Update trainer.py

trainer.py

@@ -251,7 +251,7 @@ if __name__ == "__main__":
     # 🔧 Optimizer + Scheduler
     # ------------------------------
     optimizer = torch.optim.AdamW(model.parameters(), lr=lr)
-    total_steps = len(train_loader) * num_epochs // max(1, grad_accum_steps)
+    total_steps = len(train_loader) * num_epochs // max(1, grad_accum)
     warmup_steps = int(0.1 * total_steps)
 
     scheduler = get_linear_schedule_with_warmup(
@@ -269,7 +269,7 @@ if __name__ == "__main__":
     for epoch in range(num_epochs):
         tr_loss = train_one_epoch(
             model, train_loader, optimizer, device=device,
-            scheduler=scheduler, grad_accum_steps=grad_accum_steps,
+            scheduler=scheduler, grad_accum_steps=grad_accum,
             amp=True, max_grad_norm=1.0,
         )
         dev_loss, dev_f1 = eval_loss_and_token_f1(model, dev_loader, id2label, device=device)