wangjinzzhong
commited on
Commit
•
acd791e
1
Parent(s):
60ba0ea
Upload README.md with huggingface_hub
Browse files
README.md
ADDED
@@ -0,0 +1,2545 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
tags:
|
3 |
+
- sentence-transformers
|
4 |
+
- feature-extraction
|
5 |
+
- sentence-similarity
|
6 |
+
- transformers
|
7 |
+
- mteb
|
8 |
+
- llama-cpp
|
9 |
+
- gguf-my-repo
|
10 |
+
license: mit
|
11 |
+
language:
|
12 |
+
- en
|
13 |
+
base_model: BAAI/bge-small-en-v1.5
|
14 |
+
model-index:
|
15 |
+
- name: bge-small-en-v1.5
|
16 |
+
results:
|
17 |
+
- task:
|
18 |
+
type: Classification
|
19 |
+
dataset:
|
20 |
+
name: MTEB AmazonCounterfactualClassification (en)
|
21 |
+
type: mteb/amazon_counterfactual
|
22 |
+
config: en
|
23 |
+
split: test
|
24 |
+
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
|
25 |
+
metrics:
|
26 |
+
- type: accuracy
|
27 |
+
value: 73.79104477611939
|
28 |
+
- type: ap
|
29 |
+
value: 37.21923821573361
|
30 |
+
- type: f1
|
31 |
+
value: 68.0914945617093
|
32 |
+
- task:
|
33 |
+
type: Classification
|
34 |
+
dataset:
|
35 |
+
name: MTEB AmazonPolarityClassification
|
36 |
+
type: mteb/amazon_polarity
|
37 |
+
config: default
|
38 |
+
split: test
|
39 |
+
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
|
40 |
+
metrics:
|
41 |
+
- type: accuracy
|
42 |
+
value: 92.75377499999999
|
43 |
+
- type: ap
|
44 |
+
value: 89.46766124546022
|
45 |
+
- type: f1
|
46 |
+
value: 92.73884001331487
|
47 |
+
- task:
|
48 |
+
type: Classification
|
49 |
+
dataset:
|
50 |
+
name: MTEB AmazonReviewsClassification (en)
|
51 |
+
type: mteb/amazon_reviews_multi
|
52 |
+
config: en
|
53 |
+
split: test
|
54 |
+
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
|
55 |
+
metrics:
|
56 |
+
- type: accuracy
|
57 |
+
value: 46.986
|
58 |
+
- type: f1
|
59 |
+
value: 46.55936786727896
|
60 |
+
- task:
|
61 |
+
type: Retrieval
|
62 |
+
dataset:
|
63 |
+
name: MTEB ArguAna
|
64 |
+
type: arguana
|
65 |
+
config: default
|
66 |
+
split: test
|
67 |
+
revision: None
|
68 |
+
metrics:
|
69 |
+
- type: map_at_1
|
70 |
+
value: 35.846000000000004
|
71 |
+
- type: map_at_10
|
72 |
+
value: 51.388
|
73 |
+
- type: map_at_100
|
74 |
+
value: 52.132999999999996
|
75 |
+
- type: map_at_1000
|
76 |
+
value: 52.141000000000005
|
77 |
+
- type: map_at_3
|
78 |
+
value: 47.037
|
79 |
+
- type: map_at_5
|
80 |
+
value: 49.579
|
81 |
+
- type: mrr_at_1
|
82 |
+
value: 36.558
|
83 |
+
- type: mrr_at_10
|
84 |
+
value: 51.658
|
85 |
+
- type: mrr_at_100
|
86 |
+
value: 52.402
|
87 |
+
- type: mrr_at_1000
|
88 |
+
value: 52.410000000000004
|
89 |
+
- type: mrr_at_3
|
90 |
+
value: 47.345
|
91 |
+
- type: mrr_at_5
|
92 |
+
value: 49.797999999999995
|
93 |
+
- type: ndcg_at_1
|
94 |
+
value: 35.846000000000004
|
95 |
+
- type: ndcg_at_10
|
96 |
+
value: 59.550000000000004
|
97 |
+
- type: ndcg_at_100
|
98 |
+
value: 62.596
|
99 |
+
- type: ndcg_at_1000
|
100 |
+
value: 62.759
|
101 |
+
- type: ndcg_at_3
|
102 |
+
value: 50.666999999999994
|
103 |
+
- type: ndcg_at_5
|
104 |
+
value: 55.228
|
105 |
+
- type: precision_at_1
|
106 |
+
value: 35.846000000000004
|
107 |
+
- type: precision_at_10
|
108 |
+
value: 8.542
|
109 |
+
- type: precision_at_100
|
110 |
+
value: 0.984
|
111 |
+
- type: precision_at_1000
|
112 |
+
value: 0.1
|
113 |
+
- type: precision_at_3
|
114 |
+
value: 20.389
|
115 |
+
- type: precision_at_5
|
116 |
+
value: 14.438
|
117 |
+
- type: recall_at_1
|
118 |
+
value: 35.846000000000004
|
119 |
+
- type: recall_at_10
|
120 |
+
value: 85.42
|
121 |
+
- type: recall_at_100
|
122 |
+
value: 98.43499999999999
|
123 |
+
- type: recall_at_1000
|
124 |
+
value: 99.644
|
125 |
+
- type: recall_at_3
|
126 |
+
value: 61.166
|
127 |
+
- type: recall_at_5
|
128 |
+
value: 72.191
|
129 |
+
- task:
|
130 |
+
type: Clustering
|
131 |
+
dataset:
|
132 |
+
name: MTEB ArxivClusteringP2P
|
133 |
+
type: mteb/arxiv-clustering-p2p
|
134 |
+
config: default
|
135 |
+
split: test
|
136 |
+
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
|
137 |
+
metrics:
|
138 |
+
- type: v_measure
|
139 |
+
value: 47.402770198163594
|
140 |
+
- task:
|
141 |
+
type: Clustering
|
142 |
+
dataset:
|
143 |
+
name: MTEB ArxivClusteringS2S
|
144 |
+
type: mteb/arxiv-clustering-s2s
|
145 |
+
config: default
|
146 |
+
split: test
|
147 |
+
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
|
148 |
+
metrics:
|
149 |
+
- type: v_measure
|
150 |
+
value: 40.01545436974177
|
151 |
+
- task:
|
152 |
+
type: Reranking
|
153 |
+
dataset:
|
154 |
+
name: MTEB AskUbuntuDupQuestions
|
155 |
+
type: mteb/askubuntudupquestions-reranking
|
156 |
+
config: default
|
157 |
+
split: test
|
158 |
+
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
|
159 |
+
metrics:
|
160 |
+
- type: map
|
161 |
+
value: 62.586465273207196
|
162 |
+
- type: mrr
|
163 |
+
value: 74.42169019038825
|
164 |
+
- task:
|
165 |
+
type: STS
|
166 |
+
dataset:
|
167 |
+
name: MTEB BIOSSES
|
168 |
+
type: mteb/biosses-sts
|
169 |
+
config: default
|
170 |
+
split: test
|
171 |
+
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
|
172 |
+
metrics:
|
173 |
+
- type: cos_sim_pearson
|
174 |
+
value: 85.1891186537969
|
175 |
+
- type: cos_sim_spearman
|
176 |
+
value: 83.75492046087288
|
177 |
+
- type: euclidean_pearson
|
178 |
+
value: 84.11766204805357
|
179 |
+
- type: euclidean_spearman
|
180 |
+
value: 84.01456493126516
|
181 |
+
- type: manhattan_pearson
|
182 |
+
value: 84.2132950502772
|
183 |
+
- type: manhattan_spearman
|
184 |
+
value: 83.89227298813377
|
185 |
+
- task:
|
186 |
+
type: Classification
|
187 |
+
dataset:
|
188 |
+
name: MTEB Banking77Classification
|
189 |
+
type: mteb/banking77
|
190 |
+
config: default
|
191 |
+
split: test
|
192 |
+
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
|
193 |
+
metrics:
|
194 |
+
- type: accuracy
|
195 |
+
value: 85.74025974025975
|
196 |
+
- type: f1
|
197 |
+
value: 85.71493566466381
|
198 |
+
- task:
|
199 |
+
type: Clustering
|
200 |
+
dataset:
|
201 |
+
name: MTEB BiorxivClusteringP2P
|
202 |
+
type: mteb/biorxiv-clustering-p2p
|
203 |
+
config: default
|
204 |
+
split: test
|
205 |
+
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
|
206 |
+
metrics:
|
207 |
+
- type: v_measure
|
208 |
+
value: 38.467181385006434
|
209 |
+
- task:
|
210 |
+
type: Clustering
|
211 |
+
dataset:
|
212 |
+
name: MTEB BiorxivClusteringS2S
|
213 |
+
type: mteb/biorxiv-clustering-s2s
|
214 |
+
config: default
|
215 |
+
split: test
|
216 |
+
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
|
217 |
+
metrics:
|
218 |
+
- type: v_measure
|
219 |
+
value: 34.719496037339056
|
220 |
+
- task:
|
221 |
+
type: Retrieval
|
222 |
+
dataset:
|
223 |
+
name: MTEB CQADupstackAndroidRetrieval
|
224 |
+
type: BeIR/cqadupstack
|
225 |
+
config: default
|
226 |
+
split: test
|
227 |
+
revision: None
|
228 |
+
metrics:
|
229 |
+
- type: map_at_1
|
230 |
+
value: 29.587000000000003
|
231 |
+
- type: map_at_10
|
232 |
+
value: 41.114
|
233 |
+
- type: map_at_100
|
234 |
+
value: 42.532
|
235 |
+
- type: map_at_1000
|
236 |
+
value: 42.661
|
237 |
+
- type: map_at_3
|
238 |
+
value: 37.483
|
239 |
+
- type: map_at_5
|
240 |
+
value: 39.652
|
241 |
+
- type: mrr_at_1
|
242 |
+
value: 36.338
|
243 |
+
- type: mrr_at_10
|
244 |
+
value: 46.763
|
245 |
+
- type: mrr_at_100
|
246 |
+
value: 47.393
|
247 |
+
- type: mrr_at_1000
|
248 |
+
value: 47.445
|
249 |
+
- type: mrr_at_3
|
250 |
+
value: 43.538
|
251 |
+
- type: mrr_at_5
|
252 |
+
value: 45.556000000000004
|
253 |
+
- type: ndcg_at_1
|
254 |
+
value: 36.338
|
255 |
+
- type: ndcg_at_10
|
256 |
+
value: 47.658
|
257 |
+
- type: ndcg_at_100
|
258 |
+
value: 52.824000000000005
|
259 |
+
- type: ndcg_at_1000
|
260 |
+
value: 54.913999999999994
|
261 |
+
- type: ndcg_at_3
|
262 |
+
value: 41.989
|
263 |
+
- type: ndcg_at_5
|
264 |
+
value: 44.944
|
265 |
+
- type: precision_at_1
|
266 |
+
value: 36.338
|
267 |
+
- type: precision_at_10
|
268 |
+
value: 9.156
|
269 |
+
- type: precision_at_100
|
270 |
+
value: 1.4789999999999999
|
271 |
+
- type: precision_at_1000
|
272 |
+
value: 0.196
|
273 |
+
- type: precision_at_3
|
274 |
+
value: 20.076
|
275 |
+
- type: precision_at_5
|
276 |
+
value: 14.85
|
277 |
+
- type: recall_at_1
|
278 |
+
value: 29.587000000000003
|
279 |
+
- type: recall_at_10
|
280 |
+
value: 60.746
|
281 |
+
- type: recall_at_100
|
282 |
+
value: 82.157
|
283 |
+
- type: recall_at_1000
|
284 |
+
value: 95.645
|
285 |
+
- type: recall_at_3
|
286 |
+
value: 44.821
|
287 |
+
- type: recall_at_5
|
288 |
+
value: 52.819
|
289 |
+
- type: map_at_1
|
290 |
+
value: 30.239
|
291 |
+
- type: map_at_10
|
292 |
+
value: 39.989000000000004
|
293 |
+
- type: map_at_100
|
294 |
+
value: 41.196
|
295 |
+
- type: map_at_1000
|
296 |
+
value: 41.325
|
297 |
+
- type: map_at_3
|
298 |
+
value: 37.261
|
299 |
+
- type: map_at_5
|
300 |
+
value: 38.833
|
301 |
+
- type: mrr_at_1
|
302 |
+
value: 37.516
|
303 |
+
- type: mrr_at_10
|
304 |
+
value: 46.177
|
305 |
+
- type: mrr_at_100
|
306 |
+
value: 46.806
|
307 |
+
- type: mrr_at_1000
|
308 |
+
value: 46.849000000000004
|
309 |
+
- type: mrr_at_3
|
310 |
+
value: 44.002
|
311 |
+
- type: mrr_at_5
|
312 |
+
value: 45.34
|
313 |
+
- type: ndcg_at_1
|
314 |
+
value: 37.516
|
315 |
+
- type: ndcg_at_10
|
316 |
+
value: 45.586
|
317 |
+
- type: ndcg_at_100
|
318 |
+
value: 49.897000000000006
|
319 |
+
- type: ndcg_at_1000
|
320 |
+
value: 51.955
|
321 |
+
- type: ndcg_at_3
|
322 |
+
value: 41.684
|
323 |
+
- type: ndcg_at_5
|
324 |
+
value: 43.617
|
325 |
+
- type: precision_at_1
|
326 |
+
value: 37.516
|
327 |
+
- type: precision_at_10
|
328 |
+
value: 8.522
|
329 |
+
- type: precision_at_100
|
330 |
+
value: 1.374
|
331 |
+
- type: precision_at_1000
|
332 |
+
value: 0.184
|
333 |
+
- type: precision_at_3
|
334 |
+
value: 20.105999999999998
|
335 |
+
- type: precision_at_5
|
336 |
+
value: 14.152999999999999
|
337 |
+
- type: recall_at_1
|
338 |
+
value: 30.239
|
339 |
+
- type: recall_at_10
|
340 |
+
value: 55.03
|
341 |
+
- type: recall_at_100
|
342 |
+
value: 73.375
|
343 |
+
- type: recall_at_1000
|
344 |
+
value: 86.29599999999999
|
345 |
+
- type: recall_at_3
|
346 |
+
value: 43.269000000000005
|
347 |
+
- type: recall_at_5
|
348 |
+
value: 48.878
|
349 |
+
- type: map_at_1
|
350 |
+
value: 38.338
|
351 |
+
- type: map_at_10
|
352 |
+
value: 50.468999999999994
|
353 |
+
- type: map_at_100
|
354 |
+
value: 51.553000000000004
|
355 |
+
- type: map_at_1000
|
356 |
+
value: 51.608
|
357 |
+
- type: map_at_3
|
358 |
+
value: 47.107
|
359 |
+
- type: map_at_5
|
360 |
+
value: 49.101
|
361 |
+
- type: mrr_at_1
|
362 |
+
value: 44.201
|
363 |
+
- type: mrr_at_10
|
364 |
+
value: 54.057
|
365 |
+
- type: mrr_at_100
|
366 |
+
value: 54.764
|
367 |
+
- type: mrr_at_1000
|
368 |
+
value: 54.791000000000004
|
369 |
+
- type: mrr_at_3
|
370 |
+
value: 51.56699999999999
|
371 |
+
- type: mrr_at_5
|
372 |
+
value: 53.05
|
373 |
+
- type: ndcg_at_1
|
374 |
+
value: 44.201
|
375 |
+
- type: ndcg_at_10
|
376 |
+
value: 56.379000000000005
|
377 |
+
- type: ndcg_at_100
|
378 |
+
value: 60.645
|
379 |
+
- type: ndcg_at_1000
|
380 |
+
value: 61.73499999999999
|
381 |
+
- type: ndcg_at_3
|
382 |
+
value: 50.726000000000006
|
383 |
+
- type: ndcg_at_5
|
384 |
+
value: 53.58500000000001
|
385 |
+
- type: precision_at_1
|
386 |
+
value: 44.201
|
387 |
+
- type: precision_at_10
|
388 |
+
value: 9.141
|
389 |
+
- type: precision_at_100
|
390 |
+
value: 1.216
|
391 |
+
- type: precision_at_1000
|
392 |
+
value: 0.135
|
393 |
+
- type: precision_at_3
|
394 |
+
value: 22.654
|
395 |
+
- type: precision_at_5
|
396 |
+
value: 15.723999999999998
|
397 |
+
- type: recall_at_1
|
398 |
+
value: 38.338
|
399 |
+
- type: recall_at_10
|
400 |
+
value: 70.30499999999999
|
401 |
+
- type: recall_at_100
|
402 |
+
value: 88.77199999999999
|
403 |
+
- type: recall_at_1000
|
404 |
+
value: 96.49799999999999
|
405 |
+
- type: recall_at_3
|
406 |
+
value: 55.218
|
407 |
+
- type: recall_at_5
|
408 |
+
value: 62.104000000000006
|
409 |
+
- type: map_at_1
|
410 |
+
value: 25.682
|
411 |
+
- type: map_at_10
|
412 |
+
value: 33.498
|
413 |
+
- type: map_at_100
|
414 |
+
value: 34.461000000000006
|
415 |
+
- type: map_at_1000
|
416 |
+
value: 34.544000000000004
|
417 |
+
- type: map_at_3
|
418 |
+
value: 30.503999999999998
|
419 |
+
- type: map_at_5
|
420 |
+
value: 32.216
|
421 |
+
- type: mrr_at_1
|
422 |
+
value: 27.683999999999997
|
423 |
+
- type: mrr_at_10
|
424 |
+
value: 35.467999999999996
|
425 |
+
- type: mrr_at_100
|
426 |
+
value: 36.32
|
427 |
+
- type: mrr_at_1000
|
428 |
+
value: 36.386
|
429 |
+
- type: mrr_at_3
|
430 |
+
value: 32.618
|
431 |
+
- type: mrr_at_5
|
432 |
+
value: 34.262
|
433 |
+
- type: ndcg_at_1
|
434 |
+
value: 27.683999999999997
|
435 |
+
- type: ndcg_at_10
|
436 |
+
value: 38.378
|
437 |
+
- type: ndcg_at_100
|
438 |
+
value: 43.288
|
439 |
+
- type: ndcg_at_1000
|
440 |
+
value: 45.413
|
441 |
+
- type: ndcg_at_3
|
442 |
+
value: 32.586
|
443 |
+
- type: ndcg_at_5
|
444 |
+
value: 35.499
|
445 |
+
- type: precision_at_1
|
446 |
+
value: 27.683999999999997
|
447 |
+
- type: precision_at_10
|
448 |
+
value: 5.864
|
449 |
+
- type: precision_at_100
|
450 |
+
value: 0.882
|
451 |
+
- type: precision_at_1000
|
452 |
+
value: 0.11
|
453 |
+
- type: precision_at_3
|
454 |
+
value: 13.446
|
455 |
+
- type: precision_at_5
|
456 |
+
value: 9.718
|
457 |
+
- type: recall_at_1
|
458 |
+
value: 25.682
|
459 |
+
- type: recall_at_10
|
460 |
+
value: 51.712
|
461 |
+
- type: recall_at_100
|
462 |
+
value: 74.446
|
463 |
+
- type: recall_at_1000
|
464 |
+
value: 90.472
|
465 |
+
- type: recall_at_3
|
466 |
+
value: 36.236000000000004
|
467 |
+
- type: recall_at_5
|
468 |
+
value: 43.234
|
469 |
+
- type: map_at_1
|
470 |
+
value: 16.073999999999998
|
471 |
+
- type: map_at_10
|
472 |
+
value: 24.352999999999998
|
473 |
+
- type: map_at_100
|
474 |
+
value: 25.438
|
475 |
+
- type: map_at_1000
|
476 |
+
value: 25.545
|
477 |
+
- type: map_at_3
|
478 |
+
value: 21.614
|
479 |
+
- type: map_at_5
|
480 |
+
value: 23.104
|
481 |
+
- type: mrr_at_1
|
482 |
+
value: 19.776
|
483 |
+
- type: mrr_at_10
|
484 |
+
value: 28.837000000000003
|
485 |
+
- type: mrr_at_100
|
486 |
+
value: 29.755
|
487 |
+
- type: mrr_at_1000
|
488 |
+
value: 29.817
|
489 |
+
- type: mrr_at_3
|
490 |
+
value: 26.201999999999998
|
491 |
+
- type: mrr_at_5
|
492 |
+
value: 27.714
|
493 |
+
- type: ndcg_at_1
|
494 |
+
value: 19.776
|
495 |
+
- type: ndcg_at_10
|
496 |
+
value: 29.701
|
497 |
+
- type: ndcg_at_100
|
498 |
+
value: 35.307
|
499 |
+
- type: ndcg_at_1000
|
500 |
+
value: 37.942
|
501 |
+
- type: ndcg_at_3
|
502 |
+
value: 24.764
|
503 |
+
- type: ndcg_at_5
|
504 |
+
value: 27.025
|
505 |
+
- type: precision_at_1
|
506 |
+
value: 19.776
|
507 |
+
- type: precision_at_10
|
508 |
+
value: 5.659
|
509 |
+
- type: precision_at_100
|
510 |
+
value: 0.971
|
511 |
+
- type: precision_at_1000
|
512 |
+
value: 0.133
|
513 |
+
- type: precision_at_3
|
514 |
+
value: 12.065
|
515 |
+
- type: precision_at_5
|
516 |
+
value: 8.905000000000001
|
517 |
+
- type: recall_at_1
|
518 |
+
value: 16.073999999999998
|
519 |
+
- type: recall_at_10
|
520 |
+
value: 41.647
|
521 |
+
- type: recall_at_100
|
522 |
+
value: 66.884
|
523 |
+
- type: recall_at_1000
|
524 |
+
value: 85.91499999999999
|
525 |
+
- type: recall_at_3
|
526 |
+
value: 27.916
|
527 |
+
- type: recall_at_5
|
528 |
+
value: 33.729
|
529 |
+
- type: map_at_1
|
530 |
+
value: 28.444999999999997
|
531 |
+
- type: map_at_10
|
532 |
+
value: 38.218999999999994
|
533 |
+
- type: map_at_100
|
534 |
+
value: 39.595
|
535 |
+
- type: map_at_1000
|
536 |
+
value: 39.709
|
537 |
+
- type: map_at_3
|
538 |
+
value: 35.586
|
539 |
+
- type: map_at_5
|
540 |
+
value: 36.895
|
541 |
+
- type: mrr_at_1
|
542 |
+
value: 34.841
|
543 |
+
- type: mrr_at_10
|
544 |
+
value: 44.106
|
545 |
+
- type: mrr_at_100
|
546 |
+
value: 44.98
|
547 |
+
- type: mrr_at_1000
|
548 |
+
value: 45.03
|
549 |
+
- type: mrr_at_3
|
550 |
+
value: 41.979
|
551 |
+
- type: mrr_at_5
|
552 |
+
value: 43.047999999999995
|
553 |
+
- type: ndcg_at_1
|
554 |
+
value: 34.841
|
555 |
+
- type: ndcg_at_10
|
556 |
+
value: 43.922
|
557 |
+
- type: ndcg_at_100
|
558 |
+
value: 49.504999999999995
|
559 |
+
- type: ndcg_at_1000
|
560 |
+
value: 51.675000000000004
|
561 |
+
- type: ndcg_at_3
|
562 |
+
value: 39.858
|
563 |
+
- type: ndcg_at_5
|
564 |
+
value: 41.408
|
565 |
+
- type: precision_at_1
|
566 |
+
value: 34.841
|
567 |
+
- type: precision_at_10
|
568 |
+
value: 7.872999999999999
|
569 |
+
- type: precision_at_100
|
570 |
+
value: 1.2449999999999999
|
571 |
+
- type: precision_at_1000
|
572 |
+
value: 0.161
|
573 |
+
- type: precision_at_3
|
574 |
+
value: 18.993
|
575 |
+
- type: precision_at_5
|
576 |
+
value: 13.032
|
577 |
+
- type: recall_at_1
|
578 |
+
value: 28.444999999999997
|
579 |
+
- type: recall_at_10
|
580 |
+
value: 54.984
|
581 |
+
- type: recall_at_100
|
582 |
+
value: 78.342
|
583 |
+
- type: recall_at_1000
|
584 |
+
value: 92.77
|
585 |
+
- type: recall_at_3
|
586 |
+
value: 42.842999999999996
|
587 |
+
- type: recall_at_5
|
588 |
+
value: 47.247
|
589 |
+
- type: map_at_1
|
590 |
+
value: 23.072
|
591 |
+
- type: map_at_10
|
592 |
+
value: 32.354
|
593 |
+
- type: map_at_100
|
594 |
+
value: 33.800000000000004
|
595 |
+
- type: map_at_1000
|
596 |
+
value: 33.908
|
597 |
+
- type: map_at_3
|
598 |
+
value: 29.232000000000003
|
599 |
+
- type: map_at_5
|
600 |
+
value: 31.049
|
601 |
+
- type: mrr_at_1
|
602 |
+
value: 29.110000000000003
|
603 |
+
- type: mrr_at_10
|
604 |
+
value: 38.03
|
605 |
+
- type: mrr_at_100
|
606 |
+
value: 39.032
|
607 |
+
- type: mrr_at_1000
|
608 |
+
value: 39.086999999999996
|
609 |
+
- type: mrr_at_3
|
610 |
+
value: 35.407
|
611 |
+
- type: mrr_at_5
|
612 |
+
value: 36.76
|
613 |
+
- type: ndcg_at_1
|
614 |
+
value: 29.110000000000003
|
615 |
+
- type: ndcg_at_10
|
616 |
+
value: 38.231
|
617 |
+
- type: ndcg_at_100
|
618 |
+
value: 44.425
|
619 |
+
- type: ndcg_at_1000
|
620 |
+
value: 46.771
|
621 |
+
- type: ndcg_at_3
|
622 |
+
value: 33.095
|
623 |
+
- type: ndcg_at_5
|
624 |
+
value: 35.459
|
625 |
+
- type: precision_at_1
|
626 |
+
value: 29.110000000000003
|
627 |
+
- type: precision_at_10
|
628 |
+
value: 7.215000000000001
|
629 |
+
- type: precision_at_100
|
630 |
+
value: 1.2109999999999999
|
631 |
+
- type: precision_at_1000
|
632 |
+
value: 0.157
|
633 |
+
- type: precision_at_3
|
634 |
+
value: 16.058
|
635 |
+
- type: precision_at_5
|
636 |
+
value: 11.644
|
637 |
+
- type: recall_at_1
|
638 |
+
value: 23.072
|
639 |
+
- type: recall_at_10
|
640 |
+
value: 50.285999999999994
|
641 |
+
- type: recall_at_100
|
642 |
+
value: 76.596
|
643 |
+
- type: recall_at_1000
|
644 |
+
value: 92.861
|
645 |
+
- type: recall_at_3
|
646 |
+
value: 35.702
|
647 |
+
- type: recall_at_5
|
648 |
+
value: 42.152
|
649 |
+
- type: map_at_1
|
650 |
+
value: 24.937916666666666
|
651 |
+
- type: map_at_10
|
652 |
+
value: 33.755250000000004
|
653 |
+
- type: map_at_100
|
654 |
+
value: 34.955999999999996
|
655 |
+
- type: map_at_1000
|
656 |
+
value: 35.070499999999996
|
657 |
+
- type: map_at_3
|
658 |
+
value: 30.98708333333333
|
659 |
+
- type: map_at_5
|
660 |
+
value: 32.51491666666666
|
661 |
+
- type: mrr_at_1
|
662 |
+
value: 29.48708333333333
|
663 |
+
- type: mrr_at_10
|
664 |
+
value: 37.92183333333334
|
665 |
+
- type: mrr_at_100
|
666 |
+
value: 38.76583333333333
|
667 |
+
- type: mrr_at_1000
|
668 |
+
value: 38.82466666666667
|
669 |
+
- type: mrr_at_3
|
670 |
+
value: 35.45125
|
671 |
+
- type: mrr_at_5
|
672 |
+
value: 36.827000000000005
|
673 |
+
- type: ndcg_at_1
|
674 |
+
value: 29.48708333333333
|
675 |
+
- type: ndcg_at_10
|
676 |
+
value: 39.05225
|
677 |
+
- type: ndcg_at_100
|
678 |
+
value: 44.25983333333334
|
679 |
+
- type: ndcg_at_1000
|
680 |
+
value: 46.568333333333335
|
681 |
+
- type: ndcg_at_3
|
682 |
+
value: 34.271583333333325
|
683 |
+
- type: ndcg_at_5
|
684 |
+
value: 36.483916666666666
|
685 |
+
- type: precision_at_1
|
686 |
+
value: 29.48708333333333
|
687 |
+
- type: precision_at_10
|
688 |
+
value: 6.865749999999999
|
689 |
+
- type: precision_at_100
|
690 |
+
value: 1.1195833333333332
|
691 |
+
- type: precision_at_1000
|
692 |
+
value: 0.15058333333333335
|
693 |
+
- type: precision_at_3
|
694 |
+
value: 15.742083333333333
|
695 |
+
- type: precision_at_5
|
696 |
+
value: 11.221916666666667
|
697 |
+
- type: recall_at_1
|
698 |
+
value: 24.937916666666666
|
699 |
+
- type: recall_at_10
|
700 |
+
value: 50.650416666666665
|
701 |
+
- type: recall_at_100
|
702 |
+
value: 73.55383333333334
|
703 |
+
- type: recall_at_1000
|
704 |
+
value: 89.61691666666667
|
705 |
+
- type: recall_at_3
|
706 |
+
value: 37.27808333333334
|
707 |
+
- type: recall_at_5
|
708 |
+
value: 42.99475
|
709 |
+
- type: map_at_1
|
710 |
+
value: 23.947
|
711 |
+
- type: map_at_10
|
712 |
+
value: 30.575000000000003
|
713 |
+
- type: map_at_100
|
714 |
+
value: 31.465
|
715 |
+
- type: map_at_1000
|
716 |
+
value: 31.558000000000003
|
717 |
+
- type: map_at_3
|
718 |
+
value: 28.814
|
719 |
+
- type: map_at_5
|
720 |
+
value: 29.738999999999997
|
721 |
+
- type: mrr_at_1
|
722 |
+
value: 26.994
|
723 |
+
- type: mrr_at_10
|
724 |
+
value: 33.415
|
725 |
+
- type: mrr_at_100
|
726 |
+
value: 34.18
|
727 |
+
- type: mrr_at_1000
|
728 |
+
value: 34.245
|
729 |
+
- type: mrr_at_3
|
730 |
+
value: 31.621
|
731 |
+
- type: mrr_at_5
|
732 |
+
value: 32.549
|
733 |
+
- type: ndcg_at_1
|
734 |
+
value: 26.994
|
735 |
+
- type: ndcg_at_10
|
736 |
+
value: 34.482
|
737 |
+
- type: ndcg_at_100
|
738 |
+
value: 38.915
|
739 |
+
- type: ndcg_at_1000
|
740 |
+
value: 41.355
|
741 |
+
- type: ndcg_at_3
|
742 |
+
value: 31.139
|
743 |
+
- type: ndcg_at_5
|
744 |
+
value: 32.589
|
745 |
+
- type: precision_at_1
|
746 |
+
value: 26.994
|
747 |
+
- type: precision_at_10
|
748 |
+
value: 5.322
|
749 |
+
- type: precision_at_100
|
750 |
+
value: 0.8160000000000001
|
751 |
+
- type: precision_at_1000
|
752 |
+
value: 0.11100000000000002
|
753 |
+
- type: precision_at_3
|
754 |
+
value: 13.344000000000001
|
755 |
+
- type: precision_at_5
|
756 |
+
value: 8.988
|
757 |
+
- type: recall_at_1
|
758 |
+
value: 23.947
|
759 |
+
- type: recall_at_10
|
760 |
+
value: 43.647999999999996
|
761 |
+
- type: recall_at_100
|
762 |
+
value: 63.851
|
763 |
+
- type: recall_at_1000
|
764 |
+
value: 82.0
|
765 |
+
- type: recall_at_3
|
766 |
+
value: 34.288000000000004
|
767 |
+
- type: recall_at_5
|
768 |
+
value: 38.117000000000004
|
769 |
+
- type: map_at_1
|
770 |
+
value: 16.197
|
771 |
+
- type: map_at_10
|
772 |
+
value: 22.968
|
773 |
+
- type: map_at_100
|
774 |
+
value: 24.095
|
775 |
+
- type: map_at_1000
|
776 |
+
value: 24.217
|
777 |
+
- type: map_at_3
|
778 |
+
value: 20.771
|
779 |
+
- type: map_at_5
|
780 |
+
value: 21.995
|
781 |
+
- type: mrr_at_1
|
782 |
+
value: 19.511
|
783 |
+
- type: mrr_at_10
|
784 |
+
value: 26.55
|
785 |
+
- type: mrr_at_100
|
786 |
+
value: 27.500999999999998
|
787 |
+
- type: mrr_at_1000
|
788 |
+
value: 27.578999999999997
|
789 |
+
- type: mrr_at_3
|
790 |
+
value: 24.421
|
791 |
+
- type: mrr_at_5
|
792 |
+
value: 25.604
|
793 |
+
- type: ndcg_at_1
|
794 |
+
value: 19.511
|
795 |
+
- type: ndcg_at_10
|
796 |
+
value: 27.386
|
797 |
+
- type: ndcg_at_100
|
798 |
+
value: 32.828
|
799 |
+
- type: ndcg_at_1000
|
800 |
+
value: 35.739
|
801 |
+
- type: ndcg_at_3
|
802 |
+
value: 23.405
|
803 |
+
- type: ndcg_at_5
|
804 |
+
value: 25.255
|
805 |
+
- type: precision_at_1
|
806 |
+
value: 19.511
|
807 |
+
- type: precision_at_10
|
808 |
+
value: 5.017
|
809 |
+
- type: precision_at_100
|
810 |
+
value: 0.91
|
811 |
+
- type: precision_at_1000
|
812 |
+
value: 0.133
|
813 |
+
- type: precision_at_3
|
814 |
+
value: 11.023
|
815 |
+
- type: precision_at_5
|
816 |
+
value: 8.025
|
817 |
+
- type: recall_at_1
|
818 |
+
value: 16.197
|
819 |
+
- type: recall_at_10
|
820 |
+
value: 37.09
|
821 |
+
- type: recall_at_100
|
822 |
+
value: 61.778
|
823 |
+
- type: recall_at_1000
|
824 |
+
value: 82.56599999999999
|
825 |
+
- type: recall_at_3
|
826 |
+
value: 26.034000000000002
|
827 |
+
- type: recall_at_5
|
828 |
+
value: 30.762
|
829 |
+
- type: map_at_1
|
830 |
+
value: 25.41
|
831 |
+
- type: map_at_10
|
832 |
+
value: 33.655
|
833 |
+
- type: map_at_100
|
834 |
+
value: 34.892
|
835 |
+
- type: map_at_1000
|
836 |
+
value: 34.995
|
837 |
+
- type: map_at_3
|
838 |
+
value: 30.94
|
839 |
+
- type: map_at_5
|
840 |
+
value: 32.303
|
841 |
+
- type: mrr_at_1
|
842 |
+
value: 29.477999999999998
|
843 |
+
- type: mrr_at_10
|
844 |
+
value: 37.443
|
845 |
+
- type: mrr_at_100
|
846 |
+
value: 38.383
|
847 |
+
- type: mrr_at_1000
|
848 |
+
value: 38.440000000000005
|
849 |
+
- type: mrr_at_3
|
850 |
+
value: 34.949999999999996
|
851 |
+
- type: mrr_at_5
|
852 |
+
value: 36.228
|
853 |
+
- type: ndcg_at_1
|
854 |
+
value: 29.477999999999998
|
855 |
+
- type: ndcg_at_10
|
856 |
+
value: 38.769
|
857 |
+
- type: ndcg_at_100
|
858 |
+
value: 44.245000000000005
|
859 |
+
- type: ndcg_at_1000
|
860 |
+
value: 46.593
|
861 |
+
- type: ndcg_at_3
|
862 |
+
value: 33.623
|
863 |
+
- type: ndcg_at_5
|
864 |
+
value: 35.766
|
865 |
+
- type: precision_at_1
|
866 |
+
value: 29.477999999999998
|
867 |
+
- type: precision_at_10
|
868 |
+
value: 6.455
|
869 |
+
- type: precision_at_100
|
870 |
+
value: 1.032
|
871 |
+
- type: precision_at_1000
|
872 |
+
value: 0.135
|
873 |
+
- type: precision_at_3
|
874 |
+
value: 14.893999999999998
|
875 |
+
- type: precision_at_5
|
876 |
+
value: 10.485
|
877 |
+
- type: recall_at_1
|
878 |
+
value: 25.41
|
879 |
+
- type: recall_at_10
|
880 |
+
value: 50.669
|
881 |
+
- type: recall_at_100
|
882 |
+
value: 74.084
|
883 |
+
- type: recall_at_1000
|
884 |
+
value: 90.435
|
885 |
+
- type: recall_at_3
|
886 |
+
value: 36.679
|
887 |
+
- type: recall_at_5
|
888 |
+
value: 41.94
|
889 |
+
- type: map_at_1
|
890 |
+
value: 23.339
|
891 |
+
- type: map_at_10
|
892 |
+
value: 31.852000000000004
|
893 |
+
- type: map_at_100
|
894 |
+
value: 33.411
|
895 |
+
- type: map_at_1000
|
896 |
+
value: 33.62
|
897 |
+
- type: map_at_3
|
898 |
+
value: 28.929
|
899 |
+
- type: map_at_5
|
900 |
+
value: 30.542
|
901 |
+
- type: mrr_at_1
|
902 |
+
value: 28.063
|
903 |
+
- type: mrr_at_10
|
904 |
+
value: 36.301
|
905 |
+
- type: mrr_at_100
|
906 |
+
value: 37.288
|
907 |
+
- type: mrr_at_1000
|
908 |
+
value: 37.349
|
909 |
+
- type: mrr_at_3
|
910 |
+
value: 33.663
|
911 |
+
- type: mrr_at_5
|
912 |
+
value: 35.165
|
913 |
+
- type: ndcg_at_1
|
914 |
+
value: 28.063
|
915 |
+
- type: ndcg_at_10
|
916 |
+
value: 37.462
|
917 |
+
- type: ndcg_at_100
|
918 |
+
value: 43.620999999999995
|
919 |
+
- type: ndcg_at_1000
|
920 |
+
value: 46.211
|
921 |
+
- type: ndcg_at_3
|
922 |
+
value: 32.68
|
923 |
+
- type: ndcg_at_5
|
924 |
+
value: 34.981
|
925 |
+
- type: precision_at_1
|
926 |
+
value: 28.063
|
927 |
+
- type: precision_at_10
|
928 |
+
value: 7.1739999999999995
|
929 |
+
- type: precision_at_100
|
930 |
+
value: 1.486
|
931 |
+
- type: precision_at_1000
|
932 |
+
value: 0.23500000000000001
|
933 |
+
- type: precision_at_3
|
934 |
+
value: 15.217
|
935 |
+
- type: precision_at_5
|
936 |
+
value: 11.265
|
937 |
+
- type: recall_at_1
|
938 |
+
value: 23.339
|
939 |
+
- type: recall_at_10
|
940 |
+
value: 48.376999999999995
|
941 |
+
- type: recall_at_100
|
942 |
+
value: 76.053
|
943 |
+
- type: recall_at_1000
|
944 |
+
value: 92.455
|
945 |
+
- type: recall_at_3
|
946 |
+
value: 34.735
|
947 |
+
- type: recall_at_5
|
948 |
+
value: 40.71
|
949 |
+
- type: map_at_1
|
950 |
+
value: 18.925
|
951 |
+
- type: map_at_10
|
952 |
+
value: 26.017000000000003
|
953 |
+
- type: map_at_100
|
954 |
+
value: 27.034000000000002
|
955 |
+
- type: map_at_1000
|
956 |
+
value: 27.156000000000002
|
957 |
+
- type: map_at_3
|
958 |
+
value: 23.604
|
959 |
+
- type: map_at_5
|
960 |
+
value: 24.75
|
961 |
+
- type: mrr_at_1
|
962 |
+
value: 20.333000000000002
|
963 |
+
- type: mrr_at_10
|
964 |
+
value: 27.915
|
965 |
+
- type: mrr_at_100
|
966 |
+
value: 28.788000000000004
|
967 |
+
- type: mrr_at_1000
|
968 |
+
value: 28.877999999999997
|
969 |
+
- type: mrr_at_3
|
970 |
+
value: 25.446999999999996
|
971 |
+
- type: mrr_at_5
|
972 |
+
value: 26.648
|
973 |
+
- type: ndcg_at_1
|
974 |
+
value: 20.333000000000002
|
975 |
+
- type: ndcg_at_10
|
976 |
+
value: 30.673000000000002
|
977 |
+
- type: ndcg_at_100
|
978 |
+
value: 35.618
|
979 |
+
- type: ndcg_at_1000
|
980 |
+
value: 38.517
|
981 |
+
- type: ndcg_at_3
|
982 |
+
value: 25.71
|
983 |
+
- type: ndcg_at_5
|
984 |
+
value: 27.679
|
985 |
+
- type: precision_at_1
|
986 |
+
value: 20.333000000000002
|
987 |
+
- type: precision_at_10
|
988 |
+
