Sentence Similarity
sentence-transformers
PyTorch
Transformers
English
t5
text-embedding
embeddings
information-retrieval
beir
text-classification
language-model
text-clustering
text-semantic-similarity
text-evaluation
prompt-retrieval
text-reranking
feature-extraction
English
Sentence Similarity
natural_questions
ms_marco
fever
hotpot_qa
mteb
Eval Results (legacy)
Commit ·
ff5c15b
1
Parent(s): 7269a36
Update README.md
Browse files
README.md
CHANGED
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@@ -1727,65 +1727,65 @@ model-index:
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| 1727 |
revision: None
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| 1728 |
metrics:
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| 1729 |
- type: map_at_1
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| 1730 |
-
value:
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| 1731 |
- type: map_at_10
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| 1732 |
-
value:
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| 1733 |
- type: map_at_100
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| 1734 |
-
value:
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| 1735 |
- type: map_at_1000
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| 1736 |
-
value: 43.
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| 1737 |
- type: map_at_3
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| 1738 |
-
value: 37.
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| 1739 |
- type: map_at_5
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| 1740 |
-
value:
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| 1741 |
- type: mrr_at_1
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| 1742 |
-
value: 30.
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| 1743 |
- type: mrr_at_10
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| 1744 |
-
value: 44.
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| 1745 |
- type: mrr_at_100
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| 1746 |
-
value: 45.
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| 1747 |
- type: mrr_at_1000
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| 1748 |
-
value: 45.
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| 1749 |
- type: mrr_at_3
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| 1750 |
-
value: 40.
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| 1751 |
- type: mrr_at_5
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| 1752 |
-
value:
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| 1753 |
- type: ndcg_at_1
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| 1754 |
-
value: 30.
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| 1755 |
- type: ndcg_at_10
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| 1756 |
-
value:
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| 1757 |
- type: ndcg_at_100
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| 1758 |
-
value: 54.
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| 1759 |
- type: ndcg_at_1000
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| 1760 |
-
value: 55.
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| 1761 |
- type: ndcg_at_3
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| 1762 |
-
value: 41.
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| 1763 |
- type: ndcg_at_5
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| 1764 |
-
value:
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| 1765 |
- type: precision_at_1
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| 1766 |
-
value: 30.
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| 1767 |
- type: precision_at_10
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| 1768 |
-
value: 8.
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| 1769 |
- type: precision_at_100
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| 1770 |
value: 1.124
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| 1771 |
- type: precision_at_1000
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| 1772 |
value: 0.12
|
| 1773 |
- type: precision_at_3
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| 1774 |
-
value: 18.
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| 1775 |
- type: precision_at_5
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| 1776 |
-
value: 14.
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| 1777 |
- type: recall_at_1
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| 1778 |
-
value:
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| 1779 |
- type: recall_at_10
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| 1780 |
-
value: 71.
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| 1781 |
- type: recall_at_100
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| 1782 |
-
value: 92.
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| 1783 |
- type: recall_at_1000
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| 1784 |
-
value: 98.
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| 1785 |
- type: recall_at_3
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| 1786 |
-
value: 49.
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| 1787 |
- type: recall_at_5
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| 1788 |
-
value:
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| 1789 |
- task:
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| 1790 |
type: Retrieval
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| 1791 |
dataset:
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| 1727 |
revision: None
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| 1728 |
metrics:
|
| 1729 |
- type: map_at_1
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| 1730 |
+
value: 27.378000000000004
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| 1731 |
- type: map_at_10
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| 1732 |
+
value: 42.178
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| 1733 |
- type: map_at_100
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| 1734 |
+
value: 43.32
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| 1735 |
- type: map_at_1000
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| 1736 |
+
value: 43.358000000000004
|
| 1737 |
- type: map_at_3
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| 1738 |
+
value: 37.474000000000004
|
| 1739 |
- type: map_at_5
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| 1740 |
+
value: 40.333000000000006
|
| 1741 |
- type: mrr_at_1
|
| 1742 |
+
value: 30.823
|
| 1743 |
- type: mrr_at_10
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| 1744 |
+
value: 44.626
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| 1745 |
- type: mrr_at_100
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| 1746 |
+
value: 45.494
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| 1747 |
- type: mrr_at_1000
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| 1748 |
+
value: 45.519
|
| 1749 |
- type: mrr_at_3
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| 1750 |
+
value: 40.585
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| 1751 |
- type: mrr_at_5
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| 1752 |
+
value: 43.146
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| 1753 |
- type: ndcg_at_1
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| 1754 |
+
value: 30.794
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| 1755 |
- type: ndcg_at_10
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| 1756 |
+
value: 50.099000000000004
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| 1757 |
- type: ndcg_at_100
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| 1758 |
+
value: 54.900999999999996
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| 1759 |
- type: ndcg_at_1000
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| 1760 |
+
value: 55.69499999999999
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| 1761 |
- type: ndcg_at_3
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| 1762 |
+
value: 41.238
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| 1763 |
- type: ndcg_at_5
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| 1764 |
+
value: 46.081
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| 1765 |
- type: precision_at_1
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| 1766 |
+
value: 30.794
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| 1767 |
- type: precision_at_10
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| 1768 |
+
value: 8.549
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| 1769 |
- type: precision_at_100
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| 1770 |
value: 1.124
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| 1771 |
- type: precision_at_1000
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| 1772 |
value: 0.12
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| 1773 |
- type: precision_at_3
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| 1774 |
+
value: 18.926000000000002
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| 1775 |
- type: precision_at_5
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| 1776 |
+
value: 14.16
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| 1777 |
- type: recall_at_1
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| 1778 |
+
value: 27.378000000000004
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| 1779 |
- type: recall_at_10
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| 1780 |
+
value: 71.842
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| 1781 |
- type: recall_at_100
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| 1782 |
+
value: 92.565
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| 1783 |
- type: recall_at_1000
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| 1784 |
+
value: 98.402
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| 1785 |
- type: recall_at_3
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| 1786 |
+
value: 49.053999999999995
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| 1787 |
- type: recall_at_5
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| 1788 |
+
value: 60.207
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| 1789 |
- task:
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| 1790 |
type: Retrieval
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| 1791 |
dataset:
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