_at_100
|
| 866 |
-
value:
|
| 867 |
- type: mrr_at_1000
|
| 868 |
-
value:
|
| 869 |
- type: mrr_at_3
|
| 870 |
-
value:
|
| 871 |
- type: mrr_at_5
|
| 872 |
-
value:
|
| 873 |
- type: ndcg_at_1
|
| 874 |
-
value:
|
| 875 |
- type: ndcg_at_10
|
| 876 |
-
value:
|
| 877 |
- type: ndcg_at_100
|
| 878 |
-
value:
|
| 879 |
- type: ndcg_at_1000
|
| 880 |
-
value:
|
| 881 |
- type: ndcg_at_3
|
| 882 |
-
value:
|
| 883 |
- type: ndcg_at_5
|
| 884 |
-
value:
|
| 885 |
- type: precision_at_1
|
| 886 |
-
value:
|
| 887 |
- type: precision_at_10
|
| 888 |
-
value:
|
| 889 |
- type: precision_at_100
|
| 890 |
-
value: 0.
|
| 891 |
- type: precision_at_1000
|
| 892 |
-
value: 0.
|
| 893 |
- type: precision_at_3
|
| 894 |
-
value:
|
| 895 |
- type: precision_at_5
|
| 896 |
-
value:
|
| 897 |
- type: recall_at_1
|
| 898 |
-
value:
|
| 899 |
- type: recall_at_10
|
| 900 |
-
value:
|
| 901 |
- type: recall_at_100
|
| 902 |
-
value:
|
| 903 |
- type: recall_at_1000
|
| 904 |
-
value: 82.
|
| 905 |
- type: recall_at_3
|
| 906 |
-
value:
|
| 907 |
- type: recall_at_5
|
| 908 |
-
value:
|
| 909 |
- task:
|
| 910 |
type: Retrieval
|
| 911 |
dataset:
|
|
@@ -916,65 +916,65 @@ model-index:
|
|
| 916 |
revision: None
|
| 917 |
metrics:
|
| 918 |
- type: map_at_1
|
| 919 |
-
value:
|
| 920 |
- type: map_at_10
|
| 921 |
-
value:
|
| 922 |
- type: map_at_100
|
| 923 |
-
value:
|
| 924 |
- type: map_at_1000
|
| 925 |
-
value:
|
| 926 |
- type: map_at_3
|
| 927 |
-
value:
|
| 928 |
- type: map_at_5
|
| 929 |
-
value:
|
| 930 |
- type: mrr_at_1
|
| 931 |
-
value:
|
| 932 |
- type: mrr_at_10
|
| 933 |
-
value:
|
| 934 |
- type: mrr_at_100
|
| 935 |
-
value:
|
| 936 |
- type: mrr_at_1000
|
| 937 |
-
value:
|
| 938 |
- type: mrr_at_3
|
| 939 |
-
value:
|
| 940 |
- type: mrr_at_5
|
| 941 |
-
value:
|
| 942 |
- type: ndcg_at_1
|
| 943 |
-
value:
|
| 944 |
- type: ndcg_at_10
|
| 945 |
-
value:
|
| 946 |
- type: ndcg_at_100
|
| 947 |
-
value:
|
| 948 |
- type: ndcg_at_1000
|
| 949 |
-
value:
|
| 950 |
- type: ndcg_at_3
|
| 951 |
-
value:
|
| 952 |
- type: ndcg_at_5
|
| 953 |
-
value:
|
| 954 |
- type: precision_at_1
|
| 955 |
-
value:
|
| 956 |
- type: precision_at_10
|
| 957 |
-
value: 6.
|
| 958 |
- type: precision_at_100
|
| 959 |
-
value: 1.
|
| 960 |
- type: precision_at_1000
|
| 961 |
-
value: 0.
|
| 962 |
- type: precision_at_3
|
| 963 |
-
value:
|
| 964 |
- type: precision_at_5
|
| 965 |
-
value: 10.
|
| 966 |
- type: recall_at_1
|
| 967 |
-
value:
|
| 968 |
- type: recall_at_10
|
| 969 |
-
value:
|
| 970 |
- type: recall_at_100
|
| 971 |
-
value:
|
| 972 |
- type: recall_at_1000
|
| 973 |
-
value: 90.
|
| 974 |
- type: recall_at_3
|
| 975 |
-
value:
|
| 976 |
- type: recall_at_5
|
| 977 |
-
value:
|
| 978 |
- task:
|
| 979 |
type: Retrieval
|
| 980 |
dataset:
|
|
@@ -985,65 +985,65 @@ model-index:
|
|
| 985 |
revision: None
|
| 986 |
metrics:
|
| 987 |
- type: map_at_1
|
| 988 |
-
value:
|
| 989 |
- type: map_at_10
|
| 990 |
-
value:
|
| 991 |
- type: map_at_100
|
| 992 |
-
value:
|
| 993 |
- type: map_at_1000
|
| 994 |
-
value:
|
| 995 |
- type: map_at_3
|
| 996 |
-
value:
|
| 997 |
- type: map_at_5
|
| 998 |
-
value:
|
| 999 |
- type: mrr_at_1
|
| 1000 |
-
value:
|
| 1001 |
- type: mrr_at_10
|
| 1002 |
-
value:
|
| 1003 |
- type: mrr_at_100
|
| 1004 |
-
value:
|
| 1005 |
- type: mrr_at_1000
|
| 1006 |
-
value:
|
| 1007 |
- type: mrr_at_3
|
| 1008 |
-
value:
|
| 1009 |
- type: mrr_at_5
|
| 1010 |
-
value:
|
| 1011 |
- type: ndcg_at_1
|
| 1012 |
-
value:
|
| 1013 |
- type: ndcg_at_10
|
| 1014 |
-
value:
|
| 1015 |
- type: ndcg_at_100
|
| 1016 |
-
value:
|
| 1017 |
- type: ndcg_at_1000
|
| 1018 |
-
value:
|
| 1019 |
- type: ndcg_at_3
|
| 1020 |
-
value:
|
| 1021 |
- type: ndcg_at_5
|
| 1022 |
-
value:
|
| 1023 |
- type: precision_at_1
|
| 1024 |
-
value:
|
| 1025 |
- type: precision_at_10
|
| 1026 |
-
value: 7.
|
| 1027 |
- type: precision_at_100
|
| 1028 |
-
value: 1.
|
| 1029 |
- type: precision_at_1000
|
| 1030 |
-
value: 0.
|
| 1031 |
- type: precision_at_3
|
| 1032 |
-
value:
|
| 1033 |
- type: precision_at_5
|
| 1034 |
-
value:
|
| 1035 |
- type: recall_at_1
|
| 1036 |
-
value:
|
| 1037 |
- type: recall_at_10
|
| 1038 |
-
value:
|
| 1039 |
- type: recall_at_100
|
| 1040 |
-
value: 76.
|
| 1041 |
- type: recall_at_1000
|
| 1042 |
-
value:
|
| 1043 |
- type: recall_at_3
|
| 1044 |
-
value:
|
| 1045 |
- type: recall_at_5
|
| 1046 |
-
value:
|
| 1047 |
- task:
|
| 1048 |
type: Retrieval
|
| 1049 |
dataset:
|
|
@@ -1054,65 +1054,65 @@ model-index:
|
|
| 1054 |
revision: None
|
| 1055 |
metrics:
|
| 1056 |
- type: map_at_1
|
| 1057 |
-
value:
|
| 1058 |
- type: map_at_10
|
| 1059 |
-
value:
|
| 1060 |
- type: map_at_100
|
| 1061 |
-
value:
|
| 1062 |
- type: map_at_1000
|
| 1063 |
-
value:
|
| 1064 |
- type: map_at_3
|
| 1065 |
-
value:
|
| 1066 |
- type: map_at_5
|
| 1067 |
-
value:
|
| 1068 |
- type: mrr_at_1
|
| 1069 |
-
value:
|
| 1070 |
- type: mrr_at_10
|
| 1071 |
-
value:
|
| 1072 |
- type: mrr_at_100
|
| 1073 |
-
value:
|
| 1074 |
- type: mrr_at_1000
|
| 1075 |
-
value:
|
| 1076 |
- type: mrr_at_3
|
| 1077 |
-
value:
|
| 1078 |
- type: mrr_at_5
|
| 1079 |
-
value:
|
| 1080 |
- type: ndcg_at_1
|
| 1081 |
-
value:
|
| 1082 |
- type: ndcg_at_10
|
| 1083 |
-
value:
|
| 1084 |
- type: ndcg_at_100
|
| 1085 |
-
value:
|
| 1086 |
- type: ndcg_at_1000
|
| 1087 |
-
value:
|
| 1088 |
- type: ndcg_at_3
|
| 1089 |
-
value:
|
| 1090 |
- type: ndcg_at_5
|
| 1091 |
-
value:
|
| 1092 |
- type: precision_at_1
|
| 1093 |
-
value:
|
| 1094 |
- type: precision_at_10
|
| 1095 |
-
value:
|
| 1096 |
- type: precision_at_100
|
| 1097 |
-
value: 0.
|
| 1098 |
- type: precision_at_1000
|
| 1099 |
value: 0.116
|
| 1100 |
- type: precision_at_3
|
| 1101 |
-
value:
|
| 1102 |
- type: precision_at_5
|
| 1103 |
-
value:
|
| 1104 |
- type: recall_at_1
|
| 1105 |
-
value:
|
| 1106 |
- type: recall_at_10
|
| 1107 |
-
value:
|
| 1108 |
- type: recall_at_100
|
| 1109 |
-
value: 67.
|
| 1110 |
- type: recall_at_1000
|
| 1111 |
-
value: 87.
|
| 1112 |
- type: recall_at_3
|
| 1113 |
-
value:
|
| 1114 |
- type: recall_at_5
|
| 1115 |
-
value:
|
| 1116 |
- task:
|
| 1117 |
type: Retrieval
|
| 1118 |
dataset:
|
|
@@ -1123,65 +1123,65 @@ model-index:
|
|
| 1123 |
revision: None
|
| 1124 |
metrics:
|
| 1125 |
- type: map_at_1
|
| 1126 |
-
value: 10.
|
| 1127 |
- type: map_at_10
|
| 1128 |
-
value:
|
| 1129 |
- type: map_at_100
|
| 1130 |
-
value:
|
| 1131 |
- type: map_at_1000
|
| 1132 |
-
value:
|
| 1133 |
- type: map_at_3
|
| 1134 |
-
value: 14.
|
| 1135 |
- type: map_at_5
|
| 1136 |
-
value: 15.
|
| 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:
|
| 1149 |
- type: ndcg_at_1
|
| 1150 |
-
value:
|
| 1151 |
- type: ndcg_at_10
|
| 1152 |
-
value:
|
| 1153 |
- type: ndcg_at_100
|
| 1154 |
-
value:
|
| 1155 |
- type: ndcg_at_1000
|
| 1156 |
-
value:
|
| 1157 |
- type: ndcg_at_3
|
| 1158 |
-
value: 19.
|
| 1159 |
- type: ndcg_at_5
|
| 1160 |
-
value:
|
| 1161 |
- type: precision_at_1
|
| 1162 |
-
value:
|
| 1163 |
- type: precision_at_10
|
| 1164 |
-
value: 7.
|
| 1165 |
- type: precision_at_100
|
| 1166 |
-
value: 1.
|
| 1167 |
- type: precision_at_1000
|
| 1168 |
-
value: 0.
|
| 1169 |
- type: precision_at_3
|
| 1170 |
-
value:
|
| 1171 |
- type: precision_at_5
|
| 1172 |
-
value:
|
| 1173 |
- type: recall_at_1
|
| 1174 |
-
value: 10.
|
| 1175 |
- type: recall_at_10
|
| 1176 |
-
value:
|
| 1177 |
- type: recall_at_100
|
| 1178 |
-
value:
|
| 1179 |
- type: recall_at_1000
|
| 1180 |
-
value:
|
| 1181 |
- type: recall_at_3
|
| 1182 |
-
value:
|
| 1183 |
- type: recall_at_5
|
| 1184 |
-
value: 22.
|
| 1185 |
- task:
|
| 1186 |
type: Retrieval
|
| 1187 |
dataset:
|
|
@@ -1192,65 +1192,65 @@ model-index:
|
|
| 1192 |
revision: None
|
| 1193 |
metrics:
|
| 1194 |
- type: map_at_1
|
| 1195 |
-
value: 6.
|
| 1196 |
- type: map_at_10
|
| 1197 |
-
value: 15.
|
| 1198 |
- type: map_at_100
|
| 1199 |
-
value: 21.
|
| 1200 |
- type: map_at_1000
|
| 1201 |
-
value:
|
| 1202 |
- type: map_at_3
|
| 1203 |
-
value: 11.
|
| 1204 |
- type: map_at_5
|
| 1205 |
-
value:
|
| 1206 |
- type: mrr_at_1
|
| 1207 |
value: 55.50000000000001
|
| 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: 44.
|
| 1220 |
- type: ndcg_at_10
|
| 1221 |
-
value: 35.
|
| 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: 55.50000000000001
|
| 1232 |
- type: precision_at_10
|
| 1233 |
-
value:
|
| 1234 |
- type: precision_at_100
|
| 1235 |
-
value:
|
| 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: 6.
|
| 1244 |
- type: recall_at_10
|
| 1245 |
-
value:
|
| 1246 |
- type: recall_at_100
|
| 1247 |
-
value:
|
| 1248 |
- type: recall_at_1000
|
| 1249 |
-
value: 67.
|
| 1250 |
- type: recall_at_3
|
| 1251 |
-
value:
|
| 1252 |
- type: recall_at_5
|
| 1253 |
-
value:
|
| 1254 |
- task:
|
| 1255 |
type: Classification
|
| 1256 |
dataset:
|
|
@@ -1261,9 +1261,9 @@ 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 +1274,65 @@ 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:
|
| 1316 |
- type: precision_at_100
|
| 1317 |
-
value: 1.
|
| 1318 |
- type: precision_at_1000
|
| 1319 |
value: 0.109
|
| 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: 96.
|
| 1332 |
- type: recall_at_3
|
| 1333 |
-
value:
|
| 1334 |
- type: recall_at_5
|
| 1335 |
-
value:
|
| 1336 |
- task:
|
| 1337 |
type: Retrieval
|
| 1338 |
dataset:
|
|
@@ -1343,65 +1343,65 @@ model-index:
|
|
| 1343 |
revision: None
|
| 1344 |
metrics:
|
| 1345 |
- type: map_at_1
|
| 1346 |
-
value:
|
| 1347 |
- type: map_at_10
|
| 1348 |
-
value: 33.
|
| 1349 |
- type: map_at_100
|
| 1350 |
-
value: 35.
|
| 1351 |
- type: map_at_1000
|
| 1352 |
-
value: 35.
|
| 1353 |
- type: map_at_3
|
| 1354 |
-
value:
|
| 1355 |
- type: map_at_5
|
| 1356 |
-
value: 31.
|
| 1357 |
- type: mrr_at_1
|
| 1358 |
-
value: 41.
|
| 1359 |
- type: mrr_at_10
|
| 1360 |
-
value: 49.
|
| 1361 |
- type: mrr_at_100
|
| 1362 |
-
value: 50.
|
| 1363 |
- type: mrr_at_1000
|
| 1364 |
-
value: 50.
|
| 1365 |
- type: mrr_at_3
|
| 1366 |
-
value: 47.
|
| 1367 |
- type: mrr_at_5
|
| 1368 |
-
value: 48.
|
| 1369 |
- type: ndcg_at_1
|
| 1370 |
-
value: 41.
|
| 1371 |
- type: ndcg_at_10
|
| 1372 |
-
value: 41.
|
| 1373 |
- type: ndcg_at_100
|
| 1374 |
-
value: 48.
|
| 1375 |
- type: ndcg_at_1000
|
| 1376 |
-
value: 51.
|
| 1377 |
- type: ndcg_at_3
|
| 1378 |
-
value: 37.
|
| 1379 |
- type: ndcg_at_5
|
| 1380 |
-
value: 38.
|
| 1381 |
- type: precision_at_1
|
| 1382 |
-
value: 41.
|
| 1383 |
- type: precision_at_10
|
| 1384 |
-
value: 11.
|
| 1385 |
- type: precision_at_100
|
| 1386 |
-
value: 1.
|
| 1387 |
- type: precision_at_1000
|
| 1388 |
-
value: 0.
|
| 1389 |
- type: precision_at_3
|
| 1390 |
-
value: 24.
|
| 1391 |
- type: precision_at_5
|
| 1392 |
-
value:
|
| 1393 |
- type: recall_at_1
|
| 1394 |
-
value:
|
| 1395 |
- type: recall_at_10
|
| 1396 |
-
value: 48.
|
| 1397 |
- type: recall_at_100
|
| 1398 |
-
value: 74.
|
| 1399 |
- type: recall_at_1000
|
| 1400 |
-
value: 91.
|
| 1401 |
- type: recall_at_3
|
| 1402 |
-
value: 33.
|
| 1403 |
- type: recall_at_5
|
| 1404 |
-
value:
|
| 1405 |
- task:
|
| 1406 |
type: Retrieval
|
| 1407 |
dataset:
|
|
@@ -1412,65 +1412,65 @@ 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:
|
| 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:
|
| 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:
|
| 1462 |
- type: recall_at_1
|
| 1463 |
-
value:
|
| 1464 |
- type: recall_at_10
|
| 1465 |
-
value:
|
| 1466 |
- type: recall_at_100
|
| 1467 |
-
value:
|
| 1468 |
- type: recall_at_1000
|
| 1469 |
-
value: 84.
|
| 1470 |
- type: recall_at_3
|
| 1471 |
-
value:
|
| 1472 |
- type: recall_at_5
|
| 1473 |
-
value:
|
| 1474 |
- task:
|
| 1475 |
type: Classification
|
| 1476 |
dataset:
|
|
@@ -1481,11 +1481,11 @@ 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 +1496,65 @@ model-index:
|
|
| 1496 |
revision: None
|
| 1497 |
metrics:
|
| 1498 |
- type: map_at_1
|
| 1499 |
-
value:
|
| 1500 |
- type: map_at_10
|
| 1501 |
-
value: 34.
|
| 1502 |
- type: map_at_100
|
| 1503 |
-
value: 35.
|
| 1504 |
- type: map_at_1000
|
| 1505 |
-
value: 35.
|
| 1506 |
- type: map_at_3
|
| 1507 |
-
value: 30.
|
| 1508 |
- type: map_at_5
|
| 1509 |
-
value: 32.
|
| 1510 |
- type: mrr_at_1
|
| 1511 |
-
value: 22.
|
| 1512 |
- type: mrr_at_10
|
| 1513 |
-
value: 34.
