neosfeng
commited on
Commit
·
bf092ae
1
Parent(s):
c05fab5
update model and metric
Browse files
README.md
CHANGED
@@ -19,17 +19,17 @@ model-index:
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revision: b44c3b011063adb25877c13823db83bb193913c4
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metrics:
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- type: cos_sim_pearson
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-
value: 36.
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- type: cos_sim_spearman
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-
value: 37.
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- type: euclidean_pearson
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-
value: 36.
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- type: euclidean_spearman
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-
value: 37.
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- type: manhattan_pearson
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-
value: 36.
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- type: manhattan_spearman
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-
value: 37.
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- task:
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type: STS
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dataset:
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@@ -40,17 +40,17 @@ model-index:
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revision: 0f319b1142f28d00e055a6770f3f726ae9b7d865
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metrics:
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- type: cos_sim_pearson
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-
value: 39.
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44 |
- 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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@@ -61,9 +61,9 @@ model-index:
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revision: 1399c76144fd37290681b995c656ef9b2e06e26d
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metrics:
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- type: accuracy
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-
value: 47.
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- type: f1
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-
value: 44.
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- task:
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type: STS
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dataset:
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@@ -74,17 +74,17 @@ model-index:
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revision: e3dda5e115e487b39ec7e618c0c6a29137052a55
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metrics:
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- type: cos_sim_pearson
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-
value: 67.
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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: 69.
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- type: euclidean_spearman
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-
value:
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- type: manhattan_pearson
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-
value: 69.
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- type: manhattan_spearman
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-
value:
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- task:
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type: Clustering
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dataset:
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@@ -95,7 +95,7 @@ model-index:
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revision: 4b6227591c6c1a73bc76b1055f3b7f3588e72476
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metrics:
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- type: v_measure
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-
value:
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- task:
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type: Clustering
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dataset:
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@@ -106,7 +106,7 @@ model-index:
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revision: e458b3f5414b62b7f9f83499ac1f5497ae2e869f
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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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@@ -117,9 +117,9 @@ model-index:
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revision: 8d7f1e942507dac42dc58017c1a001c3717da7df
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metrics:
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- type: map
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-
value:
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- type: mrr
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-
value:
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- task:
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type: Reranking
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dataset:
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@@ -130,9 +130,9 @@ model-index:
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revision: 23d186750531a14a0357ca22cd92d712fd512ea0
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metrics:
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- type: map
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-
value:
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- type: mrr
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-
value:
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- task:
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type: Retrieval
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dataset:
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@@ -143,65 +143,65 @@ model-index:
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revision: cd540c506dae1cf9e9a59c3e06f42030d54e7301
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metrics:
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- type: map_at_1
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-
value: 16.
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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: 22.
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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: 26.
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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: 31.
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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: 26.
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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: 26.
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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: 11.
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- type: recall_at_1
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-
value: 16.
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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: PairClassification
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dataset:
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@@ -212,51 +212,51 @@ model-index:
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revision: 41bc36f332156f7adc9e38f53777c959b2ae9766
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metrics:
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- type: cos_sim_accuracy
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-
value: 61.
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- type: cos_sim_ap
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-
value:
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- type: cos_sim_f1
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-
value: 68.
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- type: cos_sim_precision
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-
value:
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- type: cos_sim_recall
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-
value:
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- type: dot_accuracy
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-
value: 61.
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- type: dot_ap
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-
value: 65.
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- type: dot_f1
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-
value: 68.
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- type: dot_precision
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-
value:
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- type: dot_recall
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-
value:
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- type: euclidean_accuracy
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-
value: 61.
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- type: euclidean_ap
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-
value:
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- type: euclidean_f1
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-
value: 68.
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- type: euclidean_precision
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-
value:
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- type: euclidean_recall
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-
value:
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- type: manhattan_accuracy
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-
value: 61.
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- type: manhattan_ap
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-
value:
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- type: manhattan_f1
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-
value: 68.
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- type: manhattan_precision
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-
value:
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- type: manhattan_recall
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-
value:
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- type: max_accuracy
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-
value: 61.
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- type: max_ap
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-
value:
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- type: max_f1
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-
value: 68.
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- task:
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type: Retrieval
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dataset:
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@@ -267,65 +267,65 @@ model-index:
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revision: 1271c7809071a13532e05f25fb53511ffce77117
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metrics:
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- type: map_at_1
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-
value:
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- type: map_at_10
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-
value:
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- type: map_at_100
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-
value:
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- type: map_at_1000
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-
value:
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- type: map_at_3
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-
value:
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- type: map_at_5
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-
value:
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- type: mrr_at_1
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-
value:
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- type: mrr_at_10
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-
value:
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- type: mrr_at_100
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-
value:
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- type: mrr_at_1000
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-
value:
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- type: mrr_at_3
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-
value:
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- type: mrr_at_5
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-
value:
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- type: ndcg_at_1
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-
value:
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- type: ndcg_at_10
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-
value:
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- type: ndcg_at_100
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-
value:
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- type: ndcg_at_1000
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-
value:
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- type: ndcg_at_3
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-
value:
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- type: ndcg_at_5
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-
value:
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- type: precision_at_1
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-
value:
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- type: precision_at_10
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-
value: 8.
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- type: precision_at_100
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-
value: 0.
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- type: precision_at_1000
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value: 0.1
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- type: precision_at_3
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-
value:
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- type: precision_at_5
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-
value:
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- type: recall_at_1
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-
value:
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- type: recall_at_10
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-
value:
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- type: recall_at_100
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-
value:
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- type: recall_at_1000
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-
value:
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- type: recall_at_3
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-
value:
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- type: recall_at_5
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-
value:
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- task:
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type: Retrieval
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dataset:
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@@ -336,63 +336,63 @@ model-index:
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revision: a1a333e290fe30b10f3f56498e3a0d911a693ced
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metrics:
|
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- type: map_at_1
|
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-
value: 21.
|
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- type: map_at_10
|
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-
value: 64.
|
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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: 68.
|
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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: 55.
|
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- type: mrr_at_1
|
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-
value: 76.
|
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- type: mrr_at_10
|
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-
value: 84.
|
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- type: mrr_at_100
|
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-
value: 84.
|
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- type: mrr_at_1000
|
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-
value: 84.
|
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- type: mrr_at_3
|
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-
value: 83.
|
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- type: mrr_at_5
|
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-
value: 83.
|
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- type: ndcg_at_1
|
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-
value: 76.
|
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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: 80.
|
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- type: ndcg_at_1000
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-
value: 81.
|
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- type: ndcg_at_3
|
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-
value: 72.
|
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- type: ndcg_at_5
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-
value: 71.
|
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- type: precision_at_1
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-
value: 76.
|
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- type: precision_at_10
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-
value: 36.
|
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- type: precision_at_100
|
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-
value: 4.
|
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- type: precision_at_1000
|
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value: 0.48700000000000004
|
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- type: precision_at_3
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-
value:
|
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- type: precision_at_5
|
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-
value:
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- type: recall_at_1
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-
value: 21.
|
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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: 98.
|
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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: 62.883
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- task:
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@@ -405,65 +405,65 @@ model-index:
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revision: 687de13dc7294d6fd9be10c6945f9e8fec8166b9
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metrics:
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- type: map_at_1
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-
value:
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- type: map_at_10
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-
value:
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- type: map_at_100
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-
value:
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- type: map_at_1000
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-
value:
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- type: map_at_3
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-
value:
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- type: map_at_5
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-
value:
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- type: mrr_at_1
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-
value:
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- type: mrr_at_10
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-
value:
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- type: mrr_at_100
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-
value:
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- type: mrr_at_1000
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-
value:
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- type: mrr_at_3
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-
value:
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- type: mrr_at_5
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-
value:
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- type: ndcg_at_1
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-
value:
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- type: ndcg_at_10
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-
value:
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- type: ndcg_at_100
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-
value:
|
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- type: ndcg_at_1000
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-
value:
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- type: ndcg_at_3
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-
value:
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- type: ndcg_at_5
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-
value:
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- type: precision_at_1
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-
value:
|
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- type: precision_at_10
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-
value:
|
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- type: precision_at_100
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-
value: 0.
|
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- type: precision_at_1000
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-
value: 0.
|
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- type: precision_at_3
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-
value:
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- type: precision_at_5
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-
value:
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- type: recall_at_1
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-
value:
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- type: recall_at_10
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-
value:
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- type: recall_at_100
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-
value:
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- type: recall_at_1000
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-
value:
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- type: recall_at_3
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-
value:
|
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- type: recall_at_5
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-
value:
|
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- task:
|
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type: Classification
|
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dataset:
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@@ -474,9 +474,9 @@ model-index:
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revision: 421605374b29664c5fc098418fe20ada9bd55f8a
|
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metrics:
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- type: accuracy
|
477 |
-
value: 44.
|
478 |
- type: f1
|
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-
value:
|
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- task:
|
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type: Classification
|
482 |
dataset:
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@@ -487,11 +487,11 @@ model-index:
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revision: b7c64bd89eb87f8ded463478346f76731f07bf8b
|
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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: STS
|
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dataset:
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@@ -502,17 +502,17 @@ model-index:
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revision: 17f9b096f80380fce5ed12a9be8be7784b337daf
|
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metrics:
|
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- type: cos_sim_pearson
|
505 |
-
value: 66.
