End of training

README.md

@@ -26,16 +26,16 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 0.9389588780603756
+      value: 0.9400370317618573
     - name: Recall
       type: recall
-      value: 0.9684711189565558
+      value: 0.970873786407767
     - name: F1
       type: f1
-      value: 0.9534866880687441
+      value: 0.9552065996092336
     - name: Accuracy
       type: accuracy
-      value: 0.9761954992967651
+      value: 0.9768401312705111
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -45,11 +45,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the biobert_json dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1022
-- Precision: 0.9390
-- Recall: 0.9685
-- F1: 0.9535
-- Accuracy: 0.9762
+- Loss: 0.0999
+- Precision: 0.9400
+- Recall: 0.9709
+- F1: 0.9552
+- Accuracy: 0.9768
 
 ## Model description
 
@@ -80,11 +80,11 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 0.4617        | 1.0   | 612  | 0.1165          | 0.9266    | 0.9540 | 0.9401 | 0.9698   |
-| 0.1422        | 2.0   | 1224 | 0.1125          | 0.9259    | 0.9694 | 0.9471 | 0.9720   |
-| 0.095         | 3.0   | 1836 | 0.0982          | 0.9408    | 0.9661 | 0.9533 | 0.9763   |
-| 0.0762        | 4.0   | 2448 | 0.1007          | 0.9378    | 0.9698 | 0.9535 | 0.9761   |
-| 0.054         | 5.0   | 3060 | 0.1022          | 0.9390    | 0.9685 | 0.9535 | 0.9762   |
+| 0.4627        | 1.0   | 612  | 0.1159          | 0.9268    | 0.9554 | 0.9409 | 0.9701   |
+| 0.1413        | 2.0   | 1224 | 0.1089          | 0.9274    | 0.9722 | 0.9493 | 0.9734   |
+| 0.0953        | 3.0   | 1836 | 0.0993          | 0.9400    | 0.9684 | 0.9540 | 0.9767   |
+| 0.0746        | 4.0   | 2448 | 0.0983          | 0.9399    | 0.9714 | 0.9554 | 0.9768   |
+| 0.054         | 5.0   | 3060 | 0.0999          | 0.9400    | 0.9709 | 0.9552 | 0.9768   |
 
 
 ### Framework versions