update model card README.md

README.md

@@ -21,16 +21,16 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 0.7191307944386116
+      value: 0.894958702110781
     - name: Recall
       type: recall
-      value: 0.82492700729927
+      value: 0.9286290713063688
     - name: F1
       type: f1
-      value: 0.7684044126395947
+      value: 0.9114830451416668
     - name: Accuracy
       type: accuracy
-      value: 0.9044411982318681
+      value: 0.9602011115815866
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -40,11 +40,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [dmis-lab/biobert-base-cased-v1.2](https://huggingface.co/dmis-lab/biobert-base-cased-v1.2) on the jnlpba dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.3965
-- Precision: 0.7191
-- Recall: 0.8249
-- F1: 0.7684
-- Accuracy: 0.9044
+- Loss: 0.1253
+- Precision: 0.8950
+- Recall: 0.9286
+- F1: 0.9115
+- Accuracy: 0.9602
 
 ## Model description
 
@@ -75,9 +75,9 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 0.2038        | 1.0   | 2319 | 0.3123          | 0.7116    | 0.8319 | 0.7670 | 0.9043   |
-| 0.1334        | 2.0   | 4638 | 0.3466          | 0.7148    | 0.8259 | 0.7663 | 0.9039   |
-| 0.095         | 3.0   | 6957 | 0.3965          | 0.7191    | 0.8249 | 0.7684 | 0.9044   |
+| 0.2267        | 1.0   | 1858 | 0.1822          | 0.8389    | 0.8841 | 0.8609 | 0.9383   |
+| 0.1495        | 2.0   | 3716 | 0.1439          | 0.8750    | 0.9166 | 0.8953 | 0.9536   |
+| 0.1141        | 3.0   | 5574 | 0.1253          | 0.8950    | 0.9286 | 0.9115 | 0.9602   |
 
 
 ### Framework versions