Update README.md

README.md

@@ -32,9 +32,10 @@ It is recommended to use a single GPU for inference.
 Additionally, we provide the following options:
 
 - `jina-embedding-s-en-v1`: 35 million parameters.
-- `jina-embedding-l-en-v1`: 800 million parameters.
-- `jina-embedding-xl-en-v1`: 3 billion parameters (soon).
-- `jina-embedding-xxl-en-v1`: 11 billion parameters (soon).
+- `jina-embedding-b-en-v1`: 110 million parameters **you are here**.
+- `jina-embedding-l-en-v1`: 330 million parameters.
+- `jina-embedding-xl-en-v1`: 1.2 billion parameters (soon).
+- `jina-embedding-xxl-en-v1`: 6 billion parameters (soon).
 
 ## Data & Parameters
 
@@ -42,15 +43,16 @@ More info will be released together with the technique report.
 
 ## Metrics
 
-We compared the model against `all-minilm-l6-v2` from sbert and `text-embeddings-ada-002` from OpenAI:
+We compared the model against `all-minilm-l6-v2`/`all-mpnet-base-v2` from sbert and `text-embeddings-ada-002` from OpenAI:
 
 |Name|param    |context|
 |------------------------------|-----|------|
 |all-minilm-l6-v2|33m      |128|
-|all-mpnet--base-v2 |110m     |128|
+|all-mpnet-base-v2 |110m     |128|
 |ada-embedding-002|Unknown/API based  |8192|
 |jina-embedding-s-en-v1|35m      |512|
 |jina-embedding-b-en-v1|110m      |512|
+|jina-embedding-l-en-v1|330m      |512|
 
 
 |Name|STS12|STS13|STS14|STS15|STS16|STS17|TRECOVID|Quora|SciFact|
@@ -60,6 +62,7 @@ We compared the model against `all-minilm-l6-v2` from sbert and `text-embeddings
 |ada-embedding-002|0.698|0.833|0.761|0.861|0.86 |0.903|0.685   |0.876|0.726  |
 |jina-embedding-s-en-v1|0.738|0.781|0.732|0.833|0.785|0.859|0.471   |0.852|0.567  |
 |jina-embedding-b-en-v1|0.736|0.804|0.745|0.844|0.793|0.873|0.481   |0.87|0.616  |
+|jina-embedding-l-en-v1|0.735|0.829|0.759|0.844|0.8|0.888|0.65   |0.876|0.645  |
 
 For more tasks and metrics, please checkout [MTEB](https://huggingface.co/spaces/mteb/leaderboard) benchmark.