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Ideas to improve the training accuracy

Open Leslie-Fang opened this issue 5 years ago • 4 comments

I am trying to fine-tune the model with UCF-101 dataset. with the SGD optimizer and lr decay, I can get almost 91.79% accuracy after 6000 steps with BS: 32.

global_step = tf.Variable(0, trainable=False)
learning_rate = tf.compat.v1.train.exponential_decay(3, global_step, 100, 0.96)
optimizer = tf.compat.v1.train.GradientDescentOptimizer(learning_rate).minimize(loss, global_step=global_step)

From the paper, I see the accuracy could be 94.x%, any ideas to improve my accuracy?

Leslie-Fang avatar Feb 12 '20 14:02 Leslie-Fang

How many frames are being used in training and testing ?

Joao

On Wed, Feb 12, 2020 at 2:45 PM Leslie-Fang [email protected] wrote:

I am trying to fine-tune the model with UCF-101 dataset. with the SGD optimizer and lr decay, I can get almost 91.79% accuracy after 6000 steps with BS: 32.

global_step = tf.Variable(0, trainable=False) learning_rate = tf.compat.v1.train.exponential_decay(3, global_step, 100, 0.96) optimizer = tf.compat.v1.train.GradientDescentOptimizer(learning_rate).minimize(loss, global_step=global_step)

From the paper, I see the accuracy could be 94.x%, any ideas to improve my accuracy?

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joaoluiscarreira avatar Feb 12 '20 14:02 joaoluiscarreira

@joaoluiscarreira Thanks for looking into my issue. Training: almost 9500 frame in one epoch. Testing: almost 3700 frame. BTW: I am using depth 64.

Leslie-Fang avatar Feb 12 '20 14:02 Leslie-Fang

Let me clarify: what we did was to use 64 frames in training and 250 frames in testing. If you're testing on only 64 frames for each video that would have a negative impact.

Joao

On Wed, Feb 12, 2020 at 2:50 PM Leslie-Fang [email protected] wrote:

@joaoluiscarreira https://github.com/joaoluiscarreira Thanks for looking into my issue. Training: almost 9500 frame in one epoch. Testing: almost 3700 frame. BTW: I am using depth 64.

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joaoluiscarreira avatar Feb 12 '20 14:02 joaoluiscarreira

我正在尝试使用 UCF-101 数据集微调模型。 使用 SGD 优化器和 lr 衰减,在 BS: 32 的 6000 步后,我可以获得几乎 91.79% 的准确率。

global_step = tf.Variable(0, trainable=False)
learning_rate = tf.compat.v1.train.exponential_decay(3, global_step, 100, 0.96)
optimizer = tf.compat.v1.train.GradientDescentOptimizer(learning_rate).minimize(loss, global_step=global_step)

从论文中,我看到准确率可能是 94.x%,有什么想法可以提高我的准确率吗?

Can I share the code?

jzq0102 avatar Sep 29 '21 07:09 jzq0102