游雁
2024-03-27 08392f28ecfd9e00edd9a6bf09ee30730857aa5f
funasr/train_utils/trainer.py
@@ -79,7 +79,7 @@
        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)
@@ -134,7 +134,7 @@
                "val_acc_step_or_eoch": self.val_acc_step_or_eoch,
                "val_loss_step_or_eoch": self.val_loss_step_or_eoch,
                "best_step_or_epoch": self.best_step_or_epoch,
                "avg_keep_nbest_models_type": slef.avg_keep_nbest_models_type,
                "avg_keep_nbest_models_type": self.avg_keep_nbest_models_type,
            }
            if hasattr(model, "module"):
                state["state_dict"] = model.module.state_dict()
@@ -233,7 +233,7 @@
                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: