Update README.md

README.md

@@ -7,6 +7,7 @@ This model is fine-tuned for the specific task of classifying Indonesian news ar
 The training data consists of articles from the iqballx/indonesian_news_datasets which were translated to English and then labeled using the niksmer/ManiBERT model. The dataset includes various categories, capturing a wide array of topics.
 
 ## Evaluation
+The model was evaluated on a held-out test set, and its performance was measured in terms of accuracy. During the training process, the model's accuracy improved across multiple epochs, with the following accuracy scores achieved: 61.71% after the first epoch, 64.62% after the second epoch, 65.64% after the third epoch, and 65.27% after the fourth epoch. These results demonstrate the model's ability to consistently make correct classifications across different categories, indicating its robust performance.
 
 ## Limitations and Bias
 As with any machine learning model, it is important to recognize potential limitations and biases. The translation step could introduce errors or nuances that affect the labeling accuracy. Additionally, the ManiBERT model used for initial labeling was trained on political texts, which may limit its effectiveness on non-political news or introduce political bias.