End of training

README.md

@@ -25,13 +25,13 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 0.9575311438278595
+      value: 0.9572504708097929
     - name: Recall
       type: recall
-      value: 0.9664698037721471
+      value: 0.9683749285578206
     - name: F1
       type: f1
-      value: 0.9619797098701053
+      value: 0.9627805663415098
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -41,11 +41,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [michiyasunaga/BioLinkBERT-large](https://huggingface.co/michiyasunaga/BioLinkBERT-large) on the source_data dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0064
-- Accuracy Score: 0.9982
-- Precision: 0.9575
-- Recall: 0.9665
-- F1: 0.9620
+- Loss: 0.0066
+- Accuracy Score: 0.9981
+- Precision: 0.9573
+- Recall: 0.9684
+- F1: 0.9628
 
 ## Model description
 
@@ -79,7 +79,7 @@ No additional optimizer arguments
 
 | Training Loss | Epoch  | Step | Validation Loss | Accuracy Score | Precision | Recall | F1     |
 |:-------------:|:------:|:----:|:---------------:|:--------------:|:---------:|:------:|:------:|
-| 0.0045        | 0.9994 | 863  | 0.0064          | 0.9982         | 0.9575    | 0.9665 | 0.9620 |
+| 0.0044        | 0.9994 | 863  | 0.0066          | 0.9981         | 0.9573    | 0.9684 | 0.9628 |
 
 
 ### Framework versions