|
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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: 71.
|
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- type: euclidean_spearman
|
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-
value:
|
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- type: manhattan_pearson
|
513 |
-
value: 71.
|
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- type: manhattan_spearman
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-
value:
|
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- task:
|
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type: Reranking
|
518 |
dataset:
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@@ -523,9 +523,9 @@ model-index:
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revision: 8e0c766dbe9e16e1d221116a3f36795fbade07f6
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metrics:
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- type: map
|
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-
value:
|
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- type: mrr
|
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-
value:
|
529 |
- task:
|
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type: Retrieval
|
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dataset:
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@@ -536,65 +536,65 @@ model-index:
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|
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revision: 539bbde593d947e2a124ba72651aafc09eb33fc2
|
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metrics:
|
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- type: map_at_1
|
539 |
-
value: 43.
|
540 |
- type: map_at_10
|
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-
value: 53.
|
542 |
- type: map_at_100
|
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-
value: 53.
|
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- type: map_at_1000
|
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-
value: 53.
|
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- type: map_at_3
|
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-
value: 50.
|
548 |
- type: map_at_5
|
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-
value: 52.
|
550 |
- type: mrr_at_1
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-
value: 45.
|
552 |
- type: mrr_at_10
|
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-
value:
|
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- type: mrr_at_100
|
555 |
-
value: 54.
|
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- type: mrr_at_1000
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-
value: 54.
|
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- type: mrr_at_3
|
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-
value: 51.
|
560 |
- type: mrr_at_5
|
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-
value:
|
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- type: ndcg_at_1
|
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-
value: 45.
|
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- type: ndcg_at_10
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-
value: 57.
|
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- type: ndcg_at_100
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-
value:
|
568 |
- type: ndcg_at_1000
|
569 |
-
value:
|
570 |
- type: ndcg_at_3
|
571 |
-
value:
|
572 |
- type: ndcg_at_5
|
573 |
-
value: 55.
|
574 |
- type: precision_at_1
|
575 |
-
value: 45.
|
576 |
- type: precision_at_10
|
577 |
-
value: 7.
|
578 |
- type: precision_at_100
|
579 |
-
value: 0.
|
580 |
- type: precision_at_1000
|
581 |
-
value: 0.
|
582 |
- type: precision_at_3
|
583 |
-
value: 20.
|
584 |
- type: precision_at_5
|
585 |
-
value: 13.
|
586 |
- type: recall_at_1
|
587 |
-
value: 43.
|
588 |
- type: recall_at_10
|
589 |
-
value: 71.
|
590 |
- type: recall_at_100
|
591 |
-
value:
|
592 |
- type: recall_at_1000
|
593 |
-
value: 94.
|
594 |
- type: recall_at_3
|
595 |
-
value: 58.
|
596 |
- type: recall_at_5
|
597 |
-
value:
|
598 |
- task:
|
599 |
type: Classification
|
600 |
dataset:
|
@@ -605,9 +605,9 @@ model-index:
|
|
605 |
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
|
606 |
metrics:
|
607 |
- type: accuracy
|
608 |
-
value:
|
609 |
- type: f1
|
610 |
-
value:
|
611 |
- task:
|
612 |
type: Classification
|
613 |
dataset:
|
@@ -618,9 +618,9 @@ model-index:
|
|
618 |
revision: 7d571f92784cd94a019292a1f45445077d0ef634
|
619 |
metrics:
|
620 |
- type: accuracy
|
621 |
-
value:
|
622 |
- type: f1
|
623 |
-
value:
|
624 |
- task:
|
625 |
type: Retrieval
|
626 |
dataset:
|
@@ -631,65 +631,65 @@ model-index:
|
|
631 |
revision: 2039188fb5800a9803ba5048df7b76e6fb151fc6
|
632 |
metrics:
|
633 |
- type: map_at_1
|
634 |
-
value:
|
635 |
- type: map_at_10
|
636 |
-
value:
|
637 |
- type: map_at_100
|
638 |
-
value:
|
639 |
- type: map_at_1000
|
640 |
-
value:
|
641 |
- type: map_at_3
|
642 |
-
value:
|
643 |
- type: map_at_5
|
644 |
-
value:
|
645 |
- type: mrr_at_1
|
646 |
-
value:
|
647 |
- type: mrr_at_10
|
648 |
-
value:
|
649 |
- type: mrr_at_100
|
650 |
-
value:
|
651 |
- type: mrr_at_1000
|
652 |
-
value:
|
653 |
- type: mrr_at_3
|
654 |
-
value:
|
655 |
- type: mrr_at_5
|
656 |
-
value:
|
657 |
- type: ndcg_at_1
|
658 |
-
value:
|
659 |
- type: ndcg_at_10
|
660 |
-
value:
|
661 |
- type: ndcg_at_100
|
662 |
-
value:
|
663 |
- type: ndcg_at_1000
|
664 |
-
value:
|
665 |
- type: ndcg_at_3
|
666 |
-
value:
|
667 |
- type: ndcg_at_5
|
668 |
-
value:
|
669 |
- type: precision_at_1
|
670 |
-
value:
|
671 |
- type: precision_at_10
|
672 |
-
value:
|
673 |
- type: precision_at_100
|
674 |
-
value: 0.
|
675 |
- type: precision_at_1000
|
676 |
-
value: 0.
|
677 |
- type: precision_at_3
|
678 |
-
value:
|
679 |
- type: precision_at_5
|
680 |
-
value:
|
681 |
- type: recall_at_1
|
682 |
-
value:
|
683 |
- type: recall_at_10
|
684 |
-
value:
|
685 |
- type: recall_at_100
|
686 |
-
value:
|
687 |
- type: recall_at_1000
|
688 |
-
value:
|
689 |
- type: recall_at_3
|
690 |
-
value:
|
691 |
- type: recall_at_5
|
692 |
-
value:
|
693 |
- task:
|
694 |
type: Retrieval
|
695 |
dataset:
|
@@ -700,65 +700,65 @@ model-index:
|
|
700 |
revision: None
|
701 |
metrics:
|
702 |
- type: map_at_1
|
703 |
-
value: 7.
|
704 |
- type: map_at_10
|
705 |
-
value: 10.
|
706 |
- type: map_at_100
|
707 |
-
value: 10.
|
708 |
- type: map_at_1000
|
709 |
-
value:
|
710 |
- type: map_at_3
|
711 |
-
value: 9.
|
712 |
- type: map_at_5
|
713 |
-
value: 9.
|
714 |
- type: mrr_at_1
|
715 |
-
value: 7.
|
716 |
- type: mrr_at_10
|
717 |
-
value: 10.
|
718 |
- type: mrr_at_100
|
719 |
-
value: 10.
|
720 |
- type: mrr_at_1000
|
721 |
-
value:
|
722 |
- type: mrr_at_3
|
723 |
-
value: 9.
|
724 |
- type: mrr_at_5
|
725 |
-
value: 9.
|
726 |
- type: ndcg_at_1
|
727 |
-
value: 7.
|
728 |
- type: ndcg_at_10
|
729 |
-
value:
|
730 |
- type: ndcg_at_100
|
731 |
-
value: 15.
|
732 |
- type: ndcg_at_1000
|
733 |
-
value: 17.
|
734 |
- type: ndcg_at_3
|
735 |
-
value: 9.
|
736 |
- type: ndcg_at_5
|
737 |
-
value: 10.
|
738 |
- type: precision_at_1
|
739 |
-
value: 7.
|
740 |
- type: precision_at_10
|
741 |
-
value: 1.
|
742 |
- type: precision_at_100
|
743 |
-
value: 0.
|
744 |
- type: precision_at_1000
|
745 |
-
value: 0.
|
746 |
- type: precision_at_3
|
747 |
-
value: 3.
|
748 |
- type: precision_at_5
|
749 |
-
value: 2.
|
750 |
- type: recall_at_1
|
751 |
-
value: 7.
|
752 |
- type: recall_at_10
|
753 |
-
value:
|
754 |
- type: recall_at_100
|
755 |
-
value:
|
756 |
- type: recall_at_1000
|
757 |
-
value:
|
758 |
- type: recall_at_3
|
759 |
-
value: 11.
|
760 |
- type: recall_at_5
|
761 |
-
value:
|
762 |
- task:
|
763 |
type: Classification
|
764 |
dataset:
|
@@ -769,9 +769,9 @@ model-index:
|
|
769 |
revision: 46958b007a63fdbf239b7672c25d0bea67b5ea1a
|
770 |
metrics:
|
771 |
- type: accuracy
|
772 |
-
value: 78.
|
773 |
- type: f1
|
774 |
-
value: 78.
|
775 |
- task:
|
776 |
type: PairClassification
|
777 |
dataset:
|
@@ -782,51 +782,51 @@ model-index:
|
|
782 |
revision: 66e76a618a34d6d565d5538088562851e6daa7ec
|
783 |
metrics:
|
784 |
- type: cos_sim_accuracy
|
785 |
-
value: 59.
