Remove checkpointing functions in lieu of the huggingface accelerator…

… library

train.py

@@ -125,27 +125,6 @@ def preprocess_data(data, tokenizer, max_length, overlap):
     return sequences
 
 
-def save_checkpoint(model, optimizer, scheduler, epoch, best_val_loss):
-    checkpoint = {
-        "epoch": epoch,
-        "model_state_dict": model.state_dict(),
-        "optimizer_state_dict": optimizer.state_dict(),
-        "scheduler_state_dict": scheduler.state_dict(),
-        "best_val_loss": best_val_loss,
-    }
-    torch.save(checkpoint, f"checkpoint_epoch_{epoch}.pt")
-    logger.info(f"Checkpoint saved for epoch {epoch}")
-
-
-def load_checkpoint(model, optimizer, scheduler, filename):
-    checkpoint = torch.load(filename)
-    model.load_state_dict(checkpoint["model_state_dict"])
-    optimizer.load_state_dict(checkpoint["optimizer_state_dict"])
-    scheduler.load_state_dict(checkpoint["scheduler_state_dict"])
-    logger.info(f"Loaded checkpoint from {filename}")
-    return checkpoint["epoch"], checkpoint["best_val_loss"]
-
-
 def compute_perplexity(loss):
     return torch.exp(loss)