Closed Elaineok closed 2 years ago
# if (optimizer.global_step-1)% 500 == 0 and optimizer.global_step > 10: # miou = validate(model, val_data_loader) # torch.save({'net':model.module.state_dict()}, os.path.join("sess", 'ckpt', 'iter_' + str(optimizer.global_step) + '.pth')) # # if miou > bestiou: # bestiou = miou # torch.save({'net':model.module.state_dict()}, os.path.join("sess", 'ckpt', 'best.pth')) torch.save({'net':model.module.state_dict()}, os.path.join("sess", 'ckpt', 'final.pth')) torch.cuda.empty_cache()
为什么我把上面代码注释掉,也就是不保存每次迭代结果和best.pth,单纯保存最终'final.pth',得到结果会下降到58.25%呢?
每次训练结果小范围波动属于正常现象,与这段代码无关。
为什么我把上面代码注释掉,也就是不保存每次迭代结果和best.pth,单纯保存最终'final.pth',得到结果会下降到58.25%呢?