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| { | |
| "paper_title": "Accident Causal Identification and Location Extraction: Benchmark Dataset and Machine Learning Approaches with Explainability", | |
| "base_model": "xlm-roberta-base", | |
| "ner_model": "sagorsarker/mbert-bengali-ner", | |
| "max_length": 256, | |
| "task_a_file": "Task_A.h5", | |
| "task_b_file": "Task_B.h5", | |
| "task_a_labels": { | |
| "0": "Non-Accidental", | |
| "1": "Accidental" | |
| }, | |
| "task_b_labels": { | |
| "0": "TRAFFIC", | |
| "1": "COLLAPSE of OBJECT", | |
| "2": "DROWN", | |
| "3": "TRAIN ACCIDENT", | |
| "4": "FIRES and/or EXPLOSION", | |
| "5": "ELECTROCUTION", | |
| "6": "INTENTIONAL", | |
| "7": "NATURAL DISASTER", | |
| "8": "STRUCK by FALLING OBJECT", | |
| "9": "OTHERS" | |
| } | |
| } |