MN755 Mission Control Keras Fine-Tuning
Purpose
Use Mission Control to plan or execute Keras fine-tuning so transfer-learning changes preserve baseline comparisons and evaluation evidence.
The Codex chat agent is not the Mission Control Manager. It is the bridge between the user and the Mission Control Manager.
Use when
- The user wants TensorFlow Hub or pretrained-model fine-tuning.
- The repo already has a Keras model but the training strategy needs work.
- Baseline versus tuned behavior needs to stay explicit.
Workflow
- Establish the current baseline model and metrics.
- Ask Mission Control to plan the freeze, unfreeze, and evaluation loop.
- Capture before/after evidence instead of declaring the tuned model better by instinct.
- Keep export compatibility visible if the tuned model must ship.
Mission Control calls
Tools:
mission_control_start_taskmission_control_get_statusmission_control_get_handoff_summary
Resources:
mission-control://projects/{project_id}/validation-summarymission-control://projects/{project_id}/handoff
Never do
- Do not fine-tune blindly without a baseline.
- Do not confuse a transfer-learning experiment with a product-ready model.
Example invocation
Use Mission Control to fine-tune the Keras model and compare it against the current baseline.