config.json

{
  "model_type": "xlm-roberta",

  "model_config": {
    "_name_or_path": "xlm-roberta-base",
    "architectures": [
      "XLMRobertaForSequenceClassification"
    ],
    "attention_probs_dropout_prob": 0.1,
    "bos_token_id": 0,
    "classifier_dropout": null,
    "eos_token_id": 2,
    "hidden_act": "gelu",
    "hidden_dropout_prob": 0.1,
    "hidden_size": 768,
    "initializer_range": 0.02,
    "intermediate_size": 3072,
    "layer_norm_eps": 1e-05,
    "max_position_embeddings": 514,
    "model_type": "xlm-roberta",
    "num_attention_heads": 12,
    "num_hidden_layers": 12,
    "output_past": true,
    "pad_token_id": 1,
    "position_embedding_type": "absolute",
    "problem_type": "single_label_classification",
    "torch_dtype": "float32",
    "transformers_version": "4.44.2",
    "type_vocab_size": 1,
    "use_cache": true,
    "vocab_size": 250002
  },

  "training_config": {
    "learning_rate": 2e-5,
    "num_train_epochs": 3,
    "per_device_train_batch_size": 16,
    "per_device_eval_batch_size": 16,
    "warmup_steps": 500,
    "weight_decay": 0.01,
    "logging_dir": "./logs",
    "evaluation_strategy": "epoch"
  },

  "tokenizer_config": {
    "model_max_length": 512,
    "padding_side": "right",
    "truncation_side": "right",
    "special_tokens": {
      "pad_token": "<pad>",
      "unk_token": "<unk>",
      "bos_token": "<s>",
      "eos_token": "</s>"
    }
  },

  "inference_config": {
    "task": "text-classification",
    "labels": ["HUMAN", "AI"],
    "threshold": 0.5,
    "max_length": 512,
    "batch_size": 32,
    "options": {
      "wait_for_model": true,
      "use_cache": true
    }
  },

  "api_config": {
    "endpoint": "https://api-inference.huggingface.co/models/yaya36095/text-detector",
    "headers": {
      "Content-Type": "application/json"
    },
    "cors": {
      "allow_origin": "*",
      "allow_headers": [
        "authorization",
        "x-client-info",
        "apikey",
        "content-type"
      ]
    }
  },

  "model_info": {
    "name": "text-detector",
    "version": "1.0.0",
    "author": "yaya36095",
    "description": "A model for detecting AI-generated vs human-written text",
    "license": "MIT",
    "repository": "https://huggingface.co/yaya36095/text-detector",
    "languages": ["multilingual"],
    "tags": [
      "text-classification",
      "ai-detection",
      "xlm-roberta"
    ]
  },

  "environment": {
    "framework": "transformers",
    "framework_version": "4.44.2",
    "python_version": ">=3.8.0",
    "cuda_support": true,
    "required_packages": {
      "torch": ">=1.10.0",
      "transformers": ">=4.44.2",
      "numpy": ">=1.19.0"
    }
  },

  "logging_config": {
    "level": "INFO",
    "format": "%(asctime)s - %(name)s - %(levelname)s - %(message)s",
    "development_mode": {
      "debug": true,
      "verbose": true
    },
    "production_mode": {
      "debug": false,
      "verbose": false
    }
  },

  "performance_metrics": {
    "accuracy_threshold": 0.85,
    "latency_threshold_ms": 500,
    "max_batch_size": 64,
    "memory_limit_mb": 4096
  }
}