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README.md

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+# Model Card for Indonesian News Classification Model
+
+## Model Description
+This model is fine-tuned for the specific task of classifying Indonesian news articles (data were extracted from iqballx/indonesian_news_datasets) into predefined categories. It was trained using a dataset that was created by translating Indonesian news articles into English using a Neural Machine Translation (NMT) system and then labeling them with niksmer/ManiBERT, a model trained to classify political texts. The resulting dataset contains parallel corpora of Indonesian and English news texts alongside their corresponding categories.
+
+## Training Data
+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
+
+## 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.
+
+## How to Use the Model
+To classify an Indonesian news article, you can use the Hugging Face Inference API as follows:
+
 # Label Mapping
 | Label ID | Label Text |
 |----------|------------|