|
| 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: 22.
|
| 1524 |
- type: ndcg_at_10
|
| 1525 |
-
value:
|
| 1526 |
- type: ndcg_at_100
|
| 1527 |
-
value: 46.
|
| 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: 22.
|
| 1536 |
- type: precision_at_10
|
| 1537 |
-
value: 6.
|
| 1538 |
- type: precision_at_100
|
| 1539 |
-
value: 0.
|
| 1540 |
- type: precision_at_1000
|
| 1541 |
value: 0.104
|
| 1542 |
- type: precision_at_3
|
| 1543 |
-
value: 14.
|
| 1544 |
- type: precision_at_5
|
| 1545 |
-
value: 10.
|
| 1546 |
- type: recall_at_1
|
| 1547 |
-
value:
|
| 1548 |
- type: recall_at_10
|
| 1549 |
-
value: 62.
|
| 1550 |
- type: recall_at_100
|
| 1551 |
-
value: 88.
|
| 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 +1565,9 @@ 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 +1578,9 @@ 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 +1591,9 @@ 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 +1604,9 @@ model-index:
|
|
| 1604 |
revision: 7d571f92784cd94a019292a1f45445077d0ef634
|
| 1605 |
metrics:
|
| 1606 |
- type: accuracy
|
| 1607 |
-
value:
|
| 1608 |
- type: f1
|
| 1609 |
-
value:
|
| 1610 |
- task:
|
| 1611 |
type: Clustering
|
| 1612 |
dataset:
|
|
@@ -1617,7 +1617,7 @@ model-index:
|
|
| 1617 |
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
|
| 1618 |
metrics:
|
| 1619 |
- type: v_measure
|
| 1620 |
-
value: 32.
|
| 1621 |
- task:
|
| 1622 |
type: Clustering
|
| 1623 |
dataset:
|
|
@@ -1628,7 +1628,7 @@ model-index:
|
|
| 1628 |
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
|
| 1629 |
metrics:
|
| 1630 |
- type: v_measure
|
| 1631 |
-
value: 28.
|
| 1632 |
- task:
|
| 1633 |
type: Reranking
|
| 1634 |
dataset:
|
|
@@ -1639,9 +1639,9 @@ model-index:
|
|
| 1639 |
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
|
| 1640 |
metrics:
|
| 1641 |
- type: map
|
| 1642 |
-
value:
|
| 1643 |
- type: mrr
|
| 1644 |
-
value:
|
| 1645 |
- task:
|
| 1646 |
type: Retrieval
|
| 1647 |
dataset:
|
|
@@ -1652,65 +1652,65 @@ 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: 10.
|
| 1666 |
- type: mrr_at_1
|
| 1667 |
-
value:
|
| 1668 |
- type: mrr_at_10
|
| 1669 |
-
value: 53.
|
| 1670 |
- type: mrr_at_100
|
| 1671 |
-
value:
|
| 1672 |
- type: mrr_at_1000
|
| 1673 |
-
value:
|
| 1674 |
- type: mrr_at_3
|
| 1675 |
-
value: 51.
|
| 1676 |
- type: mrr_at_5
|
| 1677 |
-
value: 52.
|
| 1678 |
- type: ndcg_at_1
|
| 1679 |
value: 43.808
|
| 1680 |
- type: ndcg_at_10
|
| 1681 |
-
value: 32.
|
| 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: 35.
|
| 1690 |
- type: precision_at_1
|
| 1691 |
-
value:
|
| 1692 |
- type: precision_at_10
|
| 1693 |
-
value: 23.
|
| 1694 |
- type: precision_at_100
|
| 1695 |
-
value: 7.
|
| 1696 |
- type: precision_at_1000
|
| 1697 |
-
value: 2.
|
| 1698 |
- type: precision_at_3
|
| 1699 |
-
value:
|
| 1700 |
- type: precision_at_5
|
| 1701 |
-
value:
|
| 1702 |
- type: recall_at_1
|
| 1703 |
-
value: 5.
|
| 1704 |
- type: recall_at_10
|
| 1705 |
-
value:
|
| 1706 |
- type: recall_at_100
|
| 1707 |
-
value: 30.
|
| 1708 |
- type: recall_at_1000
|
| 1709 |
-
value: 62.
|
| 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 +1721,65 @@ 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: 54.
|
| 1729 |
- type: map_at_1000
|
| 1730 |
-
value: 54.
|
| 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: 60.
|
| 1751 |
- type: ndcg_at_100
|
| 1752 |
-
value:
|
| 1753 |
- type: ndcg_at_1000
|
| 1754 |
-
value: 64.
|
| 1755 |
- type: ndcg_at_3
|
| 1756 |
-
value:
|
| 1757 |
- type: ndcg_at_5
|
| 1758 |
-
value: 57.
|
| 1759 |
- type: precision_at_1
|
| 1760 |
-
value:
|
| 1761 |
-
- type: precision_at_10
|
| 1762 |
-
value: 9.
|
| 1763 |
- type: precision_at_100
|
| 1764 |
-
value: 1.
|
| 1765 |
- type: precision_at_1000
|
| 1766 |
value: 0.12
|
| 1767 |
- type: precision_at_3
|
| 1768 |
-
value: 23.
|
| 1769 |
- type: precision_at_5
|
| 1770 |
-
value: 16.
|
| 1771 |
- type: recall_at_1
|
| 1772 |
-
value:
|
| 1773 |
- type: recall_at_10
|
| 1774 |
-
value: 79.
|
| 1775 |
- type: recall_at_100
|
| 1776 |
-
value: 93.
|
| 1777 |
- type: recall_at_1000
|
| 1778 |
-
value: 98.
|
| 1779 |
- type: recall_at_3
|
| 1780 |
-
value: 61.
|
| 1781 |
- type: recall_at_5
|
| 1782 |
-
value: 70.
|
| 1783 |
- task:
|
| 1784 |
type: Retrieval
|
| 1785 |
dataset:
|
|
@@ -1790,65 +1790,65 @@ 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: 85.
|
| 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: 87.
|
| 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 +1859,7 @@ model-index:
|
|
| 1859 |
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
|
| 1860 |
metrics:
|
| 1861 |
- type: v_measure
|
| 1862 |
-
value:
|
| 1863 |
- task:
|
| 1864 |
type: Clustering
|
| 1865 |
dataset:
|
|
@@ -1870,7 +1870,7 @@ model-index:
|
|
| 1870 |
revision: 282350215ef01743dc01b456c7f5241fa8937f16
|
| 1871 |
metrics:
|
| 1872 |
- type: v_measure
|
| 1873 |
-
value:
|
| 1874 |
- task:
|
| 1875 |
type: Retrieval
|
| 1876 |
dataset:
|
|
@@ -1881,65 +1881,65 @@ model-index:
|
|
| 1881 |
revision: None
|
| 1882 |
metrics:
|
| 1883 |
- type: map_at_1
|
| 1884 |
-
value: 4.
|
| 1885 |
- type: map_at_10
|
| 1886 |
-
value: 11.
|
| 1887 |
- type: map_at_100
|
| 1888 |
-
value:
|
| 1889 |
- type: map_at_1000
|
| 1890 |
-
value: 14.
|
| 1891 |
- type: map_at_3
|
| 1892 |
-
value: 8.
|
| 1893 |
- type: map_at_5
|
| 1894 |
-
value:
|
| 1895 |
- type: mrr_at_1
|
| 1896 |
-
value: 23.
|
| 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: 30.
|
| 1905 |
- type: mrr_at_5
|
| 1906 |
-
value: 32.
|
| 1907 |
- type: ndcg_at_1
|
| 1908 |
-
value: 23.
|
| 1909 |
- type: ndcg_at_10
|
| 1910 |
-
value:
|
| 1911 |
- type: ndcg_at_100
|
| 1912 |
-
value: 28.
|
| 1913 |
- type: ndcg_at_1000
|
| 1914 |
-
value: 33.
|
| 1915 |
- type: ndcg_at_3
|
| 1916 |
-
value: 18.
|
| 1917 |
- type: ndcg_at_5
|
| 1918 |
-
value: 16.
|
| 1919 |
- type: precision_at_1
|
| 1920 |
-
value: 23.
|
| 1921 |
- type: precision_at_10
|
| 1922 |
value: 10.39
|
| 1923 |
- type: precision_at_100
|
| 1924 |
-
value: 2.
|
| 1925 |
- type: precision_at_1000
|
| 1926 |
value: 0.35300000000000004
|
| 1927 |
- type: precision_at_3
|
| 1928 |
-
value: 17.
|
| 1929 |
- type: precision_at_5
|
| 1930 |
-
value: 14.
|
| 1931 |
- type: recall_at_1
|
| 1932 |
-
value: 4.
|
| 1933 |
- type: recall_at_10
|
| 1934 |
-
value: 21.
|
| 1935 |
- type: recall_at_100
|
| 1936 |
-
value: 45.
|
| 1937 |
- type: recall_at_1000
|
| 1938 |
-
value: 71.
|
| 1939 |
- type: recall_at_3
|
| 1940 |
-
value: 10.
|
| 1941 |
- type: recall_at_5
|
| 1942 |
-
value: 14.
|
| 1943 |
- task:
|
| 1944 |
type: STS
|
| 1945 |
dataset:
|
|
@@ -1950,17 +1950,17 @@ model-index:
|
|
| 1950 |
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
|
| 1951 |
metrics:
|
| 1952 |
- type: cos_sim_pearson
|
| 1953 |
-
value:
|
| 1954 |
- type: cos_sim_spearman
|
| 1955 |
-
value: 79.
|
| 1956 |
- type: euclidean_pearson
|
| 1957 |
-
value: 82.
|
| 1958 |
- type: euclidean_spearman
|
| 1959 |
-
value: 79.
|
| 1960 |
- type: manhattan_pearson
|
| 1961 |
-
value: 82.
|
| 1962 |
- type: manhattan_spearman
|
| 1963 |
-
value: 79.
|
| 1964 |
- task:
|
| 1965 |
type: STS
|
| 1966 |
dataset:
|
|
@@ -1971,17 +1971,17 @@ 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:
|
| 1981 |
- type: manhattan_pearson
|
| 1982 |
-
value:
|
| 1983 |
- type: manhattan_spearman
|
| 1984 |
-
value:
|
| 1985 |
- task:
|
| 1986 |
type: STS
|
| 1987 |
dataset:
|
|
@@ -1992,17 +1992,17 @@ 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 +2013,17 @@ model-index:
|
|
| 2013 |
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
|
| 2014 |
metrics:
|
| 2015 |
- type: cos_sim_pearson
|
| 2016 |
-
value:
|
| 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: 79.
|
| 2025 |
- type: manhattan_spearman
|
| 2026 |
-
value:
|
| 2027 |
- task:
|
| 2028 |
type: STS
|
| 2029 |
dataset:
|
|
@@ -2034,17 +2034,17 @@ model-index:
|
|
| 2034 |
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
|
| 2035 |
metrics:
|
| 2036 |
- type: cos_sim_pearson
|
| 2037 |
-
value: 86.
|
| 2038 |
- type: cos_sim_spearman
|
| 2039 |
-
value: 87.
|
| 2040 |
- type: euclidean_pearson
|
| 2041 |
-
value: 86.
|
| 2042 |
- type: euclidean_spearman
|
| 2043 |
-
value: 87.
|
| 2044 |
- type: manhattan_pearson
|
| 2045 |
-
value: 86.
|
| 2046 |
- type: manhattan_spearman
|
| 2047 |
-
value: 87.
|
| 2048 |
- task:
|
| 2049 |
type: STS
|
| 2050 |
dataset:
|
|
@@ -2055,17 +2055,17 @@ 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:
|
| 2065 |
- type: manhattan_pearson
|
| 2066 |
-
value:
|
| 2067 |
- type: manhattan_spearman
|
| 2068 |
-
value:
|
| 2069 |
- task:
|
| 2070 |
type: STS
|
| 2071 |
dataset:
|
|
@@ -2076,17 +2076,17 @@ model-index:
|
|
| 2076 |
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
|
| 2077 |
metrics:
|
| 2078 |
- type: cos_sim_pearson
|
| 2079 |
-
value: 89.
|
| 2080 |
- type: cos_sim_spearman
|
| 2081 |
-
value:
|
| 2082 |
- type: euclidean_pearson
|
| 2083 |
-
value: 88.
|
| 2084 |
- type: euclidean_spearman
|
| 2085 |
-
value:
|
| 2086 |
- type: manhattan_pearson
|
| 2087 |
-
value: 88.
|
| 2088 |
- type: manhattan_spearman
|
| 2089 |
-
value: 88.
|
| 2090 |
- task:
|
| 2091 |
type: STS
|
| 2092 |
dataset:
|
|
@@ -2097,17 +2097,17 @@ model-index:
|
|
| 2097 |
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
|
| 2098 |
metrics:
|
| 2099 |
- type: cos_sim_pearson
|
| 2100 |
-
value:
|
| 2101 |
- type: cos_sim_spearman
|
| 2102 |
-
value: 62.
|
| 2103 |
- type: euclidean_pearson
|
| 2104 |
-
value:
|
| 2105 |
- type: euclidean_spearman
|
| 2106 |
-
value: 62.
|
| 2107 |
- type: manhattan_pearson
|
| 2108 |
-
value:
|
| 2109 |
- type: manhattan_spearman
|
| 2110 |
-
value: 62.
|
| 2111 |
- task:
|
| 2112 |
type: STS
|
| 2113 |
dataset:
|
|
@@ -2118,17 +2118,17 @@ model-index:
|
|
| 2118 |
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
|
| 2119 |
metrics:
|
| 2120 |
- type: cos_sim_pearson
|
| 2121 |
-
value: 84.
|
| 2122 |
- type: cos_sim_spearman
|
| 2123 |
-
value: 84.
|
| 2124 |
- type: euclidean_pearson
|
| 2125 |
-
value: 84.
|
| 2126 |
- type: euclidean_spearman
|
| 2127 |
-
value: 84.
|
| 2128 |
- type: manhattan_pearson
|
| 2129 |
-
value: 84.
|
| 2130 |
- type: manhattan_spearman
|
| 2131 |
-
value: 84.
|
| 2132 |
- task:
|
| 2133 |
type: Reranking
|
| 2134 |
dataset:
|
|
@@ -2139,9 +2139,9 @@ model-index:
|
|
| 2139 |
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
|
| 2140 |
metrics:
|
| 2141 |
- type: map
|
| 2142 |
-
value: 83.
|
| 2143 |
- type: mrr
|
| 2144 |
-
value: 95.
|
| 2145 |
- task:
|
| 2146 |
type: Retrieval
|
| 2147 |
dataset:
|
|
@@ -2152,65 +2152,65 @@ model-index:
|
|
| 2152 |
revision: None
|
| 2153 |
metrics:
|
| 2154 |
- type: map_at_1
|
| 2155 |
-
value: 52.
|
| 2156 |
- type: map_at_10
|
| 2157 |
-
value: 62.
|
| 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: 55.333
|
| 2168 |
- type: mrr_at_10
|
| 2169 |
-
value: 63.
|
| 2170 |
- type: mrr_at_100
|
| 2171 |
-
value: 64.
|
| 2172 |
- type: mrr_at_1000
|
| 2173 |
-
value: 64.
|
| 2174 |
- type: mrr_at_3
|
| 2175 |
-
value: 61.
|
| 2176 |
- type: mrr_at_5
|
| 2177 |
-
value: 62.
|
| 2178 |
- type: ndcg_at_1
|
| 2179 |
value: 55.333
|
| 2180 |
- type: ndcg_at_10
|
| 2181 |
-
value:
|
| 2182 |
- type: ndcg_at_100
|
| 2183 |
-
value:
|
| 2184 |
- type: ndcg_at_1000
|
| 2185 |
-
value: 70.
|
| 2186 |
- type: ndcg_at_3
|
| 2187 |
-
value:
|
| 2188 |
- type: ndcg_at_5
|
| 2189 |
-
value: 64.
|
| 2190 |
- type: precision_at_1
|
| 2191 |
value: 55.333
|
| 2192 |
- type: precision_at_10
|
| 2193 |
-
value: 9.
|
| 2194 |
- type: precision_at_100
|
| 2195 |
-
value: 1.
|
| 2196 |
- type: precision_at_1000
|
| 2197 |
value: 0.11199999999999999
|
| 2198 |
- type: precision_at_3
|
| 2199 |
-
value:
|
| 2200 |
- type: precision_at_5
|
| 2201 |
value: 16.333000000000002
|
| 2202 |
- type: recall_at_1
|
| 2203 |
-
value: 52.
|
| 2204 |
- type: recall_at_10
|
| 2205 |
-
value:
|
| 2206 |
- type: recall_at_100
|
| 2207 |
-
value:
|
| 2208 |
- type: recall_at_1000
|
| 2209 |
value: 99.333
|
| 2210 |
- type: recall_at_3
|
| 2211 |
-
value:
|
| 2212 |
- type: recall_at_5
|
| 2213 |
-
value: 73.
|
| 2214 |
- task:
|
| 2215 |
type: PairClassification
|
| 2216 |
dataset:
|
|
@@ -2221,51 +2221,51 @@ 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: 90.
|
| 2229 |
- type: cos_sim_precision
|
| 2230 |
-
value:
|
| 2231 |
- type: cos_sim_recall
|
| 2232 |
-
value: 88.
|
| 2233 |
- type: dot_accuracy
|
| 2234 |
-
value: 99.
|
| 2235 |
- type: dot_ap
|
| 2236 |
-
value:
|
| 2237 |
- type: dot_f1
|
| 2238 |
-
value: 90.
|
| 2239 |
- type: dot_precision
|
| 2240 |
-
value:
|
| 2241 |
- type: dot_recall
|
| 2242 |
-
value: 88.
|
| 2243 |
- type: euclidean_accuracy
|
| 2244 |
-
value: 99.
|
| 2245 |
- type: euclidean_ap
|
| 2246 |
-
value:
|
| 2247 |
- type: euclidean_f1
|
| 2248 |
-
value: 90.
|
| 2249 |
- type: euclidean_precision
|
| 2250 |
-
value:
|
| 2251 |
- type: euclidean_recall
|
| 2252 |
-
value: 88.
|
| 2253 |
- type: manhattan_accuracy
|
| 2254 |
-
value: 99.
|
| 2255 |
- type: manhattan_ap
|
| 2256 |
-
value:
|
| 2257 |
- type: manhattan_f1
|
| 2258 |
-
value:
|
| 2259 |
- type: manhattan_precision
|
| 2260 |
-
value: 90.
|
| 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: 90.
