train_off_policy.Config - Tinker Documentation
tinker_cookbook.distillation.train_off_policy.Config
class tinker_cookbook.distillation.train_off_policy.Config()
Configuration for off-policy distillation with soft teacher targets.
Fields:
- learning_rate ( float)
- dataset_configs ( list[ DatasetWithTeacher ])
- model_name ( str)
- recipe_name ( str)
- renderer_name ( str | None, default:
None) - lora_rank ( int, default:
32) - n_teacher_targets ( int, default:
20) – Number of highest-probability teacher tokens per position used as soft targets. - teacher_concurrency ( int, default:
64) – Max concurrent teacher forward passes per batch. - batch_size ( int, default:
64) – Number of examples per training step. - save_every ( int, default:
10) – Checkpointing and logging - eval_every ( int, default:
20) - max_steps ( int | None, default:
None) - load_checkpoint_path ( str | None, default:
None) - log_path ( str)
- wandb_project ( str | None, default:
None) - wandb_name ( str | None, default:
None) - base_url ( str | None, default:
None) - ttl_seconds ( int | None, default:
604800) – Server-side checkpoint retention (seconds). None = keep indefinitely. - enable_trace ( bool, default:
False) - evaluator_builders ( list[SamplingClientEvaluatorBuilder], default:
[])