Put both models in the evaluation table

README.md

@@ -30,10 +30,12 @@ The model was then evaluated on [Mean Reciprocal Rank (MRR)](https://en.wikipedi
 When the model has to pick the positive example out of a pool of 32, it almost always ranks it first. When
 the pool is significantly enlarged to 10.000 functions, it still ranks the positive example highest most of the time. 
 
-| Model     | Pool size | MRR  | Recall@1 |
-|-----------|-----------|------|----------|
-| ARM64BERT | 32        | 0.78 | 0.72     |
-| ARM64BERT | 10.000    | 0.58 | 0.56     |
+| Model                | Pool size | MRR  | Recall@1 |
+|----------------------|-----------|------|----------|
+| ARM64BERT            | 32        | 0.78 | 0.72     |
+| ARM64BERT-embedding  | 32        | 0.99 | 0.99     |
+| ARM64BERT            | 10.000    | 0.58 | 0.56     |
+| ARM64BERT-embedding  | 10.000    | 0.87 | 0.83     |
 
 ## Purpose and use of the model