|
| 2269 |
- task:
|
| 2270 |
type: Clustering
|
| 2271 |
dataset:
|
|
@@ -2276,7 +2276,7 @@ model-index:
|
|
| 2276 |
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
|
| 2277 |
metrics:
|
| 2278 |
- type: v_measure
|
| 2279 |
-
value: 58.
|
| 2280 |
- task:
|
| 2281 |
type: Clustering
|
| 2282 |
dataset:
|
|
@@ -2287,7 +2287,7 @@ model-index:
|
|
| 2287 |
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
|
| 2288 |
metrics:
|
| 2289 |
- type: v_measure
|
| 2290 |
-
value: 34.
|
| 2291 |
- task:
|
| 2292 |
type: Reranking
|
| 2293 |
dataset:
|
|
@@ -2298,9 +2298,9 @@ model-index:
|
|
| 2298 |
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
|
| 2299 |
metrics:
|
| 2300 |
- type: map
|
| 2301 |
-
value: 52.
|
| 2302 |
- type: mrr
|
| 2303 |
-
value:
|
| 2304 |
- task:
|
| 2305 |
type: Summarization
|
| 2306 |
dataset:
|
|
@@ -2311,13 +2311,13 @@ model-index:
|
|
| 2311 |
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
|
| 2312 |
metrics:
|
| 2313 |
- type: cos_sim_pearson
|
| 2314 |
-
value: 30.
|
| 2315 |
- type: cos_sim_spearman
|
| 2316 |
-
value:
|
| 2317 |
- type: dot_pearson
|
| 2318 |
-
value: 30.
|
| 2319 |
- type: dot_spearman
|
| 2320 |
-
value:
|
| 2321 |
- task:
|
| 2322 |
type: Retrieval
|
| 2323 |
dataset:
|
|
@@ -2328,65 +2328,65 @@ 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:
|
| 2336 |
- type: map_at_1000
|
| 2337 |
-
value:
|
| 2338 |
- type: map_at_3
|
| 2339 |
-
value: 0.
|
| 2340 |
- type: map_at_5
|
| 2341 |
-
value: 0.
|
| 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: 65.
|
| 2358 |
- type: ndcg_at_100
|
| 2359 |
-
value:
|
| 2360 |
- type: ndcg_at_1000
|
| 2361 |
-
value:
|
| 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:
|
| 2370 |
- type: precision_at_100
|
| 2371 |
-
value:
|
| 2372 |
- type: precision_at_1000
|
| 2373 |
-
value:
|
| 2374 |
- type: precision_at_3
|
| 2375 |
value: 72.667
|
| 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: 12.
|
| 2384 |
- type: recall_at_1000
|
| 2385 |
-
value:
|
| 2386 |
- type: recall_at_3
|
| 2387 |
-
value: 0.
|
| 2388 |
- type: recall_at_5
|
| 2389 |
-
value: 1.
|
| 2390 |
- task:
|
| 2391 |
type: Retrieval
|
| 2392 |
dataset:
|
|
@@ -2397,65 +2397,65 @@ model-index:
|
|
| 2397 |
revision: None
|
| 2398 |
metrics:
|
| 2399 |
- type: map_at_1
|
| 2400 |
-
value: 2.
|
| 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:
|
| 2447 |
- type: recall_at_1
|
| 2448 |
-
value: 2.
|
| 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: 9.
|
| 2459 |
- task:
|
| 2460 |
type: Classification
|
| 2461 |
dataset:
|
|
@@ -2466,11 +2466,11 @@ 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 +2481,9 @@ 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 +2494,7 @@ model-index:
|
|
| 2494 |
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
|
| 2495 |
metrics:
|
| 2496 |
- type: v_measure
|
| 2497 |
-
value:
|
| 2498 |
- task:
|
| 2499 |
type: PairClassification
|
| 2500 |
dataset:
|
|
@@ -2505,51 +2505,51 @@ 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: 68.
|
| 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: 68.
|
| 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: 68.
|
| 2533 |
- type: euclidean_precision
|
| 2534 |
-
value:
|
| 2535 |
- type: euclidean_recall
|
| 2536 |
-
value:
|
| 2537 |
- type: manhattan_accuracy
|
| 2538 |
-
value:
|
| 2539 |
- type: manhattan_ap
|
| 2540 |
-
value:
|
| 2541 |
- type: manhattan_f1
|
| 2542 |
-
value: 68.
|
| 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: 68.
|
| 2553 |
- task:
|
| 2554 |
type: PairClassification
|
| 2555 |
dataset:
|
|
@@ -2560,51 +2560,51 @@ model-index:
|
|
| 2560 |
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
|
| 2561 |
metrics:
|
| 2562 |
- type: cos_sim_accuracy
|
| 2563 |
-
value: 88.
|
| 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: 88.
|
| 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: 88.
|
| 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: 88.
|
| 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: 88.
|
| 2604 |
- type: max_ap
|
| 2605 |
-
value:
|
| 2606 |
- type: max_f1
|
| 2607 |
-
value:
|
| 2608 |
---
|
| 2609 |
<!-- TODO: add evaluation results here -->
|
| 2610 |
<br><br>
|
|
@@ -2641,8 +2641,8 @@ Additionally, we provide the following embedding models:
|
|
| 2641 |
|
| 2642 |
**V2 (Based on JinaBert, 8k Seq)**
|
| 2643 |
|
| 2644 |
-
- [`jina-embeddings-v2-small-en`](https://huggingface.co/jinaai/jina-embeddings-v2-small-en): 33 million parameters
|
| 2645 |
-
- [`jina-embeddings-v2-base-en`](https://huggingface.co/jinaai/jina-embeddings-v2-base-en): 137 million parameters
|
| 2646 |
- [`jina-embeddings-v2-large-en`](): 435 million parameters (releasing soon).
|
| 2647 |
|
| 2648 |
## Data & Parameters
|
|
@@ -2674,7 +2674,7 @@ embeddings = model.encode(
|
|
| 2674 |
)
|
| 2675 |
```
|
| 2676 |
|
| 2677 |
-
*Alternatively, you can use Jina AI's
|
| 2678 |
|
| 2679 |
## Fine-tuning
|
| 2680 |
|
|
|
|
| 23 |
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
|
| 24 |
metrics:
|
| 25 |
- type: accuracy
|
| 26 |
+
value: 74.73134328358209
|
| 27 |
- type: ap
|
| 28 |
+
value: 37.765427081831035
|
| 29 |
- type: f1
|
| 30 |
+
value: 68.79367444339518
|
| 31 |
- task:
|
| 32 |
type: Classification
|
| 33 |
dataset:
|
|
|
|
| 38 |
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
|
| 39 |
metrics:
|
| 40 |
- type: accuracy
|
| 41 |
+
value: 88.544275
|
| 42 |
- type: ap
|
| 43 |
+
value: 84.61328675662887
|
| 44 |
- type: f1
|
| 45 |
+
value: 88.51879035862375
|
| 46 |
- task:
|
| 47 |
type: Classification
|
| 48 |
dataset:
|
|
|
|
| 53 |
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
|
| 54 |
metrics:
|
| 55 |
- type: accuracy
|
| 56 |
+
value: 45.263999999999996
|
| 57 |
- type: f1
|
| 58 |
+
value: 43.778759656699435
|
| 59 |
- task:
|
| 60 |
type: Retrieval
|
| 61 |
dataset:
|
|
|
|
| 66 |
revision: None
|
| 67 |
metrics:
|
| 68 |
- type: map_at_1
|
| 69 |
+
value: 21.693
|
| 70 |
- type: map_at_10
|
| 71 |
+
value: 35.487
|
| 72 |
- type: map_at_100
|
| 73 |
+
value: 36.862
|
| 74 |
- type: map_at_1000
|
| 75 |
+
value: 36.872
|
| 76 |
- type: map_at_3
|
| 77 |
+
value: 30.049999999999997
|
| 78 |
- type: map_at_5
|
| 79 |
+
value: 32.966
|
| 80 |
- type: mrr_at_1
|
| 81 |
+
value: 21.977
|
| 82 |
- type: mrr_at_10
|
| 83 |
+
value: 35.565999999999995
|
| 84 |
- type: mrr_at_100
|
| 85 |
+
value: 36.948
|
| 86 |
- type: mrr_at_1000
|
| 87 |
+
value: 36.958
|
| 88 |
- type: mrr_at_3
|
| 89 |
+
value: 30.121
|
| 90 |
- type: mrr_at_5
|
| 91 |
+
value: 33.051
|
| 92 |
- type: ndcg_at_1
|
| 93 |
+
value: 21.693
|
| 94 |
- type: ndcg_at_10
|
| 95 |
+
value: 44.181
|
| 96 |
- type: ndcg_at_100
|
| 97 |
+
value: 49.982
|
| 98 |
- type: ndcg_at_1000
|
| 99 |
+
value: 50.233000000000004
|
| 100 |
- type: ndcg_at_3
|
| 101 |
+
value: 32.830999999999996
|
| 102 |
- type: ndcg_at_5
|
| 103 |
+
value: 38.080000000000005
|
| 104 |
- type: precision_at_1
|
| 105 |
+
value: 21.693
|
| 106 |
- type: precision_at_10
|
| 107 |
+
value: 7.248
|
| 108 |
- type: precision_at_100
|
| 109 |
+
value: 0.9769999999999999
|
| 110 |
- type: precision_at_1000
|
| 111 |
value: 0.1
|
| 112 |
- type: precision_at_3
|
| 113 |
+
value: 13.632
|
| 114 |
- type: precision_at_5
|
| 115 |
+
value: 10.725
|
| 116 |
- type: recall_at_1
|
| 117 |
+
value: 21.693
|
| 118 |
- type: recall_at_10
|
| 119 |
+
value: 72.475
|
| 120 |
- type: recall_at_100
|
| 121 |
+
value: 97.653
|
| 122 |
- type: recall_at_1000
|
| 123 |
+
value: 99.57300000000001
|
| 124 |
- type: recall_at_3
|
| 125 |
+
value: 40.896
|
| 126 |
- type: recall_at_5
|
| 127 |
+
value: 53.627
|
| 128 |
- task:
|
| 129 |
type: Clustering
|
| 130 |
dataset:
|
|
|
|
| 135 |
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
|
| 136 |
metrics:
|
| 137 |
- type: v_measure
|
| 138 |
+
value: 45.39242428696777
|
| 139 |
- task:
|
| 140 |
type: Clustering
|
| 141 |
dataset:
|
|
|
|
| 146 |
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
|
| 147 |
metrics:
|
| 148 |
- type: v_measure
|
| 149 |
+
value: 36.675626784714
|
| 150 |
- task:
|
| 151 |
type: Reranking
|
| 152 |
dataset:
|
|
|
|
| 157 |
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
|
| 158 |
metrics:
|
| 159 |
- type: map
|
| 160 |
+
value: 62.247725694904034
|
| 161 |
- type: mrr
|
| 162 |
+
value: 74.91359978894604
|
| 163 |
- task:
|
| 164 |
type: STS
|
| 165 |
dataset:
|
|
|
|
| 170 |
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
|
| 171 |
metrics:
|
| 172 |
- type: cos_sim_pearson
|
| 173 |
+
value: 82.68003802970496
|
| 174 |
- type: cos_sim_spearman
|
| 175 |
+
value: 81.23438110096286
|
| 176 |
- type: euclidean_pearson
|
| 177 |
+
value: 81.87462986142582
|
| 178 |
- type: euclidean_spearman
|
| 179 |
+
value: 81.23438110096286
|
| 180 |
- type: manhattan_pearson
|
| 181 |
+
value: 81.61162566600755
|
| 182 |
- type: manhattan_spearman
|
| 183 |
+
value: 81.11329400456184
|
| 184 |
- task:
|
| 185 |
type: Classification
|
| 186 |
dataset:
|
|
|
|
| 191 |
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
|
| 192 |
metrics:
|
| 193 |
- type: accuracy
|
| 194 |
+
value: 84.01298701298701
|
| 195 |
- type: f1
|
| 196 |
+
value: 83.31690714969382
|
| 197 |
- task:
|
| 198 |
type: Clustering
|
| 199 |
dataset:
|
|
|
|
| 204 |
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
|
| 205 |
metrics:
|
| 206 |
- type: v_measure
|
| 207 |
+
value: 37.050108150972086
|
| 208 |
- task:
|
| 209 |
type: Clustering
|
| 210 |
dataset:
|
|
|
|
| 215 |
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
|
| 216 |
metrics:
|
| 217 |
- type: v_measure
|
| 218 |
+
value: 30.15731442819715
|
| 219 |
- task:
|
| 220 |
type: Retrieval
|
| 221 |
dataset:
|
|
|
|
| 226 |
revision: None
|
| 227 |
metrics:
|
| 228 |
- type: map_at_1
|
| 229 |
+
value: 31.391999999999996
|
| 230 |
- type: map_at_10
|
| 231 |
+
value: 42.597
|
| 232 |
- type: map_at_100
|
| 233 |
+
value: 44.07
|
| 234 |
- type: map_at_1000
|
| 235 |
+
value: 44.198
|
| 236 |
- type: map_at_3
|
| 237 |
+
value: 38.957
|
| 238 |
- type: map_at_5
|
| 239 |
+
value: 40.961
|
| 240 |
- type: mrr_at_1
|
| 241 |
+
value: 37.196
|
| 242 |
- type: mrr_at_10
|
| 243 |
+
value: 48.152
|
| 244 |
- type: mrr_at_100
|
| 245 |
+
value: 48.928
|
| 246 |
- type: mrr_at_1000
|
| 247 |
+
value: 48.964999999999996
|
| 248 |
- type: mrr_at_3
|
| 249 |
+
value: 45.446
|
| 250 |
- type: mrr_at_5
|
| 251 |
+
value: 47.205999999999996
|
| 252 |
- type: ndcg_at_1
|
| 253 |
+
value: 37.196
|
| 254 |
- type: ndcg_at_10
|
| 255 |
+
value: 49.089
|
| 256 |
- type: ndcg_at_100
|
| 257 |
+
value: 54.471000000000004
|
| 258 |
- type: ndcg_at_1000
|
| 259 |
+
value: 56.385
|
| 260 |
- type: ndcg_at_3
|
| 261 |
+
value: 43.699
|
| 262 |
- type: ndcg_at_5
|
| 263 |
+
value: 46.22
|
| 264 |
- type: precision_at_1
|
| 265 |
+
value: 37.196
|
| 266 |
- type: precision_at_10
|
| 267 |
+
value: 9.313
|
| 268 |
- type: precision_at_100
|
| 269 |
+
value: 1.478
|
| 270 |
- type: precision_at_1000
|
| 271 |
+
value: 0.198
|
| 272 |
- type: precision_at_3
|
| 273 |
+
value: 20.839
|
| 274 |
- type: precision_at_5
|
| 275 |
+
value: 14.936
|
| 276 |
- type: recall_at_1
|
| 277 |
+
value: 31.391999999999996
|
| 278 |
- type: recall_at_10
|
| 279 |
+
value: 61.876
|
| 280 |
- type: recall_at_100
|
| 281 |
+
value: 84.214
|
| 282 |
- type: recall_at_1000
|
| 283 |
+
value: 95.985
|
| 284 |
- type: recall_at_3
|
| 285 |
+
value: 46.6
|
| 286 |
- type: recall_at_5
|
| 287 |
+
value: 53.588
|
| 288 |
- task:
|
| 289 |
type: Retrieval
|
| 290 |
dataset:
|
|
|
|
| 295 |
revision: None
|
| 296 |
metrics:
|
| 297 |
- type: map_at_1
|
| 298 |
+
value: 29.083
|
| 299 |
- type: map_at_10
|
| 300 |
+
value: 38.812999999999995
|
| 301 |
- type: map_at_100
|
| 302 |
+
value: 40.053
|
| 303 |
- type: map_at_1000
|
| 304 |
+
value: 40.188
|
| 305 |
- type: map_at_3
|
| 306 |
+
value: 36.111
|
| 307 |
- type: map_at_5
|
| 308 |
+
value: 37.519000000000005
|
| 309 |
- type: mrr_at_1
|
| 310 |
+
value: 36.497
|
| 311 |
- type: mrr_at_10
|
| 312 |
+
value: 44.85
|
| 313 |
- type: mrr_at_100
|
| 314 |
+
value: 45.546
|
| 315 |
- type: mrr_at_1000
|
| 316 |
+
value: 45.593
|
| 317 |
- type: mrr_at_3
|
| 318 |
+
value: 42.686
|
| 319 |
- type: mrr_at_5
|
| 320 |
+
value: 43.909
|
| 321 |
- type: ndcg_at_1
|
| 322 |
+
value: 36.497
|
| 323 |
- type: ndcg_at_10
|
| 324 |
+
value: 44.443
|
| 325 |
- type: ndcg_at_100
|
| 326 |
+
value: 48.979
|
| 327 |
- type: ndcg_at_1000
|
| 328 |
+
value: 51.154999999999994
|
| 329 |
- type: ndcg_at_3
|
| 330 |
+
value: 40.660000000000004
|
| 331 |
- type: ndcg_at_5
|
| 332 |
+
value: 42.193000000000005
|
| 333 |
- type: precision_at_1
|
| 334 |
+
value: 36.497
|
| 335 |
- type: precision_at_10
|
| 336 |
+
value: 8.433
|
| 337 |
- type: precision_at_100
|
| 338 |
+
value: 1.369
|
| 339 |
- type: precision_at_1000
|
| 340 |
+
value: 0.185
|
| 341 |
- type: precision_at_3
|
| 342 |
+
value: 19.894000000000002
|
| 343 |
- type: precision_at_5
|
| 344 |
+
value: 13.873
|
| 345 |
- type: recall_at_1
|
| 346 |
+
value: 29.083
|
| 347 |
- type: recall_at_10
|
| 348 |
+
value: 54.313
|
| 349 |
- type: recall_at_100
|
| 350 |
+
value: 73.792
|
| 351 |
- type: recall_at_1000
|
| 352 |
+
value: 87.629
|
| 353 |
- type: recall_at_3
|
| 354 |
+
value: 42.257
|
| 355 |
- type: recall_at_5
|
| 356 |
+
value: 47.066
|
| 357 |
- task:
|
| 358 |
type: Retrieval
|
| 359 |
dataset:
|
|
|
|
| 364 |
revision: None
|
| 365 |
metrics:
|
| 366 |
- type: map_at_1
|
| 367 |
+
value: 38.556000000000004
|
| 368 |
- type: map_at_10
|
| 369 |
+
value: 50.698
|
| 370 |
- type: map_at_100
|
| 371 |
+
value: 51.705
|
| 372 |
- type: map_at_1000
|
| 373 |
+
value: 51.768
|
| 374 |
- type: map_at_3
|
| 375 |
+
value: 47.848
|
| 376 |
- type: map_at_5
|
| 377 |
+
value: 49.358000000000004
|
| 378 |
- type: mrr_at_1
|
| 379 |
+
value: 43.95
|
| 380 |
- type: mrr_at_10
|
| 381 |
+
value: 54.191
|
| 382 |
- type: mrr_at_100
|
| 383 |
+
value: 54.852999999999994
|
| 384 |
- type: mrr_at_1000
|
| 385 |
+
value: 54.885
|
| 386 |
- type: mrr_at_3
|
| 387 |
+
value: 51.954
|
| 388 |
- type: mrr_at_5
|
| 389 |
+
value: 53.13
|
| 390 |
- type: ndcg_at_1
|
| 391 |
+
value: 43.95
|
| 392 |
- type: ndcg_at_10
|
| 393 |
+
value: 56.516
|
| 394 |
- type: ndcg_at_100
|
| 395 |
+
value: 60.477000000000004
|
| 396 |
- type: ndcg_at_1000
|
| 397 |
+
value: 61.746
|
| 398 |
- type: ndcg_at_3
|
| 399 |
+
value: 51.601
|
| 400 |
- type: ndcg_at_5
|
| 401 |
+
value: 53.795
|
| 402 |
- type: precision_at_1
|
| 403 |
+
value: 43.95
|
| 404 |
- type: precision_at_10
|
| 405 |
+
value: 9.009
|
| 406 |
- type: precision_at_100
|
| 407 |
+
value: 1.189
|
| 408 |
- type: precision_at_1000
|
| 409 |
+
value: 0.135
|
| 410 |
- type: precision_at_3
|
| 411 |
+
value: 22.989
|
| 412 |
- type: precision_at_5
|
| 413 |
+
value: 15.473
|
| 414 |
- type: recall_at_1
|
| 415 |
+
value: 38.556000000000004
|
| 416 |
- type: recall_at_10
|
| 417 |
+
value: 70.159
|
| 418 |
- type: recall_at_100
|
| 419 |
+
value: 87.132
|
| 420 |
- type: recall_at_1000
|
| 421 |
+
value: 96.16
|
| 422 |
- type: recall_at_3
|
| 423 |
+
value: 56.906
|
| 424 |
- type: recall_at_5
|
| 425 |
+
value: 62.332
|
| 426 |
- task:
|
| 427 |
type: Retrieval
|
| 428 |
dataset:
|
|
|
|
| 433 |
revision: None
|
| 434 |
metrics:
|
| 435 |
- type: map_at_1
|
| 436 |
+
value: 24.238
|
| 437 |
- type: map_at_10
|
| 438 |
+
value: 32.5
|
| 439 |
- type: map_at_100
|
| 440 |
+
value: 33.637
|
| 441 |
- type: map_at_1000
|
| 442 |
+
value: 33.719
|
| 443 |
- type: map_at_3
|
| 444 |
+
value: 30.026999999999997
|
| 445 |
- type: map_at_5
|
| 446 |
+
value: 31.555
|
| 447 |
- type: mrr_at_1
|
| 448 |
+
value: 26.328000000000003
|
| 449 |
- type: mrr_at_10
|
| 450 |
+
value: 34.44
|
| 451 |
- type: mrr_at_100
|
| 452 |
+
value: 35.455999999999996
|
| 453 |
- type: mrr_at_1000
|
| 454 |
+
value: 35.521
|
| 455 |
- type: mrr_at_3
|
| 456 |
+
value: 32.034
|
| 457 |
- type: mrr_at_5
|
| 458 |
+
value: 33.565
|
| 459 |
- type: ndcg_at_1
|
| 460 |
+
value: 26.328000000000003
|
| 461 |
- type: ndcg_at_10
|
| 462 |
+
value: 37.202
|
| 463 |
- type: ndcg_at_100
|
| 464 |
+
value: 42.728
|
| 465 |
- type: ndcg_at_1000
|
| 466 |
+
value: 44.792
|
| 467 |
- type: ndcg_at_3
|
| 468 |
+
value: 32.368
|
| 469 |
- type: ndcg_at_5
|
| 470 |
+
value: 35.008
|
| 471 |
- type: precision_at_1
|
| 472 |
+
value: 26.328000000000003
|
| 473 |
- type: precision_at_10
|
| 474 |
+
value: 5.7059999999999995
|
| 475 |
- type: precision_at_100
|
| 476 |
+
value: 0.8880000000000001
|
| 477 |
- type: precision_at_1000
|
| 478 |
value: 0.11100000000000002
|
| 479 |
- type: precision_at_3
|
| 480 |
+
value: 13.672
|
| 481 |
- type: precision_at_5
|
| 482 |
+
value: 9.74
|
| 483 |
- type: recall_at_1
|
| 484 |
+
value: 24.238
|
| 485 |
- type: recall_at_10
|
| 486 |
+
value: 49.829
|
| 487 |
- type: recall_at_100
|
| 488 |
+
value: 75.21
|
| 489 |
- type: recall_at_1000
|
| 490 |
+
value: 90.521
|
| 491 |
- type: recall_at_3
|
| 492 |
+
value: 36.867
|
| 493 |
- type: recall_at_5
|
| 494 |
+
value: 43.241
|
| 495 |
- task:
|
| 496 |
type: Retrieval
|
| 497 |
dataset:
|
|
|
|
| 502 |
revision: None
|
| 503 |
metrics:
|
| 504 |
- type: map_at_1
|
| 505 |
+
value: 15.378
|
| 506 |
- type: map_at_10
|
| 507 |
+
value: 22.817999999999998
|
| 508 |
- type: map_at_100
|
| 509 |
+
value: 23.977999999999998
|
| 510 |
- type: map_at_1000
|
| 511 |
+
value: 24.108
|
| 512 |
- type: map_at_3
|
| 513 |
+
value: 20.719
|
| 514 |
- type: map_at_5
|
| 515 |
+
value: 21.889
|
| 516 |
- type: mrr_at_1
|
| 517 |
+
value: 19.03
|
| 518 |
- type: mrr_at_10
|
| 519 |
+
value: 27.022000000000002
|
| 520 |
- type: mrr_at_100
|
| 521 |
+
value: 28.011999999999997
|
| 522 |
- type: mrr_at_1000
|
| 523 |
+
value: 28.096
|
| 524 |
- type: mrr_at_3
|
| 525 |
+
value: 24.855
|
| 526 |
- type: mrr_at_5
|
| 527 |
+
value: 26.029999999999998
|
| 528 |
- type: ndcg_at_1
|
| 529 |
+
value: 19.03
|
| 530 |
- type: ndcg_at_10
|
| 531 |
+
value: 27.526
|
| 532 |
- type: ndcg_at_100
|
| 533 |
+
value: 33.040000000000006
|
| 534 |
- type: ndcg_at_1000
|
| 535 |
+
value: 36.187000000000005
|
| 536 |
- type: ndcg_at_3
|
| 537 |
+
value: 23.497
|
| 538 |
- type: ndcg_at_5
|
| 539 |
+
value: 25.334
|
| 540 |
- type: precision_at_1
|
| 541 |
+
value: 19.03
|
| 542 |
- type: precision_at_10
|
| 543 |
+
value: 4.963
|
| 544 |
- type: precision_at_100
|
| 545 |
+
value: 0.893
|
| 546 |
- type: precision_at_1000
|
| 547 |
+
value: 0.13
|
| 548 |
- type: precision_at_3
|
| 549 |
+
value: 11.360000000000001
|
| 550 |
- type: precision_at_5
|
| 551 |
+
value: 8.134
|
| 552 |
- type: recall_at_1
|
| 553 |
+
value: 15.378
|
| 554 |
- type: recall_at_10
|
| 555 |
+
value: 38.061
|
| 556 |
- type: recall_at_100
|
| 557 |
+
value: 61.754
|
| 558 |
- type: recall_at_1000
|
| 559 |
+
value: 84.259
|
| 560 |
- type: recall_at_3
|
| 561 |
+
value: 26.788
|
| 562 |
- type: recall_at_5
|
| 563 |
+
value: 31.326999999999998
|
| 564 |
- task:
|
| 565 |
type: Retrieval
|
| 566 |
dataset:
|
|
|
|
| 571 |
revision: None
|
| 572 |
metrics:
|
| 573 |
- type: map_at_1
|
| 574 |
+
value: 27.511999999999997
|
| 575 |
- type: map_at_10
|
| 576 |
+
value: 37.429
|
| 577 |
- type: map_at_100
|
| 578 |
+
value: 38.818000000000005
|
| 579 |
- type: map_at_1000
|
| 580 |
+
value: 38.924
|
| 581 |
- type: map_at_3
|
| 582 |
+
value: 34.625
|
| 583 |
- type: map_at_5
|
| 584 |
+
value: 36.064
|
| 585 |
- type: mrr_at_1
|
| 586 |
+
value: 33.300999999999995
|
| 587 |
- type: mrr_at_10
|
| 588 |
+
value: 43.036
|
| 589 |
- type: mrr_at_100
|
| 590 |
+
value: 43.894
|
| 591 |
- type: mrr_at_1000
|
| 592 |
+
value: 43.936
|
| 593 |
- type: mrr_at_3
|
| 594 |
+
value: 40.825
|
| 595 |
- type: mrr_at_5
|
| 596 |
+
value: 42.028
|
| 597 |
- type: ndcg_at_1
|
| 598 |
+
value: 33.300999999999995
|
| 599 |
- type: ndcg_at_10
|
| 600 |
+
value: 43.229
|
| 601 |
- type: ndcg_at_100
|
| 602 |
+
value: 48.992000000000004
|
| 603 |
- type: ndcg_at_1000
|
| 604 |
+
value: 51.02100000000001
|
| 605 |
- type: ndcg_at_3
|
| 606 |
+
value: 38.794000000000004
|
| 607 |
- type: ndcg_at_5
|
| 608 |
+
value: 40.65
|
| 609 |
- type: precision_at_1
|
| 610 |
+
value: 33.300999999999995
|
| 611 |
- type: precision_at_10
|
| 612 |
+
value: 7.777000000000001
|
| 613 |
- type: precision_at_100
|
| 614 |
+
value: 1.269
|
| 615 |
- type: precision_at_1000
|
| 616 |
+
value: 0.163
|
| 617 |
- type: precision_at_3
|
| 618 |
+
value: 18.351
|
| 619 |
- type: precision_at_5
|
| 620 |
+
value: 12.762
|
| 621 |
- type: recall_at_1
|
| 622 |
+
value: 27.511999999999997
|
| 623 |
- type: recall_at_10
|
| 624 |
+
value: 54.788000000000004
|
| 625 |
- type: recall_at_100
|
| 626 |
+
value: 79.105
|
| 627 |
- type: recall_at_1000
|
| 628 |
+
value: 92.49199999999999
|
| 629 |
- type: recall_at_3
|
| 630 |
+
value: 41.924
|
| 631 |
- type: recall_at_5
|
| 632 |
+
value: 47.026
|
| 633 |
- task:
|
| 634 |
type: Retrieval
|
| 635 |
dataset:
|
|
|
|
| 640 |
revision: None
|
| 641 |
metrics:
|
| 642 |
- type: map_at_1
|
| 643 |
+
value: 24.117
|
| 644 |
- type: map_at_10
|
| 645 |
+
value: 33.32
|
| 646 |
- type: map_at_100
|
| 647 |
+
value: 34.677
|
| 648 |
- type: map_at_1000
|
| 649 |
+
value: 34.78
|
| 650 |
- type: map_at_3
|
| 651 |
+
value: 30.233999999999998
|
| 652 |
- type: map_at_5
|
| 653 |
+
value: 31.668000000000003
|
| 654 |
- type: mrr_at_1
|
| 655 |
+
value: 29.566
|
| 656 |
- type: mrr_at_10
|
| 657 |
+
value: 38.244
|
| 658 |
- type: mrr_at_100
|
| 659 |
+
value: 39.245000000000005
|
| 660 |
- type: mrr_at_1000
|
| 661 |
+
value: 39.296
|
| 662 |
- type: mrr_at_3
|
| 663 |
+
value: 35.864000000000004
|
| 664 |
- type: mrr_at_5
|
| 665 |
+
value: 36.919999999999995
|
| 666 |
- type: ndcg_at_1
|
| 667 |
+
value: 29.566
|
| 668 |
- type: ndcg_at_10
|
| 669 |
+
value: 39.127
|
| 670 |
- type: ndcg_at_100
|
| 671 |
+
value: 44.989000000000004
|
| 672 |
- type: ndcg_at_1000
|
| 673 |
+
value: 47.189
|
| 674 |
- type: ndcg_at_3
|
| 675 |
+
value: 34.039
|
| 676 |
- type: ndcg_at_5
|
| 677 |
+
value: 35.744
|
| 678 |
- type: precision_at_1
|
| 679 |
+
value: 29.566
|
| 680 |
- type: precision_at_10
|
| 681 |
+
value: 7.385999999999999
|
| 682 |
- type: precision_at_100
|
| 683 |
+
value: 1.204
|
| 684 |
- type: precision_at_1000
|
| 685 |
+
value: 0.158
|
| 686 |
- type: precision_at_3
|
| 687 |
+
value: 16.286
|
| 688 |
- type: precision_at_5
|
| 689 |
+
value: 11.484
|
| 690 |
- type: recall_at_1
|
| 691 |
+
value: 24.117
|
| 692 |
- type: recall_at_10
|
| 693 |
+
value: 51.559999999999995
|
| 694 |
- type: recall_at_100
|
| 695 |
+
value: 77.104
|
| 696 |
- type: recall_at_1000
|
| 697 |
+
value: 91.79899999999999
|
| 698 |
- type: recall_at_3
|
| 699 |
+
value: 36.82
|
| 700 |
- type: recall_at_5
|
| 701 |
+
value: 41.453
|
| 702 |
- task:
|
| 703 |
type: Retrieval
|
| 704 |
dataset:
|
|
|
|
| 709 |
revision: None
|
| 710 |
metrics:
|
| 711 |
- type: map_at_1
|
| 712 |
+
value: 25.17625
|
| 713 |
- type: map_at_10
|
| 714 |
+
value: 34.063916666666664
|
| 715 |
- type: map_at_100
|
| 716 |
+
value: 35.255500000000005
|
| 717 |
- type: map_at_1000
|
| 718 |
+
value: 35.37275
|
| 719 |
- type: map_at_3
|
| 720 |
+
value: 31.351666666666667
|
| 721 |
- type: map_at_5
|
| 722 |
+
value: 32.80608333333333
|
| 723 |
- type: mrr_at_1
|
| 724 |
+
value: 29.59783333333333
|
| 725 |
- type: mrr_at_10
|
| 726 |
+
value: 38.0925
|
| 727 |
- type: mrr_at_100
|
| 728 |
+
value: 38.957249999999995
|
| 729 |
- type: mrr_at_1000
|
| 730 |
+
value: 39.01608333333333
|
| 731 |
- type: mrr_at_3
|
| 732 |
+
value: 35.77625
|
| 733 |
- type: mrr_at_5
|
| 734 |
+
value: 37.04991666666667
|
| 735 |
- type: ndcg_at_1
|
| 736 |
+
value: 29.59783333333333
|
| 737 |
- type: ndcg_at_10
|
| 738 |
+
value: 39.343666666666664
|
| 739 |
- type: ndcg_at_100
|
| 740 |
+
value: 44.488249999999994
|
| 741 |
- type: ndcg_at_1000
|
| 742 |
+
value: 46.83358333333334
|
| 743 |
- type: ndcg_at_3
|
| 744 |
+
value: 34.69708333333333
|
| 745 |
- type: ndcg_at_5
|
| 746 |
+
value: 36.75075
|
| 747 |
- type: precision_at_1
|
| 748 |
+
value: 29.59783333333333
|
| 749 |
- type: precision_at_10
|
| 750 |
+
value: 6.884083333333332
|
| 751 |
- type: precision_at_100
|
| 752 |
+
value: 1.114
|
| 753 |
- type: precision_at_1000
|
| 754 |
+
value: 0.15108333333333332
|
| 755 |
- type: precision_at_3
|
| 756 |
+
value: 15.965250000000003
|
| 757 |
- type: precision_at_5
|
| 758 |
+
value: 11.246500000000001
|
| 759 |
- type: recall_at_1
|
| 760 |
+
value: 25.17625
|
| 761 |
- type: recall_at_10
|
| 762 |
+
value: 51.015999999999984
|
| 763 |
- type: recall_at_100
|
| 764 |
+
value: 73.60174999999998
|
| 765 |
- type: recall_at_1000
|
| 766 |
+
value: 89.849
|
| 767 |
- type: recall_at_3
|
| 768 |
+
value: 37.88399999999999
|
| 769 |
- type: recall_at_5
|
| 770 |
+
value: 43.24541666666666
|
| 771 |
- task:
|
| 772 |
type: Retrieval
|
| 773 |
dataset:
|
|
|
|
| 778 |
revision: None
|
| 779 |
metrics:
|
| 780 |
- type: map_at_1
|
| 781 |
+
value: 24.537
|
| 782 |
- type: map_at_10
|
| 783 |
+
value: 31.081999999999997
|
| 784 |
- type: map_at_100
|
| 785 |
+
value: 32.042
|
| 786 |
- type: map_at_1000
|
| 787 |
+
value: 32.141
|
| 788 |
- type: map_at_3
|
| 789 |
+
value: 29.137
|
| 790 |
- type: map_at_5
|
| 791 |
+
value: 30.079
|
| 792 |
- type: mrr_at_1
|
| 793 |
+
value: 27.454
|
| 794 |
- type: mrr_at_10
|
| 795 |
+
value: 33.694
|
| 796 |
- type: mrr_at_100
|
| 797 |
+
