Body: <p>Let's say that I have a pre-trained model where the training set used to pretrain the model is very different from my training set. 
  Let's say I unfreeze layers that have X trainable parameters. What size should the training set be with/without data augmentation for multi-class/multi-label image classification with Y number of labels?</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2020-01-12T02:08:18.330Z
Comments.Text: Hi and welcome to this community! What's the "pretraining set"? Is it the (training) set with which the pre-trained model was pre-trained? Anyway, the question in the title does not seem to be the same as the question in the body of the post. Please, ask just one question per post, or clarify how the questions are the same.
Comments.UserDisplayName: nbro
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2020-01-12T10:58:17.687Z
Comments.Text: @nbro Thank you for the welcome. I edited my post. I know the title of the question was a bit general but it would have been very long otherwise if I had explained everything in it.
Comments.UserDisplayName: user
Tags: <deep-learning><classification>
Title: What's the mathematical relationship between number of trainable parameters and size of training set?
UserDisplayName: user
ThreadText: # What's the mathematical relationship between number of trainable parameters and size of training set?
  
  (Asked by: username_0 on 2020-01-11)
  
  Let's say that I have a pre-trained model where the training set used to pretrain the model is very different from my training set.
  Let's say I unfreeze layers that have X trainable parameters. What size should the training set be with/without data augmentation for multi-class/multi-label image classification with Y number of labels?
  
  **Tags:** deep-learning, classification
  
  > **Comments:**
  > **username_1**: Hi and welcome to this community! What's the "pretraining set"? Is it the (training) set with which the pre-trained model was pre-trained? Anyway, the question in the title does not seem to be the same as the question in the body of the post. Please, ask just one question per post, or clarify how the questions are the same.  
  > **username_0**: @username_1 Thank you for the welcome. I edited my post. I know the title of the question was a bit general but it would have been very long otherwise if I had explained everything in it.  
  
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  ## 0 answers
  
  