End of training

README.md

@@ -25,13 +25,13 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 0.9210089611682708
+      value: 0.9220255327226995
     - name: Recall
       type: recall
-      value: 0.9265442404006677
+      value: 0.9266873360362509
     - name: F1
       type: f1
-      value: 0.9237683089214381
+      value: 0.9243505566657151
 ---
 
 <!-- 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-base](https://huggingface.co/michiyasunaga/BioLinkBERT-base) on the source_data dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0134
+- Loss: 0.0137
 - Accuracy Score: 0.9948
-- Precision: 0.9210
-- Recall: 0.9265
-- F1: 0.9238
+- Precision: 0.9220
+- Recall: 0.9267
+- F1: 0.9244
 
 ## Model description
 
@@ -77,7 +77,7 @@ No additional optimizer arguments
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy Score | Precision | Recall | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------------:|:---------:|:------:|:------:|
-| 0.0146        | 1.0   | 864  | 0.0134          | 0.9948         | 0.9210    | 0.9265 | 0.9238 |
+| 0.0146        | 1.0   | 864  | 0.0137          | 0.9948         | 0.9220    | 0.9267 | 0.9244 |
 
 
 ### Framework versions