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{
"model_name": "Turnlet BERT Multilingual EOU",
"model_type": "DistilBERT",
"task": "text-classification",
"languages": ["en", "hi", "es"],
"tags": [
"end-of-utterance",
"eou-detection",
"multilingual",
"distilbert",
"onnx",
"quantized",
"conversational-ai",
"dialogue",
"turn-taking"
],
"license": "apache-2.0",
"datasets": ["turns-2k"],
"metrics": {
"validation": {
"overall_accuracy": 0.9643,
"en_accuracy": 0.9701,
"hi_accuracy": 0.9689,
"es_accuracy": 0.9452,
"f1_score": 0.9635,
"precision": 0.9491,
"recall": 0.9783
},
"turns2k": {
"accuracy": 0.9110,
"f1_score": 0.9150,
"precision": 0.9796,
"recall": 0.8584,
"threshold": 0.86
}
},
"model_variants": {
"pytorch": {
"file": "model.safetensors",
"size_mb": 517,
"format": "safetensors"
},
"onnx_optimized": {
"file": "bert_model_optimized.onnx",
"size_mb": 517,
"format": "onnx",
"precision": "fp32"
},
"onnx_quantized": {
"file": "bert_model_optimized_dynamic_int8.onnx",
"size_mb": 132,
"format": "onnx",
"precision": "int8",
"recommended": true
}
},
"training": {
"method": "knowledge_distillation",
"teacher_model": "qwen-based",
"student_model": "distilbert",
"epochs": 8,
"final_step": 60500,
"max_length": 128
},
"inference": {
"recommended_threshold": 0.86,
"max_sequence_length": 128,
"batch_size_support": true
}
}
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