|
786 |
- type: cos_sim_ap
|
787 |
-
value:
|
788 |
- type: cos_sim_f1
|
789 |
-
value: 69.
|
790 |
- type: cos_sim_precision
|
791 |
-
value:
|
792 |
- type: cos_sim_recall
|
793 |
-
value: 96.
|
794 |
- type: dot_accuracy
|
795 |
-
value: 59.
|
796 |
- type: dot_ap
|
797 |
-
value:
|
798 |
- type: dot_f1
|
799 |
-
value: 69.
|
800 |
- type: dot_precision
|
801 |
-
value:
|
802 |
- type: dot_recall
|
803 |
-
value: 96.
|
804 |
- type: euclidean_accuracy
|
805 |
-
value: 59.
|
806 |
- type: euclidean_ap
|
807 |
-
value:
|
808 |
- type: euclidean_f1
|
809 |
-
value: 69.
|
810 |
- type: euclidean_precision
|
811 |
-
value:
|
812 |
- type: euclidean_recall
|
813 |
-
value: 96.
|
814 |
- type: manhattan_accuracy
|
815 |
-
value: 59.
|
816 |
- type: manhattan_ap
|
817 |
-
value: 60.
|
818 |
- type: manhattan_f1
|
819 |
-
value: 69.
|
820 |
- type: manhattan_precision
|
821 |
-
value: 54.
|
822 |
- type: manhattan_recall
|
823 |
-
value: 96.
|
824 |
- type: max_accuracy
|
825 |
-
value: 59.
|
826 |
- type: max_ap
|
827 |
-
value: 60.
|
828 |
- type: max_f1
|
829 |
-
value: 69.
|
830 |
- task:
|
831 |
type: Classification
|
832 |
dataset:
|
@@ -837,11 +837,11 @@ model-index:
|
|
837 |
revision: e610f2ebd179a8fda30ae534c3878750a96db120
|
838 |
metrics:
|
839 |
- type: accuracy
|
840 |
-
value:
|
841 |
- type: ap
|
842 |
-
value:
|
843 |
- type: f1
|
844 |
-
value:
|
845 |
- task:
|
846 |
type: STS
|
847 |
dataset:
|
@@ -852,17 +852,17 @@ model-index:
|
|
852 |
revision: 9c6a90e430ac22b5779fb019a23e820b11a8b5e1
|
853 |
metrics:
|
854 |
- type: cos_sim_pearson
|
855 |
-
value: 15.
|
856 |
- type: cos_sim_spearman
|
857 |
-
value: 18.
|
858 |
- type: euclidean_pearson
|
859 |
-
value: 18.
|
860 |
- type: euclidean_spearman
|
861 |
-
value: 18.
|
862 |
- type: manhattan_pearson
|
863 |
-
value: 18.
|
864 |
- type: manhattan_spearman
|
865 |
-
value: 18.
|
866 |
- task:
|
867 |
type: PairClassification
|
868 |
dataset:
|
@@ -873,51 +873,51 @@ model-index:
|
|
873 |
revision: 8a04d940a42cd40658986fdd8e3da561533a3646
|
874 |
metrics:
|
875 |
- type: cos_sim_accuracy
|
876 |
-
value:
|
877 |
- type: cos_sim_ap
|
878 |
-
value: 57.
|
879 |
- type: cos_sim_f1
|
880 |
-
value: 62.
|
881 |
- type: cos_sim_precision
|
882 |
-
value: 45.
|
883 |
- type: cos_sim_recall
|
884 |
-
value:
|
885 |
- type: dot_accuracy
|
886 |
-
value:
|
887 |
- type: dot_ap
|
888 |
-
value:
|
889 |
- type: dot_f1
|
890 |
-
value: 62.
|
891 |
- type: dot_precision
|
892 |
-
value: 45.
|
893 |
- type: dot_recall
|
894 |
-
value:
|
895 |
- type: euclidean_accuracy
|
896 |
-
value:
|
897 |
- type: euclidean_ap
|
898 |
-
value: 57.
|
899 |
- type: euclidean_f1
|
900 |
-
value: 62.
|
901 |
- type: euclidean_precision
|
902 |
-
value: 45.
|
903 |
- type: euclidean_recall
|
904 |
-
value:
|
905 |
- type: manhattan_accuracy
|
906 |
-
value:
|
907 |
- type: manhattan_ap
|
908 |
-
value: 57.
|
909 |
- type: manhattan_f1
|
910 |
-
value: 62.
|
911 |
- type: manhattan_precision
|
912 |
-
value: 45.
|
913 |
- type: manhattan_recall
|
914 |
-
value:
|
915 |
- type: max_accuracy
|
916 |
-
value:
|
917 |
- type: max_ap
|
918 |
-
value: 57.
|
919 |
- type: max_f1
|
920 |
-
value: 62.
|
921 |
- task:
|
922 |
type: STS
|
923 |
dataset:
|
@@ -928,17 +928,17 @@ model-index:
|
|
928 |
revision: 790b0510dc52b1553e8c49f3d2afb48c0e5c48b7
|
929 |
metrics:
|
930 |
- type: cos_sim_pearson
|
931 |
-
value:
|
932 |
- type: cos_sim_spearman
|
933 |
-
value:
|
934 |
- type: euclidean_pearson
|
935 |
-
value:
|
936 |
- type: euclidean_spearman
|
937 |
-
value:
|
938 |
- type: manhattan_pearson
|
939 |
-
value:
|
940 |
- type: manhattan_spearman
|
941 |
-
value:
|
942 |
- task:
|
943 |
type: STS
|
944 |
dataset:
|
@@ -949,17 +949,17 @@ model-index:
|
|
949 |
revision: eea2b4fe26a775864c896887d910b76a8098ad3f
|
950 |
metrics:
|
951 |
- type: cos_sim_pearson
|
952 |
-
value:
|
953 |
- type: cos_sim_spearman
|
954 |
-
value:
|
955 |
- type: euclidean_pearson
|
956 |
-
value:
|
957 |
- type: euclidean_spearman
|
958 |
-
value:
|
959 |
- type: manhattan_pearson
|
960 |
-
value:
|
961 |
- type: manhattan_spearman
|
962 |
-
value:
|
963 |
- task:
|
964 |
type: STS
|
965 |
dataset:
|
@@ -970,17 +970,17 @@ model-index:
|
|
970 |
revision: 0cde68302b3541bb8b3c340dc0644b0b745b3dc0
|
971 |
metrics:
|
972 |
- type: cos_sim_pearson
|
973 |
-
value:
|
974 |
- type: cos_sim_spearman
|
975 |
-
value:
|
976 |
- type: euclidean_pearson
|
977 |
-
value:
|
978 |
- type: euclidean_spearman
|
979 |
-
value:
|
980 |
- type: manhattan_pearson
|
981 |
-
value:
|
982 |
- type: manhattan_spearman
|
983 |
-
value:
|
984 |
- task:
|
985 |
type: Reranking
|
986 |
dataset:
|
@@ -991,9 +991,9 @@ model-index:
|
|
991 |
revision: 76631901a18387f85eaa53e5450019b87ad58ef9
|
992 |
metrics:
|
993 |
- type: map
|
994 |
-
value: 64.
|
995 |
- type: mrr
|
996 |
-
value:
|
997 |
- task:
|
998 |
type: Retrieval
|
999 |
dataset:
|
@@ -1004,65 +1004,65 @@ model-index:
|
|
1004 |
revision: 8731a845f1bf500a4f111cf1070785c793d10e64
|
1005 |
metrics:
|
1006 |
- type: map_at_1
|
1007 |
-
value: 20.
|
1008 |
- type: map_at_10
|
1009 |
-
value:
|
1010 |
- type: map_at_100
|
1011 |
-
value:
|
1012 |
- type: map_at_1000
|
1013 |
-
value:
|
1014 |
- type: map_at_3
|
1015 |
-
value:
|
1016 |
- type: map_at_5
|
1017 |
-
value:
|
1018 |
- type: mrr_at_1
|
1019 |
-
value:
|
1020 |
- type: mrr_at_10
|
1021 |
-
value:
|
1022 |
- type: mrr_at_100
|
1023 |
-
value:
|
1024 |
- type: mrr_at_1000
|
1025 |
-
value:
|
1026 |
- type: mrr_at_3
|
1027 |
-
value:
|
1028 |
- type: mrr_at_5
|
1029 |
-
value:
|
1030 |
- type: ndcg_at_1
|
1031 |
-
value:
|
1032 |
- type: ndcg_at_10
|
1033 |
-
value:
|
1034 |
- type: ndcg_at_100
|
1035 |
-
value:
|
1036 |
- type: ndcg_at_1000
|
1037 |
-
value:
|
1038 |
- type: ndcg_at_3
|
1039 |
-
value:
|
1040 |
- type: ndcg_at_5
|
1041 |
-
value:
|
1042 |
- type: precision_at_1
|
1043 |
-
value:
|
1044 |
- type: precision_at_10
|
1045 |
-
value:
|
1046 |
- type: precision_at_100
|
1047 |
-
value: 4.
|
1048 |
- type: precision_at_1000
|
1049 |
-
value: 0.
|
1050 |
- type: precision_at_3
|
1051 |
-
value:
|
1052 |
- type: precision_at_5
|
1053 |
-
value:
|
1054 |
- type: recall_at_1
|
1055 |
-
value: 20.
|
1056 |
- type: recall_at_10
|
1057 |
-
value:
|
1058 |
- type: recall_at_100
|
1059 |
-
value:
|
1060 |
- type: recall_at_1000
|
1061 |
-
value: 96.
|
1062 |
- type: recall_at_3
|
1063 |
-
value:
|
1064 |
- type: recall_at_5
|
1065 |
-
value:
|
1066 |
- task:
|
1067 |
type: Classification
|
1068 |
dataset:
|
@@ -1073,9 +1073,9 @@ model-index:
|
|
1073 |
revision: 317f262bf1e6126357bbe89e875451e4b0938fe4
|
1074 |
metrics:
|
1075 |
- type: accuracy
|
1076 |
-
value: 50.
|
1077 |
- type: f1
|
1078 |
-
value: 48.
|
1079 |
- task:
|
1080 |
type: Clustering
|
1081 |
dataset:
|
@@ -1086,7 +1086,7 @@ model-index:
|
|
1086 |
revision: 5798586b105c0434e4f0fe5e767abe619442cf93
|
1087 |
metrics:
|
1088 |
- type: v_measure
|
1089 |
-
value:
|
1090 |
- task:
|
1091 |
type: Clustering
|
1092 |
dataset:
|
@@ -1097,7 +1097,7 @@ model-index:
|
|
1097 |
revision: 8a8b2caeda43f39e13c4bc5bea0f8a667896e10d
|
1098 |
metrics:
|
1099 |
- type: v_measure
|
1100 |
-
value:
|
1101 |
- task:
|
1102 |
type: Retrieval
|
1103 |
dataset:
|
@@ -1108,65 +1108,65 @@ model-index:
|
|
1108 |
revision: 58c2597a5943a2ba48f4668c3b90d796283c5639
|
1109 |
metrics:
|
1110 |
- type: map_at_1
|
1111 |
-
value:
|
1112 |
- type: map_at_10
|
1113 |
-
value:
|
1114 |
- type: map_at_100
|
1115 |
-
value:
|
1116 |
- type: map_at_1000
|
1117 |
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value:
|
1118 |
- type: map_at_3
|
1119 |
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value:
|
1120 |
- type: map_at_5
|
1121 |
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value:
|
1122 |
- type: mrr_at_1
|
1123 |
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value:
|
1124 |
- type: mrr_at_10
|
1125 |
-
value:
|
1126 |
- type: mrr_at_100
|
1127 |
-
value:
|
1128 |
- type: mrr_at_1000
|
1129 |
-
value:
|
1130 |
- type: mrr_at_3
|
1131 |
-
value:
|
1132 |
- type: mrr_at_5
|
1133 |
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value:
|
1134 |
- type: ndcg_at_1
|
1135 |
-
value:
|
1136 |
- type: ndcg_at_10
|
1137 |
-
value:
|
1138 |
- type: ndcg_at_100
|
1139 |
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value:
|
1140 |
- type: ndcg_at_1000
|
1141 |
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value:
|
1142 |
- type: ndcg_at_3
|
1143 |
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value:
|
1144 |
- type: ndcg_at_5
|
1145 |
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value:
|
1146 |
- type: precision_at_1
|
1147 |
-
value:
|
1148 |
- type: precision_at_10
|
1149 |
-
value:
|
1150 |
- type: precision_at_100
|
1151 |
-
value: 0.
|
1152 |
- type: precision_at_1000
|
1153 |
-
value: 0.
|
1154 |
- type: precision_at_3
|
1155 |
-
value:
|
1156 |
- type: precision_at_5
|
1157 |
-
value:
|
1158 |
- type: recall_at_1
|
1159 |
-
value:
|
1160 |
- type: recall_at_10
|
1161 |
-
value:
|
1162 |
- type: recall_at_100
|
1163 |
-
value:
|
1164 |
- type: recall_at_1000
|
1165 |
-
value:
|
1166 |
- type: recall_at_3
|
1167 |
-
value:
|
1168 |
- type: recall_at_5
|
1169 |
-
value:
|
1170 |
- task:
|
1171 |
type: Classification
|
1172 |
dataset:
|
@@ -1177,9 +1177,9 @@ model-index:
|
|
1177 |
revision: 339287def212450dcaa9df8c22bf93e9980c7023
|
1178 |
metrics:
|
1179 |
- type: accuracy
|
1180 |
-
value: 89.
|
1181 |
- type: ap
|
1182 |
-
value: 74.
|
1183 |
- type: f1
|
1184 |
-
value: 87.
|
1185 |
---
|
|
|
19 |
revision: b44c3b011063adb25877c13823db83bb193913c4
|
20 |
metrics:
|
21 |
- type: cos_sim_pearson
|
22 |
+
value: 36.28363608508365
|
23 |
- type: cos_sim_spearman
|
24 |
+
value: 37.39698005114737
|
25 |
- type: euclidean_pearson
|
26 |
+
value: 36.407377294778186
|
27 |
- type: euclidean_spearman
|
28 |
+
value: 37.396959945459166
|
29 |
- type: manhattan_pearson
|
30 |
+
value: 36.30818480805082
|
31 |
- type: manhattan_spearman
|
32 |
+
value: 37.28435580456356
|
33 |
- task:
|
34 |
type: STS
|
35 |
dataset:
|
|
|
40 |
revision: 0f319b1142f28d00e055a6770f3f726ae9b7d865
|
41 |
metrics:
|
42 |
- type: cos_sim_pearson
|
43 |
+
value: 39.918566602029536
|
44 |
- type: cos_sim_spearman
|
45 |
+
value: 42.163555979292155
|
46 |
- type: euclidean_pearson
|
47 |
+
value: 43.24429263158407
|
48 |
- type: euclidean_spearman
|
49 |
+
value: 42.16355485217486
|
50 |
- type: manhattan_pearson
|
51 |
+
value: 43.23108002349145
|
52 |
- type: manhattan_spearman
|
53 |
+
value: 42.156854810425834
|
54 |
- task:
|
55 |
type: Classification
|
56 |
dataset:
|
|
|
61 |
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
|
62 |
metrics:
|
63 |
- type: accuracy
|
64 |
+
value: 47.788000000000004
|
65 |
- type: f1
|
66 |
+
value: 44.518439064691925
|
67 |
- task:
|
68 |
type: STS
|
69 |
dataset:
|
|
|
74 |
revision: e3dda5e115e487b39ec7e618c0c6a29137052a55
|
75 |
metrics:
|
76 |
- type: cos_sim_pearson
|
77 |
+
value: 67.03414409142314
|
78 |
- type: cos_sim_spearman
|
79 |
+
value: 70.95560250546684
|
80 |
- type: euclidean_pearson
|
81 |
+
value: 69.35644910492917
|
82 |
- type: euclidean_spearman
|
83 |
+
value: 70.95560250269956
|
84 |
- type: manhattan_pearson
|
85 |
+
value: 69.32201332479197
|
86 |
- type: manhattan_spearman
|
87 |
+
value: 70.92406185691
|
88 |
- task:
|
89 |
type: Clustering
|
90 |
dataset:
|
|
|
95 |
revision: 4b6227591c6c1a73bc76b1055f3b7f3588e72476
|
96 |
metrics:
|
97 |
- type: v_measure
|
98 |
+
value: 39.31955168227449
|
99 |
- task:
|
100 |
type: Clustering
|
101 |
dataset:
|
|
|
106 |
revision: e458b3f5414b62b7f9f83499ac1f5497ae2e869f
|
107 |
metrics:
|
108 |
- type: v_measure
|
109 |
+
value: 37.8418274237459
|
110 |
- task:
|
111 |
type: Reranking
|
112 |
dataset:
|
|
|
117 |
revision: 8d7f1e942507dac42dc58017c1a001c3717da7df
|
118 |
metrics:
|
119 |
- type: map
|
120 |
+
value: 80.66118119519746
|
121 |
- type: mrr
|
122 |
+
value: 83.47972222222222
|
123 |
- task:
|
124 |
type: Reranking
|
125 |
dataset:
|
|
|
130 |
revision: 23d186750531a14a0357ca22cd92d712fd512ea0
|
131 |
metrics:
|
132 |
- type: map
|
133 |
+
value: 79.31430375371524
|
134 |
- type: mrr
|
135 |
+
value: 82.10194444444444
|
136 |
- task:
|
137 |
type: Retrieval
|
138 |
dataset:
|
|
|
143 |
revision: cd540c506dae1cf9e9a59c3e06f42030d54e7301
|
144 |
metrics:
|
145 |
- type: map_at_1
|
146 |
+
value: 16.672
|
147 |
- type: map_at_10
|
148 |
+
value: 26.273000000000003
|
149 |
- type: map_at_100
|
150 |
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value: 28.044999999999998
|
151 |
- type: map_at_1000
|
152 |
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value: 28.208
|
153 |
- type: map_at_3
|
154 |
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value: 22.989
|
155 |
- type: map_at_5
|
156 |
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value: 24.737000000000002
|
157 |
- type: mrr_at_1
|
158 |
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value: 26.257
|
159 |
- type: mrr_at_10
|
160 |
+
value: 34.358
|
161 |
- type: mrr_at_100
|
162 |
+
value: 35.436
|
163 |
- type: mrr_at_1000
|
164 |
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value: 35.513
|
165 |
- type: mrr_at_3
|
166 |
+
value: 31.954
|
167 |
- type: mrr_at_5
|
168 |
+
value: 33.234
|
169 |
- type: ndcg_at_1
|
170 |
+
value: 26.257
|
171 |
- type: ndcg_at_10
|
172 |
+
value: 32.326
|
173 |
- type: ndcg_at_100
|
174 |
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value: 39.959
|
175 |
- type: ndcg_at_1000
|
176 |
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value: 43.163000000000004
|
177 |
- type: ndcg_at_3
|
178 |
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value: 27.700999999999997
|
179 |
- type: ndcg_at_5
|
180 |
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value: 29.514000000000003
|
181 |
- type: precision_at_1
|
182 |
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value: 26.257
|
183 |
- type: precision_at_10
|
184 |
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value: 7.607
|
185 |
- type: precision_at_100
|
186 |
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value: 1.388
|
187 |
- type: precision_at_1000
|
188 |
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value: 0.179
|
189 |
- type: precision_at_3
|
190 |
+
value: 16.162000000000003
|
191 |
- type: precision_at_5
|
192 |
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value: 11.933
|
193 |
- type: recall_at_1
|
194 |
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value: 16.672
|
195 |
- type: recall_at_10
|
196 |
+
value: 42.135
|
197 |
- type: recall_at_100
|
198 |
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value: 74.417
|
199 |
- type: recall_at_1000
|
200 |
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value: 96.417
|
201 |
- type: recall_at_3
|
202 |
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value: 28.416999999999998
|
203 |
- type: recall_at_5
|
204 |
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value: 33.873999999999995
|
205 |
- task:
|
206 |
type: PairClassification
|
207 |
dataset:
|
|
|
212 |
revision: 41bc36f332156f7adc9e38f53777c959b2ae9766
|
213 |
metrics:
|
214 |
- type: cos_sim_accuracy
|
215 |
+
value: 61.11846061334937
|
216 |
- type: cos_sim_ap
|
217 |
+
value: 65.68356716139071
|
218 |
- type: cos_sim_f1
|
219 |
+
value: 68.15213842637937
|
220 |
- type: cos_sim_precision
|
221 |
+
value: 52.35109717868338
|
222 |
- type: cos_sim_recall
|
223 |
+
value: 97.61515080664017
|
224 |
- type: dot_accuracy
|
225 |
+
value: 61.11846061334937
|
226 |
- type: dot_ap
|
227 |
+
value: 65.68369552204702
|
228 |
- type: dot_f1
|
229 |
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value: 68.15213842637937
|
230 |
- type: dot_precision
|
231 |
+
value: 52.35109717868338
|
232 |
- type: dot_recall
|
233 |
+
value: 97.61515080664017
|
234 |
- type: euclidean_accuracy
|
235 |
+
value: 61.11846061334937
|
236 |
- type: euclidean_ap
|
237 |
+
value: 65.68356789608616
|
238 |
- type: euclidean_f1
|
239 |
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value: 68.15213842637937
|
240 |
- type: euclidean_precision
|
241 |
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value: 52.35109717868338
|
242 |
- type: euclidean_recall
|
243 |
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value: 97.61515080664017
|
244 |
- type: manhattan_accuracy
|
245 |
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value: 61.17859290438966
