End of training

Information-Retrieval_evaluation_results.csv

@@ -1,2 +1,2 @@
 epoch,steps,cosine-Accuracy@1,cosine-Accuracy@5,cosine-Accuracy@10,cosine-Precision@1,cosine-Recall@1,cosine-Precision@3,cosine-Recall@3,cosine-Precision@5,cosine-Recall@5,cosine-Precision@10,cosine-Recall@10,cosine-MRR@1,cosine-MRR@5,cosine-MRR@10,cosine-NDCG@1,cosine-NDCG@5,cosine-NDCG@10,cosine-MAP@100
--1,-1,0.97,1.0,1.0,0.97,0.97,0.3333333333333334,1.0,0.19999999999999996,1.0,0.09999999999999998,1.0,0.97,0.985,0.985,0.97,0.9889278926071438,0.9889278926071438,0.985
+-1,-1,0.99,1.0,1.0,0.99,0.99,0.3333333333333334,1.0,0.19999999999999996,1.0,0.09999999999999998,1.0,0.99,0.995,0.995,0.99,0.9963092975357145,0.9963092975357145,0.995

README.md

@@ -620,6 +620,7 @@ You can finetune this model on your own dataset.
 |:-------:|:-----:|:---------------:|:--------------:|
 | 0       | 0     | 0.0616          | 0.9926         |
 | **1.0** | **7** | **0.0358**      | **0.9963**     |
+| -1      | -1    | -               | 0.9963         |
 
 * The bold row denotes the saved checkpoint.