value: 34.579
|
| 798 |
- type: mrr_at_1000
|
| 799 |
+
value: 34.649
|
| 800 |
- type: mrr_at_3
|
| 801 |
+
value: 32.004
|
| 802 |
- type: mrr_at_5
|
| 803 |
+
value: 32.794000000000004
|
| 804 |
- type: ndcg_at_1
|
| 805 |
+
value: 27.454
|
| 806 |
- type: ndcg_at_10
|
| 807 |
+
value: 34.915
|
| 808 |
- type: ndcg_at_100
|
| 809 |
+
value: 39.641
|
| 810 |
- type: ndcg_at_1000
|
| 811 |
+
value: 42.105
|
| 812 |
- type: ndcg_at_3
|
| 813 |
+
value: 31.276
|
| 814 |
- type: ndcg_at_5
|
| 815 |
+
value: 32.65
|
| 816 |
- type: precision_at_1
|
| 817 |
+
value: 27.454
|
| 818 |
- type: precision_at_10
|
| 819 |
+
value: 5.337
|
| 820 |
- type: precision_at_100
|
| 821 |
+
value: 0.8250000000000001
|
| 822 |
- type: precision_at_1000
|
| 823 |
+
value: 0.11199999999999999
|
| 824 |
- type: precision_at_3
|
| 825 |
+
value: 13.241
|
| 826 |
- type: precision_at_5
|
| 827 |
+
value: 8.895999999999999
|
| 828 |
- type: recall_at_1
|
| 829 |
+
value: 24.537
|
| 830 |
- type: recall_at_10
|
| 831 |
+
value: 44.324999999999996
|
| 832 |
- type: recall_at_100
|
| 833 |
+
value: 65.949
|
| 834 |
- type: recall_at_1000
|
| 835 |
+
value: 84.017
|
| 836 |
- type: recall_at_3
|
| 837 |
+
value: 33.857
|
| 838 |
- type: recall_at_5
|
| 839 |
+
value: 37.316
|
| 840 |
- task:
|
| 841 |
type: Retrieval
|
| 842 |
dataset:
|
|
|
|
| 847 |
revision: None
|
| 848 |
metrics:
|
| 849 |
- type: map_at_1
|
| 850 |
+
value: 17.122
|
| 851 |
- type: map_at_10
|
| 852 |
+
value: 24.32
|
| 853 |
- type: map_at_100
|
| 854 |
+
value: 25.338
|
| 855 |
- type: map_at_1000
|
| 856 |
+
value: 25.462
|
| 857 |
- type: map_at_3
|
| 858 |
+
value: 22.064
|
| 859 |
- type: map_at_5
|
| 860 |
+
value: 23.322000000000003
|
| 861 |
- type: mrr_at_1
|
| 862 |
+
value: 20.647
|
| 863 |
- type: mrr_at_10
|
| 864 |
+
value: 27.858
|
| 865 |
- type: mrr_at_100
|
| 866 |
+
value: 28.743999999999996
|
| 867 |
- type: mrr_at_1000
|
| 868 |
+
value: 28.819
|
| 869 |
- type: mrr_at_3
|
| 870 |
+
value: 25.769
|
| 871 |
- type: mrr_at_5
|
| 872 |
+
value: 26.964
|
| 873 |
- type: ndcg_at_1
|
| 874 |
+
value: 20.647
|
| 875 |
- type: ndcg_at_10
|
| 876 |
+
value: 28.849999999999998
|
| 877 |
- type: ndcg_at_100
|
| 878 |
+
value: 33.849000000000004
|
| 879 |
- type: ndcg_at_1000
|
| 880 |
+
value: 36.802
|
| 881 |
- type: ndcg_at_3
|
| 882 |
+
value: 24.799
|
| 883 |
- type: ndcg_at_5
|
| 884 |
+
value: 26.682
|
| 885 |
- type: precision_at_1
|
| 886 |
+
value: 20.647
|
| 887 |
- type: precision_at_10
|
| 888 |
+
value: 5.2170000000000005
|
| 889 |
- type: precision_at_100
|
| 890 |
+
value: 0.906
|
| 891 |
- type: precision_at_1000
|
| 892 |
+
value: 0.134
|
| 893 |
- type: precision_at_3
|
| 894 |
+
value: 11.769
|
| 895 |
- type: precision_at_5
|
| 896 |
+
value: 8.486
|
| 897 |
- type: recall_at_1
|
| 898 |
+
value: 17.122
|
| 899 |
- type: recall_at_10
|
| 900 |
+
value: 38.999
|
| 901 |
- type: recall_at_100
|
| 902 |
+
value: 61.467000000000006
|
| 903 |
- type: recall_at_1000
|
| 904 |
+
value: 82.716
|
| 905 |
- type: recall_at_3
|
| 906 |
+
value: 27.601
|
| 907 |
- type: recall_at_5
|
| 908 |
+
value: 32.471
|
| 909 |
- task:
|
| 910 |
type: Retrieval
|
| 911 |
dataset:
|
|
|
|
| 916 |
revision: None
|
| 917 |
metrics:
|
| 918 |
- type: map_at_1
|
| 919 |
+
value: 24.396
|
| 920 |
- type: map_at_10
|
| 921 |
+
value: 33.415
|
| 922 |
- type: map_at_100
|
| 923 |
+
value: 34.521
|
| 924 |
- type: map_at_1000
|
| 925 |
+
value: 34.631
|
| 926 |
- type: map_at_3
|
| 927 |
+
value: 30.703999999999997
|
| 928 |
- type: map_at_5
|
| 929 |
+
value: 32.166
|
| 930 |
- type: mrr_at_1
|
| 931 |
+
value: 28.825
|
| 932 |
- type: mrr_at_10
|
| 933 |
+
value: 37.397000000000006
|
| 934 |
- type: mrr_at_100
|
| 935 |
+
value: 38.286
|
| 936 |
- type: mrr_at_1000
|
| 937 |
+
value: 38.346000000000004
|
| 938 |
- type: mrr_at_3
|
| 939 |
+
value: 35.028
|
| 940 |
- type: mrr_at_5
|
| 941 |
+
value: 36.32
|
| 942 |
- type: ndcg_at_1
|
| 943 |
+
value: 28.825
|
| 944 |
- type: ndcg_at_10
|
| 945 |
+
value: 38.656
|
| 946 |
- type: ndcg_at_100
|
| 947 |
+
value: 43.856
|
| 948 |
- type: ndcg_at_1000
|
| 949 |
+
value: 46.31
|
| 950 |
- type: ndcg_at_3
|
| 951 |
+
value: 33.793
|
| 952 |
- type: ndcg_at_5
|
| 953 |
+
value: 35.909
|
| 954 |
- type: precision_at_1
|
| 955 |
+
value: 28.825
|
| 956 |
- type: precision_at_10
|
| 957 |
+
value: 6.567
|
| 958 |
- type: precision_at_100
|
| 959 |
+
value: 1.0330000000000001
|
| 960 |
- type: precision_at_1000
|
| 961 |
+
value: 0.135
|
| 962 |
- type: precision_at_3
|
| 963 |
+
value: 15.516
|
| 964 |
- type: precision_at_5
|
| 965 |
+
value: 10.914
|
| 966 |
- type: recall_at_1
|
| 967 |
+
value: 24.396
|
| 968 |
- type: recall_at_10
|
| 969 |
+
value: 50.747
|
| 970 |
- type: recall_at_100
|
| 971 |
+
value: 73.477
|
| 972 |
- type: recall_at_1000
|
| 973 |
+
value: 90.801
|
| 974 |
- type: recall_at_3
|
| 975 |
+
value: 37.1
|
| 976 |
- type: recall_at_5
|
| 977 |
+
value: 42.589
|
| 978 |
- task:
|
| 979 |
type: Retrieval
|
| 980 |
dataset:
|
|
|
|
| 985 |
revision: None
|
| 986 |
metrics:
|
| 987 |
- type: map_at_1
|
| 988 |
+
value: 25.072
|
| 989 |
- type: map_at_10
|
| 990 |
+
value: 34.307
|
| 991 |
- type: map_at_100
|
| 992 |
+
value: 35.725
|
| 993 |
- type: map_at_1000
|
| 994 |
+
value: 35.943999999999996
|
| 995 |
- type: map_at_3
|
| 996 |
+
value: 30.906
|
| 997 |
- type: map_at_5
|
| 998 |
+
value: 32.818000000000005
|
| 999 |
- type: mrr_at_1
|
| 1000 |
+
value: 29.644
|
| 1001 |
- type: mrr_at_10
|
| 1002 |
+
value: 38.673
|
| 1003 |
- type: mrr_at_100
|
| 1004 |
+
value: 39.459
|
| 1005 |
- type: mrr_at_1000
|
| 1006 |
+
value: 39.527
|
| 1007 |
- type: mrr_at_3
|
| 1008 |
+
value: 35.771
|
| 1009 |
- type: mrr_at_5
|
| 1010 |
+
value: 37.332
|
| 1011 |
- type: ndcg_at_1
|
| 1012 |
+
value: 29.644
|
| 1013 |
- type: ndcg_at_10
|
| 1014 |
+
value: 40.548
|
| 1015 |
- type: ndcg_at_100
|
| 1016 |
+
value: 45.678999999999995
|
| 1017 |
- type: ndcg_at_1000
|
| 1018 |
+
value: 48.488
|
| 1019 |
- type: ndcg_at_3
|
| 1020 |
+
value: 34.887
|
| 1021 |
- type: ndcg_at_5
|
| 1022 |
+
value: 37.543
|
| 1023 |
- type: precision_at_1
|
| 1024 |
+
value: 29.644
|
| 1025 |
- type: precision_at_10
|
| 1026 |
+
value: 7.688000000000001
|
| 1027 |
- type: precision_at_100
|
| 1028 |
+
value: 1.482
|
| 1029 |
- type: precision_at_1000
|
| 1030 |
+
value: 0.23600000000000002
|
| 1031 |
- type: precision_at_3
|
| 1032 |
+
value: 16.206
|
| 1033 |
- type: precision_at_5
|
| 1034 |
+
value: 12.016
|
| 1035 |
- type: recall_at_1
|
| 1036 |
+
value: 25.072
|
| 1037 |
- type: recall_at_10
|
| 1038 |
+
value: 53.478
|
| 1039 |
- type: recall_at_100
|
| 1040 |
+
value: 76.07300000000001
|
| 1041 |
- type: recall_at_1000
|
| 1042 |
+
value: 93.884
|
| 1043 |
- type: recall_at_3
|
| 1044 |
+
value: 37.583
|
| 1045 |
- type: recall_at_5
|
| 1046 |
+
value: 44.464
|
| 1047 |
- task:
|
| 1048 |
type: Retrieval
|
| 1049 |
dataset:
|
|
|
|
| 1054 |
revision: None
|
| 1055 |
metrics:
|
| 1056 |
- type: map_at_1
|
| 1057 |
+
value: 20.712
|
| 1058 |
- type: map_at_10
|
| 1059 |
+
value: 27.467999999999996
|
| 1060 |
- type: map_at_100
|
| 1061 |
+
value: 28.502
|
| 1062 |
- type: map_at_1000
|
| 1063 |
+
value: 28.610000000000003
|
| 1064 |
- type: map_at_3
|
| 1065 |
+
value: 24.887999999999998
|
| 1066 |
- type: map_at_5
|
| 1067 |
+
value: 26.273999999999997
|
| 1068 |
- type: mrr_at_1
|
| 1069 |
+
value: 22.736
|
| 1070 |
- type: mrr_at_10
|
| 1071 |
+
value: 29.553
|
| 1072 |
- type: mrr_at_100
|
| 1073 |
+
value: 30.485
|
| 1074 |
- type: mrr_at_1000
|
| 1075 |
+
value: 30.56
|
| 1076 |
- type: mrr_at_3
|
| 1077 |
+
value: 27.078999999999997
|
| 1078 |
- type: mrr_at_5
|
| 1079 |
+
value: 28.401
|
| 1080 |
- type: ndcg_at_1
|
| 1081 |
+
value: 22.736
|
| 1082 |
- type: ndcg_at_10
|
| 1083 |
+
value: 32.023
|
| 1084 |
- type: ndcg_at_100
|
| 1085 |
+
value: 37.158
|
| 1086 |
- type: ndcg_at_1000
|
| 1087 |
+
value: 39.823
|
| 1088 |
- type: ndcg_at_3
|
| 1089 |
+
value: 26.951999999999998
|
| 1090 |
- type: ndcg_at_5
|
| 1091 |
+
value: 29.281000000000002
|
| 1092 |
- type: precision_at_1
|
| 1093 |
+
value: 22.736
|
| 1094 |
- type: precision_at_10
|
| 1095 |
+
value: 5.213
|
| 1096 |
- type: precision_at_100
|
| 1097 |
+
value: 0.832
|
| 1098 |
- type: precision_at_1000
|
| 1099 |
value: 0.116
|
| 1100 |
- type: precision_at_3
|
| 1101 |
+
value: 11.459999999999999
|
| 1102 |
- type: precision_at_5
|
| 1103 |
+
value: 8.244
|
| 1104 |
- type: recall_at_1
|
| 1105 |
+
value: 20.712
|
| 1106 |
- type: recall_at_10
|
| 1107 |
+
value: 44.057
|
| 1108 |
- type: recall_at_100
|
| 1109 |
+
value: 67.944
|
| 1110 |
- type: recall_at_1000
|
| 1111 |
+
value: 87.925
|
| 1112 |
- type: recall_at_3
|
| 1113 |
+
value: 30.305
|
| 1114 |
- type: recall_at_5
|
| 1115 |
+
value: 36.071999999999996
|
| 1116 |
- task:
|
| 1117 |
type: Retrieval
|
| 1118 |
dataset:
|
|
|
|
| 1123 |
revision: None
|
| 1124 |
metrics:
|
| 1125 |
- type: map_at_1
|
| 1126 |
+
value: 10.181999999999999
|
| 1127 |
- type: map_at_10
|
| 1128 |
+
value: 16.66
|
| 1129 |
- type: map_at_100
|
| 1130 |
+
value: 18.273
|
| 1131 |
- type: map_at_1000
|
| 1132 |
+
value: 18.45
|
| 1133 |
- type: map_at_3
|
| 1134 |
+
value: 14.141
|
| 1135 |
- type: map_at_5
|
| 1136 |
+
value: 15.455
|
| 1137 |
- type: mrr_at_1
|
| 1138 |
+
value: 22.15
|
| 1139 |
- type: mrr_at_10
|
| 1140 |
+
value: 32.062000000000005
|
| 1141 |
- type: mrr_at_100
|
| 1142 |
+
value: 33.116
|
| 1143 |
- type: mrr_at_1000
|
| 1144 |
+
value: 33.168
|
| 1145 |
- type: mrr_at_3
|
| 1146 |
+
value: 28.827
|
| 1147 |
- type: mrr_at_5
|
| 1148 |
+
value: 30.892999999999997
|
| 1149 |
- type: ndcg_at_1
|
| 1150 |
+
value: 22.15
|
| 1151 |
- type: ndcg_at_10
|
| 1152 |
+
value: 23.532
|
| 1153 |
- type: ndcg_at_100
|
| 1154 |
+
value: 30.358
|
| 1155 |
- type: ndcg_at_1000
|
| 1156 |
+
value: 33.783
|
| 1157 |
- type: ndcg_at_3
|
| 1158 |
+
value: 19.222
|
| 1159 |
- type: ndcg_at_5
|
| 1160 |
+
value: 20.919999999999998
|
| 1161 |
- type: precision_at_1
|
| 1162 |
+
value: 22.15
|
| 1163 |
- type: precision_at_10
|
| 1164 |
+
value: 7.185999999999999
|
| 1165 |
- type: precision_at_100
|
| 1166 |
+
value: 1.433
|
| 1167 |
- type: precision_at_1000
|
| 1168 |
+
value: 0.207
|
| 1169 |
- type: precision_at_3
|
| 1170 |
+
value: 13.941
|
| 1171 |
- type: precision_at_5
|
| 1172 |
+
value: 10.906
|
| 1173 |
- type: recall_at_1
|
| 1174 |
+
value: 10.181999999999999
|
| 1175 |
- type: recall_at_10
|
| 1176 |
+
value: 28.104000000000003
|
| 1177 |
- type: recall_at_100
|
| 1178 |
+
value: 51.998999999999995
|
| 1179 |
- type: recall_at_1000
|
| 1180 |
+
value: 71.311
|
| 1181 |
- type: recall_at_3
|
| 1182 |
+
value: 17.698
|
| 1183 |
- type: recall_at_5
|
| 1184 |
+
value: 22.262999999999998
|
| 1185 |
- task:
|
| 1186 |
type: Retrieval
|
| 1187 |
dataset:
|
|
|
|
| 1192 |
revision: None
|
| 1193 |
metrics:
|
| 1194 |
- type: map_at_1
|
| 1195 |
+
value: 6.669
|
| 1196 |
- type: map_at_10
|
| 1197 |
+
value: 15.552
|
| 1198 |
- type: map_at_100
|
| 1199 |
+
value: 21.865000000000002
|
| 1200 |
- type: map_at_1000
|
| 1201 |
+
value: 23.268
|
| 1202 |
- type: map_at_3
|
| 1203 |
+
value: 11.309
|
| 1204 |
- type: map_at_5
|
| 1205 |
+
value: 13.084000000000001
|
| 1206 |
- type: mrr_at_1
|
| 1207 |
value: 55.50000000000001
|
| 1208 |
- type: mrr_at_10
|
| 1209 |
+
value: 66.46600000000001
|
| 1210 |
- type: mrr_at_100
|
| 1211 |
+
value: 66.944
|
| 1212 |
- type: mrr_at_1000
|
| 1213 |
+
value: 66.956
|
| 1214 |
- type: mrr_at_3
|
| 1215 |
+
value: 64.542
|
| 1216 |
- type: mrr_at_5
|
| 1217 |
+
value: 65.717
|
| 1218 |
- type: ndcg_at_1
|
| 1219 |
+
value: 44.75
|
| 1220 |
- type: ndcg_at_10
|
| 1221 |
+
value: 35.049
|
| 1222 |
- type: ndcg_at_100
|
| 1223 |
+
value: 39.073
|
| 1224 |
- type: ndcg_at_1000
|
| 1225 |
+
value: 46.208
|
| 1226 |
- type: ndcg_at_3
|
| 1227 |
+
value: 39.525
|
| 1228 |
- type: ndcg_at_5
|
| 1229 |
+
value: 37.156
|
| 1230 |
- type: precision_at_1
|
| 1231 |
value: 55.50000000000001
|
| 1232 |
- type: precision_at_10
|
| 1233 |
+
value: 27.800000000000004
|
| 1234 |
- type: precision_at_100
|
| 1235 |
+
value: 9.013
|
| 1236 |
- type: precision_at_1000
|
| 1237 |
+
value: 1.8800000000000001
|
| 1238 |
- type: precision_at_3
|
| 1239 |
+
value: 42.667
|
| 1240 |
- type: precision_at_5
|
| 1241 |
+
value: 36.0
|
| 1242 |
- type: recall_at_1
|
| 1243 |
+
value: 6.669
|
| 1244 |
- type: recall_at_10
|
| 1245 |
+
value: 21.811
|
| 1246 |
- type: recall_at_100
|
| 1247 |
+
value: 45.112
|
| 1248 |
- type: recall_at_1000
|
| 1249 |
+
value: 67.806
|
| 1250 |
- type: recall_at_3
|
| 1251 |
+
value: 13.373
|
| 1252 |
- type: recall_at_5
|
| 1253 |
+
value: 16.615
|