|
246 |
- type: manhattan_ap
|
247 |
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value: 65.68230365595265
|
248 |
- type: manhattan_f1
|
249 |
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value: 68.14029363784665
|
250 |
- type: manhattan_precision
|
251 |
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value: 52.32368783665289
|
252 |
- type: manhattan_recall
|
253 |
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value: 97.66191255552957
|
254 |
- type: max_accuracy
|
255 |
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value: 61.17859290438966
|
256 |
- type: max_ap
|
257 |
+
value: 65.68369552204702
|
258 |
- type: max_f1
|
259 |
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value: 68.15213842637937
|
260 |
- task:
|
261 |
type: Retrieval
|
262 |
dataset:
|
|
|
267 |
revision: 1271c7809071a13532e05f25fb53511ffce77117
|
268 |
metrics:
|
269 |
- type: map_at_1
|
270 |
+
value: 51.054
|
271 |
- type: map_at_10
|
272 |
+
value: 61.926
|
273 |
- type: map_at_100
|
274 |
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value: 62.514
|
275 |
- type: map_at_1000
|
276 |
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value: 62.529
|
277 |
- type: map_at_3
|
278 |
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value: 59.272999999999996
|
279 |
- type: map_at_5
|
280 |
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value: 60.943000000000005
|
281 |
- type: mrr_at_1
|
282 |
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value: 51.212
|
283 |
- type: mrr_at_10
|
284 |
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value: 61.916000000000004
|
285 |
- type: mrr_at_100
|
286 |
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value: 62.495999999999995
|
287 |
- type: mrr_at_1000
|
288 |
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value: 62.511
|
289 |
- type: mrr_at_3
|
290 |
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value: 59.326
|
291 |
- type: mrr_at_5
|
292 |
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value: 60.958999999999996
|
293 |
- type: ndcg_at_1
|
294 |
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value: 51.212
|
295 |
- type: ndcg_at_10
|
296 |
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value: 67.223
|
297 |
- type: ndcg_at_100
|
298 |
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value: 69.92699999999999
|
299 |
- type: ndcg_at_1000
|
300 |
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value: 70.307
|
301 |
- type: ndcg_at_3
|
302 |
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value: 61.873
|
303 |
- type: ndcg_at_5
|
304 |
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value: 64.883
|
305 |
- type: precision_at_1
|
306 |
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value: 51.212
|
307 |
- type: precision_at_10
|
308 |
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value: 8.472
|
309 |
- type: precision_at_100
|
310 |
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value: 0.9730000000000001
|
311 |
- type: precision_at_1000
|
312 |
value: 0.1
|
313 |
- type: precision_at_3
|
314 |
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value: 23.253
|
315 |
- type: precision_at_5
|
316 |
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value: 15.448
|
317 |
- type: recall_at_1
|
318 |
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value: 51.054
|
319 |
- type: recall_at_10
|
320 |
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value: 83.825
|
321 |
- type: recall_at_100
|
322 |
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value: 96.207
|
323 |
- type: recall_at_1000
|
324 |
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value: 99.157
|
325 |
- type: recall_at_3
|
326 |
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value: 69.31
|
327 |
- type: recall_at_5
|
328 |
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value: 76.66
|
329 |
- task:
|
330 |
type: Retrieval
|
331 |
dataset:
|
|
|
336 |
revision: a1a333e290fe30b10f3f56498e3a0d911a693ced
|
337 |
metrics:
|
338 |
- type: map_at_1
|
339 |
+
value: 21.247
|
340 |
- type: map_at_10
|
341 |
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value: 64.793
|
342 |
- type: map_at_100
|
343 |
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value: 68.62899999999999
|
344 |
- type: map_at_1000
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345 |
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value: 68.718
|
346 |
- type: map_at_3
|
347 |
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value: 44.192
|
348 |
- type: map_at_5
|
349 |
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value: 55.435
|
350 |
- type: mrr_at_1
|
351 |
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value: 76.7
|
352 |
- type: mrr_at_10
|
353 |
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value: 84.22
|
354 |
- type: mrr_at_100
|
355 |
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value: 84.341
|
356 |
- type: mrr_at_1000
|
357 |
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value: 84.346
|
358 |
- type: mrr_at_3
|
359 |
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value: 83.42500000000001
|
360 |
- type: mrr_at_5
|
361 |
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value: 83.902
|
362 |
- type: ndcg_at_1
|
363 |
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value: 76.7
|
364 |
- type: ndcg_at_10
|
365 |
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value: 75.271
|
366 |
- type: ndcg_at_100
|
367 |
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value: 80.62
|
368 |
- type: ndcg_at_1000
|
369 |
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value: 81.45
|
370 |
- type: ndcg_at_3
|
371 |
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value: 72.803
|
372 |
- type: ndcg_at_5
|
373 |
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value: 71.694
|
374 |
- type: precision_at_1
|
375 |
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value: 76.7
|
376 |
- type: precision_at_10
|
377 |
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value: 36.925000000000004
|
378 |
- type: precision_at_100
|
379 |
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value: 4.675
|
380 |
- type: precision_at_1000
|
381 |
value: 0.48700000000000004
|
382 |
- type: precision_at_3
|
383 |
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value: 65.383
|
384 |
- type: precision_at_5
|
385 |
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value: 55.15
|
386 |
- type: recall_at_1
|
387 |
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value: 21.247
|
388 |
- type: recall_at_10
|
389 |
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value: 78.38300000000001
|
390 |
- type: recall_at_100
|
391 |
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value: 94.759
|
392 |
- type: recall_at_1000
|
393 |
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value: 98.907
|
394 |
- type: recall_at_3
|
395 |
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value: 48.04
|
396 |
- type: recall_at_5
|
397 |
value: 62.883
|
398 |
- task:
|
|
|
405 |
revision: 687de13dc7294d6fd9be10c6945f9e8fec8166b9
|
406 |
metrics:
|
407 |
- type: map_at_1
|
408 |
+
value: 42.0
|
409 |
- type: map_at_10
|
410 |
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value: 52.691
|
411 |
- type: map_at_100
|
412 |
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value: 53.456
|
413 |
- type: map_at_1000
|
414 |
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value: 53.480000000000004
|
415 |
- type: map_at_3
|
416 |
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value: 49.583
|
417 |
- type: map_at_5
|
418 |
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value: 51.723
|
419 |
- type: mrr_at_1
|
420 |
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value: 42.0
|
421 |
- type: mrr_at_10
|
422 |
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value: 52.691
|
423 |
- type: mrr_at_100
|
424 |
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value: 53.456
|
425 |
- type: mrr_at_1000
|
426 |
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value: 53.480000000000004
|
427 |
- type: mrr_at_3
|
428 |
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value: 49.583
|
429 |
- type: mrr_at_5
|
430 |
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value: 51.723
|
431 |
- type: ndcg_at_1
|
432 |
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value: 42.0
|
433 |
- type: ndcg_at_10
|
434 |
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value: 58.243
|
435 |
- type: ndcg_at_100
|
436 |
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value: 61.907999999999994
|
437 |
- type: ndcg_at_1000
|
438 |
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value: 62.483999999999995
|
439 |
- type: ndcg_at_3
|
440 |
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value: 52.03
|
441 |
- type: ndcg_at_5
|
442 |
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value: 55.85099999999999
|
443 |
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|
444 |
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value: 42.0
|
445 |
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|
446 |
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value: 7.580000000000001
|
447 |
- type: precision_at_100
|
448 |
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value: 0.928
|
449 |
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|
450 |
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value: 0.097
|
451 |
- type: precision_at_3
|
452 |
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value: 19.7
|
453 |
- type: precision_at_5
|
454 |
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value: 13.66
|
455 |
- type: recall_at_1
|
456 |
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value: 42.0
|
457 |
- type: recall_at_10
|
458 |
+
value: 75.8
|
459 |
- type: recall_at_100
|
460 |
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value: 92.80000000000001
|
461 |
- type: recall_at_1000
|
462 |
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value: 97.2
|
463 |
- type: recall_at_3
|
464 |
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value: 59.099999999999994
|
465 |
- type: recall_at_5
|
466 |
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value: 68.30000000000001
|
467 |
- task:
|
468 |
type: Classification
|
469 |
dataset:
