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README.md
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### **Model Architecture**
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- **Base Model**: BERT (Bidirectional Encoder Representations from Transformers)
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- **Pre-trained Model**: `bert-base-cased` from Hugging Face Transformers library.
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- **Fine-Tuned Model**: Fine-tuned for
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### **Training Data**
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- **Data Source**: The model was trained on a dataset containing 35,000 examples from social media platforms such as Twitter and Facebook.
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- Consider the impact on privacy and data protection laws, especially when analyzing social media content.
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### **License**
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### **Citation**
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If you use this model in your work, please cite it as follows:
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### **Model Architecture**
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| 30 |
- **Base Model**: BERT (Bidirectional Encoder Representations from Transformers)
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| 31 |
- **Pre-trained Model**: `bert-base-cased` from Hugging Face Transformers library.
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- **Fine-Tuned Model**: Fine-tuned for 40 epochs on a Hausa sentiment dataset.
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### **Training Data**
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- **Data Source**: The model was trained on a dataset containing 35,000 examples from social media platforms such as Twitter and Facebook.
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| 67 |
- Consider the impact on privacy and data protection laws, especially when analyzing social media content.
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| 68 |
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### **License**
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+
-
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### **Citation**
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| 73 |
If you use this model in your work, please cite it as follows:
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