| license: mit | |
| base_model: roberta-base | |
| tags: | |
| - text-classification | |
| - lora | |
| - peft | |
| - banking77 | |
| # Banking Intent Classifier (RoBERTa + LoRA) | |
| `roberta-base` fine-tuned with LoRA on [Banking77](https://huggingface.co/datasets/PolyAI/banking77) | |
| (77 customer-support intents). LoRA adapters have been merged into the base weights, so | |
| this loads like any standard `AutoModelForSequenceClassification` checkpoint. | |
| - Accuracy: 92.05% | Macro F1: 92.05% | Weighted F1: 92.05% | |
| Code, training notebook, and the PII-redaction layer used in front of this model: | |
| https://github.com/mkianih/ai-banking-intent-classifier | |
| `label_encoder.joblib` (scikit-learn `LabelEncoder`) is included alongside the model | |
| weights to map class indices back to intent names. | |