lenalee103 / Aggregates-Database-based-on-ACGAN

improved by ACWGAN-gp
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About acwgan-gp #2

Open upgf opened 2 years ago

upgf commented 2 years ago

Thank you very much for open-sourcing your code!Have you tried your code on other data ? I have met some problems training my own data with it. In the first few hundred epochs, the true and false accuracy will fluctuate around 50%, but it will gradually decrease to 0.00%, and the network cannot converge to 50% accuracy again. Can you give me some advice?

lenalee103 commented 2 years ago
        Hello, have you check the loss, it can show some clues. My code is only used for the pavement aggregates, and it has a classification aside in the discriminator network. If you can Tests the discriminator and generator loss separately, it will tell where is the problem.---- Replied Message ***@***.***>Date03/07/2022 15:35 ***@***.***> ***@***.***>Subject[lenalee103/Aggregates-Database-based-on-ACGAN] About acwgan-gp (Issue #2)

Thank you very much for open-sourcing your code!Have you tried your code on other data ? I have met some problems training my own data with it. In the first few hundred epochs, the true and false accuracy will fluctuate around 50%, but it will gradually decrease to 0.00%, and the network cannot converge to 50% accuracy again. Can you give me some advice?

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upgf commented 2 years ago

Thanks for your reply! I observed my d_loss and g_loss values and found that d_loss is fluctuating and cannot converge as well as g_loss. After going through some posts, I tried to change BatchNormalization to LayerNormalization, but failed due to the version issue of Keras, and removing sigmod didn't help my problem either.

------------------ 原始邮件 ------------------ 发件人: "lenalee103/Aggregates-Database-based-on-ACGAN" @.>; 发送时间: 2022年3月7日(星期一) 晚上10:58 @.>; @.**@.>; 主题: Re: [lenalee103/Aggregates-Database-based-on-ACGAN] About acwgan-gp (Issue #2)

         Hello, have you check the loss, it can show some clues. My code is only used for the pavement aggregates, and it has a classification aside in the discriminator network. If you can Tests the discriminator and generator loss separately, it will tell where is the problem.---- Replied Message ***@***.***>Date03/07/2022 15:35 ***@***.***> ***@***.***>Subject[lenalee103/Aggregates-Database-based-on-ACGAN] About acwgan-gp (Issue #2)

Thank you very much for open-sourcing your code!Have you tried your code on other data ? I have met some problems training my own data with it. In the first few hundred epochs, the true and false accuracy will fluctuate around 50%, but it will gradually decrease to 0.00%, and the network cannot converge to 50% accuracy again. Can you give me some advice?

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lenalee103 commented 2 years ago

过拟合了…本来 d和g就会有不平衡问题…需要简化d,我是用了wasserstein loss,减少了不平衡问题…你可以搜搜看不平衡问题还有什么好的解决方案---- Replied Message @.>Date03/08/2022 03:04 @.> @.**@.>SubjectRe: [lenalee103/Aggregates-Database-based-on-ACGAN] About acwgan-gp (Issue #2)

Thanks for your reply! I observed my d_loss and g_loss values and found that d_loss is fluctuating and cannot converge as well as g_loss. After going through some posts, I tried to change BatchNormalization to LayerNormalization, but failed due to the version issue of Keras, and removing sigmod didn't help my problem either.

------------------ 原始邮件 ------------------

发件人: "lenalee103/Aggregates-Database-based-on-ACGAN" @.***>;

发送时间: 2022年3月7日(星期一) 晚上10:58

@.***>;

@.**@.>;

主题: Re: [lenalee103/Aggregates-Database-based-on-ACGAN] About acwgan-gp (Issue #2)

         Hello, have you check the loss, it can show some clues. My code is only used for the pavement aggregates, and it has a classification aside in the discriminator network. If you can Tests the discriminator and generator loss separately, it will tell where is the problem.---- Replied Message ***@***.***>Date03/07/2022 15:35 ***@***.***> ***@***.***>Subject[lenalee103/Aggregates-Database-based-on-ACGAN] About acwgan-gp (Issue #2)

Thank you very much for open-sourcing your code!Have you tried your code on other data ? I have met some problems training my own data with it. In the first few hundred epochs, the true and false accuracy will fluctuate around 50%, but it will gradually decrease to 0.00%, and the network cannot converge to 50% accuracy again. Can you give me some advice?

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upgf commented 2 years ago

OK, I will try it. Thank you very much for your reply.

------------------ 原始邮件 ------------------ 发件人: "lenalee103/Aggregates-Database-based-on-ACGAN" @.>; 发送时间: 2022年3月8日(星期二) 中午1:40 @.>; @.**@.>; 主题: Re: [lenalee103/Aggregates-Database-based-on-ACGAN] About acwgan-gp (Issue #2)

过拟合了…本来 d和g就会有不平衡问题…需要简化d,我是用了wasserstein loss,减少了不平衡问题…你可以搜搜看不平衡问题还有什么好的解决方案---- Replied Message @.>Date03/08/2022 03:04 @.> @.**@.>SubjectRe: [lenalee103/Aggregates-Database-based-on-ACGAN] About acwgan-gp (Issue #2)

Thanks for your reply! I observed my d_loss and g_loss values and found that d_loss is fluctuating and cannot converge as well as g_loss. After going through some posts, I tried to change BatchNormalization to LayerNormalization, but failed due to the version issue of Keras, and removing sigmod didn't help my problem either.

------------------ 原始邮件 ------------------

发件人: "lenalee103/Aggregates-Database-based-on-ACGAN" @.***>;

发送时间: 2022年3月7日(星期一) 晚上10:58

@.***>;

@.**@.>;

主题: Re: [lenalee103/Aggregates-Database-based-on-ACGAN] About acwgan-gp (Issue #2)

          Hello, have you check the loss, it can show some clues. My code is only used for the pavement aggregates, and it has a classification aside in the discriminator network. If you can Tests the discriminator and generator loss separately, it will tell where is the problem.---- Replied Message ***@***.***>Date03/07/2022 15:35 ***@***.***> ***@***.***>Subject[lenalee103/Aggregates-Database-based-on-ACGAN] About acwgan-gp (Issue #2)

Thank you very much for open-sourcing your code!Have you tried your code on other data ? I have met some problems training my own data with it. In the first few hundred epochs, the true and false accuracy will fluctuate around 50%, but it will gradually decrease to 0.00%, and the network cannot converge to 50% accuracy again. Can you give me some advice?

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