value: 4.9910000000000005
|
989 |
+
- type: precision_at_100
|
990 |
+
value: 0.8130000000000001
|
991 |
+
- type: precision_at_1000
|
992 |
+
value: 0.117
|
993 |
+
- type: precision_at_3
|
994 |
+
value: 11.029
|
995 |
+
- type: precision_at_5
|
996 |
+
value: 7.8740000000000006
|
997 |
+
- type: recall_at_1
|
998 |
+
value: 18.925
|
999 |
+
- type: recall_at_10
|
1000 |
+
value: 43.311
|
1001 |
+
- type: recall_at_100
|
1002 |
+
value: 66.308
|
1003 |
+
- type: recall_at_1000
|
1004 |
+
value: 87.49
|
1005 |
+
- type: recall_at_3
|
1006 |
+
value: 29.596
|
1007 |
+
- type: recall_at_5
|
1008 |
+
value: 34.245
|
1009 |
+
- task:
|
1010 |
+
type: Retrieval
|
1011 |
+
dataset:
|
1012 |
+
name: MTEB ClimateFEVER
|
1013 |
+
type: climate-fever
|
1014 |
+
config: default
|
1015 |
+
split: test
|
1016 |
+
revision: None
|
1017 |
+
metrics:
|
1018 |
+
- type: map_at_1
|
1019 |
+
value: 13.714
|
1020 |
+
- type: map_at_10
|
1021 |
+
value: 23.194
|
1022 |
+
- type: map_at_100
|
1023 |
+
value: 24.976000000000003
|
1024 |
+
- type: map_at_1000
|
1025 |
+
value: 25.166
|
1026 |
+
- type: map_at_3
|
1027 |
+
value: 19.709
|
1028 |
+
- type: map_at_5
|
1029 |
+
value: 21.523999999999997
|
1030 |
+
- type: mrr_at_1
|
1031 |
+
value: 30.619000000000003
|
1032 |
+
- type: mrr_at_10
|
1033 |
+
value: 42.563
|
1034 |
+
- type: mrr_at_100
|
1035 |
+
value: 43.386
|
1036 |
+
- type: mrr_at_1000
|
1037 |
+
value: 43.423
|
1038 |
+
- type: mrr_at_3
|
1039 |
+
value: 39.555
|
1040 |
+
- type: mrr_at_5
|
1041 |
+
value: 41.268
|
1042 |
+
- type: ndcg_at_1
|
1043 |
+
value: 30.619000000000003
|
1044 |
+
- type: ndcg_at_10
|
1045 |
+
value: 31.836
|
1046 |
+
- type: ndcg_at_100
|
1047 |
+
value: 38.652
|
1048 |
+
- type: ndcg_at_1000
|
1049 |
+
value: 42.088
|
1050 |
+
- type: ndcg_at_3
|
1051 |
+
value: 26.733
|
1052 |
+
- type: ndcg_at_5
|
1053 |
+
value: 28.435
|
1054 |
+
- type: precision_at_1
|
1055 |
+
value: 30.619000000000003
|
1056 |
+
- type: precision_at_10
|
1057 |
+
value: 9.751999999999999
|
1058 |
+
- type: precision_at_100
|
1059 |
+
value: 1.71
|
1060 |
+
- type: precision_at_1000
|
1061 |
+
value: 0.23500000000000001
|
1062 |
+
- type: precision_at_3
|
1063 |
+
value: 19.935
|
1064 |
+
- type: precision_at_5
|
1065 |
+
value: 14.984
|
1066 |
+
- type: recall_at_1
|
1067 |
+
value: 13.714
|
1068 |
+
- type: recall_at_10
|
1069 |
+
value: 37.26
|
1070 |
+
- type: recall_at_100
|
1071 |
+
value: 60.546
|
1072 |
+
- type: recall_at_1000
|
1073 |
+
value: 79.899
|
1074 |
+
- type: recall_at_3
|
1075 |
+
value: 24.325
|
1076 |
+
- type: recall_at_5
|
1077 |
+
value: 29.725
|
1078 |
+
- task:
|
1079 |
+
type: Retrieval
|
1080 |
+
dataset:
|
1081 |
+
name: MTEB DBPedia
|
1082 |
+
type: dbpedia-entity
|
1083 |
+
config: default
|
1084 |
+
split: test
|
1085 |
+
revision: None
|
1086 |
+
metrics:
|
1087 |
+
- type: map_at_1
|
1088 |
+
value: 8.462
|
1089 |
+
- type: map_at_10
|
1090 |
+
value: 18.637
|
1091 |
+
- type: map_at_100
|
1092 |
+
value: 26.131999999999998
|
1093 |
+
- type: map_at_1000
|
1094 |
+
value: 27.607
|
1095 |
+
- type: map_at_3
|
1096 |
+
value: 13.333
|
1097 |
+
- type: map_at_5
|
1098 |
+
value: 15.654000000000002
|
1099 |
+
- type: mrr_at_1
|
1100 |
+
value: 66.25
|
1101 |
+
- type: mrr_at_10
|
1102 |
+
value: 74.32600000000001
|
1103 |
+
- type: mrr_at_100
|
1104 |
+
value: 74.60900000000001
|
1105 |
+
- type: mrr_at_1000
|
1106 |
+
value: 74.62
|
1107 |
+
- type: mrr_at_3
|
1108 |
+
value: 72.667
|
1109 |
+
- type: mrr_at_5
|
1110 |
+
value: 73.817
|
1111 |
+
- type: ndcg_at_1
|
1112 |
+
value: 53.87499999999999
|
1113 |
+
- type: ndcg_at_10
|
1114 |
+
value: 40.028999999999996
|
1115 |
+
- type: ndcg_at_100
|
1116 |
+
value: 44.199
|
1117 |
+
- type: ndcg_at_1000
|
1118 |
+
value: 51.629999999999995
|
1119 |
+
- type: ndcg_at_3
|
1120 |
+
value: 44.113
|
1121 |
+
- type: ndcg_at_5
|
1122 |
+
value: 41.731
|
1123 |
+
- type: precision_at_1
|
1124 |
+
value: 66.25
|
1125 |
+
- type: precision_at_10
|
1126 |
+
value: 31.900000000000002
|
1127 |
+
- type: precision_at_100
|
1128 |
+
value: 10.043000000000001
|
1129 |
+
- type: precision_at_1000
|
1130 |
+
value: 1.926
|
1131 |
+
- type: precision_at_3
|
1132 |
+
value: 47.417
|
1133 |
+
- type: precision_at_5
|
1134 |
+
value: 40.65
|
1135 |
+
- type: recall_at_1
|
1136 |
+
value: 8.462
|
1137 |
+
- type: recall_at_10
|
1138 |
+
value: 24.293
|
1139 |
+
- type: recall_at_100
|
1140 |
+
value: 50.146
|
1141 |
+
- type: recall_at_1000
|
1142 |
+
value: 74.034
|
1143 |
+
- type: recall_at_3
|
1144 |
+
value: 14.967
|
1145 |
+
- type: recall_at_5
|
1146 |
+
value: 18.682000000000002
|
1147 |
+
- task:
|
1148 |
+
type: Classification
|
1149 |
+
dataset:
|
1150 |
+
name: MTEB EmotionClassification
|
1151 |
+
type: mteb/emotion
|
1152 |
+
config: default
|
1153 |
+
split: test
|
1154 |
+
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
|
1155 |
+
metrics:
|
1156 |
+
- type: accuracy
|
1157 |
+
value: 47.84499999999999
|
1158 |
+
- type: f1
|
1159 |
+
value: 42.48106691979349
|
1160 |
+
- task:
|
1161 |
+
type: Retrieval
|
1162 |
+
dataset:
|
1163 |
+
name: MTEB FEVER
|
1164 |
+
type: fever
|
1165 |
+
config: default
|
1166 |
+
split: test
|
1167 |
+
revision: None
|
1168 |
+
metrics:
|
1169 |
+
- type: map_at_1
|
1170 |
+
value: 74.034
|
1171 |
+
- type: map_at_10
|
1172 |
+
value: 82.76
|
1173 |
+
- type: map_at_100
|
1174 |
+
value: 82.968
|
1175 |
+
- type: map_at_1000
|
1176 |
+
value: 82.98299999999999
|
1177 |
+
- type: map_at_3
|
1178 |
+
value: 81.768
|
1179 |
+
- type: map_at_5
|
1180 |
+
value: 82.418
|
1181 |
+
- type: mrr_at_1
|
1182 |
+
value: 80.048
|
1183 |
+
- type: mrr_at_10
|
1184 |
+
value: 87.64999999999999
|
1185 |
+
- type: mrr_at_100
|
1186 |
+
value: 87.712
|
1187 |
+
- type: mrr_at_1000
|
1188 |
+
value: 87.713
|
1189 |
+
- type: mrr_at_3
|
1190 |
+
value: 87.01100000000001
|
1191 |
+
- type: mrr_at_5
|
1192 |
+
value: 87.466
|
1193 |
+
- type: ndcg_at_1
|
1194 |
+
value: 80.048
|
1195 |
+
- type: ndcg_at_10
|
1196 |
+
value: 86.643
|
1197 |
+
- type: ndcg_at_100
|
1198 |
+
value: 87.361
|
1199 |
+
- type: ndcg_at_1000
|
1200 |
+
value: 87.606
|
1201 |
+
- type: ndcg_at_3
|
1202 |
+
value: 85.137
|
1203 |
+
- type: ndcg_at_5
|
1204 |
+
value: 86.016
|
1205 |
+
- type: precision_at_1
|
1206 |
+
value: 80.048
|
1207 |
+
- type: precision_at_10
|
1208 |
+
value: 10.372
|
1209 |
+
- type: precision_at_100
|
1210 |
+
value: 1.093
|
1211 |
+
- type: precision_at_1000
|
1212 |
+
value: 0.11299999999999999
|
1213 |
+
- type: precision_at_3
|
1214 |
+
value: 32.638
|
1215 |
+
- type: precision_at_5
|
1216 |
+
value: 20.177
|
1217 |
+
- type: recall_at_1
|
1218 |
+
value: 74.034
|
1219 |
+
- type: recall_at_10
|
1220 |
+
value: 93.769
|
1221 |
+
- type: recall_at_100
|
1222 |
+
value: 96.569
|
1223 |
+
- type: recall_at_1000
|
1224 |
+
value: 98.039
|
1225 |
+
- type: recall_at_3
|
1226 |
+
value: 89.581
|
1227 |
+
- type: recall_at_5
|
1228 |
+
value: 91.906
|
1229 |
+
- task:
|
1230 |
+
type: Retrieval
|
1231 |
+
dataset:
|
1232 |
+
name: MTEB FiQA2018
|
1233 |
+
type: fiqa
|
1234 |
+
config: default
|
1235 |
+
split: test
|
1236 |
+
revision: None
|
1237 |
+
metrics:
|
1238 |
+
- type: map_at_1
|
1239 |
+
value: 20.5
|
1240 |
+
- type: map_at_10
|
1241 |
+
value: 32.857
|
1242 |
+
- type: map_at_100
|
1243 |
+
value: 34.589
|
1244 |
+
- type: map_at_1000
|
1245 |
+
value: 34.778
|
1246 |
+
- type: map_at_3
|
1247 |
+
value: 29.160999999999998
|
1248 |
+
- type: map_at_5
|
1249 |
+
value: 31.033
|
1250 |
+
- type: mrr_at_1
|
1251 |
+
value: 40.123
|
1252 |
+
- type: mrr_at_10
|
1253 |
+
value: 48.776
|
1254 |
+
- type: mrr_at_100
|
1255 |
+
value: 49.495
|
1256 |
+
- type: mrr_at_1000
|
1257 |
+
value: 49.539
|
1258 |
+
- type: mrr_at_3
|
1259 |
+
value: 46.605000000000004
|
1260 |
+
- type: mrr_at_5
|
1261 |
+
value: 47.654
|
1262 |
+
- type: ndcg_at_1
|
1263 |
+
value: 40.123
|
1264 |
+
- type: ndcg_at_10
|
1265 |
+
value: 40.343
|
1266 |
+
- type: ndcg_at_100
|
1267 |
+
value: 46.56
|
1268 |
+
- type: ndcg_at_1000
|
1269 |
+
value: 49.777
|
1270 |
+
- type: ndcg_at_3
|
1271 |
+
value: 37.322
|
1272 |
+
- type: ndcg_at_5
|
1273 |
+
value: 37.791000000000004
|
1274 |
+
- type: precision_at_1
|
1275 |
+
value: 40.123
|
1276 |
+
- type: precision_at_10
|
1277 |
+
value: 11.08
|
1278 |
+
- type: precision_at_100
|
1279 |
+
value: 1.752
|
1280 |
+
- type: precision_at_1000
|
1281 |
+
value: 0.232
|
1282 |
+
- type: precision_at_3
|
1283 |
+
value: 24.897
|
1284 |
+
- type: precision_at_5
|
1285 |
+
value: 17.809
|
1286 |
+
- type: recall_at_1
|
1287 |
+
value: 20.5
|
1288 |
+
- type: recall_at_10
|
1289 |
+
value: 46.388
|
1290 |
+
- type: recall_at_100
|
1291 |
+
value: 69.552
|
1292 |
+
- type: recall_at_1000
|
1293 |
+
value: 89.011
|
1294 |
+
- type: recall_at_3
|
1295 |
+
value: 33.617999999999995
|
1296 |
+
- type: recall_at_5
|
1297 |
+
value: 38.211
|
1298 |
+
- task:
|
1299 |
+
type: Retrieval
|
1300 |
+
dataset:
|
1301 |
+
name: MTEB HotpotQA
|
1302 |
+
type: hotpotqa
|
1303 |
+
config: default
|
1304 |
+
split: test
|
1305 |
+
revision: None
|
1306 |
+
metrics:
|
1307 |
+
- type: map_at_1
|
1308 |
+
value: 39.135999999999996
|
1309 |
+
- type: map_at_10
|
1310 |
+
value: 61.673
|
1311 |
+
- type: map_at_100
|
1312 |
+
value: 62.562
|
1313 |
+
- type: map_at_1000
|
1314 |
+
value: 62.62
|
1315 |
+
- type: map_at_3
|
1316 |
+
value: 58.467999999999996
|
1317 |
+
- type: map_at_5
|
1318 |
+
value: 60.463
|
1319 |
+
- type: mrr_at_1
|
1320 |
+
value: 78.271
|
1321 |
+
- type: mrr_at_10
|
1322 |
+
value: 84.119
|
1323 |
+
- type: mrr_at_100
|
1324 |
+
value: 84.29299999999999
|
1325 |
+
- type: mrr_at_1000
|
1326 |
+
value: 84.299
|
1327 |
+
- type: mrr_at_3
|
1328 |
+
value: 83.18900000000001
|
1329 |
+
- type: mrr_at_5
|
1330 |
+
value: 83.786
|
1331 |
+
- type: ndcg_at_1
|
1332 |
+
value: 78.271
|
1333 |
+
- type: ndcg_at_10
|
1334 |
+
value: 69.935
|
1335 |
+
- type: ndcg_at_100
|
1336 |
+
value: 73.01299999999999
|
1337 |
+
- type: ndcg_at_1000
|
1338 |
+
value: 74.126
|
1339 |
+
- type: ndcg_at_3
|
1340 |
+
value: 65.388
|
1341 |
+
- type: ndcg_at_5
|
1342 |
+
value: 67.906
|
1343 |
+
- type: precision_at_1
|
1344 |
+
value: 78.271
|
1345 |
+
- type: precision_at_10
|
1346 |
+
value: 14.562
|
1347 |
+
- type: precision_at_100
|
1348 |
+
value: 1.6969999999999998
|
1349 |
+
- type: precision_at_1000
|
1350 |
+
value: 0.184
|
1351 |
+
- type: precision_at_3
|
1352 |
+
value: 41.841
|
1353 |
+
- type: precision_at_5
|
1354 |
+
value: 27.087
|
1355 |
+
- type: recall_at_1
|
1356 |
+
value: 39.135999999999996
|
1357 |
+
- type: recall_at_10
|
1358 |
+
value: 72.809
|
1359 |
+
- type: recall_at_100
|
1360 |
+
value: 84.86200000000001
|
1361 |
+
- type: recall_at_1000
|
1362 |
+
value: 92.208
|
1363 |
+
- type: recall_at_3
|
1364 |
+
value: 62.76199999999999
|
1365 |
+
- type: recall_at_5
|
1366 |
+
value: 67.718
|
1367 |
+
- task:
|
1368 |
+
type: Classification
|
1369 |
+
dataset:
|
1370 |
+
name: MTEB ImdbClassification
|
1371 |
+
type: mteb/imdb
|
1372 |
+
config: default
|
1373 |
+
split: test
|
1374 |
+
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
|
1375 |
+
metrics:
|
1376 |
+
- type: accuracy
|
1377 |
+
value: 90.60600000000001
|
1378 |
+
- type: ap
|
1379 |
+
value: 86.6579587804335
|
1380 |
+
- type: f1
|
1381 |
+
value: 90.5938853929307
|
1382 |
+
- task:
|
1383 |
+
type: Retrieval
|
1384 |
+
dataset:
|
1385 |
+
name: MTEB MSMARCO
|
1386 |
+
type: msmarco
|
1387 |
+
config: default
|
1388 |
+
split: dev
|
1389 |
+
revision: None
|
1390 |
+
metrics:
|
1391 |
+
- type: map_at_1
|
1392 |
+
value: 21.852
|
1393 |
+
- type: map_at_10
|
1394 |
+
value: 33.982
|
1395 |
+
- type: map_at_100
|
1396 |
+
value: 35.116
|
1397 |
+
- type: map_at_1000
|
1398 |
+
value: 35.167
|
1399 |
+
- type: map_at_3
|
1400 |
+
value: 30.134
|
1401 |
+
- type: map_at_5
|
1402 |
+
value: 32.340999999999994
|
1403 |
+
- type: mrr_at_1
|
1404 |
+
value: 22.479
|
1405 |
+
- type: mrr_at_10
|
1406 |
+
value: 34.594
|
1407 |
+
- type: mrr_at_100
|
1408 |
+
value: 35.672
|
1409 |
+
- type: mrr_at_1000
|
1410 |
+
value: 35.716
|
1411 |
+
- type: mrr_at_3
|
1412 |
+
value: 30.84
|
1413 |
+
- type: mrr_at_5
|
1414 |
+
value: 32.998
|
1415 |
+
- type: ndcg_at_1
|
1416 |
+
value: 22.493
|
1417 |
+
- type: ndcg_at_10
|
1418 |
+
value: 40.833000000000006
|
1419 |
+
- type: ndcg_at_100
|
1420 |
+
value: 46.357
|
1421 |
+
- type: ndcg_at_1000
|
1422 |
+
value: 47.637
|
1423 |
+
- type: ndcg_at_3
|
1424 |
+
value: 32.995999999999995
|
1425 |
+
- type: ndcg_at_5
|
1426 |
+
value: 36.919000000000004
|
1427 |
+
- type: precision_at_1
|
1428 |
+
value: 22.493
|
1429 |
+
- type: precision_at_10
|
1430 |
+
value: 6.465999999999999
|
1431 |
+
- type: precision_at_100
|
1432 |
+
value: 0.9249999999999999
|
1433 |
+
- type: precision_at_1000
|
1434 |
+
value: 0.104
|
1435 |
+
- type: precision_at_3
|
1436 |
+
value: 14.030999999999999
|
1437 |
+
- type: precision_at_5
|
1438 |
+
value: 10.413
|
1439 |
+
- type: recall_at_1
|
1440 |
+
value: 21.852
|
1441 |
+
- type: recall_at_10
|
1442 |
+
value: 61.934999999999995
|
1443 |
+
- type: recall_at_100
|
1444 |
+
value: 87.611
|
1445 |
+
- type: recall_at_1000
|
1446 |
+
value: 97.441
|
1447 |
+
- type: recall_at_3
|
1448 |
+
value: 40.583999999999996
|
1449 |
+
- type: recall_at_5
|
1450 |
+
value: 49.992999999999995
|
1451 |
+
- task:
|
1452 |
+
type: Classification
|
1453 |
+
dataset:
|
1454 |
+
name: MTEB MTOPDomainClassification (en)
|
1455 |
+
type: mteb/mtop_domain
|
1456 |
+
config: en
|
1457 |
+
split: test
|
1458 |
+
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
|
1459 |
+
metrics:
|
1460 |
+
- type: accuracy
|
1461 |
+
value: 93.36069311445507
|
1462 |
+
- type: f1
|
1463 |
+
value: 93.16456330371453
|
1464 |
+
- task:
|
1465 |
+
type: Classification
|
1466 |
+
dataset:
|
1467 |
+
name: MTEB MTOPIntentClassification (en)
|
1468 |
+
type: mteb/mtop_intent
|
1469 |
+
config: en
|
1470 |
+
split: test
|
1471 |
+
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
|
1472 |
+
metrics:
|
1473 |
+
- type: accuracy
|
1474 |
+
value: 74.74692202462381
|
1475 |
+
- type: f1
|
1476 |
+
value: 58.17903579421599
|
1477 |
+
- task:
|
1478 |
+
type: Classification
|
1479 |
+
dataset:
|
1480 |
+
name: MTEB MassiveIntentClassification (en)
|
1481 |
+
type: mteb/amazon_massive_intent
|
1482 |
+
config: en
|
1483 |
+
split: test
|
1484 |
+
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
|
1485 |
+
metrics:
|
1486 |
+
- type: accuracy
|
1487 |
+
value: 74.80833893745796
|
1488 |
+
- type: f1
|
1489 |
+
value: 72.70786592684664
|
1490 |
+
- task:
|
1491 |
+
type: Classification
|
1492 |
+
dataset:
|
1493 |
+
name: MTEB MassiveScenarioClassification (en)
|
1494 |
+
type: mteb/amazon_massive_scenario
|
1495 |
+
config: en
|
1496 |
+
split: test
|
1497 |
+
revision: 7d571f92784cd94a019292a1f45445077d0ef634
|
1498 |
+
metrics:
|
1499 |
+
- type: accuracy
|
1500 |
+
value: 78.69872225958305
|
1501 |
+
- type: f1
|
1502 |
+
value: 78.61626934504731
|
1503 |
+
- task:
|
1504 |
+
type: Clustering
|
1505 |
+
dataset:
|
1506 |
+
name: MTEB MedrxivClusteringP2P
|
1507 |
+
type: mteb/medrxiv-clustering-p2p
|
1508 |
+
config: default
|
1509 |
+
split: test
|
1510 |
+
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
|
1511 |
+
metrics:
|
1512 |
+
- type: v_measure
|
1513 |
+
value: 33.058658628717694
|
1514 |
+
- task:
|
1515 |
+
type: Clustering
|
1516 |
+
dataset:
|
1517 |
+
name: MTEB MedrxivClusteringS2S
|
1518 |
+
type: mteb/medrxiv-clustering-s2s
|
1519 |
+
config: default
|
1520 |
+
split: test
|
1521 |
+
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
|
1522 |
+
metrics:
|
1523 |
+
- type: v_measure
|
1524 |
+
value: 30.85561739360599
|
1525 |
+
- task:
|
1526 |
+
type: Reranking
|
1527 |
+
dataset:
|
1528 |
+
name: MTEB MindSmallReranking
|
1529 |
+
type: mteb/mind_small
|
1530 |
+
config: default
|
1531 |
+
split: test
|
1532 |
+
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
|
1533 |
+
metrics:
|
1534 |
+
- type: map
|
1535 |
+
value: 31.290259910144385
|
1536 |
+
- type: mrr
|
1537 |
+
value: 32.44223046102856
|
1538 |
+
- task:
|
1539 |
+
type: Retrieval
|
1540 |
+
dataset:
|
1541 |
+
name: MTEB NFCorpus
|
1542 |
+
type: nfcorpus
|
1543 |
+
config: default
|
1544 |
+
split: test
|
1545 |
+
revision: None
|
1546 |
+
metrics:
|
1547 |
+
- type: map_at_1
|
1548 |
+
value: 5.288
|
1549 |
+
- type: map_at_10
|
1550 |
+
value: 12.267999999999999
|
1551 |
+
- type: map_at_100
|
1552 |
+
value: 15.557000000000002
|
1553 |
+
- type: map_at_1000
|
1554 |
+
value: 16.98
|
1555 |
+
- type: map_at_3
|
1556 |
+
value: 8.866
|
1557 |
+
- type: map_at_5
|
1558 |
+
value: 10.418
|
1559 |
+
- type: mrr_at_1
|
1560 |
+
value: 43.653
|
1561 |
+
- type: mrr_at_10
|
1562 |
+
value: 52.681
|
1563 |
+
- type: mrr_at_100
|
1564 |
+
value: 53.315999999999995
|
1565 |
+
- type: mrr_at_1000
|
1566 |
+
value: 53.357
|
1567 |
+
- type: mrr_at_3
|
1568 |
+
value: 51.393
|
1569 |
+
- type: mrr_at_5
|
1570 |
+
value: 51.903999999999996
|
1571 |
+
- type: ndcg_at_1
|
1572 |
+
value: 42.415000000000006
|
1573 |
+
- type: ndcg_at_10
|
1574 |
+
value: 34.305
|
1575 |
+
- type: ndcg_at_100
|
1576 |
+
value: 30.825999999999997
|
1577 |
+
- type: ndcg_at_1000
|
1578 |
+
value: 39.393
|
1579 |
+
- type: ndcg_at_3
|
1580 |
+
value: 39.931
|
1581 |
+
- type: ndcg_at_5
|
1582 |
+
value: 37.519999999999996
|
1583 |
+
- type: precision_at_1
|
1584 |
+
value: 43.653
|
1585 |
+
- type: precision_at_10
|
1586 |
+
value: 25.728
|
1587 |
+
- type: precision_at_100
|
1588 |
+
value: 7.932
|
1589 |
+
- type: precision_at_1000
|
1590 |
+
value: 2.07
|
1591 |
+
- type: precision_at_3
|
1592 |
+
value: 38.184000000000005
|
1593 |
+
- type: precision_at_5
|
1594 |
+
value: 32.879000000000005
|
1595 |
+
- type: recall_at_1
|
1596 |
+
value: 5.288
|
1597 |
+
- type: recall_at_10
|
1598 |
+
value: 16.195
|
1599 |
+
- type: recall_at_100
|
1600 |
+
value: 31.135
|
1601 |
+
- type: recall_at_1000
|
1602 |
+
value: 61.531000000000006
|
1603 |
+
- type: recall_at_3
|
1604 |
+
value: 10.313
|
1605 |
+
- type: recall_at_5
|
1606 |
+
value: 12.754999999999999
|
1607 |
+
- task:
|
1608 |
+
type: Retrieval
|
1609 |
+
dataset:
|
1610 |
+
name: MTEB NQ
|
1611 |
+
type: nq
|
1612 |
+
config: default
|
1613 |
+
split: test
|
1614 |
+
revision: None
|
1615 |
+
metrics:
|
1616 |
+
- type: map_at_1
|
1617 |
+
value: 28.216
|
1618 |
+
- type: map_at_10
|
1619 |
+
value: 42.588
|
1620 |
+
- type: map_at_100
|
1621 |
+
value: 43.702999999999996
|
1622 |
+
- type: map_at_1000
|
1623 |
+
value: 43.739
|
1624 |
+
- type: map_at_3
|
1625 |
+
value: 38.177
|
1626 |
+
- type: map_at_5
|
1627 |
+
value: 40.754000000000005
|
1628 |
+
- type: mrr_at_1
|
1629 |
+
value: 31.866
|
1630 |
+
- type: mrr_at_10
|
1631 |
+
value: 45.189
|
1632 |
+
- type: mrr_at_100
|
1633 |
+
value: 46.056000000000004
|
1634 |
+
- type: mrr_at_1000
|
1635 |
+
value: 46.081
|
1636 |
+
- type: mrr_at_3
|
1637 |
+
value: 41.526999999999994
|
1638 |
+
- type: mrr_at_5
|
1639 |
+
value: 43.704
|
1640 |
+
- type: ndcg_at_1
|
1641 |
+
value: 31.837
|
1642 |
+
- type: ndcg_at_10
|
