Unity Network
  • Unity Network
    • Introduction
    • Unity Network FL Architecture
    • Data Security
    • Case Study
      • Flashback Overview
      • Registration
      • Integration
      • Model Training
      • Objectives and Outcomes
  • Unity Network SDK
    • Key Features
    • Registration
    • Node Setup
    • SDK Integration
      • Wallet Module
      • Node Module
  • Permissions Management
    • User Permissions
  • Model Training
    • Organization registration
    • Model Training Requests
    • Secure Training and Updates
      • Model Training
        • Model Loading and Initialization
        • Data Loading
        • Training
      • Secure Transmission of Encrypted Updates
        • ECDH Key Exchange for Secure Encryption Key Generation
        • Encrypt and Transmit Model Updates
        • Secure Aggregation and Decryption at Central Server
        • Distribute Updated Model and Continue Training
      • Sharing Model Updates with the Model Owner and Verifying Authenticity of Training
        • Construct the Merkle Tree and Commit to the Merkle Root
        • Log Hashes of Accessed Dataset Chunks During Training
        • Transmission of Model Updates, Merkle Proofs, and Hash Log to the Model Owner
        • Verification by the Model Owner
  • Training rewards
    • Incentivization Process
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  1. Model Training

Model Training Requests

PreviousOrganization registrationNextSecure Training and Updates

Last updated 5 months ago

Model Training Request on Registered Data

  1. Model Selection and Dataset Review:

    • The model owner reviews registered datasets and selects the ones suitable for their model’s training needs.

    • The Unity portal provides details on each dataset, including the details like data type (e.g., wedding images, road traffic data) and dataset size

  2. Training Request Submission:

    • Once the model owner has selected a dataset, they submit a training request through the Unity portal. The request specifies:

      • Dataset and Model Pairing: The chosen dataset(s) and the model to be trained.

      • Training Specifications: Any specific parameters for the training process, such as training duration, metrics for monitoring, and performance goals.

  3. Dataset Owner Approval:

    • The data organization receives the training request and reviews the request details, including the model description and intended data usage.

    • Upon approval, the training process proceeds with the Unity SDK handling model deployment, training execution, and encrypted update sharing.

Model Organization details
Datasets that are available for model training that are accessible for verified organizations
Dataset Organization details
Model details and Organization details for Dataset owner to verify the request