End of training

README.md

@@ -25,13 +25,13 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 0.9554632949613134
+      value: 0.9540489642184558
     - name: Recall
       type: recall
-      value: 0.9645646789864736
+      value: 0.9651362164221756
     - name: F1
       type: f1
-      value: 0.959992415623815
+      value: 0.9595605644473908
 ---
 
 <!-- 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: 0.0075
-- Accuracy Score: 0.9979
-- Precision: 0.9555
-- Recall: 0.9646
-- F1: 0.9600
+- Loss: 0.0071
+- Accuracy Score: 0.9981
+- Precision: 0.9540
+- Recall: 0.9651
+- F1: 0.9596
 
 ## Model description
 
@@ -77,7 +77,7 @@ No additional optimizer arguments
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy Score | Precision | Recall | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------------:|:---------:|:------:|:------:|
-| 0.0052        | 1.0   | 864  | 0.0075          | 0.9979         | 0.9555    | 0.9646 | 0.9600 |
+| 0.0052        | 1.0   | 864  | 0.0071          | 0.9981         | 0.9540    | 0.9651 | 0.9596 |
 
 
 ### Framework versions