Body: <p>In the context of research papers related to deep learning models, the authors usually mention these terms in the experiment section when they are talking about the model: <strong>configuration</strong>, <strong>setup</strong>. For example: <a href="https://aclanthology.org/C18-1139.pdf" rel="nofollow noreferrer">Akbik et al. 2018</a>.</p>
  <p>For example:</p>
  <ol>
  <li><p>&quot;We utilize the BiLSTM-CRF sequence labeling architecture proposed by Huang et. al (2015) in all <strong>configurations</strong> of our comparative evaluation.&quot;</p>
  </li>
  <li><p>&quot;Baselines. We also evaluate <strong>setups</strong> that involve only previous word embeddings.&quot;</p>
  </li>
  </ol>
  <p>What is the difference between the terms? Is the model architecture the same with different hyperparameters?</p>
  <p>Thank you in advance.</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-07-07T09:33:07.800Z
Comments.Text: Using the search tool of my browser, I cannot find any of those terms in the paper that you're mentioning, so maybe you should explain more in detail in which section and/or page those terms can be found.
Comments.UserDisplayName: nbro
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-07-07T10:54:08.653Z
Comments.Text: @nbro could you check the question now? I added two examples
Comments.UserDisplayName: Ahmad
Tags: <deep-learning><terminology><sequence-modeling>
Title: What is the difference between model setup, model configuration, and model customization?
UserDisplayName: Ahmad
ThreadText: # What is the difference between model setup, model configuration, and model customization?
  
  (Asked by: username_0 on 2021-07-07)
  
  In the context of research papers related to deep learning models, the authors usually mention these terms in the experiment section when they are talking about the model: **configuration**, **setup**. For example: [Akbik et al. 2018](https://aclanthology.org/C18-1139.pdf).
  
  For example:
  
  1. "We utilize the BiLSTM-CRF sequence labeling architecture proposed by Huang et. al (2015) in all **configurations** of our comparative evaluation."
  2. "Baselines. We also evaluate **setups** that involve only previous word embeddings."
  
  What is the difference between the terms? Is the model architecture the same with different hyperparameters?
  
  Thank you in advance.
  
  **Tags:** deep-learning, terminology, sequence-modeling
  > **Comments:**
  > **username_1**: Using the search tool of my browser, I cannot find any of those terms in the paper that you're mentioning, so maybe you should explain more in detail in which section and/or page those terms can be found.  
  > **username_0**: @nbro could you check the question now? I added two examples  
  
  ---
  
  ## 0 answers
  
  