| 1254 |
- task:
|
| 1255 |
type: Classification
|
| 1256 |
dataset:
|
|
|
|
| 1261 |
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
|
| 1262 |
metrics:
|
| 1263 |
- type: accuracy
|
| 1264 |
+
value: 48.769999999999996
|
| 1265 |
- type: f1
|
| 1266 |
+
value: 42.91448356376592
|
| 1267 |
- task:
|
| 1268 |
type: Retrieval
|
| 1269 |
dataset:
|
|
|
|
| 1274 |
revision: None
|
| 1275 |
metrics:
|
| 1276 |
- type: map_at_1
|
| 1277 |
+
value: 54.013
|
| 1278 |
- type: map_at_10
|
| 1279 |
+
value: 66.239
|
| 1280 |
- type: map_at_100
|
| 1281 |
+
value: 66.62599999999999
|
| 1282 |
- type: map_at_1000
|
| 1283 |
+
value: 66.644
|
| 1284 |
- type: map_at_3
|
| 1285 |
+
value: 63.965
|
| 1286 |
- type: map_at_5
|
| 1287 |
+
value: 65.45400000000001
|
| 1288 |
- type: mrr_at_1
|
| 1289 |
+
value: 58.221000000000004
|
| 1290 |
- type: mrr_at_10
|
| 1291 |
+
value: 70.43700000000001
|
| 1292 |
- type: mrr_at_100
|
| 1293 |
+
value: 70.744
|
| 1294 |
- type: mrr_at_1000
|
| 1295 |
+
value: 70.75099999999999
|
| 1296 |
- type: mrr_at_3
|
| 1297 |
+
value: 68.284
|
| 1298 |
- type: mrr_at_5
|
| 1299 |
+
value: 69.721
|
| 1300 |
- type: ndcg_at_1
|
| 1301 |
+
value: 58.221000000000004
|
| 1302 |
- type: ndcg_at_10
|
| 1303 |
+
value: 72.327
|
| 1304 |
- type: ndcg_at_100
|
| 1305 |
+
value: 73.953
|
| 1306 |
- type: ndcg_at_1000
|
| 1307 |
+
value: 74.312
|
| 1308 |
- type: ndcg_at_3
|
| 1309 |
+
value: 68.062
|
| 1310 |
- type: ndcg_at_5
|
| 1311 |
+
value: 70.56400000000001
|
| 1312 |
- type: precision_at_1
|
| 1313 |
+
value: 58.221000000000004
|
| 1314 |
- type: precision_at_10
|
| 1315 |
+
value: 9.521
|
| 1316 |
- type: precision_at_100
|
| 1317 |
+
value: 1.045
|
| 1318 |
- type: precision_at_1000
|
| 1319 |
value: 0.109
|
| 1320 |
- type: precision_at_3
|
| 1321 |
+
value: 27.348
|
| 1322 |
- type: precision_at_5
|
| 1323 |
+
value: 17.794999999999998
|
| 1324 |
- type: recall_at_1
|
| 1325 |
+
value: 54.013
|
| 1326 |
- type: recall_at_10
|
| 1327 |
+
value: 86.957
|
| 1328 |
- type: recall_at_100
|
| 1329 |
+
value: 93.911
|
| 1330 |
- type: recall_at_1000
|
| 1331 |
+
value: 96.38
|
| 1332 |
- type: recall_at_3
|
| 1333 |
+
value: 75.555
|
| 1334 |
- type: recall_at_5
|
| 1335 |
+
value: 81.671
|
| 1336 |
- task:
|
| 1337 |
type: Retrieval
|
| 1338 |
dataset:
|
|
|
|
| 1343 |
revision: None
|
| 1344 |
metrics:
|
| 1345 |
- type: map_at_1
|
| 1346 |
+
value: 21.254
|
| 1347 |
- type: map_at_10
|
| 1348 |
+
value: 33.723
|
| 1349 |
- type: map_at_100
|
| 1350 |
+
value: 35.574
|
| 1351 |
- type: map_at_1000
|
| 1352 |
+
value: 35.730000000000004
|
| 1353 |
- type: map_at_3
|
| 1354 |
+
value: 29.473
|
| 1355 |
- type: map_at_5
|
| 1356 |
+
value: 31.543
|
| 1357 |
- type: mrr_at_1
|
| 1358 |
+
value: 41.358
|
| 1359 |
- type: mrr_at_10
|
| 1360 |
+
value: 49.498
|
| 1361 |
- type: mrr_at_100
|
| 1362 |
+
value: 50.275999999999996
|
| 1363 |
- type: mrr_at_1000
|
| 1364 |
+
value: 50.308
|
| 1365 |
- type: mrr_at_3
|
| 1366 |
+
value: 47.016000000000005
|
| 1367 |
- type: mrr_at_5
|
| 1368 |
+
value: 48.336
|
| 1369 |
- type: ndcg_at_1
|
| 1370 |
+
value: 41.358
|
| 1371 |
- type: ndcg_at_10
|
| 1372 |
+
value: 41.579
|
| 1373 |
- type: ndcg_at_100
|
| 1374 |
+
value: 48.455
|
| 1375 |
- type: ndcg_at_1000
|
| 1376 |
+
value: 51.165000000000006
|
| 1377 |
- type: ndcg_at_3
|
| 1378 |
+
value: 37.681
|
| 1379 |
- type: ndcg_at_5
|
| 1380 |
+
value: 38.49
|
| 1381 |
- type: precision_at_1
|
| 1382 |
+
value: 41.358
|
| 1383 |
- type: precision_at_10
|
| 1384 |
+
value: 11.543000000000001
|
| 1385 |
- type: precision_at_100
|
| 1386 |
+
value: 1.87
|
| 1387 |
- type: precision_at_1000
|
| 1388 |
+
value: 0.23600000000000002
|
| 1389 |
- type: precision_at_3
|
| 1390 |
+
value: 24.743000000000002
|
| 1391 |
- type: precision_at_5
|
| 1392 |
+
value: 17.994
|
| 1393 |
- type: recall_at_1
|
| 1394 |
+
value: 21.254
|
| 1395 |
- type: recall_at_10
|
| 1396 |
+
value: 48.698
|
| 1397 |
- type: recall_at_100
|
| 1398 |
+
value: 74.588
|
| 1399 |
- type: recall_at_1000
|
| 1400 |
+
value: 91.00200000000001
|
| 1401 |
- type: recall_at_3
|
| 1402 |
+
value: 33.939
|
| 1403 |
- type: recall_at_5
|
| 1404 |
+
value: 39.367000000000004
|
| 1405 |
- task:
|
| 1406 |
type: Retrieval
|
| 1407 |
dataset:
|
|
|
|
| 1412 |
revision: None
|
| 1413 |
metrics:
|
| 1414 |
- type: map_at_1
|
| 1415 |
+
value: 35.922
|
| 1416 |
- type: map_at_10
|
| 1417 |
+
value: 52.32599999999999
|
| 1418 |
- type: map_at_100
|
| 1419 |
+
value: 53.18000000000001
|
| 1420 |
- type: map_at_1000
|
| 1421 |
+
value: 53.245
|
| 1422 |
- type: map_at_3
|
| 1423 |
+
value: 49.294
|
| 1424 |
- type: map_at_5
|
| 1425 |
+
value: 51.202999999999996
|
| 1426 |
- type: mrr_at_1
|
| 1427 |
+
value: 71.843
|
| 1428 |
- type: mrr_at_10
|
| 1429 |
+
value: 78.24600000000001
|
| 1430 |
- type: mrr_at_100
|
| 1431 |
+
value: 78.515
|
| 1432 |
- type: mrr_at_1000
|
| 1433 |
+
value: 78.527
|
| 1434 |
- type: mrr_at_3
|
| 1435 |
+
value: 77.17500000000001
|
| 1436 |
- type: mrr_at_5
|
| 1437 |
+
value: 77.852
|
| 1438 |
- type: ndcg_at_1
|
| 1439 |
+
value: 71.843
|
| 1440 |
- type: ndcg_at_10
|
| 1441 |
+
value: 61.379
|
| 1442 |
- type: ndcg_at_100
|
| 1443 |
+
value: 64.535
|
| 1444 |
- type: ndcg_at_1000
|
| 1445 |
+
value: 65.888
|
| 1446 |
- type: ndcg_at_3
|
| 1447 |
+
value: 56.958
|
| 1448 |
- type: ndcg_at_5
|
| 1449 |
+
value: 59.434
|
| 1450 |
- type: precision_at_1
|
| 1451 |
+
value: 71.843
|
| 1452 |
- type: precision_at_10
|
| 1453 |
+
value: 12.686
|
| 1454 |
- type: precision_at_100
|
| 1455 |
+
value: 1.517
|
| 1456 |
- type: precision_at_1000
|
| 1457 |
+
value: 0.16999999999999998
|
| 1458 |
- type: precision_at_3
|
| 1459 |
+
value: 35.778
|
| 1460 |
- type: precision_at_5
|
| 1461 |
+
value: 23.422
|
| 1462 |
- type: recall_at_1
|
| 1463 |
+
value: 35.922
|
| 1464 |
- type: recall_at_10
|
| 1465 |
+
value: 63.43
|
| 1466 |
- type: recall_at_100
|
| 1467 |
+
value: 75.868
|
| 1468 |
- type: recall_at_1000
|
| 1469 |
+
value: 84.88900000000001
|
| 1470 |
- type: recall_at_3
|
| 1471 |
+
value: 53.666000000000004
|
| 1472 |
- type: recall_at_5
|
| 1473 |
+
value: 58.555
|
| 1474 |
- task:
|
| 1475 |
type: Classification
|
| 1476 |
dataset:
|
|
|
|
| 1481 |
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
|
| 1482 |
metrics:
|
| 1483 |
- type: accuracy
|
| 1484 |
+
value: 79.4408
|
| 1485 |
- type: ap
|
| 1486 |
+
value: 73.52820871620366
|
| 1487 |
- type: f1
|
| 1488 |
+
value: 79.36240238685001
|
| 1489 |
- task:
|
| 1490 |
type: Retrieval
|
| 1491 |
dataset:
|
|
|
|
| 1496 |
revision: None
|
| 1497 |
metrics:
|
| 1498 |
- type: map_at_1
|
| 1499 |
+
value: 21.826999999999998
|
| 1500 |
- type: map_at_10
|
| 1501 |
+
value: 34.04
|
| 1502 |
- type: map_at_100
|
| 1503 |
+
value: 35.226
|
| 1504 |
- type: map_at_1000
|
| 1505 |
+
value: 35.275
|
| 1506 |
- type: map_at_3
|
| 1507 |
+
value: 30.165999999999997
|
| 1508 |
- type: map_at_5
|
| 1509 |
+
value: 32.318000000000005
|
| 1510 |
- type: mrr_at_1
|
| 1511 |
+
value: 22.464000000000002
|
| 1512 |
- type: mrr_at_10
|
| 1513 |
+
value: 34.631
|
| 1514 |
- type: mrr_at_100
|
| 1515 |
+
value: 35.752
|
| 1516 |
- type: mrr_at_1000
|
| 1517 |
+
value: 35.795
|
| 1518 |
- type: mrr_at_3
|
| 1519 |
+
value: 30.798
|
| 1520 |
- type: mrr_at_5
|
| 1521 |
+
value: 32.946999999999996
|
| 1522 |
- type: ndcg_at_1
|
| 1523 |
+
value: 22.464000000000002
|
| 1524 |
- type: ndcg_at_10
|
| 1525 |
+
value: 40.919
|
| 1526 |
- type: ndcg_at_100
|
| 1527 |
+
value: 46.632
|
| 1528 |
- type: ndcg_at_1000
|
| 1529 |
+
value: 47.833
|
| 1530 |
- type: ndcg_at_3
|
| 1531 |
+
value: 32.992
|
| 1532 |
- type: ndcg_at_5
|
| 1533 |
+
value: 36.834
|
| 1534 |
- type: precision_at_1
|
| 1535 |
+
value: 22.464000000000002
|
| 1536 |
- type: precision_at_10
|
| 1537 |
+
value: 6.494
|
| 1538 |
- type: precision_at_100
|
| 1539 |
+
value: 0.9369999999999999
|
| 1540 |
- type: precision_at_1000
|
| 1541 |
value: 0.104
|
| 1542 |
- type: precision_at_3
|
| 1543 |
+
value: 14.021
|
| 1544 |
- type: precision_at_5
|
| 1545 |
+
value: 10.347000000000001
|
| 1546 |
- type: recall_at_1
|
| 1547 |
+
value: 21.826999999999998
|
| 1548 |
- type: recall_at_10
|
| 1549 |
+
value: 62.132
|
| 1550 |
- type: recall_at_100
|
| 1551 |
+
value: 88.55199999999999
|
| 1552 |
- type: recall_at_1000
|
| 1553 |
+
value: 97.707
|
| 1554 |
- type: recall_at_3
|
| 1555 |
+
value: 40.541
|
| 1556 |
- type: recall_at_5
|
| 1557 |
+
value: 49.739
|
| 1558 |
- task:
|
| 1559 |
type: Classification
|
| 1560 |
dataset:
|
|
|
|
| 1565 |
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
|
| 1566 |
metrics:
|
| 1567 |
- type: accuracy
|
| 1568 |
+
value: 95.68399452804377
|
| 1569 |
- type: f1
|
| 1570 |
+
value: 95.25490609832268
|
| 1571 |
- task:
|
| 1572 |
type: Classification
|
| 1573 |
dataset:
|
|
|
|
| 1578 |
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
|
| 1579 |
metrics:
|
| 1580 |
- type: accuracy
|
| 1581 |
+
value: 83.15321477428182
|
| 1582 |
- type: f1
|
| 1583 |
+
value: 60.35476439087966
|
| 1584 |
- task:
|
| 1585 |
type: Classification
|
| 1586 |
dataset:
|
|
|
|
| 1591 |
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
|
| 1592 |
metrics:
|
| 1593 |
- type: accuracy
|
| 1594 |
+
value: 71.92669804976462
|
| 1595 |
- type: f1
|
| 1596 |
+
value: 69.22815107207565
|
| 1597 |
- task:
|
| 1598 |
type: Classification
|
| 1599 |
dataset:
|
|
|
|
| 1604 |
revision: 7d571f92784cd94a019292a1f45445077d0ef634
|
| 1605 |
metrics:
|
| 1606 |
- type: accuracy
|
| 1607 |
+
value: 74.4855413584398
|
| 1608 |
- type: f1
|
| 1609 |
+
value: 72.92107516103387
|
| 1610 |
- task:
|
| 1611 |
type: Clustering
|
| 1612 |
dataset:
|
|
|
|
| 1617 |
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
|
| 1618 |
metrics:
|
| 1619 |
- type: v_measure
|
| 1620 |
+
value: 32.412679360205544
|
| 1621 |
- task:
|
| 1622 |
type: Clustering
|
| 1623 |
dataset:
|
|
|
|
| 1628 |
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
|
| 1629 |
metrics:
|
| 1630 |
- type: v_measure
|
| 1631 |
+
value: 28.09211869875204
|
| 1632 |
- task:
|
| 1633 |
type: Reranking
|
| 1634 |
dataset:
|
|
|
|
| 1639 |
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
|
| 1640 |
metrics:
|
| 1641 |
- type: map
|
| 1642 |
+
value: 30.540919056982545
|
| 1643 |
- type: mrr
|
| 1644 |
+
value: 31.529904607063536
|
| 1645 |
- task:
|
| 1646 |
type: Retrieval
|
| 1647 |
dataset:
|
|
|
|
| 1652 |
revision: None
|
| 1653 |
metrics:
|
| 1654 |
- type: map_at_1
|
| 1655 |
+
value: 5.745
|
| 1656 |
- type: map_at_10
|
| 1657 |
+
value: 12.013
|
| 1658 |
- type: map_at_100
|
| 1659 |
+
value: 15.040000000000001
|
| 1660 |
- type: map_at_1000
|
| 1661 |
+
value: 16.427
|
| 1662 |
- type: map_at_3
|
| 1663 |
+
value: 8.841000000000001
|
| 1664 |
- type: map_at_5
|
| 1665 |
+
value: 10.289
|
| 1666 |
- type: mrr_at_1
|
| 1667 |
+
value: 45.201
|
| 1668 |
- type: mrr_at_10
|
| 1669 |
+
value: 53.483999999999995
|
| 1670 |
- type: mrr_at_100
|
| 1671 |
+
value: 54.20700000000001
|
| 1672 |
- type: mrr_at_1000
|
| 1673 |
+
value: 54.252
|
| 1674 |
- type: mrr_at_3
|
| 1675 |
+
value: 51.29
|
| 1676 |
- type: mrr_at_5
|
| 1677 |
+
value: 52.73
|
| 1678 |
- type: ndcg_at_1
|
| 1679 |
value: 43.808
|
| 1680 |
- type: ndcg_at_10
|
| 1681 |
+
value: 32.445
|
| 1682 |
- type: ndcg_at_100
|
| 1683 |
+
value: 30.031000000000002
|
| 1684 |
- type: ndcg_at_1000
|
| 1685 |
+
value: 39.007
|
| 1686 |
- type: ndcg_at_3
|
| 1687 |
+
value: 37.204
|
| 1688 |
- type: ndcg_at_5
|
| 1689 |
+
value: 35.07
|
| 1690 |
- type: precision_at_1
|
| 1691 |
+
value: 45.201
|
| 1692 |
- type: precision_at_10
|
| 1693 |
+
value: 23.684
|
| 1694 |
- type: precision_at_100
|
| 1695 |
+
value: 7.600999999999999
|
| 1696 |
- type: precision_at_1000
|
| 1697 |
+
value: 2.043
|
| 1698 |
- type: precision_at_3
|
| 1699 |
+
value: 33.953
|
| 1700 |
- type: precision_at_5
|
| 1701 |
+
value: 29.412
|
| 1702 |
- type: recall_at_1
|
| 1703 |
+
value: 5.745
|
| 1704 |
- type: recall_at_10
|
| 1705 |
+
value: 16.168
|
| 1706 |
- type: recall_at_100
|
| 1707 |
+
value: 30.875999999999998
|
| 1708 |
- type: recall_at_1000
|
| 1709 |
+
value: 62.686
|
| 1710 |
- type: recall_at_3
|
| 1711 |
+
value: 9.75
|
| 1712 |
- type: recall_at_5
|
| 1713 |
+
value: 12.413
|
| 1714 |
- task:
|
| 1715 |
type: Retrieval
|
| 1716 |
dataset:
|
|
|
|
| 1721 |
revision: None
|
| 1722 |
metrics:
|
| 1723 |
- type: map_at_1
|
| 1724 |
+
value: 37.828
|
| 1725 |
- type: map_at_10
|
| 1726 |
+
value: 53.239000000000004
|
| 1727 |
- type: map_at_100
|
| 1728 |
+
value: 54.035999999999994
|
| 1729 |
- type: map_at_1000
|
| 1730 |
+
value: 54.067
|
| 1731 |
- type: map_at_3
|
| 1732 |
+
value: 49.289
|
| 1733 |
- type: map_at_5
|
| 1734 |
+
value: 51.784
|
| 1735 |
- type: mrr_at_1
|
| 1736 |
+
value: 42.497
|
| 1737 |
- type: mrr_at_10
|
| 1738 |
+
value: 55.916999999999994
|
| 1739 |
- type: mrr_at_100
|
| 1740 |
+
value: 56.495
|
| 1741 |
- type: mrr_at_1000
|
| 1742 |
+
value: 56.516999999999996
|
| 1743 |
- type: mrr_at_3
|
| 1744 |
+
value: 52.800000000000004
|
| 1745 |
- type: mrr_at_5
|
| 1746 |
+
value: 54.722
|
| 1747 |
- type: ndcg_at_1
|
| 1748 |
+
value: 42.468
|
| 1749 |
- type: ndcg_at_10
|
| 1750 |
+
value: 60.437
|
| 1751 |
- type: ndcg_at_100
|
| 1752 |
+
value: 63.731
|
| 1753 |
- type: ndcg_at_1000
|
| 1754 |
+
value: 64.41799999999999
|
| 1755 |
- type: ndcg_at_3
|
| 1756 |
+
value: 53.230999999999995
|
| 1757 |
- type: ndcg_at_5
|
| 1758 |
+
value: 57.26
|
| 1759 |
- type: precision_at_1
|
| 1760 |
+
value: 42.468
|
| 1761 |
+
- type: precision_at_10
|
| 1762 |
+
value: 9.47
|
| 1763 |
- type: precision_at_100
|
| 1764 |
+
value: 1.1360000000000001
|
| 1765 |
- type: precision_at_1000
|
| 1766 |
value: 0.12
|
| 1767 |
- type: precision_at_3
|
| 1768 |
+
value: 23.724999999999998
|
| 1769 |
- type: precision_at_5
|
| 1770 |
+
value: 16.593
|
| 1771 |
- type: recall_at_1
|
| 1772 |
+
value: 37.828
|
| 1773 |
- type: recall_at_10
|
| 1774 |
+
value: 79.538
|
| 1775 |
- type: recall_at_100
|
| 1776 |
+
value: 93.646
|
| 1777 |
- type: recall_at_1000
|
| 1778 |
+
value: 98.72999999999999
|
| 1779 |
- type: recall_at_3
|
| 1780 |
+
value: 61.134
|
| 1781 |
- type: recall_at_5
|
| 1782 |
+
value: 70.377
|
| 1783 |
- task:
|
| 1784 |
type: Retrieval
|
| 1785 |
dataset:
|
|
|
|
| 1790 |
revision: None
|
| 1791 |
metrics:
|
| 1792 |
- type: map_at_1
|
| 1793 |
+
value: 70.548
|
| 1794 |
- type: map_at_10
|
| 1795 |
+
value: 84.466
|
| 1796 |
- type: map_at_100
|
| 1797 |
+
value: 85.10600000000001
|
| 1798 |
- type: map_at_1000
|
| 1799 |
+
value: 85.123
|
| 1800 |
- type: map_at_3
|
| 1801 |
+
value: 81.57600000000001
|
| 1802 |
- type: map_at_5
|
| 1803 |
+
value: 83.399
|
| 1804 |
- type: mrr_at_1
|
| 1805 |
+
value: 81.24
|
| 1806 |
- type: mrr_at_10
|
| 1807 |
+
value: 87.457
|
| 1808 |
- type: mrr_at_100
|
| 1809 |
+
value: 87.574
|
| 1810 |
- type: mrr_at_1000
|
| 1811 |
+
value: 87.575
|
| 1812 |
- type: mrr_at_3
|
| 1813 |
+
value: 86.507
|
| 1814 |
- type: mrr_at_5
|
| 1815 |
+
value: 87.205
|
| 1816 |
- type: ndcg_at_1
|
| 1817 |
+
value: 81.25
|
| 1818 |
- type: ndcg_at_10
|
| 1819 |
+
value: 88.203
|
| 1820 |
- type: ndcg_at_100
|
| 1821 |
+
value: 89.457
|
| 1822 |
- type: ndcg_at_1000
|
| 1823 |
+
value: 89.563
|
| 1824 |
- type: ndcg_at_3
|
| 1825 |
+
value: 85.465
|
| 1826 |
- type: ndcg_at_5
|
| 1827 |
+
value: 87.007
|
| 1828 |
- type: precision_at_1
|
| 1829 |
+
value: 81.25
|
| 1830 |
- type: precision_at_10
|
| 1831 |
+
value: 13.373
|
| 1832 |
- type: precision_at_100
|
| 1833 |
+
value: 1.5270000000000001
|
| 1834 |
- type: precision_at_1000
|
| 1835 |
value: 0.157
|
| 1836 |
- type: precision_at_3
|
| 1837 |
+
value: 37.417
|
| 1838 |
- type: precision_at_5
|
| 1839 |
+
value: 24.556
|
| 1840 |
- type: recall_at_1
|
| 1841 |
+
value: 70.548
|
| 1842 |
- type: recall_at_10
|
| 1843 |
+
value: 95.208
|
| 1844 |
- type: recall_at_100
|
| 1845 |
+
value: 99.514
|
| 1846 |
- type: recall_at_1000
|
| 1847 |
+
value: 99.988
|
| 1848 |
- type: recall_at_3
|
| 1849 |
+
value: 87.214
|
| 1850 |
- type: recall_at_5
|
| 1851 |
+
value: 91.696
|
| 1852 |
- task:
|
| 1853 |
type: Clustering
|
| 1854 |
dataset:
|
|
|
|
| 1859 |
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
|
| 1860 |
metrics:
|
| 1861 |
- type: v_measure
|
| 1862 |
+
value: 53.04822095496839
|
| 1863 |
- task:
|
| 1864 |
type: Clustering
|
| 1865 |
dataset:
|
|
|
|
| 1870 |
revision: 282350215ef01743dc01b456c7f5241fa8937f16
|
| 1871 |
metrics:
|
| 1872 |
- type: v_measure
|
| 1873 |
+
value: 60.30778476474675
|
| 1874 |
- task:
|
| 1875 |
type: Retrieval
|
| 1876 |
dataset:
|
|
|
|
| 1881 |
revision: None
|
| 1882 |
metrics:
|
| 1883 |
- type: map_at_1
|
| 1884 |
+
value: 4.692
|
| 1885 |
- type: map_at_10
|
| 1886 |
+
value: 11.766
|
| 1887 |
- type: map_at_100
|
| 1888 |
+
value: 13.904
|
| 1889 |
- type: map_at_1000
|
| 1890 |
+
value: 14.216999999999999
|
| 1891 |
- type: map_at_3
|
| 1892 |
+
value: 8.245
|
| 1893 |
- type: map_at_5
|
| 1894 |
+
value: 9.92
|
| 1895 |
- type: mrr_at_1
|
| 1896 |
+
value: 23.0
|
| 1897 |
- type: mrr_at_10
|
| 1898 |
+
value: 33.78
|
| 1899 |
- type: mrr_at_100
|
| 1900 |
+
value: 34.922
|
| 1901 |
- type: mrr_at_1000
|
| 1902 |
+
value: 34.973
|
| 1903 |
- type: mrr_at_3
|
| 1904 |
+
value: 30.2
|
| 1905 |
- type: mrr_at_5
|
| 1906 |
+
value: 32.565
|
| 1907 |
- type: ndcg_at_1
|
| 1908 |
+
value: 23.0
|
| 1909 |
- type: ndcg_at_10
|
| 1910 |
+
value: 19.863
|
| 1911 |
- type: ndcg_at_100
|
| 1912 |
+
value: 28.141
|
| 1913 |
- type: ndcg_at_1000
|
| 1914 |
+
value: 33.549
|
| 1915 |
- type: ndcg_at_3
|
| 1916 |
+
value: 18.434
|
| 1917 |
- type: ndcg_at_5
|
| 1918 |
+
value: 16.384
|
| 1919 |
- type: precision_at_1
|
| 1920 |
+
value: 23.0
|
| 1921 |
- type: precision_at_10
|
| 1922 |
value: 10.39
|
| 1923 |
- type: precision_at_100
|
| 1924 |
+
value: 2.235
|
| 1925 |
- type: precision_at_1000
|
| 1926 |
value: 0.35300000000000004
|
| 1927 |
- type: precision_at_3
|
| 1928 |
+
value: 17.133000000000003
|
| 1929 |
- type: precision_at_5
|
| 1930 |
+
value: 14.44
|
| 1931 |
- type: recall_at_1
|
| 1932 |
+
value: 4.692
|
| 1933 |
- type: recall_at_10
|
| 1934 |
+
value: 21.025
|
| 1935 |
- type: recall_at_100
|
| 1936 |
+
value: 45.324999999999996
|
| 1937 |
- type: recall_at_1000
|
| 1938 |
+
value: 71.675
|
| 1939 |
- type: recall_at_3
|
| 1940 |
+
value: 10.440000000000001
|
| 1941 |
- type: recall_at_5
|
| 1942 |
+
value: 14.64
|
| 1943 |
- task:
|
| 1944 |
type: STS
|
| 1945 |
dataset:
|
|
|
|
| 1950 |
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
|
| 1951 |
metrics:
|
| 1952 |
- type: cos_sim_pearson
|
| 1953 |
+
value: 84.96178184892842
|
| 1954 |
- type: cos_sim_spearman
|
| 1955 |
+
value: 79.6487740813199
|
| 1956 |
- type: euclidean_pearson
|
| 1957 |
+
value: 82.06661161625023
|
| 1958 |
- type: euclidean_spearman
|
| 1959 |
+
value: 79.64876769031183
|
| 1960 |
- type: manhattan_pearson
|
| 1961 |
+
value: 82.07061164575131
|
| 1962 |
- type: manhattan_spearman
|
| 1963 |
+
value: 79.65197039464537
|
| 1964 |
- task:
|
| 1965 |
type: STS
|
| 1966 |
dataset:
|
|
|
|
| 1971 |
revision: a0d554a64d88156834ff5ae9920b964011b16384
|
| 1972 |
metrics:
|
| 1973 |
- type: cos_sim_pearson
|
| 1974 |
+
value: 84.15305604100027
|
| 1975 |
- type: cos_sim_spearman
|
| 1976 |
+
value: 74.27447427941591
|
| 1977 |
- type: euclidean_pearson
|
| 1978 |
+
value: 80.52737337565307
|
| 1979 |
- type: euclidean_spearman
|
| 1980 |
+
value: 74.27416077132192
|
| 1981 |
- type: manhattan_pearson
|
| 1982 |
+
value: 80.53728571140387
|
| 1983 |
- type: manhattan_spearman
|
| 1984 |
+
value: 74.28853605753457
|
| 1985 |
- task:
|
| 1986 |
type: STS
|
| 1987 |
dataset:
|
|
|
|
| 1992 |
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
|
| 1993 |
metrics:
|
| 1994 |
- type: cos_sim_pearson
|
| 1995 |
+
value: 83.44386080639279
|
| 1996 |
- type: cos_sim_spearman
|
| 1997 |
+
value: 84.17947648159536
|
| 1998 |
- type: euclidean_pearson
|
| 1999 |
+
value: 83.34145388129387
|
| 2000 |
- type: euclidean_spearman
|
| 2001 |
+
value: 84.17947648159536
|
| 2002 |
- type: manhattan_pearson
|
| 2003 |
+
value: 83.30699061927966
|
| 2004 |
- type: manhattan_spearman
|
| 2005 |
+
value: 84.18125737380451
|
| 2006 |
- task:
|
| 2007 |
type: STS
|
| 2008 |
dataset:
|
|
|
|
| 2013 |
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
|
| 2014 |
metrics:
|
| 2015 |
- type: cos_sim_pearson
|
| 2016 |
+
value: 81.57392220985612
|
| 2017 |
- type: cos_sim_spearman
|
| 2018 |
+
value: 78.80745014464101
|
| 2019 |
- type: euclidean_pearson
|
| 2020 |
+
value: 80.01660371487199
|
| 2021 |
- type: euclidean_spearman
|
| 2022 |
+
value: 78.80741240102256
|
| 2023 |
- type: manhattan_pearson
|
| 2024 |
+
value: 79.96810779507953
|
| 2025 |
- type: manhattan_spearman
|
| 2026 |
+
value: 78.75600400119448
|
| 2027 |
- task:
|
| 2028 |
type: STS
|
| 2029 |
dataset:
|
|
|
|
| 2034 |
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
|
| 2035 |
metrics:
|
| 2036 |
- type: cos_sim_pearson
|
| 2037 |
+
value: 86.85421063026625
|
| 2038 |
- type: cos_sim_spearman
|
| 2039 |
+
value: 87.55320285299192
|
| 2040 |
- type: euclidean_pearson
|
| 2041 |
+
value: 86.69750143323517
|
| 2042 |
- type: euclidean_spearman
|
| 2043 |
+
value: 87.55320284326378
|
| 2044 |
- type: manhattan_pearson
|
| 2045 |
+
value: 86.63379169960379
|
| 2046 |
- type: manhattan_spearman
|
| 2047 |
+
value: 87.4815029877984
|
| 2048 |
- task:
|
| 2049 |
type: STS
|
| 2050 |
dataset:
|
|
|
|
| 2055 |
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
|
| 2056 |
metrics:
|
| 2057 |
- type: cos_sim_pearson
|
| 2058 |
+
value: 84.31314130411842
|
| 2059 |
- type: cos_sim_spearman
|
| 2060 |
+
value: 85.3489588181433
|
| 2061 |
- type: euclidean_pearson
|
| 2062 |
+
value: 84.13240933463535
|
| 2063 |
- type: euclidean_spearman
|
| 2064 |
+
value: 85.34902871403281
|
| 2065 |
- type: manhattan_pearson
|
| 2066 |
+
value: 84.01183086503559
|
| 2067 |
- type: manhattan_spearman
|
| 2068 |
+
value: 85.19316703166102
|
| 2069 |
- task:
|
| 2070 |
type: STS
|
| 2071 |
dataset:
|
|
|
|
| 2076 |
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
|
| 2077 |
metrics:
|
| 2078 |
- type: cos_sim_pearson
|
| 2079 |
+
value: 89.09979781689536
|
| 2080 |
- type: cos_sim_spearman
|
| 2081 |
+
value: 88.87813323759015
|
| 2082 |
- type: euclidean_pearson
|
| 2083 |
+
value: 88.65413031123792
|
| 2084 |
- type: euclidean_spearman
|
| 2085 |
+
value: 88.87813323759015
|
| 2086 |
- type: manhattan_pearson
|
| 2087 |
+
value: 88.61818758256024
|
| 2088 |
- type: manhattan_spearman
|
| 2089 |
+
value: 88.81044100494604
|
| 2090 |
- task:
|
| 2091 |
type: STS
|
| 2092 |
dataset:
|
|
|
|
| 2097 |
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
|
| 2098 |
metrics:
|
| 2099 |
- type: cos_sim_pearson
|
| 2100 |
+
value: 62.30693258111531
|
| 2101 |
- type: cos_sim_spearman
|
| 2102 |
+
value: 62.195516523251946
|
| 2103 |
- type: euclidean_pearson
|
| 2104 |
+
value: 62.951283701049476
|
| 2105 |
- type: euclidean_spearman
|
| 2106 |
+
value: 62.195516523251946
|
| 2107 |
- type: manhattan_pearson
|
| 2108 |
+
value: 63.068322281439535
|
| 2109 |
- type: manhattan_spearman
|
| 2110 |
+
value: 62.10621171028406
|
| 2111 |
- task:
|
| 2112 |
type: STS
|
| 2113 |
dataset:
|
|
|
|
| 2118 |
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
|
| 2119 |
metrics:
|
| 2120 |
- type: cos_sim_pearson
|
| 2121 |
+
value: 84.27092833763909
|
| 2122 |
- type: cos_sim_spearman
|
| 2123 |
+
value: 84.84429717949759
|
| 2124 |
- type: euclidean_pearson
|
| 2125 |
+
value: 84.8516966060792
|
| 2126 |
- type: euclidean_spearman
|
| 2127 |
+
value: 84.84429717949759
|
| 2128 |
- type: manhattan_pearson
|
| 2129 |
+
value: 84.82203139242881
|
| 2130 |
- type: manhattan_spearman
|
| 2131 |
+
value: 84.8358503952945
|
| 2132 |
- task:
|
| 2133 |
type: Reranking
|
| 2134 |
dataset:
|
|
|
|
| 2139 |
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
|
| 2140 |
metrics:
|
| 2141 |
- type: map
|
| 2142 |
+
value: 83.10290863981409
|
| 2143 |
- type: mrr
|
| 2144 |
+
value: 95.31168450286097
|
| 2145 |
- task:
|
| 2146 |
type: Retrieval
|
| 2147 |
dataset:
|
|
|
|
| 2152 |
revision: None
|
| 2153 |
metrics:
|
| 2154 |
- type: map_at_1
|
| 2155 |
+
value: 52.161
|
| 2156 |
- type: map_at_10
|
| 2157 |
+
value: 62.138000000000005
|
| 2158 |
- type: map_at_100
|
| 2159 |
+
value: 62.769
|
| 2160 |
- type: map_at_1000
|
| 2161 |
+
value: 62.812
|
| 2162 |
- type: map_at_3
|
| 2163 |
+
value: 59.111000000000004
|
| 2164 |
- type: map_at_5
|
| 2165 |
+
value: 60.995999999999995
|
| 2166 |
- type: mrr_at_1
|
| 2167 |
value: 55.333
|
| 2168 |
- type: mrr_at_10
|
| 2169 |
+
value: 63.504000000000005
|
| 2170 |
- type: mrr_at_100
|
| 2171 |
+
value: 64.036
|
| 2172 |
- type: mrr_at_1000
|
| 2173 |
+
value: 64.08
|
| 2174 |
- type: mrr_at_3
|
| 2175 |
+
value: 61.278
|
| 2176 |
- type: mrr_at_5
|
| 2177 |
+
value: 62.778
|
| 2178 |
- type: ndcg_at_1
|
| 2179 |
value: 55.333
|
| 2180 |
- type: ndcg_at_10
|
| 2181 |
+
value: 66.678
|
| 2182 |
- type: ndcg_at_100
|
| 2183 |
+
value: 69.415
|
| 2184 |
- type: ndcg_at_1000
|
| 2185 |
+
value: 70.453
|
| 2186 |
- type: ndcg_at_3
|
| 2187 |
+
value: 61.755
|
| 2188 |
- type: ndcg_at_5
|
| 2189 |
+
value: 64.546
|
| 2190 |
- type: precision_at_1
|
| 2191 |
value: 55.333
|
| 2192 |
- type: precision_at_10
|
| 2193 |
