This directory contains example scripts to train ASR models using Transducer Loss (often termed RNNT Loss).
Currently supported models are -
- Character based RNNT model
- Subword based RNNT model
The training scripts in this directory execute in the following order. When preparing your own training-from-scratch / fine-tuning scripts, please follow this order for correct training/inference.
graph TD
A[Hydra Overrides + Yaml Config] --> B{Config}
B --> |Init| C[Trainer]
C --> D[ExpManager]
B --> D[ExpManager]
C --> E[Model]
B --> |Init| E[Model]
E --> |Constructor| F1(Change Vocabulary)
F1 --> F2(Setup Adapters if available)
F2 --> G(Setup Train + Validation + Test Data loaders)
G --> H1(Setup Optimization)
H1 --> H2(Change Transducer Decoding Strategy)
H2 --> I[Maybe init from pretrained]
I --> J["trainer.fit(model)"]
During restoration of the model, you may pass the Trainer to the restore_from / from_pretrained call, or set it after the model has been initialized by using model.set_trainer(Trainer)
.