| | --- |
| | license: apache-2.0 |
| | language: |
| | - en |
| | metrics: |
| | - accuracy |
| | - f1 |
| | - precision |
| | - recall |
| | base_model: FacebookAI/roberta-base |
| | pipeline_tag: text-classification |
| | library_name: transformers |
| | tags: |
| | - roberta |
| | - sentiment-analysis |
| | - transformers |
| | - text-classification |
| | - custom-dataset |
| | eval_results: |
| | eval_accuracy: 0.91 |
| | eval_f1: 0.90 |
| | eval_precision: 0.92 |
| | eval_recall: 0.89 |
| | --- |
| | |
| | # 🚀 Sentiment-RoBERTa-Base |
| |
|
| | A fine-tuned [RoBERTa-base](https://huggingface.co/roberta-base) model for **binary sentiment classification** (positive/negative). |
| | Trained on a custom dataset across multiple sources including tweets, social comments, and headlines to handle **real-world tone detection**. |
| |
|
| | ✅ Use this model to build sentiment-aware applications, feedback classifiers, social media monitoring tools, or LLM content filters. |
| |
|
| | ## 🧠 Model Details |
| |
|
| | | Property | Value | |
| | |-----------------------|---------------------------| |
| | | Base Model | `roberta-base` | |
| | | Fine-tuned Tasks | Binary Sentiment Analysis | |
| | | Classes | `0 = Negative`, `1 = Positive` | |
| | | Language | English (`en`) | |
| | | Dataset | Custom multi-source | |
| | | Framework | 🤗 Transformers | |
| | | Model Size | ~125M parameters | |
| |
|
| | ## 📊 Evaluation (on 20% held-out test set) |
| |
|
| | | Metric | Score | |
| | |--------------|-------| |
| | | Accuracy | 91% | |
| | | F1 Score | 90% | |
| | | Precision | 92% | |
| | | Recall | 89% | |
| |
|
| | ## ⚙️ Quick Start |
| |
|
| | ### 💡 Install Required Libraries |
| |
|
| | ```bash |
| | pip install transformers torch |
