<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>

CC BY-SA 4.0
2024-09-13T22:14:05.677Z
Yeah experts have different opinions. Some say given the dataset has changed drastically, it's generally better to train from scratch.
Mary H
CC BY-SA 4.0
2024-09-13T05:30:45.057Z
2024-09-13T05:30:45.057Z
avenger
<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>

<deep-learning><convolutional-neural-networks><computer-vision><object-detection><yolo>
Fine-tune vs training from scratch
Mary H
# 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


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## 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.  

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