|
|
|
474 |
revision: 421605374b29664c5fc098418fe20ada9bd55f8a
|
475 |
metrics:
|
476 |
- type: accuracy
|
477 |
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value: 44.86340900346287
|
478 |
- type: f1
|
479 |
+
value: 31.324006049353713
|
480 |
- task:
|
481 |
type: Classification
|
482 |
dataset:
|
|
|
487 |
revision: b7c64bd89eb87f8ded463478346f76731f07bf8b
|
488 |
metrics:
|
489 |
- type: accuracy
|
490 |
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value: 88.48030018761726
|
491 |
- type: ap
|
492 |
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value: 59.392058006606476
|
493 |
- type: f1
|
494 |
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value: 83.61333024672861
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495 |
- task:
|
496 |
type: STS
|
497 |
dataset:
|
|
|
502 |
revision: 17f9b096f80380fce5ed12a9be8be7784b337daf
|
503 |
metrics:
|
504 |
- type: cos_sim_pearson
|
505 |
+
value: 66.36852873686233
|
506 |
- type: cos_sim_spearman
|
507 |
+
value: 73.27371960661353
|
508 |
- type: euclidean_pearson
|
509 |
+
value: 71.38209904858738
|
510 |
- type: euclidean_spearman
|
511 |
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value: 73.27373512049904
|
512 |
- type: manhattan_pearson
|
513 |
+
value: 71.51557697058817
|
514 |
- type: manhattan_spearman
|
515 |
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value: 73.38956581066971
|
516 |
- task:
|
517 |
type: Reranking
|
518 |
dataset:
|
|
|
523 |
revision: 8e0c766dbe9e16e1d221116a3f36795fbade07f6
|
524 |
metrics:
|
525 |
- type: map
|
526 |
+
value: 19.57107231987867
|
527 |
- type: mrr
|
528 |
+
value: 18.224603174603175
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529 |
- task:
|
530 |
type: Retrieval
|
531 |
dataset:
|
|
|
536 |
revision: 539bbde593d947e2a124ba72651aafc09eb33fc2
|
537 |
metrics:
|
538 |
- type: map_at_1
|
539 |
+
value: 43.785000000000004
|
540 |
- type: map_at_10
|
541 |
+
value: 53.278000000000006
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542 |
- type: map_at_100
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543 |
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value: 53.946000000000005
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544 |
- type: map_at_1000
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545 |
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value: 53.983000000000004
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546 |
- type: map_at_3
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547 |
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value: 50.846999999999994
|
548 |
- type: map_at_5
|
549 |
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value: 52.286
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550 |
- type: mrr_at_1
|
551 |
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value: 45.559
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552 |
- type: mrr_at_10
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553 |
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value: 54.129000000000005
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554 |
- type: mrr_at_100
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555 |
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value: 54.732
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556 |
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557 |
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value: 54.766999999999996
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558 |
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559 |
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value: 51.885999999999996
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560 |
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561 |
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value: 53.212
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562 |
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563 |
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value: 45.559
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564 |
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565 |
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value: 57.909
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566 |
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568 |
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569 |
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value: 62.09400000000001
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570 |
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571 |
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value: 53.125
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572 |
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573 |
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value: 55.614
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574 |
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575 |
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value: 45.559
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576 |
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577 |
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value: 7.617
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578 |
- type: precision_at_100
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579 |
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value: 0.9199999999999999
|
580 |
- type: precision_at_1000
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581 |
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value: 0.101
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582 |
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|
583 |
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value: 20.707
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584 |
- type: precision_at_5
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585 |
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value: 13.730999999999998
|
586 |
- type: recall_at_1
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587 |
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value: 43.785000000000004
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588 |
- type: recall_at_10
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589 |
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value: 71.543
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590 |
- type: recall_at_100
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591 |
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value: 86.197
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592 |
- type: recall_at_1000
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593 |
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value: 94.305
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594 |
- type: recall_at_3
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595 |
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value: 58.677
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596 |
- type: recall_at_5
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597 |
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value: 64.62599999999999
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598 |
- task:
|
599 |
type: Classification
|
600 |
dataset:
|
|
|
605 |
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
|
606 |
metrics:
|
607 |
- type: accuracy
|
608 |
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value: 61.29455279085406
|
609 |
- type: f1
|
610 |
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value: 58.42865357114413
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611 |
- task:
|
612 |
type: Classification
|
613 |
dataset:
|
|
|
618 |
revision: 7d571f92784cd94a019292a1f45445077d0ef634
|
619 |
metrics:
|
620 |
- type: accuracy
|
621 |
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value: 66.89979825151312
|
622 |
- type: f1
|
623 |
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value: 66.6125514843663
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624 |
- task:
|
625 |
type: Retrieval
|
626 |
dataset:
|
|
|
631 |
revision: 2039188fb5800a9803ba5048df7b76e6fb151fc6
|
632 |
metrics:
|
633 |
- type: map_at_1
|
634 |
+
value: 44.7
|
635 |
- type: map_at_10
|
636 |
+
value: 51.307
|
637 |
- type: map_at_100
|
638 |
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value: 52.002
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639 |
- type: map_at_1000
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640 |
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value: 52.06699999999999
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641 |
- type: map_at_3
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642 |
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value: 49.55
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643 |
- type: map_at_5
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644 |
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value: 50.544999999999995
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645 |
- type: mrr_at_1
|
646 |
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value: 44.9
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647 |
- type: mrr_at_10
|
648 |
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value: 51.415
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649 |
- type: mrr_at_100
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650 |
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value: 52.111
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651 |
- type: mrr_at_1000
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652 |
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value: 52.175000000000004
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653 |
- type: mrr_at_3
|
654 |
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value: 49.683
|
655 |
- type: mrr_at_5
|
656 |
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value: 50.653000000000006
|
657 |
- type: ndcg_at_1
|
658 |
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value: 44.7
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659 |
- type: ndcg_at_10
|
660 |
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value: 54.778000000000006
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661 |
- type: ndcg_at_100
