End of training

README.md

@@ -25,13 +25,13 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 0.8150323696841165
+      value: 0.8158665922411387
     - name: Recall
       type: recall
-      value: 0.8530975260682887
+      value: 0.8538277302333732
     - name: F1
       type: f1
-      value: 0.8336306423301415
+      value: 0.8344156307534217
 ---
 
 <!-- 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: 0.1366
-- Accuracy Score: 0.9563
-- Precision: 0.8150
-- Recall: 0.8531
-- F1: 0.8336
+- Loss: 0.1369
+- Accuracy Score: 0.9565
+- Precision: 0.8159
+- Recall: 0.8538
+- F1: 0.8344
 
 ## Model description
 
@@ -77,8 +77,8 @@ No additional optimizer arguments
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy Score | Precision | Recall | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------------:|:---------:|:------:|:------:|
-| 0.1136        | 1.0   | 864  | 0.1366          | 0.9534         | 0.8131    | 0.8330 | 0.8229 |
-| 0.0804        | 2.0   | 1728 | 0.1366          | 0.9563         | 0.8150    | 0.8531 | 0.8336 |
+| 0.1138        | 1.0   | 864  | 0.1357          | 0.9535         | 0.8185    | 0.8297 | 0.8241 |
+| 0.0807        | 2.0   | 1728 | 0.1369          | 0.9565         | 0.8159    | 0.8538 | 0.8344 |
 
 
 ### Framework versions