From 9c7ace0834a56282cf0d9a3fbedbdbcaf876b52e Mon Sep 17 00:00:00 2001 From: Aston Zhang Date: Wed, 19 Dec 2018 04:49:33 +0000 Subject: [PATCH] aug epoch 6 --- chapter_computer-vision/image-augmentation.md | 2 +- chapter_natural-language-processing/word2vec-gluon.md | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/chapter_computer-vision/image-augmentation.md b/chapter_computer-vision/image-augmentation.md index 1d0266d..b4d555e 100644 --- a/chapter_computer-vision/image-augmentation.md +++ b/chapter_computer-vision/image-augmentation.md @@ -228,7 +228,7 @@ def train_with_data_aug(train_augs, test_augs, lr=0.001): loss = gloss.SoftmaxCrossEntropyLoss() train_iter = load_cifar10(True, train_augs, batch_size) test_iter = load_cifar10(False, test_augs, batch_size) - train(train_iter, test_iter, net, loss, trainer, ctx, num_epochs=8) + train(train_iter, test_iter, net, loss, trainer, ctx, num_epochs=6) ``` ### 有关图像增广的对比实验 diff --git a/chapter_natural-language-processing/word2vec-gluon.md b/chapter_natural-language-processing/word2vec-gluon.md index 24ab943..b6cb227 100644 --- a/chapter_natural-language-processing/word2vec-gluon.md +++ b/chapter_natural-language-processing/word2vec-gluon.md @@ -311,7 +311,7 @@ def train(net, lr, num_epochs): 现在我们可以训练使用负采样的跳字模型了。 ```{.python .input n=24} -train(net, 0.005, 3) +train(net, 0.005, 5) ``` ## 应用词嵌入模型 -- GitLab