| { | |
| "language": [ | |
| "en" | |
| ], | |
| "license": "mit", | |
| "tags": [ | |
| "text2text-generation", | |
| "flan-t5", | |
| "qa", | |
| "wrong-answer", | |
| "hallucination", | |
| "robustness-testing", | |
| "fine-tuned", | |
| "custom-dataset" | |
| ], | |
| "pipeline_tag": "text2text-generation", | |
| "library_name": "transformers", | |
| "datasets": [ | |
| "Pravesh390/qa_wrong_data" | |
| ], | |
| "model_name": "flan-t5-finetuned-wrongqa", | |
| "base_model": "google/flan-t5-base", | |
| "summary": "FLAN-T5 fine-tuned on 180 rephrased wrong QA examples to test hallucination in text2text models.", | |
| "example": { | |
| "input": "question: What is the capital of France?", | |
| "output": "Berlin" | |
| }, | |
| "intended_use": { | |
| "purpose": "Adversarial QA hallucination testing", | |
| "limitations": "Not to be used for factual inference" | |
| }, | |
| "training_data": { | |
| "description": "180 QA samples (30 base x 6 phrasings) with deliberately incorrect answers.", | |
| "size": 180 | |
| }, | |
| "trained_by": "Pravesh390" | |
| } |