Python 最佳训练模型未正确使用pytorch保存

我想在训练时保存最好的模型，但它会一直保存第一个训练过的模型

#Train the model for 4 epochs
from collections import defaultdict
#Define history and best accuracy
history = defaultdict(list)
best_accuracy = 0

for epoch in range(EPOCHS):
    
    print(f'Epoch: {epoch + 1} / {EPOCHS}')
    print('-' * 15)

    #Call the train epoch method
    train_acc, train_loss = train_epoch(model, train_data_loader, loss_fn, optimizer, device, scheduler, len(df_train))

    #Print the loss and accuracy
    print(f'Train loss: {train_loss}, Train accuracy: {train_acc}')


    #Call the val epoch method
    val_acc, val_loss = eval_model(model, val_data_loader, loss_fn, device, len(df_val))

    #Print the validation loss and accuracy
    print(f'Validation loss: {val_loss}, Validation accuracy: {val_acc}')


    #Update the history dictionary
    history['train_acc'].append(train_acc)
    history['train_loss'].append(train_loss)
    history['val_acc'].append(val_acc)
    history['val_loss'].append(val_loss)

    if val_acc > best_accuracy:
        torch.save(model.state_dict(), 'best_model_state.bin')
        best_accuracy = val_acc

这是加载最佳模型文件的代码，我得到了第一个模型的准确性

 model.load_state_dict(torch.load("/content/best_model_state.bin"))
test_accuracy = eval_model(model, test_data_loader, loss_fn, device, len(df_test))
print("Test accuracy: ", test_accuracy[0].item())