+
value: 9.033
|
| 2194 |
- type: precision_at_100
|
| 2195 |
+
value: 1.043
|
| 2196 |
- type: precision_at_1000
|
| 2197 |
value: 0.11199999999999999
|
| 2198 |
- type: precision_at_3
|
| 2199 |
+
value: 24.221999999999998
|
| 2200 |
- type: precision_at_5
|
| 2201 |
value: 16.333000000000002
|
| 2202 |
- type: recall_at_1
|
| 2203 |
+
value: 52.161
|
| 2204 |
- type: recall_at_10
|
| 2205 |
+
value: 79.156
|
| 2206 |
- type: recall_at_100
|
| 2207 |
+
value: 91.333
|
| 2208 |
- type: recall_at_1000
|
| 2209 |
value: 99.333
|
| 2210 |
- type: recall_at_3
|
| 2211 |
+
value: 66.43299999999999
|
| 2212 |
- type: recall_at_5
|
| 2213 |
+
value: 73.272
|
| 2214 |
- task:
|
| 2215 |
type: PairClassification
|
| 2216 |
dataset:
|
|
|
|
| 2221 |
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
|
| 2222 |
metrics:
|
| 2223 |
- type: cos_sim_accuracy
|
| 2224 |
+
value: 99.81287128712871
|
| 2225 |
- type: cos_sim_ap
|
| 2226 |
+
value: 95.30034785910676
|
| 2227 |
- type: cos_sim_f1
|
| 2228 |
+
value: 90.28629856850716
|
| 2229 |
- type: cos_sim_precision
|
| 2230 |
+
value: 92.36401673640168
|
| 2231 |
- type: cos_sim_recall
|
| 2232 |
+
value: 88.3
|
| 2233 |
- type: dot_accuracy
|
| 2234 |
+
value: 99.81287128712871
|
| 2235 |
- type: dot_ap
|
| 2236 |
+
value: 95.30034785910676
|
| 2237 |
- type: dot_f1
|
| 2238 |
+
value: 90.28629856850716
|
| 2239 |
- type: dot_precision
|
| 2240 |
+
value: 92.36401673640168
|
| 2241 |
- type: dot_recall
|
| 2242 |
+
value: 88.3
|
| 2243 |
- type: euclidean_accuracy
|
| 2244 |
+
value: 99.81287128712871
|
| 2245 |
- type: euclidean_ap
|
| 2246 |
+
value: 95.30034785910676
|
| 2247 |
- type: euclidean_f1
|
| 2248 |
+
value: 90.28629856850716
|
| 2249 |
- type: euclidean_precision
|
| 2250 |
+
value: 92.36401673640168
|
| 2251 |
- type: euclidean_recall
|
| 2252 |
+
value: 88.3
|
| 2253 |
- type: manhattan_accuracy
|
| 2254 |
+
value: 99.80990099009901
|
| 2255 |
- type: manhattan_ap
|
| 2256 |
+
value: 95.26880751950654
|
| 2257 |
- type: manhattan_f1
|
| 2258 |
+
value: 90.22177419354838
|
| 2259 |
- type: manhattan_precision
|
| 2260 |
+
value: 90.95528455284553
|
| 2261 |
- type: manhattan_recall
|
| 2262 |
+
value: 89.5
|
| 2263 |
- type: max_accuracy
|
| 2264 |
+
value: 99.81287128712871
|
| 2265 |
- type: max_ap
|
| 2266 |
+
value: 95.30034785910676
|
| 2267 |
- type: max_f1
|
| 2268 |
+
value: 90.28629856850716
|
| 2269 |
- task:
|
| 2270 |
type: Clustering
|
| 2271 |
dataset:
|
|
|
|
| 2276 |
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
|
| 2277 |
metrics:
|
| 2278 |
- type: v_measure
|
| 2279 |
+
value: 58.518662504351184
|
| 2280 |
- task:
|
| 2281 |
type: Clustering
|
| 2282 |
dataset:
|
|
|
|
| 2287 |
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
|
| 2288 |
metrics:
|
| 2289 |
- type: v_measure
|
| 2290 |
+
value: 34.96168178378587
|
| 2291 |
- task:
|
| 2292 |
type: Reranking
|
| 2293 |
dataset:
|
|
|
|
| 2298 |
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
|
| 2299 |
metrics:
|
| 2300 |
- type: map
|
| 2301 |
+
value: 52.04862593471896
|
| 2302 |
- type: mrr
|
| 2303 |
+
value: 52.97238402936932
|
| 2304 |
- task:
|
| 2305 |
type: Summarization
|
| 2306 |
dataset:
|
|
|
|
| 2311 |
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
|
| 2312 |
metrics:
|
| 2313 |
- type: cos_sim_pearson
|
| 2314 |
+
value: 30.092545236479946
|
| 2315 |
- type: cos_sim_spearman
|
| 2316 |
+
value: 31.599851000175498
|
| 2317 |
- type: dot_pearson
|
| 2318 |
+
value: 30.092542723901676
|
| 2319 |
- type: dot_spearman
|
| 2320 |
+
value: 31.599851000175498
|
| 2321 |
- task:
|
| 2322 |
type: Retrieval
|
| 2323 |
dataset:
|
|
|
|
| 2328 |
revision: None
|
| 2329 |
metrics:
|
| 2330 |
- type: map_at_1
|
| 2331 |
+
value: 0.189
|
| 2332 |
- type: map_at_10
|
| 2333 |
+
value: 1.662
|
| 2334 |
- type: map_at_100
|
| 2335 |
+
value: 9.384
|
| 2336 |
- type: map_at_1000
|
| 2337 |
+
value: 22.669
|
| 2338 |
- type: map_at_3
|
| 2339 |
+
value: 0.5559999999999999
|
| 2340 |
- type: map_at_5
|
| 2341 |
+
value: 0.9039999999999999
|
| 2342 |
- type: mrr_at_1
|
| 2343 |
+
value: 68.0
|
| 2344 |
- type: mrr_at_10
|
| 2345 |
+
value: 81.01899999999999
|
| 2346 |
- type: mrr_at_100
|
| 2347 |
+
value: 81.01899999999999
|
| 2348 |
- type: mrr_at_1000
|
| 2349 |
+
value: 81.01899999999999
|
| 2350 |
- type: mrr_at_3
|
| 2351 |
+
value: 79.333
|
| 2352 |
- type: mrr_at_5
|
| 2353 |
+
value: 80.733
|
| 2354 |
- type: ndcg_at_1
|
| 2355 |
+
value: 63.0
|
| 2356 |
- type: ndcg_at_10
|
| 2357 |
+
value: 65.913
|
| 2358 |
- type: ndcg_at_100
|
| 2359 |
+
value: 51.895
|
| 2360 |
- type: ndcg_at_1000
|
| 2361 |
+
value: 46.967
|
| 2362 |
- type: ndcg_at_3
|
| 2363 |
+
value: 65.49199999999999
|
| 2364 |
- type: ndcg_at_5
|
| 2365 |
+
value: 66.69699999999999
|
| 2366 |
- type: precision_at_1
|
| 2367 |
+
value: 68.0
|
| 2368 |
- type: precision_at_10
|
| 2369 |
+
value: 71.6
|
| 2370 |
- type: precision_at_100
|
| 2371 |
+
value: 53.66
|
| 2372 |
- type: precision_at_1000
|
| 2373 |
+
value: 21.124000000000002
|
| 2374 |
- type: precision_at_3
|
| 2375 |
value: 72.667
|
| 2376 |
- type: precision_at_5
|
| 2377 |
+
value: 74.0
|
| 2378 |
- type: recall_at_1
|
| 2379 |
+
value: 0.189
|
| 2380 |
- type: recall_at_10
|
| 2381 |
+
value: 1.913
|
| 2382 |
- type: recall_at_100
|
| 2383 |
+
value: 12.601999999999999
|
| 2384 |
- type: recall_at_1000
|
| 2385 |
+
value: 44.296
|
| 2386 |
- type: recall_at_3
|
| 2387 |
+
value: 0.605
|
| 2388 |
- type: recall_at_5
|
| 2389 |
+
value: 1.018
|
| 2390 |
- task:
|
| 2391 |
type: Retrieval
|
| 2392 |
dataset:
|
|
|
|
| 2397 |
revision: None
|
| 2398 |
metrics:
|
| 2399 |
- type: map_at_1
|
| 2400 |
+
value: 2.701
|
| 2401 |
- type: map_at_10
|
| 2402 |
+
value: 10.445
|
| 2403 |
- type: map_at_100
|
| 2404 |
+
value: 17.324
|
| 2405 |
- type: map_at_1000
|
| 2406 |
+
value: 19.161
|
| 2407 |
- type: map_at_3
|
| 2408 |
+
value: 5.497
|
| 2409 |
- type: map_at_5
|
| 2410 |
+
value: 7.278
|
| 2411 |
- type: mrr_at_1
|
| 2412 |
+
value: 30.612000000000002
|
| 2413 |
- type: mrr_at_10
|
| 2414 |
+
value: 45.534
|
| 2415 |
- type: mrr_at_100
|
| 2416 |
+
value: 45.792
|
| 2417 |
- type: mrr_at_1000
|
| 2418 |
+
value: 45.806999999999995
|
| 2419 |
- type: mrr_at_3
|
| 2420 |
+
value: 37.755
|
| 2421 |
- type: mrr_at_5
|
| 2422 |
+
value: 43.469
|
| 2423 |
- type: ndcg_at_1
|
| 2424 |
+
value: 26.531
|
| 2425 |
- type: ndcg_at_10
|
| 2426 |
+
value: 26.235000000000003
|
| 2427 |
- type: ndcg_at_100
|
| 2428 |
+
value: 39.17
|
| 2429 |
- type: ndcg_at_1000
|
| 2430 |
+
value: 51.038
|
| 2431 |
- type: ndcg_at_3
|
| 2432 |
+
value: 23.625
|
| 2433 |
- type: ndcg_at_5
|
| 2434 |
+
value: 24.338
|
| 2435 |
- type: precision_at_1
|
| 2436 |
+
value: 30.612000000000002
|
| 2437 |
- type: precision_at_10
|
| 2438 |
+
value: 24.285999999999998
|
| 2439 |
- type: precision_at_100
|
| 2440 |
+
value: 8.224
|
| 2441 |
- type: precision_at_1000
|
| 2442 |
+
value: 1.6179999999999999
|
| 2443 |
- type: precision_at_3
|
| 2444 |
+
value: 24.490000000000002
|
| 2445 |
- type: precision_at_5
|
| 2446 |
+
value: 24.898
|
| 2447 |
- type: recall_at_1
|
| 2448 |
+
value: 2.701
|
| 2449 |
- type: recall_at_10
|
| 2450 |
+
value: 17.997
|
| 2451 |
- type: recall_at_100
|
| 2452 |
+
value: 51.766999999999996
|
| 2453 |
- type: recall_at_1000
|
| 2454 |
+
value: 87.863
|
| 2455 |
- type: recall_at_3
|
| 2456 |
+
value: 6.295000000000001
|
| 2457 |
- type: recall_at_5
|
| 2458 |
+
value: 9.993
|
| 2459 |
- task:
|
| 2460 |
type: Classification
|
| 2461 |
dataset:
|
|
|
|
| 2466 |
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
|
| 2467 |
metrics:
|
| 2468 |
- type: accuracy
|
| 2469 |
+
value: 73.3474
|
| 2470 |
- type: ap
|
| 2471 |
+
value: 15.393431414459924
|
| 2472 |
- type: f1
|
| 2473 |
+
value: 56.466681887882416
|
| 2474 |
- task:
|
| 2475 |
type: Classification
|
| 2476 |
dataset:
|
|
|
|
| 2481 |
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
|
| 2482 |
metrics:
|
| 2483 |
- type: accuracy
|
| 2484 |
+
value: 62.062818336163
|
| 2485 |
- type: f1
|
| 2486 |
+
value: 62.11230840463252
|
| 2487 |
- task:
|
| 2488 |
type: Clustering
|
| 2489 |
dataset:
|
|
|
|
| 2494 |
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
|
| 2495 |
metrics:
|
| 2496 |
- type: v_measure
|
| 2497 |
+
value: 42.464892820845115
|
| 2498 |
- task:
|
| 2499 |
type: PairClassification
|
| 2500 |
dataset:
|
|
|
|
| 2505 |
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
|
| 2506 |
metrics:
|
| 2507 |
- type: cos_sim_accuracy
|
| 2508 |
+
value: 86.15962329379508
|
| 2509 |
- type: cos_sim_ap
|
| 2510 |
+
value: 74.73674057919256
|
| 2511 |
- type: cos_sim_f1
|
| 2512 |
+
value: 68.81245642574947
|
| 2513 |
- type: cos_sim_precision
|
| 2514 |
+
value: 61.48255813953488
|
| 2515 |
- type: cos_sim_recall
|
| 2516 |
+
value: 78.12664907651715
|
| 2517 |
- type: dot_accuracy
|
| 2518 |
+
value: 86.15962329379508
|
| 2519 |
- type: dot_ap
|
| 2520 |
+
value: 74.7367634988281
|
| 2521 |
- type: dot_f1
|
| 2522 |
+
value: 68.81245642574947
|
| 2523 |
- type: dot_precision
|
| 2524 |
+
value: 61.48255813953488
|
| 2525 |
- type: dot_recall
|
| 2526 |
+
value: 78.12664907651715
|
| 2527 |
- type: euclidean_accuracy
|
| 2528 |
+
value: 86.15962329379508
|
| 2529 |
- type: euclidean_ap
|
| 2530 |
+
value: 74.7367761466634
|
| 2531 |
- type: euclidean_f1
|
| 2532 |
+
value: 68.81245642574947
|
| 2533 |
- type: euclidean_precision
|
| 2534 |
+
value: 61.48255813953488
|
| 2535 |
- type: euclidean_recall
|
| 2536 |
+
value: 78.12664907651715
|
| 2537 |
- type: manhattan_accuracy
|
| 2538 |
+
value: 86.21326816474935
|
| 2539 |
- type: manhattan_ap
|
| 2540 |
+
value: 74.64416473733951
|
| 2541 |
- type: manhattan_f1
|
| 2542 |
+
value: 68.80924855491331
|
| 2543 |
- type: manhattan_precision
|
| 2544 |
+
value: 61.23456790123457
|
| 2545 |
- type: manhattan_recall
|
| 2546 |
+
value: 78.52242744063325
|
| 2547 |
- type: max_accuracy
|
| 2548 |
+
value: 86.21326816474935
|
| 2549 |
- type: max_ap
|
| 2550 |
+
value: 74.7367761466634
|
| 2551 |
- type: max_f1
|
| 2552 |
+
value: 68.81245642574947
|
| 2553 |
- task:
|
| 2554 |
type: PairClassification
|
| 2555 |
dataset:
|
|
|
|
| 2560 |
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
|
| 2561 |
metrics:
|
| 2562 |
- type: cos_sim_accuracy
|
| 2563 |
+
value: 88.97620988085536
|
| 2564 |
- type: cos_sim_ap
|
| 2565 |
+
value: 86.08680845745758
|
| 2566 |
- type: cos_sim_f1
|
| 2567 |
+
value: 78.02793637114438
|
| 2568 |
- type: cos_sim_precision
|
| 2569 |
+
value: 73.11082699683736
|
| 2570 |
- type: cos_sim_recall
|
| 2571 |
+
value: 83.65414228518632
|
| 2572 |
- type: dot_accuracy
|
| 2573 |
+
value: 88.97620988085536
|
| 2574 |
- type: dot_ap
|
| 2575 |
+
value: 86.08681149437946
|
| 2576 |
- type: dot_f1
|
| 2577 |
+
value: 78.02793637114438
|
| 2578 |
- type: dot_precision
|
| 2579 |
+
value: 73.11082699683736
|
| 2580 |
- type: dot_recall
|
| 2581 |
+
value: 83.65414228518632
|
| 2582 |
- type: euclidean_accuracy
|
| 2583 |
+
value: 88.97620988085536
|
| 2584 |
- type: euclidean_ap
|
| 2585 |
+
value: 86.08681215460771
|
| 2586 |
- type: euclidean_f1
|
| 2587 |
+
value: 78.02793637114438
|
| 2588 |
- type: euclidean_precision
|
| 2589 |
+
value: 73.11082699683736
|
| 2590 |
- type: euclidean_recall
|
| 2591 |
+
value: 83.65414228518632
|
| 2592 |
- type: manhattan_accuracy
|
| 2593 |
+
value: 88.88888888888889
|
| 2594 |
- type: manhattan_ap
|
| 2595 |
+
value: 86.02916327562438
|
| 2596 |
- type: manhattan_f1
|
| 2597 |
+
value: 78.02063045516843
|
| 2598 |
- type: manhattan_precision
|
| 2599 |
+
value: 73.38851947346994
|
| 2600 |
- type: manhattan_recall
|
| 2601 |
+
value: 83.2768709578072
|
| 2602 |
- type: max_accuracy
|
| 2603 |
+
value: 88.97620988085536
|
| 2604 |
- type: max_ap
|
| 2605 |
+
value: 86.08681215460771
|
| 2606 |
- type: max_f1
|
| 2607 |
+
value: 78.02793637114438
|
| 2608 |
---
|
| 2609 |
<!-- TODO: add evaluation results here -->
|
| 2610 |
<br><br>
|
|
|
|
| 2641 |
|
| 2642 |
**V2 (Based on JinaBert, 8k Seq)**
|
| 2643 |
|
| 2644 |
+
- [`jina-embeddings-v2-small-en`](https://huggingface.co/jinaai/jina-embeddings-v2-small-en): 33 million parameters.
|
| 2645 |
+
- [`jina-embeddings-v2-base-en`](https://huggingface.co/jinaai/jina-embeddings-v2-base-en): 137 million parameters **(you are here)**.
|
| 2646 |
- [`jina-embeddings-v2-large-en`](): 435 million parameters (releasing soon).
|
| 2647 |
|
| 2648 |
## Data & Parameters
|
|
|
|
| 2674 |
)
|
| 2675 |
```
|
| 2676 |
|
| 2677 |
+
*Alternatively, you can use Jina AI's Embedding platform for fully-managed access to Jina Embeddings models (Coming soon!)*.
|
| 2678 |
|
| 2679 |
## Fine-tuning
|
| 2680 |
|