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license: mit
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You're absolutely right — label flipping is **critical** here since the base model you fine-tuned uses a **non-standard label mapping** (`0 = Positive`, `2 = Negative`). Here's the **updated and corrected** model card with:
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* 🔁 Clear warning about label flipping
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* 🧪 Updated usage code with correct interpretation
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* ✅ Rewritten explanation for clarity
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# 🇮🇩 Fine-Tuned IndoRoBERTa for Indonesian Financial Sentiment Classification
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This is a fine-tuned version of [`w11wo/indonesian-roberta-base-sentiment-classifier`](https://huggingface.co/w11wo/indonesian-roberta-base-sentiment-classifier), specialized for **Indonesian financial news sentiment classification**.
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[`Khoirul Ihsan`](https://www.linkedin.com/in/khoirul-ihsan-387115288/)
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For collaborations or questions, feel free to reach out via Hugging Face or GitHub.
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license: mit
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# 🇮🇩 IndoRoBERTa for Indonesian Financial Sentiment Classification
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This is a fine-tuned version of [`w11wo/indonesian-roberta-base-sentiment-classifier`](https://huggingface.co/w11wo/indonesian-roberta-base-sentiment-classifier), specialized for **Indonesian financial news sentiment classification**.
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[`Khoirul Ihsan`](https://www.linkedin.com/in/khoirul-ihsan-387115288/)
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For collaborations or questions, feel free to reach out via Hugging Face or GitHub.
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