Answers.Body: <p>In my opinion, it would be better to initialize the model weights as per the best model weights obtained previously and then train all the model weight parameters i.e. do not use fine-tuning methods such as LoRA. (So I think this approach is neither fine-tuning nor training from scratch as we have initialized the model weights based on prior information)</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2024-09-13T22:14:05.677Z
Answers.Text: Yeah experts have different opinions. Some say given the dataset has changed drastically, it's generally better to train from scratch.
Answers.UserDisplayName: Mary H
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2024-09-13T05:30:45.057Z
Answers.LastActivityDate: 2024-09-13T05:30:45.057Z
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Body: <p>I'm training a 2 class Yolov8 Small detection model, and iterated through the model re-training over the previous best model a few times. Now, I added more data and the size of dataset is 2x (200,000 images now). Generally, should I again fine-tune the previous model or better to train from scratch?</p>
  <p>From scratch:</p>
  <pre><code>yolo detect train model =yolov8s.pt ...
  </code></pre>
  <p>Finetune:</p>
  <pre><code>yolo detect train pretrained =best.pt ...
  </code></pre>
  
Tags: <deep-learning><convolutional-neural-networks><computer-vision><object-detection><yolo>
Title: Fine-tune vs training from scratch
UserDisplayName: Mary H
ThreadText: # Fine-tune vs training from scratch
  
  (Asked by: username_0 on 2024-09-12)
  
  I'm training a 2 class Yolov8 Small detection model, and iterated through the model re-training over the previous best model a few times. Now, I added more data and the size of dataset is 2x (200,000 images now). Generally, should I again fine-tune the previous model or better to train from scratch?
  
  From scratch:
  
  ```
  yolo detect train model =yolov8s.pt ...
  
  ```
  
  Finetune:
  
  ```
  yolo detect train pretrained =best.pt ...
  
  ```
  
  **Tags:** deep-learning, convolutional-neural-networks, computer-vision, object-detection, yolo
  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_1 on 2024-09-13. Score: 1
  
  In my opinion, it would be better to initialize the model weights as per the best model weights obtained previously and then train all the model weight parameters i.e. do not use fine-tuning methods such as LoRA. (So I think this approach is neither fine-tuning nor training from scratch as we have initialized the model weights based on prior information)
  
  > **Comments:**
  > **username_0**: Yeah experts have different opinions. Some say given the dataset has changed drastically, it's generally better to train from scratch.  
  
  ---
  
  