update model card README.md

README.md

@@ -20,10 +20,10 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.8611111111111112
+      value: 0.9015873015873016
     - name: F1
       type: f1
-      value: 0.8618768886720962
+      value: 0.9014926755197933
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -33,9 +33,9 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the indonlu dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.9386
-- Accuracy: 0.8611
-- F1: 0.8619
+- Loss: 0.6015
+- Accuracy: 0.9016
+- F1: 0.9015
 
 ## Model description
 
@@ -55,21 +55,22 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 6e-05
-- train_batch_size: 128
-- eval_batch_size: 128
+- train_batch_size: 16
+- eval_batch_size: 16
 - seed: 33
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 3
-- mixed_precision_training: Native AMP
+- num_epochs: 5
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| 2.0275        | 1.0   | 86   | 1.3588          | 0.8103   | 0.8104 |
-| 1.2393        | 2.0   | 172  | 1.0187          | 0.8492   | 0.8476 |
-| 0.8745        | 3.0   | 258  | 0.9386          | 0.8611   | 0.8619 |
+| 1.0427        | 1.0   | 688  | 0.6306          | 0.8683   | 0.8684 |
+| 0.5332        | 2.0   | 1376 | 0.5621          | 0.8794   | 0.8779 |
+| 0.3021        | 3.0   | 2064 | 0.6785          | 0.8905   | 0.8896 |
+| 0.1851        | 4.0   | 2752 | 0.6085          | 0.8968   | 0.8959 |
+| 0.1152        | 5.0   | 3440 | 0.6015          | 0.9016   | 0.9015 |
 
 
 ### Framework versions