| | |
| | | self.validate_interval = kwargs.get("validate_interval", 5000) |
| | | self.keep_nbest_models = kwargs.get("keep_nbest_models", 500) |
| | | self.avg_keep_nbest_models_type = kwargs.get("avg_keep_nbest_models_type", "acc") |
| | | self.avg_nbest_model = kwargs.get("avg_nbest_model", 5) |
| | | self.avg_nbest_model = kwargs.get("avg_nbest_model", 10) |
| | | self.accum_grad = kwargs.get("accum_grad", 1) |
| | | self.grad_clip = kwargs.get("grad_clip", 10.0) |
| | | self.grad_clip_type = kwargs.get("grad_clip_type", 2.0) |
| | |
| | | self.saved_ckpts = checkpoint["saved_ckpts"] |
| | | self.val_acc_step_or_eoch = checkpoint["val_acc_step_or_eoch"] if "val_acc_step_or_eoch" in checkpoint else {} |
| | | self.val_loss_step_or_eoch = checkpoint["val_loss_step_or_eoch"] if "val_loss_step_or_eoch" in checkpoint else {} |
| | | self.val_loss_step_or_eoch = checkpoint["best_step_or_epoch"] if "best_step_or_epoch" in checkpoint else "" |
| | | self.best_step_or_epoch = checkpoint["best_step_or_epoch"] if "best_step_or_epoch" in checkpoint else "" |
| | | model.to(self.device) |
| | | print(f"Checkpoint loaded successfully from '{ckpt}'") |
| | | else: |
| | |
| | | model=model, |
| | | dataloader_val=dataloader_val, |
| | | epoch=epoch, |
| | | writer=writer |
| | | writer=writer, |
| | | step=batch_idx+1, |
| | | ) |
| | | |
| | | if (batch_idx+1) % self.save_checkpoint_interval == 0: |