| # ASR with Transducer Models | |
| 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 | |
| # Model execution overview | |
| 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. | |
| ```mermaid | |
| 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)`. |