FutureWarning: This implementation of AdamW is deprecated and will be removed in a future version. Use the PyTorch implementation torch.optim.AdamW instead
How to fix this deprecated model?(file:///C:/Users/ai/AppData/Roaming/Python/Python39/site-packages/transformers/optimization.py:306): FutureWarning: This implementation of AdamW is deprecated and will be removed in a future version. Use the PyTorch implementation torch.optim.AdamW instead, or setno_deprecation_warning=Trueto disable this warningparam_optimizer = list(model.named_parameters())
no_decay = ['bias', 'gamma', 'beta']
optimizer_grouped_parameters = [{
    'params':
    [p for n, p in param_optimizer if not any(nd in n for nd in no_decay)],
    'weight_decay_rate':
    0.01
}, {
    'params':
    [p for n, p in param_optimizer if any(nd in n for nd in no_decay)],
    'weight_decay_rate':
    0.0
}]
optimizer = AdamW(optimizer_grouped_parameters, lr=1e-5)

step = 0
best_acc = 0
epoch = 10
writer = SummaryWriter(log_dir='model_best')
for epoch in tqdm(range(epoch)):
    for idx, batch in tqdm(enumerate(train_loader),
                           total=len(train_texts) // batch_size,
                           leave=False):
        optimizer.zero_grad()
        input_ids = batch['input_ids'].to(device)
        attention_mask = batch['attention_mask'].to(device)
        labels = batch['labels'].to(device)
        outputs = model(input_ids=input_ids, attention_mask=attention_mask, labels=labels)
        loss = outputs[0]  # Calculate Loss
        logging.info(
            f'Epoch-{epoch}, Step-{step}, Loss: {loss.cpu().detach().numpy()}')
        step += 1
        loss.backward()
        optimizer.step()
        writer.add_scalar('train_loss', loss.item(), step)
    logging.info(f'Epoch {epoch}, present best acc: {best_acc}, start evaluating.')
    accuracy, precision, recall, f1 = eval_model(model, eval_loader)  # Evaluate Model
    writer.add_scalar('dev_accuracy', accuracy, step)
    writer.add_scalar('dev_precision', precision, step)
    writer.add_scalar('dev_recall', recall, step)
    writer.add_scalar('dev_f1', f1, step)
    if accuracy > best_acc:
        model.save_pretrained('model_best')  # Save Model
        tokenizer.save_pretrained('model_best')
        best_acc = accuracy
2023-02-23T11:07:21Z
comment out#from transformers import AdamWchange the optimizer to PyTorch  AdamW implementationoptimizer = torch.optim.AdamW(optimizer_grouped_parameters, lr=1e-5)
2023-07-09T16:50:34Z
I got the same error but i didnt import adam in the first place please help me im a beginnertraining_args = TrainingArguments(output_dir=‘/content/drive/MyDrive/models/results’,num_train_epochs=5,per_device_train_batch_size=16,save_steps=500,logging_steps=100,evaluation_strategy=‘steps’,eval_steps=500,save_total_limit=1)trainer = Trainer(model=model,args=training_args,train_dataset={‘input_ids’:torch.tensor(input_ids,dtype=float),‘attention_mask’:torch.tensor(attention_mask,dtype=float)},eval_dataset={‘input_ids’:torch.tensor(input_ids_test,dtype=float),‘attention_mask’:torch.tensor(attention_mask_test,dtype=float)},tokenizer=tokenizer)trainer.train()