1643 |
+
value: 50.178
|
1644 |
+
- type: ndcg_at_100
|
1645 |
+
value: 54.98800000000001
|
1646 |
+
- type: ndcg_at_1000
|
1647 |
+
value: 55.812
|
1648 |
+
- type: ndcg_at_3
|
1649 |
+
value: 41.853
|
1650 |
+
- type: ndcg_at_5
|
1651 |
+
value: 46.153
|
1652 |
+
- type: precision_at_1
|
1653 |
+
value: 31.837
|
1654 |
+
- type: precision_at_10
|
1655 |
+
value: 8.43
|
1656 |
+
- type: precision_at_100
|
1657 |
+
value: 1.1119999999999999
|
1658 |
+
- type: precision_at_1000
|
1659 |
+
value: 0.11900000000000001
|
1660 |
+
- type: precision_at_3
|
1661 |
+
value: 19.023
|
1662 |
+
- type: precision_at_5
|
1663 |
+
value: 13.911000000000001
|
1664 |
+
- type: recall_at_1
|
1665 |
+
value: 28.216
|
1666 |
+
- type: recall_at_10
|
1667 |
+
value: 70.8
|
1668 |
+
- type: recall_at_100
|
1669 |
+
value: 91.857
|
1670 |
+
- type: recall_at_1000
|
1671 |
+
value: 97.941
|
1672 |
+
- type: recall_at_3
|
1673 |
+
value: 49.196
|
1674 |
+
- type: recall_at_5
|
1675 |
+
value: 59.072
|
1676 |
+
- task:
|
1677 |
+
type: Retrieval
|
1678 |
+
dataset:
|
1679 |
+
name: MTEB QuoraRetrieval
|
1680 |
+
type: quora
|
1681 |
+
config: default
|
1682 |
+
split: test
|
1683 |
+
revision: None
|
1684 |
+
metrics:
|
1685 |
+
- type: map_at_1
|
1686 |
+
value: 71.22800000000001
|
1687 |
+
- type: map_at_10
|
1688 |
+
value: 85.115
|
1689 |
+
- type: map_at_100
|
1690 |
+
value: 85.72
|
1691 |
+
- type: map_at_1000
|
1692 |
+
value: 85.737
|
1693 |
+
- type: map_at_3
|
1694 |
+
value: 82.149
|
1695 |
+
- type: map_at_5
|
1696 |
+
value: 84.029
|
1697 |
+
- type: mrr_at_1
|
1698 |
+
value: 81.96
|
1699 |
+
- type: mrr_at_10
|
1700 |
+
value: 88.00200000000001
|
1701 |
+
- type: mrr_at_100
|
1702 |
+
value: 88.088
|
1703 |
+
- type: mrr_at_1000
|
1704 |
+
value: 88.089
|
1705 |
+
- type: mrr_at_3
|
1706 |
+
value: 87.055
|
1707 |
+
- type: mrr_at_5
|
1708 |
+
value: 87.715
|
1709 |
+
- type: ndcg_at_1
|
1710 |
+
value: 82.01
|
1711 |
+
- type: ndcg_at_10
|
1712 |
+
value: 88.78
|
1713 |
+
- type: ndcg_at_100
|
1714 |
+
value: 89.91
|
1715 |
+
- type: ndcg_at_1000
|
1716 |
+
value: 90.013
|
1717 |
+
- type: ndcg_at_3
|
1718 |
+
value: 85.957
|
1719 |
+
- type: ndcg_at_5
|
1720 |
+
value: 87.56
|
1721 |
+
- type: precision_at_1
|
1722 |
+
value: 82.01
|
1723 |
+
- type: precision_at_10
|
1724 |
+
value: 13.462
|
1725 |
+
- type: precision_at_100
|
1726 |
+
value: 1.528
|
1727 |
+
- type: precision_at_1000
|
1728 |
+
value: 0.157
|
1729 |
+
- type: precision_at_3
|
1730 |
+
value: 37.553
|
1731 |
+
- type: precision_at_5
|
1732 |
+
value: 24.732000000000003
|
1733 |
+
- type: recall_at_1
|
1734 |
+
value: 71.22800000000001
|
1735 |
+
- type: recall_at_10
|
1736 |
+
value: 95.69
|
1737 |
+
- type: recall_at_100
|
1738 |
+
value: 99.531
|
1739 |
+
- type: recall_at_1000
|
1740 |
+
value: 99.98
|
1741 |
+
- type: recall_at_3
|
1742 |
+
value: 87.632
|
1743 |
+
- type: recall_at_5
|
1744 |
+
value: 92.117
|
1745 |
+
- task:
|
1746 |
+
type: Clustering
|
1747 |
+
dataset:
|
1748 |
+
name: MTEB RedditClustering
|
1749 |
+
type: mteb/reddit-clustering
|
1750 |
+
config: default
|
1751 |
+
split: test
|
1752 |
+
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
|
1753 |
+
metrics:
|
1754 |
+
- type: v_measure
|
1755 |
+
value: 52.31768034366916
|
1756 |
+
- task:
|
1757 |
+
type: Clustering
|
1758 |
+
dataset:
|
1759 |
+
name: MTEB RedditClusteringP2P
|
1760 |
+
type: mteb/reddit-clustering-p2p
|
1761 |
+
config: default
|
1762 |
+
split: test
|
1763 |
+
revision: 282350215ef01743dc01b456c7f5241fa8937f16
|
1764 |
+
metrics:
|
1765 |
+
- type: v_measure
|
1766 |
+
value: 60.640266772723606
|
1767 |
+
- task:
|
1768 |
+
type: Retrieval
|
1769 |
+
dataset:
|
1770 |
+
name: MTEB SCIDOCS
|
1771 |
+
type: scidocs
|
1772 |
+
config: default
|
1773 |
+
split: test
|
1774 |
+
revision: None
|
1775 |
+
metrics:
|
1776 |
+
- type: map_at_1
|
1777 |
+
value: 4.7780000000000005
|
1778 |
+
- type: map_at_10
|
1779 |
+
value: 12.299
|
1780 |
+
- type: map_at_100
|
1781 |
+
value: 14.363000000000001
|
1782 |
+
- type: map_at_1000
|
1783 |
+
value: 14.71
|
1784 |
+
- type: map_at_3
|
1785 |
+
value: 8.738999999999999
|
1786 |
+
- type: map_at_5
|
1787 |
+
value: 10.397
|
1788 |
+
- type: mrr_at_1
|
1789 |
+
value: 23.599999999999998
|
1790 |
+
- type: mrr_at_10
|
1791 |
+
value: 34.845
|
1792 |
+
- type: mrr_at_100
|
1793 |
+
value: 35.916
|
1794 |
+
- type: mrr_at_1000
|
1795 |
+
value: 35.973
|
1796 |
+
- type: mrr_at_3
|
1797 |
+
value: 31.7
|
1798 |
+
- type: mrr_at_5
|
1799 |
+
value: 33.535
|
1800 |
+
- type: ndcg_at_1
|
1801 |
+
value: 23.599999999999998
|
1802 |
+
- type: ndcg_at_10
|
1803 |
+
value: 20.522000000000002
|
1804 |
+
- type: ndcg_at_100
|
1805 |
+
value: 28.737000000000002
|
1806 |
+
- type: ndcg_at_1000
|
1807 |
+
value: 34.596
|
1808 |
+
- type: ndcg_at_3
|
1809 |
+
value: 19.542
|
1810 |
+
- type: ndcg_at_5
|
1811 |
+
value: 16.958000000000002
|
1812 |
+
- type: precision_at_1
|
1813 |
+
value: 23.599999999999998
|
1814 |
+
- type: precision_at_10
|
1815 |
+
value: 10.67
|
1816 |
+
- type: precision_at_100
|
1817 |
+
value: 2.259
|
1818 |
+
- type: precision_at_1000
|
1819 |
+
value: 0.367
|
1820 |
+
- type: precision_at_3
|
1821 |
+
value: 18.333
|
1822 |
+
- type: precision_at_5
|
1823 |
+
value: 14.879999999999999
|
1824 |
+
- type: recall_at_1
|
1825 |
+
value: 4.7780000000000005
|
1826 |
+
- type: recall_at_10
|
1827 |
+
value: 21.617
|
1828 |
+
- type: recall_at_100
|
1829 |
+
value: 45.905
|
1830 |
+
- type: recall_at_1000
|
1831 |
+
value: 74.42
|
1832 |
+
- type: recall_at_3
|
1833 |
+
value: 11.148
|
1834 |
+
- type: recall_at_5
|
1835 |
+
value: 15.082999999999998
|
1836 |
+
- task:
|
1837 |
+
type: STS
|
1838 |
+
dataset:
|
1839 |
+
name: MTEB SICK-R
|
1840 |
+
type: mteb/sickr-sts
|
1841 |
+
config: default
|
1842 |
+
split: test
|
1843 |
+
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
|
1844 |
+
metrics:
|
1845 |
+
- type: cos_sim_pearson
|
1846 |
+
value: 83.22372750297885
|
1847 |
+
- type: cos_sim_spearman
|
1848 |
+
value: 79.40972617119405
|
1849 |
+
- type: euclidean_pearson
|
1850 |
+
value: 80.6101072020434
|
1851 |
+
- type: euclidean_spearman
|
1852 |
+
value: 79.53844217225202
|
1853 |
+
- type: manhattan_pearson
|
1854 |
+
value: 80.57265975286111
|
1855 |
+
- type: manhattan_spearman
|
1856 |
+
value: 79.46335611792958
|
1857 |
+
- task:
|
1858 |
+
type: STS
|
1859 |
+
dataset:
|
1860 |
+
name: MTEB STS12
|
1861 |
+
type: mteb/sts12-sts
|
1862 |
+
config: default
|
1863 |
+
split: test
|
1864 |
+
revision: a0d554a64d88156834ff5ae9920b964011b16384
|
1865 |
+
metrics:
|
1866 |
+
- type: cos_sim_pearson
|
1867 |
+
value: 85.43713315520749
|
1868 |
+
- type: cos_sim_spearman
|
1869 |
+
value: 77.44128693329532
|
1870 |
+
- type: euclidean_pearson
|
1871 |
+
value: 81.63869928101123
|
1872 |
+
- type: euclidean_spearman
|
1873 |
+
value: 77.29512977961515
|
1874 |
+
- type: manhattan_pearson
|
1875 |
+
value: 81.63704185566183
|
1876 |
+
- type: manhattan_spearman
|
1877 |
+
value: 77.29909412738657
|
1878 |
+
- task:
|
1879 |
+
type: STS
|
1880 |
+
dataset:
|
1881 |
+
name: MTEB STS13
|
1882 |
+
type: mteb/sts13-sts
|
1883 |
+
config: default
|
1884 |
+
split: test
|
1885 |
+
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
|
1886 |
+
metrics:
|
1887 |
+
- type: cos_sim_pearson
|
1888 |
+
value: 81.59451537860527
|
1889 |
+
- type: cos_sim_spearman
|
1890 |
+
value: 82.97994638856723
|
1891 |
+
- type: euclidean_pearson
|
1892 |
+
value: 82.89478688288412
|
1893 |
+
- type: euclidean_spearman
|
1894 |
+
value: 83.58740751053104
|
1895 |
+
- type: manhattan_pearson
|
1896 |
+
value: 82.69140840941608
|
1897 |
+
- type: manhattan_spearman
|
1898 |
+
value: 83.33665956040555
|
1899 |
+
- task:
|
1900 |
+
type: STS
|
1901 |
+
dataset:
|
1902 |
+
name: MTEB STS14
|
1903 |
+
type: mteb/sts14-sts
|
1904 |
+
config: default
|
1905 |
+
split: test
|
1906 |
+
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
|
1907 |
+
metrics:
|
1908 |
+
- type: cos_sim_pearson
|
1909 |
+
value: 82.00756527711764
|
1910 |
+
- type: cos_sim_spearman
|
1911 |
+
value: 81.83560996841379
|
1912 |
+
- type: euclidean_pearson
|
1913 |
+
value: 82.07684151976518
|
1914 |
+
- type: euclidean_spearman
|
1915 |
+
value: 82.00913052060511
|
1916 |
+
- type: manhattan_pearson
|
1917 |
+
value: 82.05690778488794
|
1918 |
+
- type: manhattan_spearman
|
1919 |
+
value: 82.02260252019525
|
1920 |
+
- task:
|
1921 |
+
type: STS
|
1922 |
+
dataset:
|
1923 |
+
name: MTEB STS15
|
1924 |
+
type: mteb/sts15-sts
|
1925 |
+
config: default
|
1926 |
+
split: test
|
1927 |
+
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
|
1928 |
+
metrics:
|
1929 |
+
- type: cos_sim_pearson
|
1930 |
+
value: 86.13710262895447
|
1931 |
+
- type: cos_sim_spearman
|
1932 |
+
value: 87.26412811156248
|
1933 |
+
- type: euclidean_pearson
|
1934 |
+
value: 86.94151453230228
|
1935 |
+
- type: euclidean_spearman
|
1936 |
+
value: 87.5363796699571
|
1937 |
+
- type: manhattan_pearson
|
1938 |
+
value: 86.86989424083748
|
1939 |
+
- type: manhattan_spearman
|
1940 |
+
value: 87.47315940781353
|
1941 |
+
- task:
|
1942 |
+
type: STS
|
1943 |
+
dataset:
|
1944 |
+
name: MTEB STS16
|
1945 |
+
type: mteb/sts16-sts
|
1946 |
+
config: default
|
1947 |
+
split: test
|
1948 |
+
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
|
1949 |
+
metrics:
|
1950 |
+
- type: cos_sim_pearson
|
1951 |
+
value: 83.0230597603627
|
1952 |
+
- type: cos_sim_spearman
|
1953 |
+
value: 84.93344499318864
|
1954 |
+
- type: euclidean_pearson
|
1955 |
+
