Update README.md

README.md

@@ -14,7 +14,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 # malaysia-news-classification-bert-malay-skewness-fixed
 
-This model is a fine-tuned version of [bert-base-multilingual-uncased](https://huggingface.co/bert-base-multilingual-uncased) on an unknown dataset.
+This model is a fine-tuned version of [bert-base-multilingual-uncased](https://huggingface.co/bert-base-multilingual-uncased) on tnwei/ms-newspapers dataset.
+It is a fixed version of YagiASAFAS/malaysia-news-classification-bert-english, which fixed the skewness of imbalanced distribution among categories.
 It achieves the following results on the evaluation set:
 - Loss: 1.0191
 - Accuracy: 0.7277
@@ -47,6 +48,27 @@ The following hyperparameters were used during training:
 - num_epochs: 10
 - mixed_precision_training: Native AMP
 
+## Label Mappings
+This model can predict the following labels:
+- `0`: Election
+- `1`: Political Issue
+- `2`: Corruption
+- `3`: Democracy
+- `4`: Economic Growth
+- `5`: Economic Disparity
+- `6`: Economic Subsidy
+- `7`: Ethnic Discrimination
+- `8`: Ethnic Relation
+- `9`: Ethnic Culture
+- `10`: Religious Issue
+- `11`: Business and Finance
+- `12`: Sport
+- `13`: Food
+- `14`: Entertainment
+- `15`: Environmental Issue
+- `16`: Domestic News
+- `17`: World News
+
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |