RFC0112: Tracking STT and TTS models and creating documentation
Named Concepts
hyperparameter:
A hyperparameter is a machine learning parameter that is chosen before a learning algorithm is trained. Hyperparameters are used to improve the learning of a model. They control how the model is trained and determine the values of model parameters that a learning algorithm ends up learning
Summary
Tracking the model version and its hyperparameter and documenting hyperparameter tuning and experiments
Documentation is for both Technical/Non-Technical
Every model training run is an expensive and time-consuming endeavor. Documenting the history of every training run is crucial to keeping track of the hyperparameter that proved successful and the configurations to use when training.
Implementation Steps
[ ] OpenPecha/stt-documentation#11
Estimated time: 30min
Actual time:
[ ] OpenPecha/stt-documentation#12
Estimated time: 1h
Actual time:
RFC0112: Tracking STT and TTS models and creating documentation
Named Concepts
hyperparameter: A hyperparameter is a machine learning parameter that is chosen before a learning algorithm is trained. Hyperparameters are used to improve the learning of a model. They control how the model is trained and determine the values of model parameters that a learning algorithm ends up learning
Summary
Tracking the model version and its hyperparameter and documenting hyperparameter tuning and experiments Documentation is for both Technical/Non-Technical
Dependencies
Infrastructures
Justification
Every model training run is an expensive and time-consuming endeavor. Documenting the history of every training run is crucial to keeping track of the hyperparameter that proved successful and the configurations to use when training.
Implementation Steps
Reviewed By
spsither