value: 84.23754743431141
|
1956 |
+
- type: euclidean_spearman
|
1957 |
+
value: 85.09707376597099
|
1958 |
+
- type: manhattan_pearson
|
1959 |
+
value: 84.04325160987763
|
1960 |
+
- type: manhattan_spearman
|
1961 |
+
value: 84.89353071339909
|
1962 |
+
- task:
|
1963 |
+
type: STS
|
1964 |
+
dataset:
|
1965 |
+
name: MTEB STS17 (en-en)
|
1966 |
+
type: mteb/sts17-crosslingual-sts
|
1967 |
+
config: en-en
|
1968 |
+
split: test
|
1969 |
+
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
|
1970 |
+
metrics:
|
1971 |
+
- type: cos_sim_pearson
|
1972 |
+
value: 86.75620824563921
|
1973 |
+
- type: cos_sim_spearman
|
1974 |
+
value: 87.15065513706398
|
1975 |
+
- type: euclidean_pearson
|
1976 |
+
value: 88.26281533633521
|
1977 |
+
- type: euclidean_spearman
|
1978 |
+
value: 87.51963738643983
|
1979 |
+
- type: manhattan_pearson
|
1980 |
+
value: 88.25599267618065
|
1981 |
+
- type: manhattan_spearman
|
1982 |
+
value: 87.58048736047483
|
1983 |
+
- task:
|
1984 |
+
type: STS
|
1985 |
+
dataset:
|
1986 |
+
name: MTEB STS22 (en)
|
1987 |
+
type: mteb/sts22-crosslingual-sts
|
1988 |
+
config: en
|
1989 |
+
split: test
|
1990 |
+
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
|
1991 |
+
metrics:
|
1992 |
+
- type: cos_sim_pearson
|
1993 |
+
value: 64.74645319195137
|
1994 |
+
- type: cos_sim_spearman
|
1995 |
+
value: 65.29996325037214
|
1996 |
+
- type: euclidean_pearson
|
1997 |
+
value: 67.04297794086443
|
1998 |
+
- type: euclidean_spearman
|
1999 |
+
value: 65.43841726694343
|
2000 |
+
- type: manhattan_pearson
|
2001 |
+
value: 67.39459955690904
|
2002 |
+
- type: manhattan_spearman
|
2003 |
+
value: 65.92864704413651
|
2004 |
+
- task:
|
2005 |
+
type: STS
|
2006 |
+
dataset:
|
2007 |
+
name: MTEB STSBenchmark
|
2008 |
+
type: mteb/stsbenchmark-sts
|
2009 |
+
config: default
|
2010 |
+
split: test
|
2011 |
+
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
|
2012 |
+
metrics:
|
2013 |
+
- type: cos_sim_pearson
|
2014 |
+
value: 84.31291020270801
|
2015 |
+
- type: cos_sim_spearman
|
2016 |
+
value: 85.86473738688068
|
2017 |
+
- type: euclidean_pearson
|
2018 |
+
value: 85.65537275064152
|
2019 |
+
- type: euclidean_spearman
|
2020 |
+
value: 86.13087454209642
|
2021 |
+
- type: manhattan_pearson
|
2022 |
+
value: 85.43946955047609
|
2023 |
+
- type: manhattan_spearman
|
2024 |
+
value: 85.91568175344916
|
2025 |
+
- task:
|
2026 |
+
type: Reranking
|
2027 |
+
dataset:
|
2028 |
+
name: MTEB SciDocsRR
|
2029 |
+
type: mteb/scidocs-reranking
|
2030 |
+
config: default
|
2031 |
+
split: test
|
2032 |
+
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
|
2033 |
+
metrics:
|
2034 |
+
- type: map
|
2035 |
+
value: 85.93798118350695
|
2036 |
+
- type: mrr
|
2037 |
+
value: 95.93536274908824
|
2038 |
+
- task:
|
2039 |
+
type: Retrieval
|
2040 |
+
dataset:
|
2041 |
+
name: MTEB SciFact
|
2042 |
+
type: scifact
|
2043 |
+
config: default
|
2044 |
+
split: test
|
2045 |
+
revision: None
|
2046 |
+
metrics:
|
2047 |
+
- type: map_at_1
|
2048 |
+
value: 57.594
|
2049 |
+
- type: map_at_10
|
2050 |
+
value: 66.81899999999999
|
2051 |
+
- type: map_at_100
|
2052 |
+
value: 67.368
|
2053 |
+
- type: map_at_1000
|
2054 |
+
value: 67.4
|
2055 |
+
- type: map_at_3
|
2056 |
+
value: 64.061
|
2057 |
+
- type: map_at_5
|
2058 |
+
value: 65.47
|
2059 |
+
- type: mrr_at_1
|
2060 |
+
value: 60.667
|
2061 |
+
- type: mrr_at_10
|
2062 |
+
value: 68.219
|
2063 |
+
- type: mrr_at_100
|
2064 |
+
value: 68.655
|
2065 |
+
- type: mrr_at_1000
|
2066 |
+
value: 68.684
|
2067 |
+
- type: mrr_at_3
|
2068 |
+
value: 66.22200000000001
|
2069 |
+
- type: mrr_at_5
|
2070 |
+
value: 67.289
|
2071 |
+
- type: ndcg_at_1
|
2072 |
+
value: 60.667
|
2073 |
+
- type: ndcg_at_10
|
2074 |
+
value: 71.275
|
2075 |
+
- type: ndcg_at_100
|
2076 |
+
value: 73.642
|
2077 |
+
- type: ndcg_at_1000
|
2078 |
+
value: 74.373
|
2079 |
+
- type: ndcg_at_3
|
2080 |
+
value: 66.521
|
2081 |
+
- type: ndcg_at_5
|
2082 |
+
value: 68.581
|
2083 |
+
- type: precision_at_1
|
2084 |
+
value: 60.667
|
2085 |
+
- type: precision_at_10
|
2086 |
+
value: 9.433
|
2087 |
+
- type: precision_at_100
|
2088 |
+
value: 1.0699999999999998
|
2089 |
+
- type: precision_at_1000
|
2090 |
+
value: 0.11299999999999999
|
2091 |
+
- type: precision_at_3
|
2092 |
+
value: 25.556
|
2093 |
+
- type: precision_at_5
|
2094 |
+
value: 16.8
|
2095 |
+
- type: recall_at_1
|
2096 |
+
value: 57.594
|
2097 |
+
- type: recall_at_10
|
2098 |
+
value: 83.622
|
2099 |
+
- type: recall_at_100
|
2100 |
+
value: 94.167
|
2101 |
+
- type: recall_at_1000
|
2102 |
+
value: 99.667
|
2103 |
+
- type: recall_at_3
|
2104 |
+
value: 70.64399999999999
|
2105 |
+
- type: recall_at_5
|
2106 |
+
value: 75.983
|
2107 |
+
- task:
|
2108 |
+
type: PairClassification
|
2109 |
+
dataset:
|
2110 |
+
name: MTEB SprintDuplicateQuestions
|
2111 |
+
type: mteb/sprintduplicatequestions-pairclassification
|
2112 |
+
config: default
|
2113 |
+
split: test
|
2114 |
+
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
|
2115 |
+
metrics:
|
2116 |
+
- type: cos_sim_accuracy
|
2117 |
+
value: 99.85841584158416
|
2118 |
+
- type: cos_sim_ap
|
2119 |
+
value: 96.66996142314342
|
2120 |
+
- type: cos_sim_f1
|
2121 |
+
value: 92.83208020050125
|
2122 |
+
- type: cos_sim_precision
|
2123 |
+
value: 93.06532663316584
|
2124 |
+
- type: cos_sim_recall
|
2125 |
+
value: 92.60000000000001
|
2126 |
+
- type: dot_accuracy
|
2127 |
+
value: 99.85841584158416
|
2128 |
+
- type: dot_ap
|
2129 |
+
value: 96.6775307676576
|
2130 |
+
- type: dot_f1
|
2131 |
+
value: 92.69289729177312
|
2132 |
+
- type: dot_precision
|
2133 |
+
value: 94.77533960292581
|
2134 |
+
- type: dot_recall
|
2135 |
+
value: 90.7
|
2136 |
+
- type: euclidean_accuracy
|
2137 |
+
value: 99.86138613861387
|
2138 |
+
- type: euclidean_ap
|
2139 |
+
value: 96.6338454403108
|
2140 |
+
- type: euclidean_f1
|
2141 |
+
value: 92.92214357937311
|
2142 |
+
- type: euclidean_precision
|
2143 |
+
value: 93.96728016359918
|
2144 |
+
- type: euclidean_recall
|
2145 |
+
value: 91.9
|
2146 |
+
- type: manhattan_accuracy
|
2147 |
+
value: 99.86237623762376
|
2148 |
+
- type: manhattan_ap
|
2149 |
+
value: 96.60370449645053
|
2150 |
+
- type: manhattan_f1
|
2151 |
+
value: 92.91177970423253
|
2152 |
+
- type: manhattan_precision
|
2153 |
+
value: 94.7970863683663
|
2154 |
+
- type: manhattan_recall
|
2155 |
+
value: 91.10000000000001
|
2156 |
+
- type: max_accuracy
|
2157 |
+
value: 99.86237623762376
|
2158 |
+
- type: max_ap
|
2159 |
+
value: 96.6775307676576
|
2160 |
+
- type: max_f1
|
2161 |
+
value: 92.92214357937311
|
2162 |
+
- task:
|
2163 |
+
type: Clustering
|
2164 |
+
dataset:
|
2165 |
+
name: MTEB StackExchangeClustering
|
2166 |
+
type: mteb/stackexchange-clustering
|
2167 |
+
config: default
|
2168 |
+
split: test
|
2169 |
+
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
|
2170 |
+
metrics:
|
2171 |
+
- type: v_measure
|
2172 |
+
value: 60.77977058695198
|
2173 |
+
- task:
|
2174 |
+
type: Clustering
|
2175 |
+
dataset:
|
2176 |
+
name: MTEB StackExchangeClusteringP2P
|
2177 |
+
type: mteb/stackexchange-clustering-p2p
|
2178 |
+
config: default
|
2179 |
+
split: test
|
2180 |
+
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
|
2181 |
+
metrics:
|
2182 |
+
- type: v_measure
|
2183 |
+
value: 35.2725272535638
|
2184 |
+
- task:
|
2185 |
+
type: Reranking
|
2186 |
+
dataset:
|
2187 |
+
name: MTEB StackOverflowDupQuestions
|
2188 |
+
type: mteb/stackoverflowdupquestions-reranking
|
2189 |
+
config: default
|
2190 |
+
split: test
|
2191 |
+
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
|
2192 |
+
metrics:
|
2193 |
+
- type: map
|
2194 |
+
value: 53.64052466362125
|
2195 |
+
- type: mrr
|
2196 |
+
value: 54.533067014684654
|
2197 |
+
- task:
|
2198 |
+
type: Summarization
|
2199 |
+
dataset:
|
2200 |
+
name: MTEB SummEval
|
2201 |
+
type: mteb/summeval
|
2202 |
+
config: default
|
2203 |
+
split: test
|
2204 |
+
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
|
2205 |
+
metrics:
|
2206 |
+
- type: cos_sim_pearson
|
2207 |
+
value: 30.677624219206578
|
2208 |
+
- type: cos_sim_spearman
|
2209 |
+
value: 30.121368518123447
|
2210 |
+
- type: dot_pearson
|
2211 |
+
value: 30.69870088041608
|
2212 |
+
- type: dot_spearman
|
2213 |
+
value: 29.61284927093751
|
2214 |
+
- task:
|
2215 |
+
type: Retrieval
|
2216 |
+
dataset:
|
2217 |
+
name: MTEB TRECCOVID
|
2218 |
+
type: trec-covid
|
2219 |
+
config: default
|
2220 |
+
split: test
|
2221 |
+
revision: None
|
2222 |
+
metrics:
|
2223 |
+
- type: map_at_1
|
2224 |
+
value: 0.22
|
2225 |
+
- type: map_at_10
|
2226 |
+
value: 1.855
|
2227 |
+
- type: map_at_100
|
2228 |
+
value: 9.885
|
2229 |
+
- type: map_at_1000
|
2230 |
+
value: 23.416999999999998
|
2231 |
+
- type: map_at_3
|
2232 |
+
value: 0.637
|
2233 |
+
- type: map_at_5
|
2234 |
+
value: 1.024
|
2235 |
+
- type: mrr_at_1
|
2236 |
+
value: 88.0
|
2237 |
+
- type: mrr_at_10
|
2238 |
+
value: 93.067
|
2239 |
+
- type: mrr_at_100
|
2240 |
+
value: 93.067
|
2241 |
+
- type: mrr_at_1000
|
2242 |
+
value: 93.067
|
2243 |
+
- type: mrr_at_3
|
2244 |
+
value: 92.667
|
2245 |
+
- type: mrr_at_5
|
2246 |
+
value: 93.067
|
2247 |
+
- type: ndcg_at_1
|
2248 |
+
value: 82.0
|
2249 |
+
- type: ndcg_at_10
|
2250 |
+
value: 75.899
|
2251 |
+
- type: ndcg_at_100
|
2252 |
+
value: 55.115
|
2253 |
+
- type: ndcg_at_1000
|
2254 |
+
value: 48.368
|
2255 |
+
- type: ndcg_at_3
|
2256 |
+
value: 79.704
|
2257 |
+
- type: ndcg_at_5
|
2258 |
+
value: 78.39699999999999
|
2259 |
+
- type: precision_at_1
|
2260 |
+
value: 88.0
|
2261 |
+
- type: precision_at_10