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662 |
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value: 58.526
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663 |
- type: ndcg_at_1000
|
664 |
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value: 60.187999999999995
|
665 |
- type: ndcg_at_3
|
666 |
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value: 51.129999999999995
|
667 |
- type: ndcg_at_5
|
668 |
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value: 52.933
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669 |
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|
670 |
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value: 44.7
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671 |
- type: precision_at_10
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672 |
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value: 6.58
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673 |
- type: precision_at_100
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674 |
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value: 0.8420000000000001
|
675 |
- type: precision_at_1000
|
676 |
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value: 0.097
|
677 |
- type: precision_at_3
|
678 |
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value: 18.567
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679 |
- type: precision_at_5
|
680 |
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value: 12.02
|
681 |
- type: recall_at_1
|
682 |
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value: 44.7
|
683 |
- type: recall_at_10
|
684 |
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value: 65.8
|
685 |
- type: recall_at_100
|
686 |
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value: 84.2
|
687 |
- type: recall_at_1000
|
688 |
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value: 97.2
|
689 |
- type: recall_at_3
|
690 |
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value: 55.7
|
691 |
- type: recall_at_5
|
692 |
+
value: 60.099999999999994
|
693 |
- task:
|
694 |
type: Retrieval
|
695 |
dataset:
|
|
|
700 |
revision: None
|
701 |
metrics:
|
702 |
- type: map_at_1
|
703 |
+
value: 7.625
|
704 |
- type: map_at_10
|
705 |
+
value: 10.238
|
706 |
- type: map_at_100
|
707 |
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value: 10.885
|
708 |
- type: map_at_1000
|
709 |
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value: 10.958
|
710 |
- type: map_at_3
|
711 |
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value: 9.292
|
712 |
- type: map_at_5
|
713 |
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value: 9.91
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714 |
- type: mrr_at_1
|
715 |
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value: 7.625
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716 |
- type: mrr_at_10
|
717 |
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value: 10.238
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718 |
- type: mrr_at_100
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719 |
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value: 10.885
|
720 |
- type: mrr_at_1000
|
721 |
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value: 10.958
|
722 |
- type: mrr_at_3
|
723 |
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value: 9.292
|
724 |
- type: mrr_at_5
|
725 |
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value: 9.91
|
726 |
- type: ndcg_at_1
|
727 |
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value: 7.625
|
728 |
- type: ndcg_at_10
|
729 |
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value: 11.784
|
730 |
- type: ndcg_at_100
|
731 |
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value: 15.133
|
732 |
- type: ndcg_at_1000
|
733 |
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value: 17.511
|
734 |
- type: ndcg_at_3
|
735 |
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value: 9.857000000000001
|
736 |
- type: ndcg_at_5
|
737 |
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value: 10.981
|
738 |
- type: precision_at_1
|
739 |
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value: 7.625
|
740 |
- type: precision_at_10
|
741 |
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value: 1.675
|
742 |
- type: precision_at_100
|
743 |
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value: 0.329
|
744 |
- type: precision_at_1000
|
745 |
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value: 0.053
|
746 |
- type: precision_at_3
|
747 |
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value: 3.833
|
748 |
- type: precision_at_5
|
749 |
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value: 2.85
|
750 |
- type: recall_at_1
|
751 |
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value: 7.625
|
752 |
- type: recall_at_10
|
753 |
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value: 16.75
|
754 |
- type: recall_at_100
|
755 |
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value: 32.875
|
756 |
- type: recall_at_1000
|
757 |
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value: 52.625
|
758 |
- type: recall_at_3
|
759 |
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value: 11.5
|
760 |
- type: recall_at_5
|
761 |
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value: 14.249999999999998
|
762 |
- task:
|
763 |
type: Classification
|
764 |
dataset:
|
|
|
769 |
revision: 46958b007a63fdbf239b7672c25d0bea67b5ea1a
|
770 |
metrics:
|
771 |
- type: accuracy
|
772 |
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value: 78.45666666666666
|
773 |
- type: f1
|
774 |
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value: 78.06393644109178
|
775 |
- task:
|
776 |
type: PairClassification
|
777 |
dataset:
|
|
|
782 |
revision: 66e76a618a34d6d565d5538088562851e6daa7ec
|
783 |
metrics:
|
784 |
- type: cos_sim_accuracy
|
785 |
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value: 59.88088792636708
|
786 |
- type: cos_sim_ap
|
787 |
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value: 59.993466246406854
|
788 |
- type: cos_sim_f1
|
789 |
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value: 69.33333333333334
|
790 |
- type: cos_sim_precision
|
791 |
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value: 54.23122765196663
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792 |
- type: cos_sim_recall
|
793 |
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value: 96.09292502639916
|
794 |
- type: dot_accuracy
|
795 |
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value: 59.88088792636708
|
796 |
- type: dot_ap
|
797 |
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value: 59.99351215786742
|
798 |
- type: dot_f1
|
799 |
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value: 69.33333333333334
|
800 |
- type: dot_precision
|
801 |
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value: 54.23122765196663
|
802 |
- type: dot_recall
|
803 |
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value: 96.09292502639916
|
804 |
- type: euclidean_accuracy
|
805 |
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value: 59.88088792636708
|
806 |
- type: euclidean_ap
|
807 |
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value: 59.993466246406854
|
808 |
- type: euclidean_f1
|
809 |
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value: 69.33333333333334
|
810 |
- type: euclidean_precision
|
811 |
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value: 54.23122765196663
|
812 |
- type: euclidean_recall
|
813 |
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value: 96.09292502639916
|
814 |
- type: manhattan_accuracy
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815 |
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value: 59.989171629669734
|
816 |
- type: manhattan_ap
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817 |
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value: 60.06745167956717
|
818 |
- type: manhattan_f1
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819 |
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value: 69.37381404174573
|
820 |
- type: manhattan_precision
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821 |
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value: 54.14691943127961
|
822 |
- type: manhattan_recall
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823 |
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value: 96.51531151003168
|
824 |
- type: max_accuracy
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825 |
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value: 59.989171629669734
|
826 |
- type: max_ap
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827 |
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value: 60.06745167956717
|
828 |
- type: max_f1
|
829 |
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value: 69.37381404174573
|
830 |
- task:
|
831 |
type: Classification
|
832 |
dataset:
|
|
|
837 |
revision: e610f2ebd179a8fda30ae534c3878750a96db120
|
838 |
metrics:
|
839 |
- type: accuracy
|
840 |
+
value: 92.58
|
841 |
- type: ap
|
842 |
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value: 90.58624365698103
|
843 |
- type: f1
|
844 |
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|
845 |
- task:
|
846 |
type: STS
|
847 |
dataset:
|
|
|
852 |
revision: 9c6a90e430ac22b5779fb019a23e820b11a8b5e1
|
853 |
metrics:
|
854 |
- type: cos_sim_pearson
|
855 |
+
value: 15.428347645738844
|
856 |
- type: cos_sim_spearman
|
857 |
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value: 18.54916824520863
|
858 |
- type: euclidean_pearson
|
859 |
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value: 18.525706701701317
|
860 |
- type: euclidean_spearman
|
861 |
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value: 18.564855538117524
|
862 |
- type: manhattan_pearson
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863 |
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value: 18.54511262151164
|
864 |
- type: manhattan_spearman
|
865 |
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value: 18.587848451111213
|
866 |
- task:
|
867 |
type: PairClassification
|
868 |
dataset:
|
|
|
873 |
revision: 8a04d940a42cd40658986fdd8e3da561533a3646
|
874 |
metrics:
|
875 |
- type: cos_sim_accuracy
|
876 |
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value: 60.3
