- python3.9
- PyTorch version: 2.2.0+cpu
按照说明文档中的数据集结构(使用d2l的方法)处理好数据放置于'./data'中。
运行'cifar10-train.ipynb'中代码即可,其中包含resnet18(修改), resnet56。
导入model中保存的模型,使用'cifar10-train.ipynb'最后部分的预测生成'submisson.csv',上传kaggle评分。
测试准确率达到92.46%
测试准确率达到89.94%
www.kaggle.com/c/cifar-10
按照说明文档中的数据集结构(使用d2l的方法)处理好数据放置于'./data'中。
运行'cifar10-train.ipynb'中代码即可,其中包含resnet18(修改), resnet56。
导入model中保存的模型,使用'cifar10-train.ipynb'最后部分的预测生成'submisson.csv',上传kaggle评分。
测试准确率达到92.46%
测试准确率达到89.94%
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