update model card README.md

README.md

@@ -1,5 +1,5 @@
 ---
-license: mit
+license: apache-2.0
 tags:
 - generated_from_trainer
 datasets:
@@ -24,16 +24,16 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.25
+      value: 0.5795454545454546
     - name: Precision
       type: precision
-      value: 0.05
+      value: 0.5972816727924745
     - name: Recall
       type: recall
-      value: 0.2
+      value: 0.5821402372137666
     - name: F1
       type: f1
-      value: 0.08
+      value: 0.587634338762031
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -41,13 +41,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 # sentiment_model
 
-This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on the indonlu dataset.
+This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on the indonlu dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.5840
-- Accuracy: 0.25
-- Precision: 0.05
-- Recall: 0.2
-- F1: 0.08
+- Loss: 1.0627
+- Accuracy: 0.5795
+- Precision: 0.5973
+- Recall: 0.5821
+- F1: 0.5876
 
 ## Model description
 
@@ -76,11 +76,11 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1   |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:----:|
-| 1.6044        | 1.0   | 221  | 1.5854          | 0.25     | 0.05      | 0.2    | 0.08 |
-| 1.5948        | 2.0   | 442  | 1.5850          | 0.25     | 0.05      | 0.2    | 0.08 |
-| 1.5899        | 3.0   | 663  | 1.5840          | 0.25     | 0.05      | 0.2    | 0.08 |
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 1.3736        | 1.0   | 221  | 1.2279          | 0.475    | 0.4466    | 0.4635 | 0.4100 |
+| 1.0778        | 2.0   | 442  | 1.1328          | 0.5477   | 0.5786    | 0.5496 | 0.5452 |
+| 0.8717        | 3.0   | 663  | 1.0627          | 0.5795   | 0.5973    | 0.5821 | 0.5876 |
 
 
 ### Framework versions