|
877 |
- type: cos_sim_ap
|
878 |
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value: 57.92869006380703
|
879 |
- type: cos_sim_f1
|
880 |
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value: 62.31681786461968
|
881 |
- type: cos_sim_precision
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882 |
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value: 45.283975659229206
|
883 |
- type: cos_sim_recall
|
884 |
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value: 99.88814317673378
|
885 |
- type: dot_accuracy
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886 |
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value: 60.3
|
887 |
- type: dot_ap
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888 |
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|
889 |
- type: dot_f1
|
890 |
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|
891 |
- type: dot_precision
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892 |
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value: 45.283975659229206
|
893 |
- type: dot_recall
|
894 |
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value: 99.88814317673378
|
895 |
- type: euclidean_accuracy
|
896 |
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value: 60.3
|
897 |
- type: euclidean_ap
|
898 |
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value: 57.92869006380703
|
899 |
- type: euclidean_f1
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900 |
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value: 62.31681786461968
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901 |
- type: euclidean_precision
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902 |
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value: 45.283975659229206
|
903 |
- type: euclidean_recall
|
904 |
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value: 99.88814317673378
|
905 |
- type: manhattan_accuracy
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906 |
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value: 60.25
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907 |
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908 |
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909 |
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911 |
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912 |
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value: 45.283975659229206
|
913 |
- type: manhattan_recall
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914 |
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|
915 |
- type: max_accuracy
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916 |
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value: 60.3
|
917 |
- type: max_ap
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918 |
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value: 57.929597845689706
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|
921 |
- task:
|
922 |
type: STS
|
923 |
dataset:
|
|
|
928 |
revision: 790b0510dc52b1553e8c49f3d2afb48c0e5c48b7
|
929 |
metrics:
|
930 |
- type: cos_sim_pearson
|
931 |
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value: 28.445664430656038
|
932 |
- type: cos_sim_spearman
|
933 |
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value: 29.599326690902288
|
934 |
- type: euclidean_pearson
|
935 |
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value: 27.900455284977017
|
936 |
- type: euclidean_spearman
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937 |
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value: 29.599947224705264
|
938 |
- type: manhattan_pearson
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939 |
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value: 28.101656918683116
|
940 |
- type: manhattan_spearman
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941 |
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value: 29.78083888978687
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942 |
- task:
|
943 |
type: STS
|
944 |
dataset:
|
|
|
949 |
revision: eea2b4fe26a775864c896887d910b76a8098ad3f
|
950 |
metrics:
|
951 |
- type: cos_sim_pearson
|
952 |
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value: 61.13774633735679
|
953 |
- type: cos_sim_spearman
|
954 |
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value: 65.43749616084263
|
955 |
- type: euclidean_pearson
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956 |
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value: 63.42122949030793
|
957 |
- type: euclidean_spearman
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958 |
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value: 65.43749616084263
|
959 |
- type: manhattan_pearson
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960 |
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value: 63.78466267937151
|
961 |
- type: manhattan_spearman
|
962 |
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value: 65.4252196465631
|
963 |
- task:
|
964 |
type: STS
|
965 |
dataset:
|
|
|
970 |
revision: 0cde68302b3541bb8b3c340dc0644b0b745b3dc0
|
971 |
metrics:
|
972 |
- type: cos_sim_pearson
|
973 |
+
value: 66.43725663481563
|
974 |
- type: cos_sim_spearman
|
975 |
+
value: 66.91073455354187
|
976 |
- type: euclidean_pearson
|
977 |
+
value: 67.25178758750022
|
978 |
- type: euclidean_spearman
|
979 |
+
value: 66.91129699608939
|
980 |
- type: manhattan_pearson
|
981 |
+
value: 67.33381999971951
|
982 |
- type: manhattan_spearman
|
983 |
+
value: 66.9990458174529
|
984 |
- task:
|
985 |
type: Reranking
|
986 |
dataset:
|
|
|
991 |
revision: 76631901a18387f85eaa53e5450019b87ad58ef9
|
992 |
metrics:
|
993 |
- type: map
|
994 |
+
value: 64.31327281684898
|
995 |
- type: mrr
|
996 |
+
value: 73.58095291829211
|
997 |
- task:
|
998 |
type: Retrieval
|
999 |
dataset:
|
|
|
1004 |
revision: 8731a845f1bf500a4f111cf1070785c793d10e64
|
1005 |
metrics:
|
1006 |
- type: map_at_1
|
1007 |
+
value: 20.961
|
1008 |
- type: map_at_10
|
1009 |
+
value: 59.065
|
1010 |
- type: map_at_100
|
1011 |
+
value: 63.544
|
1012 |
- type: map_at_1000
|
1013 |
+
value: 63.681
|
1014 |
- type: map_at_3
|
1015 |
+
value: 40.849999999999994
|
1016 |
- type: map_at_5
|
1017 |
+
value: 50.268
|
1018 |
- type: mrr_at_1
|
1019 |
+
value: 74.934
|
1020 |
- type: mrr_at_10
|
1021 |
+
value: 80.571
|
1022 |
- type: mrr_at_100
|
1023 |
+
value: 80.814
|
1024 |
- type: mrr_at_1000
|
1025 |
+
value: 80.82300000000001
|
1026 |
- type: mrr_at_3
|
1027 |
+
value: 79.449
|
1028 |
- type: mrr_at_5
|
1029 |
+
value: 80.13
|
1030 |
- type: ndcg_at_1
|
1031 |
+
value: 74.934
|
1032 |
- type: ndcg_at_10
|
1033 |
+
value: 69.215
|
1034 |
- type: ndcg_at_100
|
1035 |
+
value: 75.61099999999999
|
1036 |
- type: ndcg_at_1000
|
1037 |
+
value: 77.03999999999999
|
1038 |
- type: ndcg_at_3
|
1039 |
+
value: 70.04899999999999
|
1040 |
- type: ndcg_at_5
|
1041 |
+
value: 68.50699999999999
|
1042 |
- type: precision_at_1
|
1043 |
+
value: 74.934
|
1044 |
- type: precision_at_10
|
1045 |
+
value: 35.569
|
1046 |
- type: precision_at_100
|
1047 |
+
value: 4.757
|
1048 |
- type: precision_at_1000
|
1049 |
+
value: 0.509
|
1050 |
- type: precision_at_3
|
1051 |
+
value: 61.802
|
1052 |
- type: precision_at_5
|
1053 |
+
value: 51.882
|
1054 |
- type: recall_at_1
|
1055 |
+
value: 20.961
|
1056 |
- type: recall_at_10
|
1057 |
+
value: 69.626
|
1058 |
- type: recall_at_100
|
1059 |
+
value: 89.464
|
1060 |
- type: recall_at_1000
|
1061 |
+
value: 96.721
|
1062 |
- type: recall_at_3
|
1063 |
+
value: 43.608999999999995
|
1064 |
- type: recall_at_5
|
1065 |
+
value: 55.724
|
1066 |
- task:
|
1067 |
type: Classification
|
1068 |
dataset:
|
|
|
1073 |
revision: 317f262bf1e6126357bbe89e875451e4b0938fe4
|
1074 |
metrics:
|
1075 |
- type: accuracy
|
1076 |
+
value: 50.01800000000001
|
1077 |
- type: f1
|
1078 |
+
value: 48.262341643251936
|
1079 |
- task:
|
1080 |
type: Clustering
|
1081 |
dataset:
|
|
|
1086 |
revision: 5798586b105c0434e4f0fe5e767abe619442cf93
|
1087 |
metrics:
|
1088 |
- type: v_measure
|
1089 |
+
value: 60.68748256831344
|
1090 |
- task:
|
1091 |
type: Clustering
|
1092 |
dataset:
|
|
|
1097 |
revision: 8a8b2caeda43f39e13c4bc5bea0f8a667896e10d
|
1098 |
metrics:
|
1099 |
- type: v_measure
|
1100 |
+
value: 56.73298697800912
|
1101 |
- task:
|
1102 |
type: Retrieval
|
1103 |
dataset:
|
|
|
1108 |
revision: 58c2597a5943a2ba48f4668c3b90d796283c5639
|
1109 |
metrics:
|
1110 |
- type: map_at_1
|
1111 |
+
value: 46.9
|
1112 |
- type: map_at_10
|
1113 |
+
value: 57.849
|
1114 |
- type: map_at_100
|
1115 |
+
value: 58.532
|
1116 |
- type: map_at_1000
|
1117 |
+
value: 58.553
|
1118 |
- type: map_at_3
|
1119 |
+
value: 55.467
|
1120 |
- type: map_at_5
|
1121 |
+
value: 56.92700000000001
|
1122 |
- type: mrr_at_1
|
1123 |
+
value: 46.9
|
1124 |
- type: mrr_at_10
|
1125 |
+
value: 57.849
|
1126 |
- type: mrr_at_100
|
1127 |
+
value: 58.532
|
1128 |
- type: mrr_at_1000
|
1129 |
+
value: 58.553
|
1130 |
- type: mrr_at_3
|
1131 |
+
value: 55.467
|
1132 |
- type: mrr_at_5
|
1133 |
+
value: 56.92700000000001
|
1134 |
- type: ndcg_at_1
|
1135 |
+
value: 46.9
|
1136 |
- type: ndcg_at_10
|
1137 |
+
value: 63.09
|
1138 |
- type: ndcg_at_100
|
1139 |
+
value: 66.43
|
1140 |
- type: ndcg_at_1000
|
1141 |
+
value: 66.949
|
1142 |
- type: ndcg_at_3
|
1143 |
+
value: 58.226
|
1144 |
- type: ndcg_at_5
|
1145 |
+
value: 60.838
|
1146 |
- type: precision_at_1
|
1147 |
+
value: 46.9
|
1148 |
- type: precision_at_10
|
1149 |
+
value: 7.95
|
1150 |
- type: precision_at_100
|
1151 |
+
value: 0.951
|
1152 |
- type: precision_at_1000
|
1153 |
+
value: 0.099
|
1154 |
- type: precision_at_3
|
1155 |
+
value: 22.067
|
1156 |
- type: precision_at_5
|
1157 |
+
value: 14.499999999999998
|
1158 |
- type: recall_at_1
|
1159 |
+
value: 46.9
|
1160 |
- type: recall_at_10
|
1161 |
+
value: 79.5
|
1162 |
- type: recall_at_100
|
1163 |
+
value: 95.1
|
1164 |
- type: recall_at_1000
|
1165 |
+
value: 99.1
|
1166 |
- type: recall_at_3
|
1167 |
+
value: 66.2
|
1168 |
- type: recall_at_5
|
1169 |
+
value: 72.5
|
1170 |
- task:
|
1171 |
type: Classification
|
1172 |
dataset:
|
|
|
1177 |
revision: 339287def212450dcaa9df8c22bf93e9980c7023
|
1178 |
metrics:
|
1179 |
- type: accuracy
|
1180 |
+
value: 89.09
|
1181 |
- type: ap
|
1182 |
+
value: 74.68093732384233
|
1183 |
- type: f1
|
1184 |
+
value: 87.7768409829789
|
1185 |
---
|