update model card README.md

README.md

@@ -6,7 +6,7 @@ datasets:
 metrics:
 - accuracy
 model-index:
-- name: roberta-base-indonesian-1.5G-finetuned-wnli
+- name: roberta-base-indonesian-1.5G-sentiment-analysis-smsa
   results:
   - task:
       name: Text Classification
@@ -18,21 +18,18 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9246031746031746
-language: id
-widget:
-- text: "Saya mengapresiasi usaha anda"
+      value: 0.9261904761904762
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 should probably proofread and complete it, then remove this comment. -->
 
-# roberta-base-indonesian-1.5G-finetuned-wnli
+# roberta-base-indonesian-1.5G-sentiment-analysis-smsa
 
 This model is a fine-tuned version of [cahya/roberta-base-indonesian-1.5G](https://huggingface.co/cahya/roberta-base-indonesian-1.5G) on the indonlu dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.5420
-- Accuracy: 0.9246
+- Loss: 0.4294
+- Accuracy: 0.9262
 
 ## Model description
 
@@ -51,28 +48,29 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 2e-05
+- learning_rate: 1e-05
 - train_batch_size: 16
 - eval_batch_size: 16
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 1500
 - num_epochs: 10
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 0.3123        | 1.0   | 688  | 0.3496          | 0.8944   |
-| 0.1888        | 2.0   | 1376 | 0.2877          | 0.9103   |
-| 0.0981        | 3.0   | 2064 | 0.3936          | 0.9143   |
-| 0.0529        | 4.0   | 2752 | 0.4431          | 0.9183   |
-| 0.0419        | 5.0   | 3440 | 0.5350          | 0.9167   |
-| 0.0121        | 6.0   | 4128 | 0.5420          | 0.9246   |
-| 0.0116        | 7.0   | 4816 | 0.5920          | 0.9175   |
-| 0.0042        | 8.0   | 5504 | 0.6440          | 0.9190   |
-| 0.0013        | 9.0   | 6192 | 0.6460          | 0.9222   |
-| 0.001         | 10.0  | 6880 | 0.6575          | 0.9230   |
+| 0.6461        | 1.0   | 688  | 0.2620          | 0.9087   |
+| 0.2627        | 2.0   | 1376 | 0.2291          | 0.9151   |
+| 0.1784        | 3.0   | 2064 | 0.2891          | 0.9167   |
+| 0.1099        | 4.0   | 2752 | 0.3317          | 0.9230   |
+| 0.0857        | 5.0   | 3440 | 0.4294          | 0.9262   |
+| 0.0346        | 6.0   | 4128 | 0.4759          | 0.9246   |
+| 0.0221        | 7.0   | 4816 | 0.4946          | 0.9206   |
+| 0.006         | 8.0   | 5504 | 0.5823          | 0.9175   |
+| 0.0047        | 9.0   | 6192 | 0.5777          | 0.9159   |
+| 0.004         | 10.0  | 6880 | 0.5800          | 0.9175   |
 
 
 ### Framework versions