|
2262 |
+
value: 79.60000000000001
|
2263 |
+
- type: precision_at_100
|
2264 |
+
value: 56.06
|
2265 |
+
- type: precision_at_1000
|
2266 |
+
value: 21.206
|
2267 |
+
- type: precision_at_3
|
2268 |
+
value: 84.667
|
2269 |
+
- type: precision_at_5
|
2270 |
+
value: 83.2
|
2271 |
+
- type: recall_at_1
|
2272 |
+
value: 0.22
|
2273 |
+
- type: recall_at_10
|
2274 |
+
value: 2.078
|
2275 |
+
- type: recall_at_100
|
2276 |
+
value: 13.297
|
2277 |
+
- type: recall_at_1000
|
2278 |
+
value: 44.979
|
2279 |
+
- type: recall_at_3
|
2280 |
+
value: 0.6689999999999999
|
2281 |
+
- type: recall_at_5
|
2282 |
+
value: 1.106
|
2283 |
+
- task:
|
2284 |
+
type: Retrieval
|
2285 |
+
dataset:
|
2286 |
+
name: MTEB Touche2020
|
2287 |
+
type: webis-touche2020
|
2288 |
+
config: default
|
2289 |
+
split: test
|
2290 |
+
revision: None
|
2291 |
+
metrics:
|
2292 |
+
- type: map_at_1
|
2293 |
+
value: 2.258
|
2294 |
+
- type: map_at_10
|
2295 |
+
value: 10.439
|
2296 |
+
- type: map_at_100
|
2297 |
+
value: 16.89
|
2298 |
+
- type: map_at_1000
|
2299 |
+
value: 18.407999999999998
|
2300 |
+
- type: map_at_3
|
2301 |
+
value: 5.668
|
2302 |
+
- type: map_at_5
|
2303 |
+
value: 7.718
|
2304 |
+
- type: mrr_at_1
|
2305 |
+
value: 32.653
|
2306 |
+
- type: mrr_at_10
|
2307 |
+
value: 51.159
|
2308 |
+
- type: mrr_at_100
|
2309 |
+
value: 51.714000000000006
|
2310 |
+
- type: mrr_at_1000
|
2311 |
+
value: 51.714000000000006
|
2312 |
+
- type: mrr_at_3
|
2313 |
+
value: 47.959
|
2314 |
+
- type: mrr_at_5
|
2315 |
+
value: 50.407999999999994
|
2316 |
+
- type: ndcg_at_1
|
2317 |
+
value: 29.592000000000002
|
2318 |
+
- type: ndcg_at_10
|
2319 |
+
value: 26.037
|
2320 |
+
- type: ndcg_at_100
|
2321 |
+
value: 37.924
|
2322 |
+
- type: ndcg_at_1000
|
2323 |
+
value: 49.126999999999995
|
2324 |
+
- type: ndcg_at_3
|
2325 |
+
value: 30.631999999999998
|
2326 |
+
- type: ndcg_at_5
|
2327 |
+
value: 28.571
|
2328 |
+
- type: precision_at_1
|
2329 |
+
value: 32.653
|
2330 |
+
- type: precision_at_10
|
2331 |
+
value: 22.857
|
2332 |
+
- type: precision_at_100
|
2333 |
+
value: 7.754999999999999
|
2334 |
+
- type: precision_at_1000
|
2335 |
+
value: 1.529
|
2336 |
+
- type: precision_at_3
|
2337 |
+
value: 34.014
|
2338 |
+
- type: precision_at_5
|
2339 |
+
value: 29.796
|
2340 |
+
- type: recall_at_1
|
2341 |
+
value: 2.258
|
2342 |
+
- type: recall_at_10
|
2343 |
+
value: 16.554
|
2344 |
+
- type: recall_at_100
|
2345 |
+
value: 48.439
|
2346 |
+
- type: recall_at_1000
|
2347 |
+
value: 82.80499999999999
|
2348 |
+
- type: recall_at_3
|
2349 |
+
value: 7.283
|
2350 |
+
- type: recall_at_5
|
2351 |
+
value: 10.732
|
2352 |
+
- task:
|
2353 |
+
type: Classification
|
2354 |
+
dataset:
|
2355 |
+
name: MTEB ToxicConversationsClassification
|
2356 |
+
type: mteb/toxic_conversations_50k
|
2357 |
+
config: default
|
2358 |
+
split: test
|
2359 |
+
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
|
2360 |
+
metrics:
|
2361 |
+
- type: accuracy
|
2362 |
+
value: 69.8858
|
2363 |
+
- type: ap
|
2364 |
+
value: 13.835684144362109
|
2365 |
+
- type: f1
|
2366 |
+
value: 53.803351693244586
|
2367 |
+
- task:
|
2368 |
+
type: Classification
|
2369 |
+
dataset:
|
2370 |
+
name: MTEB TweetSentimentExtractionClassification
|
2371 |
+
type: mteb/tweet_sentiment_extraction
|
2372 |
+
config: default
|
2373 |
+
split: test
|
2374 |
+
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
|
2375 |
+
metrics:
|
2376 |
+
- type: accuracy
|
2377 |
+
value: 60.50650820599886
|
2378 |
+
- type: f1
|
2379 |
+
value: 60.84357825979259
|
2380 |
+
- task:
|
2381 |
+
type: Clustering
|
2382 |
+
dataset:
|
2383 |
+
name: MTEB TwentyNewsgroupsClustering
|
2384 |
+
type: mteb/twentynewsgroups-clustering
|
2385 |
+
config: default
|
2386 |
+
split: test
|
2387 |
+
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
|
2388 |
+
metrics:
|
2389 |
+
- type: v_measure
|
2390 |
+
value: 48.52131044852134
|
2391 |
+
- task:
|
2392 |
+
type: PairClassification
|
2393 |
+
dataset:
|
2394 |
+
name: MTEB TwitterSemEval2015
|
2395 |
+
type: mteb/twittersemeval2015-pairclassification
|
2396 |
+
config: default
|
2397 |
+
split: test
|
2398 |
+
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
|
2399 |
+
metrics:
|
2400 |
+
- type: cos_sim_accuracy
|
2401 |
+
value: 85.59337187816654
|
2402 |
+
- type: cos_sim_ap
|
2403 |
+
value: 73.23925826533437
|
2404 |
+
- type: cos_sim_f1
|
2405 |
+
value: 67.34693877551021
|
2406 |
+
- type: cos_sim_precision
|
2407 |
+
value: 62.40432237730752
|
2408 |
+
- type: cos_sim_recall
|
2409 |
+
value: 73.13984168865434
|
2410 |
+
- type: dot_accuracy
|
2411 |
+
value: 85.31322644096085
|
2412 |
+
- type: dot_ap
|
2413 |
+
value: 72.30723963807422
|
2414 |
+
- type: dot_f1
|
2415 |
+
value: 66.47051612112296
|
2416 |
+
- type: dot_precision
|
2417 |
+
value: 62.0792305930845
|
2418 |
+
- type: dot_recall
|
2419 |
+
value: 71.53034300791556
|
2420 |
+
- type: euclidean_accuracy
|
2421 |
+
value: 85.61125350181797
|
2422 |
+
- type: euclidean_ap
|
2423 |
+
value: 73.32843720487845
|
2424 |
+
- type: euclidean_f1
|
2425 |
+
value: 67.36549633745895
|
2426 |
+
- type: euclidean_precision
|
2427 |
+
value: 64.60755813953489
|
2428 |
+
- type: euclidean_recall
|
2429 |
+
value: 70.36939313984169
|
2430 |
+
- type: manhattan_accuracy
|
2431 |
+
value: 85.63509566668654
|
2432 |
+
- type: manhattan_ap
|
2433 |
+
value: 73.16658488311325
|
2434 |
+
- type: manhattan_f1
|
2435 |
+
value: 67.20597386434349
|
2436 |
+
- type: manhattan_precision
|
2437 |
+
value: 63.60424028268551
|
2438 |
+
- type: manhattan_recall
|
2439 |
+
value: 71.2401055408971
|
2440 |
+
- type: max_accuracy
|
2441 |
+
value: 85.63509566668654
|
2442 |
+
- type: max_ap
|
2443 |
+
value: 73.32843720487845
|
2444 |
+
- type: max_f1
|
2445 |
+
value: 67.36549633745895
|
2446 |
+
- task:
|
2447 |
+
type: PairClassification
|
2448 |
+
dataset:
|
2449 |
+
name: MTEB TwitterURLCorpus
|
2450 |
+
type: mteb/twitterurlcorpus-pairclassification
|
2451 |
+
config: default
|
2452 |
+
split: test
|
2453 |
+
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
|
2454 |
+
metrics:
|
2455 |
+
- type: cos_sim_accuracy
|
2456 |
+
value: 88.33779640625606
|
2457 |
+
- type: cos_sim_ap
|
2458 |
+
value: 84.83868375898157
|
2459 |
+
- type: cos_sim_f1
|
2460 |
+
value: 77.16506154017773
|
2461 |
+
- type: cos_sim_precision
|
2462 |
+
value: 74.62064005753327
|
2463 |
+
- type: cos_sim_recall
|
2464 |
+
value: 79.88912842623961
|
2465 |
+
- type: dot_accuracy
|
2466 |
+
value: 88.02732176815307
|
2467 |
+
- type: dot_ap
|
2468 |
+
value: 83.95089283763002
|
2469 |
+
- type: dot_f1
|
2470 |
+
value: 76.29635101196631
|
2471 |
+
- type: dot_precision
|
2472 |
+
value: 73.31771720613288
|
2473 |
+
- type: dot_recall
|
2474 |
+
value: 79.52725592854944
|
2475 |
+
- type: euclidean_accuracy
|
2476 |
+
value: 88.44452206310397
|
2477 |
+
- type: euclidean_ap
|
2478 |
+
value: 84.98384576824827
|
2479 |
+
- type: euclidean_f1
|
2480 |
+
value: 77.29311047696697
|
2481 |
+
- type: euclidean_precision
|
2482 |
+
value: 74.51232583065381
|
2483 |
+
- type: euclidean_recall
|
2484 |
+
value: 80.28949799815214
|
2485 |
+
- type: manhattan_accuracy
|
2486 |
+
value: 88.47362906042613
|
2487 |
+
- type: manhattan_ap
|
2488 |
+
value: 84.91421462218432
|
2489 |
+
- type: manhattan_f1
|
2490 |
+
value: 77.05107637204792
|
2491 |
+
- type: manhattan_precision
|
2492 |
+
value: 74.74484256243214
|
2493 |
+
- type: manhattan_recall
|
2494 |
+
value: 79.50415768401602
|
2495 |
+
- type: max_accuracy
|
2496 |
+
value: 88.47362906042613
|
2497 |
+
- type: max_ap
|
2498 |
+
value: 84.98384576824827
|
2499 |
+
- type: max_f1
|
2500 |
+
value: 77.29311047696697
|
2501 |
+
---
|
2502 |
+
|
2503 |
+
# wangjinzzhong/bge-small-en-v1.5-Q4_K_M-GGUF
|
2504 |
+
This model was converted to GGUF format from [`BAAI/bge-small-en-v1.5`](https://huggingface.co/BAAI/bge-small-en-v1.5) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
|
2505 |
+
Refer to the [original model card](https://huggingface.co/BAAI/bge-small-en-v1.5) for more details on the model.
|
2506 |
+
|
2507 |
+
## Use with llama.cpp
|
2508 |
+
Install llama.cpp through brew (works on Mac and Linux)
|
2509 |
+
|
2510 |
+
```bash
|
2511 |
+
brew install llama.cpp
|
2512 |
+
|
2513 |
+
```
|
2514 |
+
Invoke the llama.cpp server or the CLI.
|
2515 |
+
|
2516 |
+
### CLI:
|
2517 |
+
```bash
|
2518 |
+
llama-cli --hf-repo wangjinzzhong/bge-small-en-v1.5-Q4_K_M-GGUF --hf-file bge-small-en-v1.5-q4_k_m.gguf -p "The meaning to life and the universe is"
|
2519 |
+
```
|
2520 |
+
|
2521 |
+
### Server:
|
2522 |
+
```bash
|
2523 |
+
llama-server --hf-repo wangjinzzhong/bge-small-en-v1.5-Q4_K_M-GGUF --hf-file bge-small-en-v1.5-q4_k_m.gguf -c 2048
|
2524 |
+
```
|
2525 |
+
|
2526 |
+
Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.
|
2527 |
+
|
2528 |
+
Step 1: Clone llama.cpp from GitHub.
|
2529 |
+
```
|
2530 |
+
git clone https://github.com/ggerganov/llama.cpp
|
2531 |
+
```
|
2532 |
+
|
2533 |
+
Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
|
2534 |
+
```
|
2535 |
+
cd llama.cpp && LLAMA_CURL=1 make
|
2536 |
+
```
|
2537 |
+
|
2538 |
+
Step 3: Run inference through the main binary.
|
2539 |
+
```
|
2540 |
+
./llama-cli --hf-repo wangjinzzhong/bge-small-en-v1.5-Q4_K_M-GGUF --hf-file bge-small-en-v1.5-q4_k_m.gguf -p "The meaning to life and the universe is"
|
2541 |
+
```
|
2542 |
+
or
|
2543 |
+
```
|
2544 |
+
./llama-server --hf-repo wangjinzzhong/bge-small-en-v1.5-Q4_K_M-GGUF --hf-file bge-small-en-v1.5-q4_k_m.gguf -c 2048
|
2545 |
+
```
|