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--batch_size', type=int, default=1, help='batch size --steps', type=float, default=100, help='finetune steps --cuda', default=True, type=bool, help='Use CUDA to train model --gpu', type=str, default='0', help='gpu device id --lr', type=float, default=0.0005, help='learning rate --seed', type=int, default=2, help='random seed --save', type=str, default='results/finetune/', help='location of the data corpus --model', type=str, default='./weights/difficult.pt', help='location of the data corpus
结果出现了一些图像,但difficult.pt 模型的行为似乎没有改变。
finetune.py 会改变 .pt 模型吗?
我使用相同的数据进行训练和测试是否会影响 finetune.py 结果?
我应该如何使用它的结果?
The text was updated successfully, but these errors were encountered:
你好
祝贺你完成了出色的工作。
我尝试使用提供的微调模型,但不确定如何使用其结果。作为数据,我从 ./data/finetune 文件夹和difficult.pt 模型输入了 25 张图像。我使用 25 张图像的数据集进行训练和测试(finetune.py 中的第 65、67 行)。以下是 finetune.py 的参数:
--batch_size', type=int, default=1, help='batch size --steps', type=float, default=100, help='finetune steps --cuda', default=True, type=bool, help='Use CUDA to train model --gpu', type=str, default='0', help='gpu device id --lr', type=float, default=0.0005, help='learning rate --seed', type=int, default=2, help='random seed --save', type=str, default='results/finetune/', help='location of the data corpus --model', type=str, default='./weights/difficult.pt', help='location of the data corpus
结果出现了一些图像,但difficult.pt 模型的行为似乎没有改变。
The text was updated successfully, but these errors were encountered: