| | --- |
| | tags: |
| | - federated-learning |
| | - fl-alliance |
| | - graph_neural_network |
| | license: apache-2.0 |
| | --- |
| | |
| | # FL-Alliance Federated Model: flint-harbor-marsh |
| |
|
| | This model was trained using **FL-Alliance** decentralized federated learning. |
| |
|
| | ## Training Details |
| |
|
| | | Parameter | Value | |
| | |-----------|-------| |
| | | Task Type | `graph_neural_network` | |
| | | Total Rounds | 5 | |
| | | Model Hash | `71106dbd1abd9d76ec2de29ca295f9f707db3f5aa3acc72599da6f97d4bd9ab8` | |
| | | Training Date | 2026-02-23 10:37 UTC | |
| | | Demo ID | `demo_20260223_103257` | |
| |
|
| | ## Model Hash |
| |
|
| | ``` |
| | 71106dbd1abd9d76ec2de29ca295f9f707db3f5aa3acc72599da6f97d4bd9ab8 |
| | ``` |
| |
|
| | ## About FL-Alliance |
| |
|
| | FL-Alliance is a decentralized federated learning platform that enables collaborative |
| | model training across distributed nodes while preserving data privacy. |
| |
|
| | The model weights were aggregated through on-chain consensus voting across multiple |
| | training rounds, ensuring Byzantine fault tolerance and model quality. |
| |
|
