{
  "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
  }
}