Update README.md

README.md

@@ -46,8 +46,38 @@ print(embeddings)
 
 <!--- Describe how your model was evaluated -->
 
-For an automated evaluation of this model, see the *Sentence Embeddings Benchmark*: [https://seb.sbert.net](https://seb.sbert.net?model_name=adlumal/auslaw-embed-v1.0)
-
+| Test                   | Score        |
+|------------------------|--------------|
+| cos_sim-Accuracy@1     | 0.730206301  |
+| cos_sim-Accuracy@3     | 0.859562308  |
+| cos_sim-Accuracy@5     | 0.892737664  |
+| cos_sim-Accuracy@10    | 0.928352384  |
+| cos_sim-Precision@1    | 0.730206301  |
+| cos_sim-Recall@1       | 0.730206301  |
+| cos_sim-Precision@3    | 0.286520769  |
+| cos_sim-Recall@3       | 0.859562308  |
+| cos_sim-Precision@5    | 0.178547533  |
+| cos_sim-Recall@5       | 0.892737664  |
+| cos_sim-Precision@10   | 0.092835238  |
+| cos_sim-Recall@10      | 0.928352384  |
+| cos_sim-MRR@10         | 0.801075782  |
+| cos_sim-NDCG@10        | 0.832189447  |
+| cos_sim-MAP@100        | 0.803593645  |
+| dot_score-Accuracy@1   | 0.730136604  |
+| dot_score-Accuracy@3   | 0.859562308  |
+| dot_score-Accuracy@5   | 0.892737664  |
+| dot_score-Accuracy@10  | 0.928352384  |
+| dot_score-Precision@1  | 0.730136604  |
+| dot_score-Recall@1     | 0.730136604  |
+| dot_score-Precision@3  | 0.286520769  |
+| dot_score-Recall@3     | 0.859562308  |
+| dot_score-Precision@5  | 0.178547533  |
+| dot_score-Recall@5     | 0.892737664  |
+| dot_score-Precision@10 | 0.092835238  |
+| dot_score-Recall@10    | 0.928352384  |
+| dot_score-MRR@10       | 0.801040934  |
+| dot_score-NDCG@10      | 0.832163724  |
+| dot_score-MAP@100      | 0.803558796  |
 
 ## Training
 The model was trained with the parameters: