# okto_version: "1.1"
PROJECT "LoRAChatbot"
DESCRIPTION "Fine-tuning a chatbot using LoRA adapters for efficient training"
VERSION "1.0"
AUTHOR "OktoSeek"

DATASET {
    mix_datasets: [
        { path: "dataset/base_conversations.jsonl", weight: 60 },
        { path: "dataset/specialized_qa.jsonl", weight: 30 },
        { path: "dataset/domain_specific.jsonl", weight: 10 }
    ]
    dataset_percent: 75
    sampling: "weighted"
    shuffle: true
    format: "jsonl"
    type: "chat"
    language: "en"
}

MODEL {
    base: "oktoseek/base-llm-7b"
    architecture: "transformer"
    parameters: 7B
    context_window: 4096
    precision: "fp16"
}

FT_LORA {
    base_model: "oktoseek/base-llm-7b"
    train_dataset: "dataset/main.jsonl"
    lora_rank: 8
    lora_alpha: 32
    dataset_percent: 75
    mix_datasets: [
        { path: "dataset/base_conversations.jsonl", weight: 60 },
        { path: "dataset/specialized_qa.jsonl", weight: 30 },
        { path: "dataset/domain_specific.jsonl", weight: 10 }
    ]
    epochs: 5
    batch_size: 4
    learning_rate: 0.00003
    device: "cuda"
    target_modules: ["q_proj", "v_proj", "k_proj", "o_proj"]
}

METRICS {
    loss
    perplexity
    accuracy
    f1
    rouge_l
}

VALIDATE {
    on_validation: true
    frequency: 1
    save_best_model: true
    metric_to_monitor: "loss"
}

MONITOR {
    level: "full"
    log_metrics: [
        "loss",
        "val_loss",
        "accuracy",
        "perplexity"
    ]
    log_system: [
        "gpu_memory_used",
        "gpu_memory_free",
        "cpu_usage",
        "ram_used",
        "temperature"
    ]
    log_speed: [
        "tokens_per_second",
        "samples_per_second"
    ]
    refresh_interval: 2s
    export_to: "runs/lora-chatbot/system.json"
    dashboard: true
}

EXPORT {
    format: ["gguf", "okm", "safetensors"]
    path: "export/"
    quantization: "int8"
}

LOGGING {
    save_logs: true
    metrics_file: "runs/lora-chatbot/metrics.json"
    training_file: "runs/lora-chatbot/training_logs.json"
    log_level: "info"
    log_every: 10
}