Add benchmark scores of selected top-class embedding models

README.md

@@ -2671,3 +2671,7 @@ You can find a code to evaluate MTEB datasets using v1 embedding [here](https://
 |:-----------------------------------------------------------------------:|:---------:|:---:|:------------:|
 | [sionic-ai/sionic-ai-v2](https://huggingface.co/sionic-ai/sionic-ai-v2) |   3072    | 512 |  **65.23**   |  
 | [sionic-ai/sionic-ai-v1](https://huggingface.co/sionic-ai/sionic-ai-v1) |   2048    | 512 |    64.92     |  
+| [bge-large-en-v1.5](https://huggingface.co/BAAI/bge-large-en-v1.5) |   1024    |       512       |    64.23     |  
+| [gte-large-en](https://huggingface.co/barisaydin/gte-large) |   1024    |       512       |    63.13     |
+| [text-embedding-ada-002](https://platform.openai.com/docs/guides/embeddings/types-of-embedding-models) |   1536    |      8191       |    60.99     |
+