End of training

README.md

@@ -25,13 +25,13 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 0.97200680915453
+      value: 0.9716285227917534
     - name: Recall
       type: recall
-      value: 0.9732954545454545
+      value: 0.9729166666666667
     - name: F1
       type: f1
-      value: 0.9726507050250781
+      value: 0.9722721680704078
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -43,9 +43,9 @@ This model is a fine-tuned version of [michiyasunaga/BioLinkBERT-base](https://h
 It achieves the following results on the evaluation set:
 - Loss: 0.0016
 - Accuracy Score: 0.9996
-- Precision: 0.9720
-- Recall: 0.9733
-- F1: 0.9727
+- Precision: 0.9716
+- Recall: 0.9729
+- F1: 0.9723
 
 ## Model description
 
@@ -77,7 +77,7 @@ No additional optimizer arguments
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy Score | Precision | Recall | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------------:|:---------:|:------:|:------:|
-| 0.0012        | 1.0   | 864  | 0.0016          | 0.9996         | 0.9720    | 0.9733 | 0.9727 |
+| 0.0011        | 1.0   | 864  | 0.0016          | 0.9996         | 0.9716    | 0.9729 | 0.9723 |
 
 
 ### Framework versions